WO2021158702A1 - Artificial intelligence selection and configuration - Google Patents

Artificial intelligence selection and configuration Download PDF

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Publication number
WO2021158702A1
WO2021158702A1 PCT/US2021/016473 US2021016473W WO2021158702A1 WO 2021158702 A1 WO2021158702 A1 WO 2021158702A1 US 2021016473 W US2021016473 W US 2021016473W WO 2021158702 A1 WO2021158702 A1 WO 2021158702A1
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WIPO (PCT)
Prior art keywords
artificial intelligence
model
component
loan
data
Prior art date
Application number
PCT/US2021/016473
Other languages
French (fr)
Inventor
Charles Howard CELLA
Teymour S. EL-TAHRY
Jenna Lynn PARENTI
Taylor D. CHARON
Original Assignee
Strong Force TX Portfolio 2018, LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Priority to US16/780,519 priority Critical
Priority to US16/780,519 priority patent/US20200184556A1/en
Priority to US202062994581P priority
Priority to US62/994,581 priority
Priority to US202063069542P priority
Priority to US63/069,542 priority
Priority to US202063127980P priority
Priority to US63/127,980 priority
Application filed by Strong Force TX Portfolio 2018, LLC filed Critical Strong Force TX Portfolio 2018, LLC
Priority claimed from US17/243,145 external-priority patent/US20210248514A1/en
Priority claimed from US17/332,700 external-priority patent/US20210358032A1/en
Publication of WO2021158702A1 publication Critical patent/WO2021158702A1/en

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    • G06Q30/00Commerce, e.g. shopping or e-commerce
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    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0207Discounts or incentives, e.g. coupons, rebates, offers or upsales
    • G06Q30/0208Trade or exchange of a good or service for an incentive
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    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0207Discounts or incentives, e.g. coupons, rebates, offers or upsales
    • G06Q30/0215Including financial accounts
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    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0278Product appraisal
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    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02Banking, e.g. interest calculation, credit approval, mortgages, home banking or on-line banking
    • G06Q40/025Credit processing or loan processing, e.g. risk analysis for mortgages
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08Insurance, e.g. risk analysis or pensions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/01Social networking
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
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    • H04L9/00Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3236Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions
    • H04L9/3239Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions involving non-keyed hash functions, e.g. modification detection codes [MDCs], MD5, SHA or RIPEMD
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
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    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Computing arrangements based on biological models using neural network models
    • G06N3/04Architectures, e.g. interconnection topology
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L2209/00Additional information or applications relating to cryptographic mechanisms or cryptographic arrangements for secret or secure communication H04L9/00
    • H04L2209/56Financial cryptography, e.g. electronic payment or e-cash
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/50Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees

Abstract

A system includes an opportunity mining module structured to receive input regarding an attribute of a task or a domain, and process the input to determine if an artificial intelligence system can be applied to the task or the domain, an artificial intelligence search engine structured to receive the input, and perform a search of an artificial intelligence store of a plurality of domain-specific and general artificial intelligence models and model components using the input and/or at least one selection criteria to identify at least one artificial intelligence model or model component to apply to the task or the domain, and an artificial intelligence configuration module structured to configure one or more data inputs to use with the at least one artificial intelligence model or model component.

Description

ARTIFICIAL INTELLIGENCE SELECTION AND CONFIGURATION
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] The present application claims the benefit of priority to and is a continuation-in-part of U.S. Patent Application 16/780,519 (Attorney Docket No. SFTX-0012-U01), filed February 3, 2020, entitled “ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM RESPONSIVE TO CROWD SOURCED INFORMATION.”
[0002] U.S. Patent Application 16/780,519 (Attorney Docket No. SFTX-0012-U01) claims the benefit of priority to and is a continuation-in-part of PCT Application PCT/US 19/58647 (Attorney Docket No. SFTX-0009-WO), filed October 29, 2019, entitled "ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM."
[0003] PCT Application PCT/US 19/58647 (Attorney Docket No. SFTX-0009-WO) claims the benefit of priority to the following U.S. Provisional Patent Applications: Serial No. 62/751,713 (Attorney Docket No. SFTX-0003-P01), filed October 29, 2018, entitled "METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES", Serial No. 62/843,992 (Attorney Docket No. SFTX-0005-P01), filed May 6, 2019, entitled "ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM WITH ROBOTIC PROCESS ARCHITECTURE"; Serial No. 62/818,100 Attorney Docket No. SFTX-0006-P01), filed March 13, 2019, entitled "ROBOTIC PROCESS AUTOMATION ARCHITECTURE, SYSTEMS AND METHODS IN TRANSACTION ENVIRONMENTS"; Serial No. 62/843,455 (Attorney Docket No. SFTX-0007-P01), filed May 5, 2019, entitled "ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM WITH ROBOTIC PROCESS ARCHITECTURE"; and Serial No. 62/843,456 (Attorney Docket No. SFTX-0008-P01), filed May 5, 2019, entitled ADAPTIVE INTELLIGENCE AND SHARED INFRASTRUCTURE LENDING TRANSACTION ENABLEMENT PLATFORM WITH ROBOTIC PROCESS ARCHITECTURE."
[0004] PCT Application PCT/US 19/58647 also claims the benefit of priority to and is a continuation-in-part of PCT Application PCT/US2019/030934 (Attorney Docket No. SFTX- 0004-WO), filed May 6, 2019, entitled, "METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES."
[0005] U.S. Patent Application 16/780,519 (Attorney Docket No. SFTX-0012-U01) also claims the benefit of priority to and is a continuation-in-part of PCT Application PCT/US2019/030934 (Attorney Docket No. SFTX-0004-WO), filed May 6, 2019, entitled, "METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES."
[0006] PCT Application PCT/US2019/030934 (Attorney Docket No. SFTX-0004-WO) claims the benefit of priority to the following U.S. Provisional Patent Applications: Serial No. 62/787,206 (Attorney Docket No. SFTX-0001-P01), filed December 31, 2018, entitled "METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES"; Serial No. 62/667,550 (Attorney Docket No. SFTX-0002-P01), filed May 6, 2018, entitled "METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES"; and Serial No. 62/751,713 (Attorney Docket No. SFTX-0003-P01), filed October 29, 2018, entitled "METHODS AND SYSTEMS FOR IMPROVING MACHINES AND SYSTEMS THAT AUTOMATE EXECUTION OF DISTRIBUTED LEDGER AND OTHER TRANSACTIONS IN SPOT AND FORWARD MARKETS FOR ENERGY, COMPUTE, STORAGE AND OTHER RESOURCES."
[0007] The present application also claims priority to the following U.S. Provisional Patent Applications: Serial No. 63/127,980 (Attorney Docket No. SFTX-0016-P01), filed December 18, 2020, entitled “MARKET ORCHESTRATION SYSTEM FOR FACILITATING ELECTRONIC MARKETPLACE TRANSACTIONS”; Serial No. 63/069,542 (Attorney Docket No. SFTX- 0015-P01), filed August 24, 2020, entitled “INFORMATION TECHNOLOGY SYSTEMS AND METHODS FOR TRANSACTION ARTIFICIAL INTELLIGENCE LEVERAGING DIGITAL TWINS”; and Serial No. 62/994,581 (Attorney Docket No. SFTX-0014-P01), filed March 25, 2020, entitled “COMPLIANCE SYSTEM FOR FACILITATING LICENSING OF PERSONALITY RIGHTS”.
[0008] Each of the foregoing applications is incorporated herein by reference in its entirety. BACKGROUND
[0009] Field. This application is related to the field of lending, and more particularly to the field of adaptive intelligent systems used to enable lending transactions.
[00010] Description of the Related Art. Lending transactions provide financing for a wide variety of needs, ranging from housing and education to corporate and government projects, among many others, while enabling lenders to earn financial returns. However, lending transactions are plagued by a number of problems, including opacity and asymmetry of information, moral hazard induced by shifting of the consequences of risky or inappropriate behavior, complexity of application and negotiation processes, burdensome regulatory and policy regimes, difficulty in determining the value of property that is used as collateral or backing for obligations, difficulty in determining the reliability or financial health of entities, and others. A need exists for lending systems that address these and other problems of lending transactions and environments.
SUMMARY
[00011] Provided herein is a lending transaction enablement platform having a set of data- integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions. The platform is capable of enabling a wide range of dedicated solutions, which may share data collection and storage infrastructure, and which may share or exchange inputs, events, activities, and outputs, such as to reinforce learning, enable automation, and enable adaptive intelligence across the various solutions.
[00012] In embodiments a lending platform is provided having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction.
[00013] In embodiments a lending platform is provided having a smart contract and distributed ledger platform for managing at least one of ownership of a set of collateral and a set of events related to a set of collateral.
[00014] In embodiments a lending platform is provided having a smart contract system that automatically adjusts an interest rate for a loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analytic services and a set of data collection and monitoring services.
[0015] In embodiments a lending platform is provided having a crowdsourcing system for obtaining information about at least one of a state of a set of collateral for a loan and a state of an entity relevant to a guarantee for a loan. [0016] In embodiments a lending platform is provided having a smart contract that automatically adjusts an interest rate for a loan based on at least one of a regulatory factor and a market factor for a specific jurisdiction.
[0017] In embodiments a lending platform is provided having a smart contract that automatically restructures debt based on a monitored condition.
[0018] In embodiments a lending platform is provided having a social network monitoring system for validating the reliability of a guarantee for a loan.
[0019] In embodiments a lending platform is provided having an Internet of Things data collection and monitoring system for validating reliability of a guarantee for a loan.
[0020] In embodiments a lending platform is provided having a robotic process automation system for negotiation of a set of terms and conditions for a loan.
[0021] In embodiments a lending platform is provided having a robotic process automation system for loan collection.
[0022] In embodiments a lending platform is provided having a robotic process automation system for consolidating a set of loans.
[0023] In embodiments a lending platform is provided having a robotic process automation system for managing a factoring loan.
[0024] In embodiments a lending platform is provided having a robotic process automation system for brokering a mortgage loan.
[0025] In embodiments a lending platform is provided having a crowdsourcing and automated classification system for validating condition of an issuer for a bond.
[0026] In embodiments a lending platform is provided having a social network monitoring system with artificial intelligence for classifying a condition about a bond.
[0027] In embodiments a lending platform is provided having an Internet of Things data collection and monitoring system with artificial intelligence for classifying a condition about a bond.
[0028] In embodiments a lending platform is provided having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored by the IoT.
[0029] In embodiments a lending platform is provided having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored in a social network.
[0030] In embodiments a lending platform is provided having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored by crowdsourcing.
[0031] In embodiments a lending platform is provided having an automated blockchain custody service for managing a set of custodial assets.
[0032] In embodiments a lending platform is provided having an underwriting system for a loan with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions.
[0033] In embodiments a lending platform is provided having a loan marketing system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services and smart contract services for marketing a loan to a set of prospective parties.
[0034] In embodiments a lending platform is provided having a rating system with a set of data- integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for rating a set of loan-related entities. [0035] In embodiments a lending platform is provided having a compliance system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for automatically facilitating compliance with at least one of a law, a regulation and a policy that applies to a lending transaction. [0036] One aspect of the present disclosure relates to a method for electronically facilitating licensing of one or more personality rights of a licensor. The method may include receiving an access request from a licensee to obtain approval to license personality rights from a set of available licensors. The method may include selectively granting access to the licensee based on the access request. The method may include receiving confirmation of a deposit of an amount of funds from the licensee. The method may include issuing an amount of cryptocurrency corresponding to the amount of funds deposited by the licensee to an account of the licensee. The method may include receiving a smart contract request to create a smart contract governing the licensing of the one or more personality rights of the licensor by the licensee. The smart contract request may indicate one or more terms including a consideration amount of cryptocurrency to be paid to the licensor in exchange for one or more obligations on the licensor. The method may include generating the smart contract based on the smart contract request. The method may include escrowing the consideration amount of cryptocurrency from the account of the licensee. The method may include deploying the smart contract to a distributed ledger. The method may include verifying, by the smart contract, that the licensor has performed the one or more obligations. The method may include, in response to receiving verification that the licensor has performed the one or more obligations, releasing at least a portion of the consideration amount of cryptocurrency into a licensor account of the licensor. The method may include outputting a record indicating a completion of a licensing transaction defined by the smart contract to the distributed ledger. [0037] In some implementations of the method, the smart contract may be generated using a smart contract template provided by an interested third party. [0038] In some implementations of the method, the interested third party may be one of a university, a sports team, or a collegiate athletics governance organization.
[0039] In some implementations of the method, the distributed ledger may be auditable by a set of third parties, including the interested third party.
[0040] In some implementations of the method, the cryptocurrency may be one of Bitcoin, Ethereum, Litecoin, and Ripple.
[0041] In some implementations of the method, the cryptocurrency may be a private cryptocurrency.
[0042] In some implementations of the method, the cryptocurrency may be pegged to a particular type of real currency.
[0043] In some implementations of the method, the distributed ledger may be a public ledger. [0044] In some implementations of the method, the distributed ledger may be a private ledger that is only hosted on computing devices associated with interested third parties.
[0045] In some implementations of the method, the distributed ledger may be a blockchain. [0046] In some implementations of the method, verifying that the licensor may have performed the one or more obligations includes receiving location data from a wearable device associated with the licensor. In some implementations of the method, verifying that the licensor may have performed the one or more obligations includes verifying that the licensor has performed the one or more obligations based on the location data.
[0047] In some implementations of the method, verifying that the licensor may have performed the one or more obligations includes receiving social media data from a social media website. In some implementations of the method, verifying that the licensor may have performed the one or more obligations includes verifying that the licensor has performed the one or more obligations based on the social media data.
[0048] In some implementations of the method, verifying that the licensor may have performed the one or more obligations includes receiving media content from an external data source. In some implementations of the method, verifying that the licensor may have performed the one or more obligations includes verifying that the licensor has performed the one or more obligations based on the media content.
[0049] In some implementations of the method, the media content may be one of a video recording, a photograph, or an audio recording.
[0050] In some implementations of the method, selectively granting access to the licensor may include receiving a set of affiliations of the licensee. In some implementations of the method, selectively granting access to the licensor may include verifying that the licensee is permitted to engage with a set of licensors including the licensor based on the set of affiliations. In some implementations of the method, selectively granting access to the licensor may include in response to verifying that the licensee is permitted to engage with the set of licensors, granting the licensee approval to engage with the set of licensees.
[0051] In some implementations of the method, the set of affiliations of the licensee may include organizations to which the licensee or a principal associated with the licensee donates to or owns. [0052] In some implementations of the method, releasing at least a portion of the consideration amount of cryptocurrency into a licensee account of the licensee may include identifying an allocation smart contract associated with the licensee. In some implementations of the method, the allocation smart contract may define allocation rules governing a manner by which funds resulting from licensing the one or more personality rights are to be distributed amongst the licensor and one or more additional entities. In some implementations of the method, releasing at least a portion of the consideration amount of cryptocurrency into a licensee account of the licensee may include distributing the consideration amount of the cryptocurrency in accordance with the allocation rules.
[0053] In some implementations of the method, the additional entities may include one or more of teammates of the licensor, coaches of the licensor, a team of the licensor, a university of the licensee, and the NCAA.
[0054] In some implementations of the method, it may include obtaining a set of records indicating completion of a set of respective transactions from the distributed ledger. In some implementations of the method, the set of records may include the record indicating the completion of the transaction defined by the smart contract. In some implementations of the method, it may include determining whether an organization associated with the licensor is likely in violation of one or more regulations based on the set of records and a fraud detection model.
[0055] In some implementations of the method, the fraud detection model may be trained using training data that indicates permissible transactions and fraudulent transactions.
[0056] Another aspect of the present disclosure relates to a system configured for electronically facilitating licensing of one or more personality rights of a licensor. The system may include one or more hardware processors configured by machine-readable instructions. The processor(s) may be configured to receive an access request from a licensee to obtain approval to license personality rights from a set of available licensors. The processor(s) may be configured to selectively grant access to the licensee based on the access request. The processor(s) may be configured to receive confirmation of a deposit of an amount of funds from the licensee. The processor(s) may be configured to issue an amount of cryptocurrency corresponding to the amount of funds deposited by the licensee to an account of the licensee. The processor(s) may be configured to receive a smart contract request to create a smart contract governing the licensing of the one or more personality rights of the licensor by the licensee. The smart contract request may indicate one or more terms including a consideration amount of cryptocurrency to be paid to the licensor in exchange for one or more obligations on the licensor. The processor(s) may be configured to generate the smart contract based on the smart contract request. The processor(s) may be configured to escrow the consideration amount of cryptocurrency from the account of the licensee. The processor(s) may be configured to deploy the smart contract to a distributed ledger. The processor(s) may be configured to verify, by the smart contract, that the licensor has performed the one or more obligations. The processor(s) may be configured to, in response to receiving verification that the licensor has performed the one or more obligations, release at least a portion of the consideration amount of cryptocurrency into a licensor account of the licensor. The processor(s) may be configured to output a record indicating a completion of a licensing transaction defined by the smart contract to the distributed ledger.
BRIEF DESCRIPTION OF THE FIGURES
[0057] Fig. 1 depicts components and interactions of an embodiment of a lending platform having a set of data-integrated microservices including data collection and monitoring services for handling lending entities and transactions.
[0058] Fig. 2 depicts components and interactions of an embodiment of a lending platform in which a set of lending solutions are supported by a data-integrated set of data collection and monitoring services, adaptive intelligent systems, and data storage systems.
[0059] Fig. 3 depicts components and interactions of an embodiment of a lending platform having a set of data integrated blockchain services, smart contract services, social network analytic services, crowdsourcing services and Internet of Things data collection and monitoring services for collecting, monitoring, and processing information about entities involved in or related to a lending transaction.
[0060] Fig. 4 depicts components and interactions of a lending platform having an Internet of Things and sensor platform for monitoring at least one of a set of assets, a set of collateral, and a guarantee for a loan, a bond, or a debt transaction.
[0061] Fig. 5 depicts components and interactions of a lending platform having a crowdsourcing system for collecting information related to entities involved in a lending transaction.
[0062] Fig. 6 depicts an embodiment of a crowdsourcing workflow enabled by a lending platform. [0063] Fig. 7 depicts components and interactions of an embodiment of a lending platform having a smart contract system that automatically adjusts an interest rate for a loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analytic services and a set of data collection and monitoring services. [0064] Fig. 8 depicts components and interactions of an embodiment of a lending platform having a having a smart contract that automatically restructures debt based on a monitored condition. [0065] Fig. 9 depicts components and interactions of a lending platform having a set of data collection and monitoring systems for validating the reliability of a guarantee for a loan, including an Internet of Things system and a social network analytics system.
[0066] Fig. 10 depicts components and interactions of a lending platform having a robotic process automation system for negotiation of a set of terms and conditions for a loan.
[0067] Fig. 11 depicts components and interactions of a lending platform having a robotic process automation system for loan collection.
[0068] Fig. 12 depicts components and interactions of a lending platform having a robotic process automation system for consolidating a set of loans.
[0069] Fig. 13 depicts components and interactions of a lending platform having a robotic process automation system for managing a factoring loan.
[0070] Fig. 14 depicts components and interactions of a lending platform having a robotic process automation system for brokering a mortgage loan.
[0071] Fig. 15 depicts components and interactions of a lending platform having a crowdsourcing and automated classification system for validating condition of an issuer for a bond, a social network monitoring system with artificial intelligence for classifying a condition about a bond, and an Internet of Things data collection and monitoring system with artificial intelligence for classifying a condition about a bond.
[0072] Fig. 16 depicts components and interactions of a lending platform having a system that manages the terms and conditions of a loan based on a parameter monitored by the IoT, by a parameter determined by a social network analytic system, or a parameter determined by a crowdsourcing system.
[0073] Fig. 17 depicts components and interactions of a lending platform having an automated blockchain custody service for managing a set of custodial assets.
[0074] Fig. 18 depicts components and interactions of a lending platform having an underwriting system for a loan with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions.
[0075] Fig. 19 depicts components and interactions of a lending platform having a loan marketing system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services and smart contract services for marketing a loan to a set of prospective parties. [0076] Fig. 20 depicts components and interactions of a lending platform having a rating system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for rating a set of loan-related entities.
[0077] Fig. 21 depicts components and interactions of a lending platform having a regulatory and/or compliance system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for automatically facilitating compliance with at least one of a law, a regulation and a policy that applies to a lending transaction.
[0078] Fig. 22 to Fig. 49 are schematic diagrams of embodiments of neural net systems that may connect to, be integrated in, and be accessible by the platform for enabling intelligent lending and transactions including ones involving expert systems, self-organization, machine learning, artificial intelligence and including neural net systems trained for pattern recognition, for classification of one or more parameters, characteristics, or phenomena, for support of autonomous control, and other purposes in accordance with embodiments of the present disclosure.
[0079] Fig. 50 depicts general components and interactions of a lending platform.
[0080] Fig. 51 depicts components and interactions of a lending platform that leverages entity data to identify loan-events and initiate automatic loan-actions.
[0081] Fig. 52 depicts a method of processing entity data to initiate automatic loan-actions. [0082] Fig. 53 depicts components and interactions of a lending platform to value collateral and determine collateral condition.
[0083] Fig. 54 depicts a method of processing collateral data to determine a collateral condition and initiate loan-actions in response.
[0084] Fig. 55 depicts components and interactions of a lending platform.
[0085] Fig. 56 depicts a method of a lending platform.
[0086] Fig. 57 depicts components and interactions of a lending platform that identifies a collateral event and initiates an automatic action in response.
[0087] Fig. 58 depicts a method of a lending platform that automatically initiates a loan-action in response to a collateral event.
[0088] Fig. 59 depicts components and interactions of a lending platform.
[0089] Fig. 60 depicts a method of a lending platform.
[0090] Fig. 61 depicts components and interactions of a lending platform.
[0091] Fig. 62 depicts a method of a lending platform.
[0092] Fig. 63 depicts components and interactions of a lending platform. [0093] Fig. 64 depicts a method of a lending platform.
[0094] Fig. 65 depicts components and interactions of a lending platform. [0095] Fig. 66 depicts a method of a lending platform.
[0096] Fig. 67 depicts components and interactions of a lending platform. [0097] Fig. 68 depicts a method of a lending platform.
[0098] Fig. 69 depicts components and interactions of a lending platform. [0099] Fig. 70 depicts a method of a lending platform.
[00100] Fig. 71 depicts components and interactions of a lending platform. [00101] Fig. 72 depicts a method of a lending platform.
[00102] Fig. 73 depicts components and interactions of a lending platform. [00103] Fig. 74 depicts a method of a lending platform.
[00104] Fig. 75 depicts components and interactions of a lending platform. [00105] Fig. 76 depicts a method of a lending platform.
[00106] Fig. 77 depicts components and interactions of a lending platform. [00107] Fig. 78 depicts a method of a lending platform.
[00108] Fig. 79 depicts components and interactions of a lending platform. [00109] Fig. 80 depicts a method of a lending platform.
[00110] Fig. 81 depicts components and interactions of a lending platform. [00111] Fig. 82 depicts a method of a lending platform.
[00112] Fig. 83 depicts components and interactions of a lending platform. [00113] Fig. 84 depicts a method of a lending platform.
[00114] Fig. 85 depicts components and interactions of a lending platform. [00115] Fig. 86 depicts a method of a lending platform.
[00116] Fig. 87 depicts components and interactions of a lending platform. [00117] Fig. 88 depicts a method of a lending platform.
[00118] Fig. 89 depicts components and interactions of a lending platform. [00119] Fig. 90 depicts a method of a lending platform.
[00120] Fig. 91 depicts components and interactions of a lending platform. [00121] Fig. 92 depicts a method of a lending platform.
[00122] Fig. 93 depicts components and interactions of a lending platform. [00123] Fig. 94 depicts a method of a lending platform.
[00124] Fig. 95 depicts components and interactions of a lending platform. [00125] Fig. 96 depicts a method of a lending platform.
[0126] Fig. 97 depicts components and interactions of a lending platform. [0127] Fig. 98 depicts a method of a lending platform. [0128] Fig. 99 depicts components and interactions of a lending platform.
[0129] Fig. 100 depicts a method of a lending platform.
[0130] Fig. 101 depicts components and interactions of a lending platform.
[0131] Fig. 102 depicts a method of a lending platform.
[0132] Fig. 103 depicts components and interactions of a lending platform.
[0133] Fig. 104 depicts a method of a lending platform.
[0134] Fig. 105 depicts components and interactions of a lending platform.
[0135] Fig. 106 depicts a method of a lending platform.
[0136] Fig. 107 depicts components and interactions of a lending platform.
[0137] Fig. 108 depicts a method of a lending platform.
[0138] Fig. 109 depicts components and interactions of a lending platform.
[0139] Fig. 110 depicts a method of a lending platform.
[0140] Fig. Ill depicts a schematic illustrating an example of a portion of an information technology system for transaction artificial intelligence leveraging digital twins according to some embodiments of the present disclosure.
[0141] Fig. 112 depicts a schematic illustrating a compliance system that facilitates the licensing of personality rights according to some embodiments of the present disclosure.
[0142] Fig. 113 depicts a schematic illustrating an example set of components of a compliance system according to some embodiments of the present disclosure.
[0143] Fig. 114 depicts a set of operations of a method for vetting a potential licensee for purposes of licensing personality rights of a licensor according to some embodiments of the present disclosure.
[0144] Fig. 115 depicts a set of operations of a method for facilitating the licensing of personality rights of a licensor by a licensee according to some embodiments of the present disclosure.
[0145] Fig. 116 depicts a set of operations of a method for detecting potential circumvention of rules or regulations by a licensor and/or licensee according to some embodiments of the present disclosure.
[0146] Fig. 117 depicts a method for selecting an AI solution.
[0147] Fig. 118 depicts a method for selecting an AI solution.
[0148] Fig. 119 depicts an example of an assembled AI solution.
[0149] Fig. 120 depicts a method for selecting an AI solution.
[0150] Fig. 121 depicts a method for selecting an AI solution.
[0151] Fig. 122 depicts an AI solution selection and configuration system.
[0152] Fig. 123 depicts an AI solution selection and configuration system.
[0153] Fig. 124 depicts an AI solution selection and configuration system. [0154] Fig. 125 depicts a component configuration circuit.
[0155] Fig. 126 depicts an AI solution selection and configuration system.
[0156] Fig. 127 depicts a system for selecting and configuring an artificial intelligence model. [0157] Fig. 128 depicts a method of selecting and configuring an artificial intelligence model.
DETAILED DESCRIPTION
[0158] The term services/microservices (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a service/microservice includes any system (or platform) configured to functionally perform the operations of the service, where the system may be data-integrated, including data collection circuits, blockchain circuits, artificial intelligence circuits, and/or smart contract circuits for handling lending entities and transactions. Services/microservices may facilitate data handling and may include facilities for data extraction, transformation and loading; data cleansing and deduplication facilities; data normalization facilities; data synchronization facilities; data security facilities; computational facilities (e.g., for performing pre-defined calculation operations on data streams and providing an output stream); compression and de-compression facilities; analytic facilities (such as providing automated production of data visualizations), data processing facilities, and/or data storage facilities (including storage retention, formatting, compression, migration, etc.), and others.
[0159] Services/microservices may include controllers, processors, network infrastructure, input/output devices, servers, client devices (e.g., laptops, desktops, terminals, mobile devices, and/or dedicated devices), sensors (e.g., IoT sensors associated with one or more entities, equipment, and/or collateral), actuators (e.g., automated locks, notification devices, lights, camera controls, etc.), virtualized versions of any one or more of the foregoing (e.g., outsourced computing resources such as a cloud storage, computing operations; virtual sensors; subscribed data to be gathered such as stock or commodity prices, recordal logs, etc.), and/or include components configured as computer readable instructions that, when performed by a processor, cause the processor to perform one or more functions of the service, etc. Services may be distributed across a number of devices, and/or functions of a service may be performed by one or more devices cooperating to perform the given function of the service.
[0160] Services/ microservices may include application programming interfaces that facilitate connection among the components of the system performing the service (e.g., microservices) and between the system to entities (e.g., programs, web sites, user devices, etc.) that are external to the system. Without limitation to any other aspect of the present disclosure, example microservices that may be present in certain embodiments include (a) a multi-modal set of data collection circuits that collect information about and monitor entities related to a lending transaction; (b) blockchain circuits for maintaining a secure historical ledger of events related to a loan, the blockchain circuits having access control features that govern access by a set of parties involved in a loan; (c) a set of application programming interfaces, data integration services, data processing workflows and user interfaces for handling loan-related events and loan-related activities; and (d) smart contract circuits for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan-related events and loan-related activities. Any of the services/microservices may be controlled by or have control over a controller. Certain systems may not be considered to be a service/microservice. For example, a point of sale device that simply charges a set cost for a good or service may not be a service. In another example, a service that tracks the cost of a good or service and triggers notifications when the value changes may not be a valuation service itself, but may rely on valuation services, and/or may form a portion of a valuation service in certain embodiments. It can be seen that a given circuit, controller, or device may be a service or a part of a service in certain embodiments, such as when the functions or capabilities of the circuit, controller, or device are configured to support a service or microservice as described herein, but may not be a service or part of a service for other embodiments (e.g., where the functions or capabilities of the circuit, controller, or device are not relevant to a service or microservice as described herein). In another example, a mobile device being operated by a user may form a portion of a service as described herein at a first point in time (e.g., when the user accesses a feature of the service through an application or other communication from the mobile device, and/or when a monitoring function is being performed via the mobile device), but may not form a portion of the service at a second point in time (e.g., after a transaction is completed, after the user un-installs an application, and/or when a monitoring function is stopped and/or passed to another device). Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes or systems, and any such processes or systems may be considered a service (or a part of a service) herein.
[0161] One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, how to combine processes and systems from the present disclosure to construct, provide performance characteristics (e.g., bandwidth, computing power, time response, etc.), and/or provide operational capabilities (e.g., time between checks, up-time requirements including longitudinal (e.g., continuous operating time) and/or sequential (e.g., time-of-day, calendar time, etc.), resolution and/or accuracy of sensing, data determinations (e.g., accuracy, timing, amount of data), and/or actuator confirmation capability) of components of the service that are sufficient to provide a given embodiment of a service, platform, and/or microservice as described herein. Certain considerations for the person of skill in the art, in determining the configuration of components, circuits, controllers, and/or devices to implement a service, platform, and/or microservice (“service” in the listing following) as described herein include, without limitation: the balance of capital costs versus operating costs in implementing and operating the service; the availability, speed, and/or bandwidth of network services available for system components, service users, and/or other entities that interact with the service; the response time of considerations for the service (e.g., how quickly decisions within the service must be implemented to support the commercial function of the service, the operating time for various artificial intelligence or other high computation operations) and/or the capital or operating cost to support a given response time; the location of interacting components of the service, and the effects of such locations on operations of the service (e.g., data storage locations and relevant regulatory schemes, network communication limitations and/or costs, power costs as a function of the location, support availability for time zones relevant to the service, etc.); the availability of certain sensor types, the related support for those sensors, and the availability of sufficient substitutes (e.g., a camera may require supportive lighting, and/or high network bandwidth or local storage) for the sensing purpose; an aspect of the underlying value of an aspect of the service (e.g., a principal amount of a loan, a value of collateral, a volatility of the collateral value, a net worth or relative net worth of a lender, guarantor, and/or borrower, etc.) including the time sensitivity of the underlying value (e.g., if it changes quickly or slowly relative to the operations of the service or the term of the loan); a trust indicator between parties of a transaction (e.g., history of performance between the parties, a credit rating, social rating, or other external indicator, conformance of activity related to the transaction to an industry standard or other normalized transaction type, etc.); and/or the availability of cost recovery options (e.g., subscriptions, fees, payment for services, etc.) for given configurations and/or capabilities of the service, platform, and/or microservice. Without limitation to any other aspect of the present disclosure, certain operations performed by services herein include: performing real-time alterations to a loan based on tracked data; utilizing data to execute a collateral-backed smart contract; re-evaluating debt transactions in response to a tracked condition or data, and the like. While specific examples of services/microservices and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0162] Without limitation, services include a financial service (e.g., a loan transaction service), a data collection service (e.g., a data collection service for collecting and monitoring data), a blockchain service (e.g., a blockchain service to maintain secure data), data integration services (e.g., a data integration service to aggregate data), smart contract services (e.g., a smart contract service to determine aspects of smart contracts), software services (e.g., a software service to extract data related to the entities from publicly available information sites), crowdsourcing services (e.g., a crowdsourcing service to solicit and report information), Internet of Things services (e.g., an Internet of Things service to monitor an environment), publishing services (e.g., a publishing services to publish data), microservices (e.g., having a set of application programming interfaces that facilitate connection among the microservices), valuation services (e.g., that use a valuation model to set a value for collateral based on information), artificial intelligence services, market value data collection services (e.g., that monitor and report on marketplace information), clustering services (e.g., for grouping the collateral items based on similarity of attributes), social networking services (e.g., that enables configuration with respect to parameters of a social network), asset identification services (e.g., for identifying a set of assets for which a financial institution is responsible for taking custody), identity management services (e.g., by which a financial institution verifies identities and credentials), and the like, and/or similar functional terminology. Example services to perform one or more functions herein include computing devices; servers; networked devices; user interfaces; inter-device interfaces such as communication protocols, shared information and/or information storage, and/or application programming interfaces (APIs); sensors (e.g., IoT sensors operationally coupled to monitored components, equipment, locations, or the like); distributed ledgers; circuits; and/or computer readable code configured to cause a processor to execute one or more functions of the service. One or more aspects or components of services herein may be distributed across a number of devices, and/or may consolidated, in whole or part, on a given device. In embodiments, aspects or components of services herein may be implemented at least in part through circuits, such as, in non-limiting examples, a data collection service implemented at least in part as a data collection circuit structed to collect and monitor data, a blockchain service implemented at least in part as a blockchain circuit structured to maintain secure data, data integration services implemented at least in part as a data integration circuit structured to aggregate data, smart contract services implemented at least in part as a smart contract circuit structed to determine aspects of smart contracts, software services implemented at least in part as a software service circuit structured to extract data related to the entities from publicly available information sites, crowdsourcing services implemented at least in part as a crowdsourcing circuit structured to solicit and report information, Internet of Things services implemented at least in part as an Internet of Things circuit structured to monitor an environment, publishing services implemented at least in part as a publishing services circuit structured to publish data, microservice service implemented at least in part as a microservice circuit structured to interconnect a plurality of service circuits, valuation service implemented at least in part as valuation services circuit structured to access a valuation model to set a value for collateral based on data, artificial intelligence service implemented at least in part as an artificial intelligence services circuit, market value data collection service implemented at least in part as market value data collection service circuit structured to monitor and report on marketplace information, clustering service implemented at least in part as a clustering services circuit structured to group collateral items based on similarity of attributes, a social networking service implemented at least in part as a social networking analytic services circuit structured to configure parameters with respect to a social network, asset identification services implemented at least in part as an asset identification service circuit for identifying a set of assets for which a financial institution is responsible for taking custody, identity management services implemented at least in part as an identity management service circuit enabling a financial institution to verify identities and credentials, and the like. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered with respect to items and services herein, while in certain embodiments a given system may not be considered with respect to items and services herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Among the considerations that one of skill in the art may contemplate to determine a configuration for a particular service include: the distribution and access devices available to one or more parties to a particular transaction; jurisdictional limitations on the storage, type, and communication of certain types of information; requirements or desired aspects of security and verification of information communication for the service; the response time of information gathering, inter-party communications, and determinations to be made by algorithms, machine learning components, and/or artificial intelligence components of the service; cost considerations of the service, including capital expenses and operating costs, as well as which party or entity will bear the costs and availability to recover costs such as through subscriptions, service fees, or the like; the amount of information to be stored and/or communicated to support the service; and/or the processing or computing power to be utilized to support the service.
[0163] The terms items and services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, items and service includes any items and service, including, without limitation, items and services used as a reward, used as collateral, become the subject of a negotiation, and the like, such as, without limitation, an application for a warranty or guarantee with respect to an item that is the subject of a loan, collateral for a loan, or the like, such as a product, a service, an offering, a solution, a physical product, software, a level of service, quality of service, a financial instrument, a debt, an item of collateral, performance of a service, or other item. Without limitation to any other aspect or description of the present disclosure, items and service includes any items and service, including, without limitation, items and services as applied to physical items (e.g., a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property), a financial item (e.g., a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency), a consumable item (e.g., an edible item, a beverage), a highly valued item (e.g., a precious metal, an item of jewelry, a gemstone), an intellectual item (e.g., an item of intellectual property, an intellectual property right, a contractual right), and the like. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered with respect to items and services herein, while in certain embodiments a given system may not be considered with respect to items and services herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system.
[0164] The terms agent, automated agent, and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, an agent or automated agent may process events relevant to at least one of the value, the condition, and the ownership of items of collateral or assets. The agent or automated agent may also undertake an action related to a loan, debt transaction, bond transaction, subsidized loan, or the like to which the collateral or asset is subject, such as in response to the processed events. The agent or automated agent may interact with a marketplace for purposes of collecting data, testing spot market transactions, executing transactions, and the like, where dynamic system behavior involves complex interactions that a user may desire to understand, predict, control, and/or optimize. Certain systems may not be considered an agent or an automated agent. For example, if events are merely collected but not processed, the system may not be an agent or automated agent. In some embodiments, if a loan-related action is undertaken not in response to a processed event, it may not have been undertaken by an agent or automated agent. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure include and/or benefit from agents or automated agent. Certain considerations for the person of skill in the art, or embodiments of the present disclosure with respect to an agent or automated agent include, without limitation: rules that determine when there is a change in a value, condition or ownership of an asset or collateral, and/or rules to determine if a change warrants a further action on a loan or other transaction, and other considerations. While specific examples of market values and marketplace information are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.
[0165] The term marketplace information, market value and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, marketplace information and market value describes a status or value of an asset, collateral, food, or service at a defined point or period in time. Market value may refer to the expected value placed on an item in a marketplace or auction setting, or pricing or financial data for items that are similar to the item, asset, or collateral in at least one public marketplace. For a company, market value may be the number of its outstanding shares multiplied by the current share price. Valuation services may include market value data collection services that monitor and report on marketplace information relevant to the value (e.g. market value) of collateral, the issuer, a set of bonds, and a set of assets a set of subsidized loans, a party, and the like. Market values may be dynamic in nature because they depend on an assortment of factors, from physical operating conditions to economic climate to the dynamics of demand and supply. Market value may be affected by, and marketplace information may include, proximity to other assets, inventory or supply of assets, demand for assets, origin of items, history of items, underlying current value of item components, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity. In certain embodiments, a market value may include information such as a volatility of a value, a sensitivity of a value (e.g., relative to other parameters having an uncertainty associated therewith), and/or a specific value of the valuated object to a particular party (e.g., an object may have more value as possessed by a first party than as possessed by a second party).
[0166] Certain information may not be marketplace information or a market value. For example, where variables related to a value are not market-derived, they may be a value-in-use or an investment value. In certain embodiments, an investment value may be considered a market value (e.g., when the valuating party intends to utilize the asset as an investment if acquired), and not a market value in other embodiments (e.g., when the valuating party intends to immediately liquidate the investment if acquired). One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit from marketplace information or a market value. Certain considerations for the person of skill in the art, in determining whether the term market value is referring to an asset, item, collateral, good, or service include: the presence of other similar assets in a marketplace, the change in value depending on location, an opening bid of an item exceeding a list price, and other considerations. While specific examples of market values and marketplace information are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.
[0167] The term apportion value or apportioned value and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, apportion value describes a proportional distribution or allocation of value proportionally, or a process to divide and assign value according to a rule of proportional distribution. Apportionment of the value may be to several parties (e.g., each of the several parties is a beneficiary of a portion of the value), to several transactions (e.g., each of the transactions utilizes a portion of the value), and/or in a many-to-many relationship (e.g., a group of objects has an aggregate value that is apportioned between a number of parties and/or transactions). In some embodiments, the value may be a net loss and the apportioned value is the allocation of a liability to each entity. In other embodiments, apportioned value may refer to the distribution or allocation of an economic benefit, real estate, collateral, or the like. In certain embodiments, apportionment may include a consideration of the value relative to the parties - for example, a $10 million asset apportioned 50/50 between two parties, where the parties have distinct value considerations for the asset, may result in one party crediting the apportionment differing resulting values from the apportionment. In certain embodiments, apportionment may include a consideration of the value relative to given transactions - for example, a first type of transaction (e.g., a long-term loan) may have a different valuation of a given asset than a second type of transaction (e.g., a short-term line of credit).
[0168] Certain conditions or processes may not relate to apportioned value. For example, the total value of an item may provide its inherent worth, but not how much of the value is held by each identified entity. One of skill in the art, having the benefit of the disclosure herein and knowledge about apportioned value, can readily determine which aspects of the present disclosure will benefit a particular application for apportioned value. Certain considerations for the person of skill in the art, or embodiments of the present disclosure with respect to an apportioned value include, without limitation: the currency of the principal sum, the anticipated transaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross transaction/loan amount, the amount of the principal sum, the number of entities owed, the value of the collateral, and the like. While specific examples of apportioned values are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.
[0169] The term financial condition and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, financial condition describes a current status of an entity’s assets, liabilities, and equity positions at a defined point or period in time. The financial condition may be memorialized in financial statement. The financial condition may further include an assessment of the ability of the entity to survive future risk scenarios or meet future or maturing obligations. Financial condition may be based on a set of attributes of the entity selected from among a publicly stated valuation of the entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatoly violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity. A financial condition may also describe a requirement or threshold for an agreement or loan. For example, conditions for allowing a developer to proceed may be various certifications and their agreement to a financial payout. That is, the developer’s ability to proceed is conditioned upon a financial element, among others. Certain conditions may not be a financial condition. For example, a credit card balance alone may be a clue as to the financial condition, but may not be the financial condition on its own. In another example, a payment schedule may determine how long a debt may be on an entity’s balance sheet, but in a silo may not accurately provide a financial condition. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure include and/or will benefit from a financial condition. Certain considerations for the person of skill in the art, in determining whether the term financial condition is referring to a current status of an entity’s assets, liabilities, and equity positions at a defined point or period in time and/or for a given purpose include: the reporting of more than one financial data point, the ratio of a loan to value of collateral, the ratio of the collateral to the loan, the gross transaction/loan amount, the credit scores of the borrower and the lender, and other considerations. While specific examples of financial conditions are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.
[0170] The term interest rate and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, interest rate includes an amount of interest due per period, as a proportion of an amount lent, deposited, or borrowed. The total interest on an amount lent or borrowed may depend on the principal sum, the interest rate, the compounding frequency, and the length of time over which it is lent, deposited, or borrowed. Typically, interest rate is expressed as an annual percentage but can be defined for any time period. The interest rate relates to the amount a bank or other lender charges to borrow its money, or the rate a bank or other entity pays its savers for keeping money in an account. Interest rate may be variable or fixed. For example, an interest rate may vary in accordance with a government or other stakeholder directive, the currency of the principal sum lent or borrowed, the term to maturity of the investment, the perceived default probability of the borrower, supply and demand in the market, the amount of collateral, the status of an economy, or special features like call provisions. In certain embodiments, an interest rate may be a relative rate (e.g., relative to a prime rate, an inflation index, etc.). In certain embodiments, an interest rate may further consider costs or fees applied (e.g., “points”) to adjust the interest rate. A nominal interest rate may not be adjusted for inflation while a real interest rate takes inflation into account. Certain examples may not be an interest rate for purposes of particular embodiments. For example, a bank account growing by a fixed dollar amount each year, and/or a fixed fee amount, may not be an example of an interest rate for certain embodiments. One of skill in the art, having the benefit of the disclosure herein and knowledge about interest rates, can readily determine the characteristics of an interest rate for a particular embodiment. Certain considerations for the person of skill in the art, or embodiments of the present disclosure with respect to an interest rate include, without limitation: the currency of the principal sum, variables for setting an interest rate, criteria for modifying an interest rate, the anticipated transaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross transaction/loan amount, the amount of the principal sum, the appropriate lifespans of transactions and/or collateral for a particular industry, the likelihood that a lender will sell and/or consolidate a loan before the term, and the like. While specific examples of interest rates are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.
[0171] The term valuation services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a valuation service includes any service that sets a value for a good or service. Valuation services may use a valuation model to set a value for collateral based on information from data collection and monitoring services. Smart contract services may process output from the set of valuation services and assign items of collateral sufficient to provide security for a loan and/or apportion value for an item of collateral among a set of lenders and/or transactions. Valuation services may include artificial intelligence services that may iteratively improve the valuation model based on outcome data relating to transactions in collateral. Valuation services may include market value data collection services that may monitor and report on marketplace information relevant to the value of collateral. Certain processes may not be considered to be a valuation service. For example, a point of sale device that simply charges a set cost for a good or service may not be a valuation service. In another example, a service that tracks the cost of a good or service and triggers notifications when the value changes may not be a valuation service itself, but may rely on valuation services and/or form a part of a valuation service. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a valuation service herein, while in certain embodiments a given service may not be considered a valuation service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to enhance operations of the contemplated system and/or to provide a valuation service. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a valuation service and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: perform real-time alterations to a loan based on a value of a collateral; utilize marketplace data to execute a collateral-backed smart contract; re evaluate collateral based on a storage condition or geolocation; the tendency of the collateral to have a volatile value, be utilized, and/or be moved; and the like. While specific examples of valuation services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0172] The term collateral attributes (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, collateral attributes include any identification of the durability (ability of the collateral to withstand wear or the useful life of the collateral), value, identification (does the collateral have definite characteristics that make it easy to identify or market), stability of value (does the collateral maintain value over time), standardization, grade, quality, marketability, liquidity, transferability, desirability, trackability, deliverability (ability of the collateral be delivered or transfer without a deterioration in value), market transparency (is the collateral value easily verifiable or widely agreed upon), physical or virtual. Collateral attributes may be measured in absolute or relative terms, and/or may include qualitative (e.g., categorical descriptions) or quantitative descriptions. Collateral attributes may be different for different industries, products, elements, uses, and the like. Collateral attributes may be assigned quantitative or qualitative values. Values associated with collateral attributes may be based on a scale (such as 1-10) or a relative designation (high, low, better, etc.). Collateral may include various components; each component may have collateral attributes. Collateral may, therefore, have multiple values for the same collateral attribute. In some embodiments, multiple values of collateral attributes may be combined to generate one value for each attribute. Some collateral attributes may apply only to specific portions of collateral. Some collateral attributes, even for a given component of the collateral, may have distinct values depending upon the party of interest (e.g., a party that values an aspect of the collateral more highly than another party) and/or depending upon the type of transaction (e.g., the collateral may be more valuable or appropriate for a first type of loan than for a second type of loan). Certain attributes associated with collateral may not be collateral attributes as described herein depending upon the purpose of the collateral attributes herein. For example, a product may be rated as durable relative to similar products; however, if the life of the product is much lower than the term of a particular loan in consideration, the durability of the product may be rated differently (e.g., not durable) or irrelevant (e.g., where the current inventory of the product is attached as the collateral, and is expected to change out during the term of the loan). Accordingly, the benefits of the present disclosure may be applied to a variety of attributes, and any such attributes may be considered collateral attributes herein, while in certain embodiments a given attribute may not be considered a collateral attribute herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about contemplated collateral attributes ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular collateral attribute. Certain considerations for the person of skill in the art, in determining whether a contemplated attribute is a collateral attribute and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: the source of the attribute and the source of the value of the attribute (e.g. does the attribute and attribute value comes from a reputable source), the volatility of the attribute (e.g. does the attribute values for the collateral fluctuate, is the attribute a new attribute for the collateral), relative differences in attribute values for similar collateral, exceptional values for attributes (e.g., some attribute values may be high, such as, in the 98th percentile or very low, such as in the 2nd percentile, compared to similar class of collateral), the fungibility of the collateral, the type of transaction related to the collateral, and/or the purpose of the utilization of collateral for a particular party or transaction. While specific examples of collateral attributes and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0173] The term blockchain services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, blockchain services includes any service related to the processing, recordation, and/or updating of a blockchain, and may include services for processing blocks, computing hash values, generating new blocks in a blockchain, appending a block to the blockchain, creating a fork in the blockchain, merging of forks in the blockchain, verifying previous computations, updating a shared ledger, updating a distributed ledger, generating cryptographic keys, verifying transactions, maintaining a blockchain, updating a blockchain, verifying a blockchain, generating random numbers. The services may be performed by execution of computer readable instructions on local computers and/or by remote servers and computers. Certain services may not be considered blockchain services individually but may be considered blockchain services based on the final use of the service and/or in a particular embodiment - for example, a computing a hash value may be performed in a context outside of a blockchain such in the context of secure communication. Some initial services may be invoked without first being applied to blockchains, but further actions or services in conjunction with the initial services may associate the initial service with aspects of blockchains. For example, a random number may be periodically generated and stored in memory; the random numbers may initially not be generated for blockchain purposes but may be utilized for blockchains. Accordingly, the benefits of the present disclosure may be applied in a wide variety of services, and any such services may be considered blockchain services herein, while in certain embodiments a given service may not be considered a blockchain service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated blockchain service ordinarily available to that person, can readily determine which aspects of the present disclosure can be configured to implement, and/or will benefit, a particular blockchain service. Certain considerations for the person of skill in the art, in determining whether a contemplated service is a blockchain service and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: the application of the service, the source of the service (e.g., if the service is associated with a known or verifiable blockchain service provider), responsiveness of the service (e.g., some blockchain services may have an expected completion time, and/or may be determined through utilization), cost of the service, the amount of data requested for the service, and/or the amount of data generated by the service (blocks of blockchain or keys associated with blockchains may be a specific size or a specific range of sizes). While specific examples of blockchain services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0174] The term blockchain (and variations such as cryptocurrency ledger, and the like) as utilized herein may be understood broadly to describe a cryptocurrency ledger that records, administrates, or otherwise processes online transactions. A blockchain may be public, private, or a combination thereof, without limitation. A blockchain may also be used to represent a set of digital transactions, agreement, terms, or other digital value. Without limitation to any other aspect or description of the present disclosure, in the former case, a blockchain may also be used in conjunction with investment applications, token-trading applications, and/or digital/cryptocurrency based marketplaces. A blockchain can also be associated with rendering consideration, such as providing goods, services, items, fees, access to a restricted area or event, data, or other valuable benefit. Blockchains in various forms may be included where discussing a unit of consideration, collateral, currency, cryptocurrency, or any other form of value. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the value symbolized or represented by a blockchain. While specific examples of blockchains are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0175] The terms ledger and distributed ledger (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a ledger may be a document, file, computer file, database, book, and the like which maintains a record of transactions. Ledgers may be physical or digital. Ledgers may include records related to sales, accounts, purchases, transactions, assets, liabilities, incomes, expenses, capital, and the like. Ledgers may provide a history of transactions that may be associated with time. Ledgers may be centralized or decentralized/distributed. A centralized ledger may be a document that is controlled, updated, or viewable by one or more selected entities or a clearinghouse and wherein changes or updates to the ledger are governed or controlled by the entity or clearinghouse. A distributed ledger may be a ledger that is distributed across a plurality of entities, participants or regions which may independently, concurrently, or consensually, update, or modify their copies of the ledger. Ledgers and distributed ledgers may include security measures and cryptographic functions for signing, concealing, or verifying content. In the case of distributed ledgers, blockchain technology may be used. In the case of distributed ledgers implemented using blockchain, the ledger may be Merkle trees comprising a linked list of nodes in which each node contains hashed or encrypted transactional data of the previous nodes. Certain records of transactions may not be considered ledgers. A file, computer file, database, or book may or may not be a ledger depending on what data it stores, how the data is organized, maintained, or secured. For example, a list of transactions may not be considered a ledger if it cannot be trusted or verified, and/or if it is based on inconsistent, fraudulent, or incomplete data. Data in ledgers may be organized in any format such as tables, lists, binary streams of data, or the like which may depend on convenience, source of data, type of data, environment, applications, and the like. A ledger that is shared among various entities may not be a distributed ledger, but the distinction of distributed may be based on which entities are authorized to make changes to the ledger and/or how the changes are shared and processed among the different entities. Accordingly, the benefits of the present disclosure may be applied in a wide variety of data, and any such data may be considered ledgers herein, while in certain embodiments a given data may not be considered a ledger herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about contemplated ledgers and distributed ledger ordinarily available to that person, can readily determine which aspects of the present disclosure can be utilized to implement, and/or will benefit a particular ledger. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a ledger and/or whether aspects of the present disclosure can benefit or enhance the contemplated ledger include, without limitation: the security of the data in the ledger (can the data be tampered or modified), the time associated with making changes to the data in the ledger, cost of making changes (computationally and monetarily), detail of data, organization of data (does the data need to be processed for use in an application), who controls the ledger (can the party be trusted or relied to manage the ledger), confidentiality of the data (who can see or track the data in the ledger), size of the infrastructure, communication requirements (distributed ledgers may require a communication interface or specific infrastructure), resiliency. While specific examples of blockchain services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0176] The term loan (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a loan may be an agreement related to an asset that is borrowed, and that is expected to be returned in kind (e.g., money borrowed and money returned) or as an agreed transaction (e.g., a first good or service is borrowed, and money, a second good or service, or a combination, is returned). Assets may be money, property, time, physical objects, virtual objects, services, a right (e.g., a ticket, a license, or other right), a depreciation amount, a credit (e.g., a tax credit, an emissions credit, etc.), an agreed assumption of a risk or liability, and/or any combination thereof. A loan may be based on a formal or informal agreement between a borrower and a lender wherein a lender may provide an asset to the borrower for a predefined amount of time, a variable period of time, or indefinitely. Lenders and borrowers may be individuals, entities, corporations, governments, groups of people, organizations, and the like. Loan types may include mortgage loans, personal loans, secured loans, unsecured loans, concessional loans, commercial loans, microloans, and the like. The agreement between the borrower and the lender may specify terms of the loan. The borrower may be required to return an asset or repay with a different asset than was borrowed. In some cases, a loan may require interest to be repaid on the borrowed asset. Borrowers and lenders may be intermediaries between other entities and may never possess or use the asset. In some embodiments, a loan may not be associated with direct transfer of goods but may be associated with usage rights or shared usage rights. In certain embodiments, the agreement between the borrower and the lender may be executed between the borrower and the lender, and/or executed between an intermediary (e.g., a beneficiary of a loan right such as through a sale of the loan). In certain embodiment, the agreement between the borrower and the lender may be executed through services herein, such as through a smart contract service that determines at least a portion of the terms and conditions of the loans, and in certain embodiments may commit the borrower and/or the lender to the terms of the agreement, which may be a smart contract. In certain embodiments, the smart contract service may populate the terms of the agreement, and present them to the borrower and/or lender for execution. In certain embodiments, the smart contract service may automatically commit one of the borrower or the lender to the terms (at least as an offer), and may present the offer to the other one of the borrower or the lender for execution. In certain embodiments, a loan agreement may include multiple borrowers and/or multiple lenders, for example where a set of loans includes a number of beneficiaries of payment on the set of loans, and/or a number of borrowers on the set of loans. In certain embodiments, the risks and/or obligations of the set of loans may be individualized (e.g., each borrower and/or lender is related to specific loans of the set of loans), apportioned (e.g., a default on a particular loan has an associated loss apportioned between the lenders), and/or combinations of these (e.g., one or more subsets of the set of loans is treated individually and/or apportioned).
[0177] Certain agreements may not be considered a loan. An agreement to transfer or borrow assets may not be a loan depending on what assets are transferred, how the assets were transferred, or the parties involved. For example, in some cases, the transfer of assets may be for an indefinite time and may be considered a sale of the asset or a permanent transfer. Likewise, if an asset is borrowed or transferred without clear or definite terms or lack of consensus between the lender and the borrower it may, in some cases, not be considered a loan. An agreement may be considered a loan even if a formal agreement is not directly codified in a written agreement as long as the parties willingly and knowingly agreed to the arrangement, and/or ordinary practices (e.g., in a particular industry) may treat the transaction as a loan. Accordingly, the benefits of the present disclosure may be applied in a wide variety of agreements, and any such agreement may be considered a loan herein, while in certain embodiments a given agreement may not be considered a loan herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about contemplated loans ordinarily available to that person, can readily determine which aspects of the present disclosure implement a loan, utilize a loan, or benefit a particular loan transaction. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan and/or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, without limitation: the value of the assets involved, the ability of the borrower to return or repay the loan, the types of assets involved (e.g., whether the asset is consumed through utilization), the repayment time frame associated with the loan, the interest on the loan, how the agreement of the loan was arranged, formality of the agreement, detail of the agreement, the detail of the agreements of the loan, the collateral attributes associated with the loan, and/or the ordinary business expectations of any of the foregoing in a particular context. While specific examples of loans and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0178] The term loan related event(s) (and similar terms, including loan-related events) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a loan related events may include any event related to terms of the loan or events triggered by the agreement associated with the loan. Loan-related events may include default on loan, breach of contract, fulfillment, repayment, payment, change in interest, late fee assessment, refund assessment, distribution, and the like. Loan-related events may be triggered by explicit agreement terms; for example - an agreement may specify a rise in interest rate after a time period has elapsed from the beginning of the loan; the rise in interest rate triggered by the agreement may be a loan related event. Loan-related events may be triggered implicitly by related loan agreement terms. In certain embodiments, any occurrence that may be considered relevant to assumptions of the loan agreement, and/or expectations of the parties to the loan agreement, may be considered an occurrence of an event. For example, if collateral for a loan is expected to be replaceable (e.g., an inventory as collateral), then a change in inventory levels may be considered an occurrence of a loan related event. In another example, if review and/or confirmation of the collateral is expected, then a lack of access to the collateral, the disablement or failure of a monitoring sensor, etc. may be considered an occurrence of a loan related event. In certain embodiments, circuits, controllers, or other devices described herein may automatically trigger the determination of a loan-related events. In some embodiments, loan-related events may be triggered by entities that manage loans or loan-related contracts. Loan-related events may be conditionally triggered based on one or more conditions in the loan agreement. Loan related events may be related to tasks or requirements that need to be completed by the lender, borrower, or a third party. Certain events may be considered loan-related events in certain embodiments and/or in certain contexts, but may not be considered a loan-related event in another embodiment or context. Many events may be associated with loans but may be caused by external triggers not associated with a loan. However, in certain embodiments, an externally triggered event (e.g., a commodity price change related to a collateral item) may be loan-related events in certain embodiments. For example, renegotiation of loan terms initiated by a lender may not be considered a loan related event if the terms and/or performance of the existing loan agreement did not trigger the renegotiation. Accordingly, the benefits of the present disclosure may be applied in a wide variety of events, and any such event may be considered a loan related event herein, while in certain embodiments given events may not be considered a loan related event herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure may be considered a loan-related event for the contemplated system and/or for particular transactions supported by the system. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan related event and/or whether aspects of the present disclosure can benefit or enhance the contemplated transaction system include, without limitation: the impact of the related event on the loan (events that cause default or termination of the loan may have higher impact), the cost (capital and/or operating) associated with the event, the cost (capital and/or operating) associated with monitoring for an occurrence of the event, the entities responsible for responding to the event, a time period and/or response time associated with the event (e.g., time required to complete the event and time that is allotted from the time the event is triggered to when processing or detection of the event is desired to occur), the entity responsible for the event, the data required for processing the event (e.g., confidential information may have different safeguards or restrictions), the availability of mitigating actions if an undetected event occurs, and/or the remedies available to an at-risk party if the event occurs without detection. While specific examples of loan-related events and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0179] The term loan-related activities (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a loan related activity may include activities related to the generation, maintenance, termination, collection, enforcement, servicing, billing, marketing, ability to perform, or negotiation of a loan. Loan-related activity may include activities related to the signing of a loan agreement or a promissory note, review of loan documents, processing of payments, evaluation of collateral, evaluation of compliance of the borrower or lender to the loan terms, renegotiation of terms, perfection of security or collateral for the loan, and/or a negation of terms. Loan-related activities may relate to events associated with a loan before formal agreement on the terms, such as activities associated with initial negotiations. Loan-related activities may relate to events during the life of the loan and after the termination of a loan. Loan-related activities may be performed by a lender, borrower, or a third party. Certain activities may not be considered loan related activities services individually but may be considered loan related activities based on the specificity of the activity to the loan lifecycle- for example, billing or invoicing related to outstanding loans may be considered a loan related activity, however when the invoicing or billing of loans is combined with billing or invoicing for non loan-related elements the invoicing may not be considered a loan related activity. Some activities may be performed in relation to an asset regardless if a loan is associated with the asset; in these cases, the activity may not be considered a loan related activity. For example, regular audits related to an asset may occur regardless if the asset is associated with a loan and may not be considered a loan related activity. In another example, a regular audit related to an asset may be required by a loan agreement and would not typically occur but for the association with a loan, in this case, the activity may be considered a loan related activity. In some embodiments, activities may be considered loan-related activities if the activity would otherwise not occur if the loan were not active or present, but may still be considered a loan-related activity in some instances (e.g., if auditing occurs normally, but the lender does not have the ability to enforce or review the audit, then the audit may be considered a loan-related activity even though it already occurs otherwise). Accordingly, the benefits of the present disclosure may be applied in a wide variety of events, and any such event may be considered a loan related event herein, while in certain embodiments given events may not be considered a loan related events herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine a loan related activity for the purposes of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan related activity and/or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, without limitation: the necessity of the activity for the loan (can the loan agreement or terms be satisfied without the activity), the cost of the activity, the specificity of the activity to the loan (is the activity similar or identical to other industries), time involved in the activity, the impact of the activity on a loan life cycle, entity performing the activity, amount of data required for the activity (does the activity require confidential information related to the loan, or personal information related to the entities), and/or the ability of parties to enforce and/or review the activity. While specific examples of loan- related events and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0180] The terms loan-terms, loan terms, terms for a loan, terms and conditions, and the like as utilized herein should be understood broadly (“loan terms”). Without limitation to any other aspect or description of the present disclosure, loan terms may relate to conditions, rules, limitations, contract obligations, and the like related to the timing, repayment, origination, and other enforceable conditions agreed to by the borrower and the lender of the loan. Loan terms may be specified in a formal contract between a borrower and the lender. Loan terms may specify aspects of an interest rate, collateral, foreclose conditions, consequence of debt, payment options, payment schedule, a covenant, and the like. Loan terms may be negotiable or may change during the life of a loan. Loan terms may be change or be affected by outside parameters such as market prices, bond prices, conditions associated with a lender or borrower, and the like. Certain aspects of a loan may not be considered loan terms. In certain embodiments, aspects of loan that have not been formally agreed upon between a lender and a borrower, and/or that are not ordinarily understood in the course of business (and/or the particular industry) may not be considered loan terms. Certain aspects of a loan may be preliminary or informal until they have been formally agreed or confirmed in a contract or a formal agreement. Certain aspects of a loan may not be considered loan terms individually but may not be considered loan terms based on the specificity of the aspect to a specific loan. Certain aspects of a loan may not be considered loan terms at a particular time during the loan, but may be considered loan terms at another time during the loan (e.g., obligations and/or waivers that may occur through the performance of the parties, and/or expiration of a loan term). For example, an interest rate may generally not be considered a loan term until it is defined in relation of a loan and defined as to how the interest compounded (annual, monthly), calculated, and the like. An aspect of a loan may not be considered a term if it is indefinite or unenforceable. Some aspects may be manifestations or related to terms of a loan but may themselves not be the terms. For example, a loan term be the repayment period of a loan, such as one year. The term may not specify how the loan is to be repaid in the year. The loan may be repaid with 12 monthly payments or one annual payment. A monthly payment plan in this case may not be considered a loan term as it just one or many options for repayment not directly specified by a loan. Accordingly, the benefits of the present disclosure may be applied in a wide variety of loan aspects, and any such aspect may be considered a loan term herein, while in certain embodiments given aspects may not be considered loan terms herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure are loan terms for the contemplated system.
[0181] Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan term and/or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, without limitation: the enforceability of the terms (can the conditions be enforced by the lender or the lender or the borrower), the cost of enforcing the terms (amount of time, or effort required ensure the conditions are being followed), the complexity of the terms (how easily can they be followed or understood by the parties involved, are the terms error prone or easily misunderstood), entities responsible for the terms, fairness of the terms, stability of the terms (how often do they change), observability of the terms (can the terms be verified by a another party), favorability of the terms to one party (do the terms favor the borrower or the lender), risk associated with the loan (terms may depend on the probability that the loan may not be repaid), characteristics of the borrower or lender (their ability to meet the terms), and/or ordinary expectations for the loan and/or related industry.
[0182] While specific examples of loan terms are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0183] The term loan conditions, loan-conditions, conditions for a loan, terms and conditions, and the like as utilized herein should be understood broadly (“loan conditions”). Without limitation to any other aspect or description of the present disclosure, loan conditions may relate to rules, limits, and/or obligations related to a loan. Loan conditions may relate to rules or necessary obligations for obtaining a loan, for maintaining a loan, for applying for a loan, for transferring a loan, and the like. Loan conditions may include principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, treatment of collateral, access to collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, conditions related to other debts of the borrower, and a consequence of default.
[0184] Certain aspects of a loan may not be considered loan conditions. Aspects of loan that have not been formally agreed upon between a lender and a borrower, and/or that are not ordinarily understood in the course of business (and/or the particular industry), may not be considered loan conditions. Certain aspects of a loan may be preliminary or informal until they have been formally agreed or confirmed in a contract or a formal agreement. Certain aspects of a loan may not be considered loan conditions individually but may be considered loan conditions based on the specificity of the aspect to a specific loan. Certain aspects of a loan may not be considered loan conditions at a particular time during the loan, but may be considered loan conditions at another time during the loan (e.g., obligations and/or waivers that may occur through the performance of the parties, and/or expiration of a loan condition). Accordingly, the benefits of the present disclosure may be applied in a wide variety of loan aspects, and any such aspect may be considered loan conditions herein, while in certain embodiments given aspects may not be considered loan conditions herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure are loan conditions for the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan condition and/or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, without limitation: the enforceability of the condition (can the conditions be enforced by the lender or the borrower), the cost of enforcing the condition (amount of time, or effort required ensure the conditions are being followed), the complexity of the condition (how easily can they be followed or understood by the parties involved, are the conditions error prone or easily misunderstood), entities responsible for the conditions, fairness of the conditions, observability of the conditions (can the conditions be verified by a another party), favorability of the conditions to one party (do the conditions favor the borrower or the lender), risk associated with the loan (conditions may depend on the probability that the loan may not be repaid), and/or ordinary expectations for the loan and/or related industry. [0185] While specific examples of loan conditions are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0186] The term loan collateral, collateral, item of collateral, collateral item, and the like as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a loan collateral may relate to any asset or property that a borrower promises to a lender as backup in exchange for a loan, and/or as security for the loan. Collateral may be any item of value that is accepted as an alternate form of repayment in case of default on a loan. Collateral may include any number of physical or virtual items such as a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. Collateral may include more than one item or types of items. [0187] A collateral item may describe an asset, a property, a value, or other item defined as a security for a loan or a transaction. A set of collateral items may be defined, and within that set substitution, removal or addition of collateral items may be effected. For example, a collateral item may be, without limitation: a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, or an item of personal property, or the like. If a set or plurality of collateral items is defined, substitution, removal or addition of collateral items may be effected, such as substituting, removing or adding a collateral item to or from a set of collateral items. Without limitation to any other aspect or description of the present disclosure, a collateral item or set of collateral items may also be used in conjunction with other terms to an agreement or loan, such as a representation, a warranty, an indemnity, a covenant, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. In certain embodiments, a smart contract may calculate whether a borrower has satisfied conditions or covenants and in cases where the borrower has not satisfied such conditions or covenants, may enable automated action or trigger another conditions or terms that may affect the status, ownership or transfer of a collateral item, or initiate the substitution, removal, or addition of collateral items to a set of collateral for a loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about collateral items, can readily determine the purposes and use of collateral items in various embodiments and contexts disclosed herein, including the substitution, removal, and addition thereof.
[0188] While specific examples of loan collateral are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0189] The term smart contract services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a smart contract service includes any service or application that manages a smart contract or a smart lending contract. For example, the smart contract service may specify terms and conditions of a smart contract, such as in a rules database, or process output from a set of valuation services and assign items of collateral sufficient to provide security for a loan. Smart contract services may automatically execute a set of rules or conditions that embody the smart contract, wherein the execution may be based on or take advantage of collected data. Smart contract services may automatically initiate a demand for payment of a loan, automatically initiate a foreclosure process, automatically initiate an action to claim substitute or backup collateral or transfer ownership of collateral, automatically initiate an inspection process, automatically change a payment or interest rate term that is based on the collateral, and may also configure smart contracts to automatically undertake a loan-related action. Smart contracts may govern at least one of loan terms and conditions, loan-related events, and loan-related activities. Smart contracts may be agreements that are encoded as computer protocols and may facilitate, verify, or enforce the negotiation or performance of a smart contract. Smart contracts may or may not be one or more of partially or fully self-executing, or partially or fully self-enforcing.
[0190] Certain processes may not be considered to be smart-contract related individually, but may be considered smart-contract related in an aggregated system - for example automatically undertaking a loan-related action may not be smart contract-related in one instance, but in another instance, may be governed by terms of a smart contract. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a smart contract or smart contract service herein, while in certain embodiments a given service may not be considered a smart contract service herein. [0191] One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to implement a smart contract service and/or enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system includes a smart contract service or smart contract and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: ability to transfer ownership of collateral automatically in response to an event; automated actions available upon a finding of covenant compliance (or lack of compliance); the amenity of the collateral to clustering, re-balancing, distribution, addition, substitution, and removal of items from collateral; the modification parameters of an aspect of a loan in response to an event (e.g., timing, complexity, suitability for the loan type, etc.); the complexity of terms and conditions of loans for the system, including benefits from rapid determination and/or predictions of changes to entities (e.g., in the collateral, a financial condition of a party, offset collateral, and/or in an industry related to a party) related to the loan; the suitability of automated generation of terms and conditions and/or execution of terms and conditions for the types of loans, parties, and/or industries contemplated for the system; and the like. While specific examples of smart contract services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0192] The term IoT system (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, an IoT system includes any system of uniquely identified and interrelated computing devices, mechanical and digital machines, sensors, and objects that are able to transfer data over a network without intervention. Certain components may not be considered an IoT system individually, but may be considered an IoT system in an aggregated system - for example, a single networked sensor, smart speaker, and/or medical device may be not an IoT system, but may be a part of a larger system and/or be accumulated with a number of other similar components to be considered an IoT system and/or a part of an IoT system. In certain embodiments, a system may be considered an IoT system for some purposes but not for other purposes - for example, a smart speaker may be considered part of an IoT system for certain operations, such as for providing surround sound, or the like, but not part of an IoT system for other operations such as directly streaming content from a single, locally networked source. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such systems are IoT systems, and/or which type of IoT system. For example, one group of medical devices may not, at a given time, be sharing to an aggregated HER database, while another group of medical devices may be sharing data to an aggregate HER for the purposes of a clinical study, and accordingly one group of medical devices may be an IoT system, while the other is not. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered an IoT system herein, while in certain embodiments a given system may not be considered an IoT system herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, how to combine processes and systems from the present disclosure to enhance operations of the contemplated system, and which circuits, controllers, and/or devices include an IoT system for the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is an IoT system and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: the transmission environment of the system (e.g., availability of low power, inter-device networking); the shared data storage of a group of devices; establishment of a geofence by a group of devices; service as blockchain nodes; the performance of asset, collateral, or entity monitoring; the relay of data between devices; ability to aggregate data from a plurality of sensors or monitoring devices, and the like. While specific examples of IoT systems and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0193] The term data collection services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a data collection service includes any service that collects data or information, including any circuit, controller, device, or application that may store, transmit, transfer, share, process, organize, compare, report on and/or aggregate data. The data collection service may include data collection devices (e.g., sensors) and/or may be in communication with data collection devices. The data collection service may monitor entities, such as to identify data or information for collection. The data collection service may be event-driven, run on a periodic basis, or retrieve data from an application at particular points in the application’ s execution. Certain processes may not be considered to be a data collection service individually, but may be considered a data collection service in an aggregated system - for example, a networked storage device may be a component of a data collection service in one instance, but in another instance, may have stand alone functionality. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a data collection service herein, while in certain embodiments a given service may not be considered a data collection service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure implement a data collection service and/or to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a data collection service and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: ability to modify a business rule on the fly and alter a data collection protocol; perform real-time monitoring of events; connection of a device for data collection to a monitoring infrastructure, execution of computer readable instructions that cause a processor to log or track events; use of an automated inspection system; occurrence of sales at a networked point-of-sale; need for data from one or more distributed sensors or cameras; and the like. While specific examples of data collection services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0194] The term data integration services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a data integration service includes any service that integrates data or information, including any device or application that may extract, transform, load, normalize, compress, decompress, encode, decode, and otherwise process data packets, signals, and other information. The data integration service may monitor entities, such as to identify data or information for integration. The data integration service may integrate data regardless of required frequency, communication protocol, or business rules needed for intricate integration patterns. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a data integration service herein, while in certain embodiments a given service may not be considered a data integration service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to implement a data integration service and/or enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a data integration service and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: ability to modify a business rule on the fly and alter a data integration protocol; communication with third party databases to pull in data to integrate with; synchronization of data across disparate platforms; connection to a central data warehouse; data storage capacity, processing capacity, and/or communication capacity distributed throughout the system; the connection of separate, automated workflows; and the like. While specific examples of data integration services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0195] The term computational services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, computational services may be included as a part of one or more services, platforms, or microservices, such as blockchain services, data collection services, data integration services, valuation services, smart contract services, data monitoring services, data mining, and/or any service that facilitates collection, access, processing, transformation, analysis, storage, visualization, or sharing of data. Certain processes may not be considered to be a computational service. For example, a process may not be considered a computational service depending on the sorts of rules governing the service, an end product of the service, or the intent of the service. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a computational service herein, while in certain embodiments a given service may not be considered a computational service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to implement one or more computational service, and/or to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a computational service and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: agreement-based access to the service; mediate an exchange between different services; provides on demand computational power to a web service; accomplishes one or more of monitoring, collection, access, processing, transformation, analysis, storage, integration, visualization, mining, or sharing of data. While specific examples of computational services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure. [0196] The term sensor as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a sensor may be a device, module, machine, or subsystem that detects or measures a physical quality, event, or change. In embodiments, may record, indicate, transmit, or otherwise respond to the detection or measurement. Examples of sensors may be sensors for sensing movement of entities, for sensing temperatures, pressures or other attributes about entities or their environments, cameras that capture still or video images of entities, sensors that collect data about collateral or assets, such as, for example, regarding the location, condition (health, physical, or otherwise), quality, security, possession, or the like. In embodiments, sensors may be sensitive to, but not influential on, the property to be measured but insensitive to other properties. Sensors may be analog or digital. Sensors may include processors, transmitters, transceivers, memory, power, sensing circuit, electrochemical fluid reservoirs, light sources, and the like. Further examples of sensors contemplated for use in the system include biosensors, chemical sensors, black silicon sensor, IR sensor, acoustic sensor, induction sensor, motion sensor, optical sensor, opacity sensor, proximity sensor, inductive sensor, Eddy-current sensor, passive infrared proximity sensor, radar, capacitance sensor, capacitive displacement sensor, hall-effect sensor, magnetic sensor, GPS sensor, thermal imaging sensor, thermocouple, thermistor, photoelectric sensor, ultrasonic sensor, infrared laser sensor, inertial motion sensor, MEMS internal motion sensor, ultrasonic 3D motion sensor, accelerometer, inclinometer, force sensor, piezoelectric sensor, rotary encoders, linear encoders, ozone sensor, smoke sensor, heat sensor, magnetometer, carbon dioxide detector, carbon monoxide detector, oxygen sensor, glucose sensor, smoke detector, metal detector, rain sensor, altimeter, GPS, detection of being outside, detection of context, detection of activity, object detector (e.g. collateral), marker detector (e.g. geo-location marker), laser rangefinder, sonar, capacitance, optical response, heart rate sensor, or an RF/micropower impulse radio (MIR) sensor. In certain embodiments, a sensor may be a virtual sensor - for example determining a parameter of interest as a calculation based on other sensed parameters in the system. In certain embodiments, a sensor may be a smart sensor - for example reporting a sensed value as an abstracted communication (e.g., as a network communication) of the sensed value. In certain embodiments, a sensor may provide a sensed value directly (e.g., as a voltage level, frequency parameter, etc.) to a circuit, controller, or other device in the system. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit from a sensor. Certain considerations for the person of skill in the art, in determining whether a contemplated device is a sensor and/or whether aspects of the present disclosure can benefit from or be enhanced by the contemplated sensor include, without limitation: the conditioning of an activation/deactivation of a system to an environmental quality; the conversion of electrical output into measured quantities; the ability to enforce a geofence; the automatic modification of a loan in response to change in collateral; and the like. While specific examples of sensors and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure. [0197] The term storage condition and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, storage condition includes an environment, physical location, environmental quality, level of exposure, security measures, maintenance description, accessibility description, and the like related to the storage of an asset, collateral, or an entity specified and monitored in a contract, loan, or agreement or backing the contract, loan or other agreement, and the like. Based on a storage condition of a collateral, an asset, or entity, actions may be taken to, maintain, improve, and/or confirm a condition of the asset or the use of that asset as collateral. Based on a storage condition, actions may be taken to alter the terms or conditions of a loan or bond. Storage condition may be classified in accordance with various rules, thresholds, conditional procedures, workflows, model parameters, and the like and may be based on self-reporting or on data from Internet of Things devices (IoT data), data from a set of environmental condition sensors, data from a set of social network analytic services and a set of algorithms for querying network domains, social media data, crowdsourced data, and the like. The storage condition may be tied to a geographic location relating to the collateral, the issuer, the borrower, the distribution of the funds or other geographic locations. Examples of IoT data may include images, sensor data, location data, and the like. Examples of social media data or crowdsourced data may include behavior of parties to the loan, financial condition of parties, adherence to a parties to a term or condition of the loan, or bond, or the like. Parties to the loan may include issuers of a bond, related entities, lender, borrower, 3rd parties with an interest in the debt. Storage condition may relate to an asset or type of collateral such as a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. The storage condition may include an environment where environment may include an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle. Actions based on the storage condition of a collateral, an asset or an entity may include managing, reporting on, altering, syndicating, consolidating, terminating, maintaining, modifying terms and/or conditions, foreclosing an asset, or otherwise handling a loan, contract, or agreement. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated storage condition, can readily determine which aspects of the present disclosure will benefit a particular application for a storage condition. Certain considerations for the person of skill in the art, or embodiments of the present disclosure in choosing an appropriate storage condition to manage and/or monitor, include, without limitation: the legality of the condition given the jurisdiction of the transaction, the data available for a given collateral, the anticipated transaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross transaction/loan amount, the credit scores of the borrower and the lender, ordinary practices in the industry, and other considerations. While specific examples of storage conditions are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.
[0198] The term geolocation and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, geolocation includes the identification or estimation of the real-world geographic location of an object, including the generation of a set of geographic coordinates (e.g. latitude and longitude) and/or street address. Based on a geolocation of a collateral, an asset, or entity, actions may be taken to maintain or improve a condition of the asset or the use of that asset as collateral. Based on a geolocation, actions may be taken to alter the terms or conditions of a loan or bond. Based on a geolocation, determinations or predictions related to a transaction may be performed - for example based upon the weather, civil unrest in a particular area, and/or local disasters (e.g., an earthquake, flood, tornado, hurricane, industrial accident, etc.). Geolocations may be determined in accordance with various rules, thresholds, conditional procedures, workflows, model parameters, and the like and may be based on self-reporting or on data from Internet of Things devices, data from a set of environmental condition sensors, data from a set of social network analytic services and a set of algorithms for querying network domains, social media data, crowdsourced data, and the like. Examples of geolocation data may include GPS coordinates, images, sensor data, street address, and the like. Geolocation data may be quantitative (e.g., longitude/latitude, relative to a plat map, etc.) and/or qualitative (e.g., categorical such as “coastal”, “rural”, etc.; “within New York City”, etc.). Geolocation data may be absolute (e.g., GPS location) or relative (e.g., within 100 yards of an expected location). Examples of social media data or crowdsourced data may include behavior of parties to the loan as inferred by their geolocation, financial condition of parties inferred by geolocation, adherence of parties to a term or condition of the loan, or bond, or the like. Geolocation may be determined for an asset or type of collateral such as a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. Geolocation may be determined for an entity such as one of the parties, a third-party (e.g., an inspection service, maintenance service, cleaning service, etc. relevant to a transaction), or any other entity related to a transaction. The geolocation may include an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle. Actions based on the geolocation of a collateral, an asset or an entity may include managing, reporting on, altering, syndicating, consolidating, terminating, maintaining, modifying terms and/or conditions, foreclosing an asset, or otherwise handling a loan, contract, or agreement. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system, can readily determine which aspects of the present disclosure will benefit a particular application for a geolocation, and which location aspect of an item is a geolocation for the contemplated system. Certain considerations for the person of skill in the art, or embodiments of the present disclosure in choosing an appropriate geolocation to manage, include, without limitation: the legality of the geolocation given the jurisdiction of the transaction, the data available for a given collateral, the anticipated transaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross transaction/loan amount, the frequency of travel of the borrower to certain jurisdictions and other considerations, the mobility of the collateral, and/or a likelihood of location-specific event occurrence relevant to the transaction (e.g., weather, location of a relevant industrial facility, availability of relevant services, etc.). While specific examples of geolocation are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.
[0199] The term jurisdictional location and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, jurisdictional location refers to the laws and legal authority governing a loan entity. The jurisdictional location may be based on a geolocation of an entity, a registration location of an entity (e.g. a ship’s flag state, a state of incorporation for a business, and the like), a granting state for certain rights such as intellectual priority, and the like. In certain embodiments, a jurisdictional location may be one or more of the geolocations for an entity in the system. In certain embodiments, a jurisdictional location may not be the same as the geolocation of any entity in the system (e.g., where an agreement specifies some other jurisdiction). In certain embodiments, a jurisdictional location may vary for entities in the system (e.g., borrower at A, lender at B, collateral positioned at C, agreement enforced at D, etc.). In certain embodiments, a jurisdictional location for a given entity may vary during the operations of the system (e.g., due to movement of collateral, related data, changes in terms and conditions, etc.). In certain embodiments, a given entity of the system may have more than one jurisdictional location (e.g., due to operations of the relevant law, and/or options available to one or more parties), and/or may have distinct jurisdictional locations for different purposes. A jurisdictional location of an item of collateral, an asset, or entity, actions may dictate certain terms or conditions of a loan or bond, and/or may indicate different obligations for notices to parties, foreclosure and/or default execution, treatment of collateral and/or debt security, and/or treatment of various data within the system. While specific examples of jurisdictional location are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.
[0200] The terms token of value, token, and variations such as cryptocurrency token, and the like, as utilized herein, in the context of increments of value, may be understood broadly to describe either: (a) a unit of currency or cryptocurrency (e.g. a cryptocurrency token), and (b) may also be used to represent a credential that can be exchanged for a good, service, data or other valuable consideration (e.g. a token of value). Without limitation to any other aspect or description of the present disclosure, in the former case, a token may also be used in conjunction with investment applications, token-trading applications, and token-based marketplaces. In the latter case, a token can also be associated with rendering consideration, such as providing goods, services, fees, access to a restricted area or event, data, or other valuable benefit. Tokens can be contingent (e.g. contingent access token) or not contingent. For example, a token of value may be exchanged for accommodations, (e.g. hotel rooms), dining/food goods and services, space (e.g. shared space, workspace, convention space, etc.), fitness/wellness goods or services, event tickets or event admissions, travel, flights or other transportation, digital content, virtual goods, license keys, or other valuable goods, services, data, or consideration. Tokens in various forms may be included where discussing a unit of consideration, collateral, or value, whether currency, cryptocurrency, or any other form of value such as goods, services, data or other benefits. One of skill in the art, having the benefit of the disclosure herein and knowledge about a token, can readily determine the value symbolized or represented by a token, whether currency, cryptocurrency, good, service, data, or other value. While specific examples of tokens are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0201] The term pricing data as utilized herein may be understood broadly to describe a quantity of information such as a price or cost, of one or more items in a marketplace. Without limitation to any other aspect or description of the present disclosure, pricing data may also be used in conjunction with spot market pricing, forward market pricing, pricing discount information, promotional pricing, and other information relating to the cost or price of items. Pricing data may satisfy one or more conditions, or may trigger application of one or more rules of a smart contract. Pricing data may be used in conjunction with other forms of data such as market value data, accounting data, access data, asset and facility data, worker data, event data, underwriting data, claims data or other forms of data. Pricing data may be adjusted for the context of the valued item (e.g., condition, liquidity, location, etc.) and/or for the context of a particular party. One of skill in the art, having the benefit of the disclosure herein and knowledge about pricing data, can readily determine the purposes and use of pricing data in various embodiments and contexts disclosed herein.
[0202] Without limitation to any other aspect or description of the present disclosure, a token includes any token including, without limitation, a token of value, such as collateral, an asset, a reward, such as in a token serving as representation of value, such as a value holding voucher that can be exchanged for goods or services. Certain components may not be considered tokens individually, but may be considered tokens in an aggregated system - for example, a value placed on an asset may not be in itself be a token, but the value of an asset may be placed in a token of value, such as to be stored, exchanged, traded, and the like. For instance, in a non-limiting example, a blockchain circuit may be structured to provide lenders a mechanism to store the value of assets, where the value attributed to the token is stored in a distributed ledger of the blockchain circuit, but the token itself, assigned the value, may be exchanged or traded such as through a token marketplace. In certain embodiments, a toke may be considered a token for some purposes but not for other purposes - for example, a token may be used to as an indication of ownership of an asset, but this use of a token would not be traded as a value where a token including the value of the asset might. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered a token herein, while in certain embodiments a given system may not be considered a token herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a token and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation, access data such as relating to rights of access, tickets, and tokens; use in an investment application such as for investment in shares, interests, and tokens; a token-trading application; a token-based marketplace; forms of consideration such as monetary rewards and tokens; translating the value of a resources in tokens; a cryptocurrency token; indications of ownership such as identity information, event information, and token information; a blockchain-based access token traded in a marketplace application; pricing application such as for setting and monitoring pricing for contingent access rights, underlying access rights, tokens, and fees; trading applications such as for trading or exchanging contingent access rights or underlying access rights or tokens; tokens created and stored on a blockchain for contingent access rights resulting in an ownership (e.g., a ticket); and the like.
[0203] The term financial data as utilized herein may be understood broadly to describe a collection of financial information about an asset, collateral or other item or items. Financial data may include revenues, expenses, assets, liabilities, equity, bond ratings, default, return on assets (ROA), return on investment (ROI), past performance, expected future performance, earnings per share (EPS), internal rate of return (IRR), earnings announcements, ratios, statistical analysis of any of the foregoing (e.g. moving averages), and the like. Without limitation to any other aspect or description of the present disclosure, financial data may also be used in conjunction with pricing data and market value data. Financial data may satisfy one or more conditions, or may trigger application of one or more rules of a smart contract. Financial data may be used in conjunction with other forms of data such as market value data, pricing data, accounting data, access data, asset and facility data, worker data, event data, underwriting data, claims data or other forms of data. One of skill in the art, having the benefit of the disclosure herein and knowledge about financial data, can readily determine the purposes and use of pricing data in various embodiments and contexts disclosed herein.
[0204] The term covenant as utilized herein may be understood broadly to describe a term, agreement or promise, such as performance of some action or inaction. For example, a covenant may relate to behavior of a party or legal status of a party. Without limitation to any other aspect or description of the present disclosure, a covenant may also be used in conjunction with other related terms to an agreement or loan, such as a representation, a warranty, an indemnity, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. A covenant or lack of performance of a covenant may satisfy one or more conditions, or may trigger collection, breach or other terms and conditions. In certain embodiments, a smart contract may calculate whether a covenant is satisfied and in cases where the covenant is not satisfied, may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about covenants, can readily determine the purposes and use of covenants in various embodiments and contexts disclosed herein.
[0205] The term entity as utilized herein may be understood broadly to describe a party, a third- party (e.g., an auditor, regulator, service provider, etc.), and/or an identifiable related object such as an item of collateral related to a transaction. Example entities include an individual, partnership, corporation, limited liability company or other legal organization. Other example entities include an identifiable item of collateral, offset collateral, potential collateral, or the like. For example, an entity may be a given party, such as an individual, to an agreement or loan. Data or other terms herein may be characterized as having a context relating to an entity, such as entity-oriented data. An entity may be characterized with a specific context or application, such as a human entity, physical entity, transactional entity or a financial entity, without limitation. An entity may have representatives that represent or act on its behalf. Without limitation to any other aspect or description of the present disclosure, an entity may also be used in conjunction with other related entities or terms to an agreement or loan, such as a representation, a warranty, an indemnity, a covenant, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. An entity may have a set of attributes such as: a publicly stated valuation, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition, a foreclosure status, a contractual default status, a regulatory violation status, a criminal status, an export controls status, an embargo status, a tariff status, a tax status, a credit report, a credit rating, a website rating, a set of customer reviews for a product of an entity, a social network rating, a set of credentials, a set of referrals, a set of testimonials, a set of behavior, a location, and a geolocation, without limitation. In certain embodiments, a smart contract may calculate whether an entity has satisfied conditions or covenants and in cases where the entity has not satisfied such conditions or covenants, may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about entities, can readily determine the purposes and use of entities in various embodiments and contexts disclosed herein.
[0206] The term party as utilized herein may be understood broadly to describe a member of an agreement, such as an individual, partnership, corporation, limited liability company or other legal organization. For example, a party may be a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, a bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, an accountant or other entities having rights or obligations to an agreement, transaction or loan. A party may characterize a different term, such as transaction as in the term multi-party transaction, where multiple parties are involved in a transaction, or the like, without limitation. A party may have representatives that represent or act on its behalf. In certain embodiments, the term party may reference a potential party or a prospective party - for example an intended lender or borrower interacting with a system, that may not yet be committed to an actual agreement during the interactions with the system. Without limitation to any other aspect or description of the present disclosure, an party may also be used in conjunction with other related parties or terms to an agreement or loan, such as a representation, a warranty, an indemnity, a covenant, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, an entity, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. A party may have a set of attributes such as: an identity, a creditworthiness, an activity, a behavior, a business practice, a status of performance of a contract, information about accounts receivable, information about accounts payable, information about the value of collateral, and other types of information, without limitation. In certain embodiments, a smart contract may calculate whether a party has satisfied conditions or covenants and in cases where the party has not satisfied such conditions or covenants, may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about parties, can readily determine the purposes and use of parties in various embodiments and contexts disclosed herein.
[0207] The term party attribute, entity attribute, or party/entity attribute as utilized herein may be understood broadly to describe a value, characteristic, or status of a party or entity. For example, attributes of a party or entity may be, without limitation: value, quality, location, net worth, price, physical condition, health condition, security, safety, ownership, identity, creditworthiness, activity, behavior, business practice, status of performance of a contract, information about accounts receivable, information about accounts payable, information about the value of collateral, and other types of information, and the like. In certain embodiments, a smart contract may calculate values, status or conditions associated with attributes of a party or entity, and in cases where the party or entity has not satisfied such conditions or covenants, may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about attributes of a party or entity, can readily determine the purposes and use of these attributes in various embodiments and contexts disclosed herein. [0208] The term lender as utilized herein may be understood broadly to describe a party to an agreement offering an asset for lending, proceeds of a loan, and may include an individual, partnership, corporation, limited liability company, or other legal organization. For example, a lender may be a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, an unsecured lender, or other party having rights or obligations to an agreement, transaction or loan offering a loan to a borrower, without limitation. A lender may have representatives that represent or act on its behalf. Without limitation to any other aspect or description of the present disclosure, a party may also be used in conjunction with other related parties or terms to an agreement or loan, such as a borrower, a guarantor, a representation, a warranty, an indemnity, a covenant, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. In certain embodiments, a smart contract may calculate whether a lender has satisfied conditions or covenants and in cases where the lender has not satisfied such conditions or covenants, may enable automated action, a notification or alert, or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about a lender, can readily determine the purposes and use of a lender in various embodiments and contexts disclosed herein.
[0209] The term crowdsourcing services as utilized herein may be understood broadly to describe services offered or rendered in conjunction with a crowdsourcing model or transaction, wherein a large group of people or entities supply contributions to fulfill a need, such as a loan, for the transaction. Crowdsourcing services may be provided by a platform or system, without limitation. A crowdsourcing request may be communicated to a group of information suppliers and by which responses to the request may be collected and processed to provide a reward to at least one successful information supplier. The request and parameters may be configured to obtain information related to the condition of a set of collateral for a loan. The crowdsourcing request may be published. In certain embodiments, without limitation, crowdsourcing services may be performed by a smart contract, wherein the reward is managed by a smart contract that processes responses to the crowdsourcing request and automatically allocates a reward to information that satisfies a set of parameter configured for the crowdsourcing request. One of skill in the art, having the benefit of the disclosure herein and knowledge about crowdsourcing services, can readily determine the purposes and use of crowdsourcing services in various embodiments and contexts disclosed herein.
[0210] The term publishing services as utilized herein may be understood to describe a set of services to publish a crowdsourcing request. Publishing services may be provided by a platform or system, without limitation. In certain embodiments, without limitation, publishing services may be performed by a smart contract, wherein the crowdsourcing request is published or publication is initiated by the smart contract. One of skill in the art, having the benefit of the disclosure herein and knowledge about publishing services, can readily determine the purposes and use of publishing services in various embodiments and contexts disclosed herein.
[0211] The term interface as utilized herein may be understood broadly to describe a component by which interaction or communication is achieved, such as a component of a computer, which may be embodied in software, hardware or a combination thereof. For example, an interface may serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: an application programming interface, a graphic user interface, user interface, software interface, marketplace interface, demand aggregation interface, crowdsourcing interface, secure access control interface, network interface, data integration interface or a cloud computing interface, or combinations thereof. An interface may serve to act as a way to enter, receive or display data, within the scope of lending, refinancing, collection, consolidation, factoring, brokering or foreclosure, without limitation. An interface may serve as an interface for another interface. Without limitation to any other aspect or description of the present disclosure, an interface may be used in conjunction with applications, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. In certain embodiments, an interface may be embodied in software, hardware or a combination thereof, as well as stored on a medium or in memory. One of skill in the art, having the benefit of the disclosure herein and knowledge about an interface, can readily determine the purposes and use of an interface in various embodiments and contexts disclosed herein.
[0212] The term graphical user interface as utilized herein may be understood as a type of interface to allow a user to interact with a system, computer or other interface, in which interaction or communication is achieved through graphical devices or representations. A graphical user interface may be a component of a computer, which may be embodied in computer readable instructions, hardware, or a combination thereof. A graphical user interface may serve a number of different purposes or be configured for different applications or contexts. Such an interface may serve to act as a way to receive or display data using visual representation, stimulus or interactive data, without limitation. A graphical user interface may serve as an interface for another graphical user interface or other interface. Without limitation to any other aspect or description of the present disclosure, a graphical user interface may be used in conjunction with applications, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. In certain embodiments, a graphical user interface may be embodied in computer readable instructions, hardware or a combination thereof, as well as stored on a medium or in memory. Graphical user interfaces may be configured for any input types, including keyboards, a mouse, a touch screen, and the like. Graphical user interfaces may be configured for any desired user interaction environments, including for example a dedicated application, a web page interface, or combinations of these. One of skill in the art, having the benefit of the disclosure herein and knowledge about a graphical user interface, can readily determine the purposes and use of a graphical user interface in various embodiments and contexts disclosed herein.
[0213] The term user interface as utilized herein may be understood as a type of interface to allow a user to interact with a system, computer, or other apparatus, in which interaction or communication is achieved through graphical devices or representations. A user interface may be a component of a computer, which may be embodied in software, hardware, or a combination thereof. The user interface may be stored on a medium or in memory. User interfaces may include drop-down menus, tables, forms, or the like with default, templated, recommended, or pre configured conditions. In certain embodiments, a user interface may include voice interaction. Without limitation to any other aspect or description of the present disclosure, a user interface may be used in conjunction with applications, circuits, controllers, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. User interfaces may serve a number of different purposes or be configured for different applications or contexts. For example, a lender-side user interface may include features to view a plurality of customer profiles, but may be restricted from making certain changes. A debtor-side user interface may include features to view details and make changes to a user account. A 3rd party neutral-side interface (e.g. a 3rd party not having an interest in an underlying transaction, such as a regulator, auditor, etc.) may have features that enable a view of company oversight and anonymized user data without the ability to manipulate any data, and may have scheduled access depending upon the 3rd party and the purpose for the access. A 3rd party interested- side interface (e.g. a 3rd party that may have an interest in an underlying transaction, such as a collector, debtor advocate, investigator, partial owner, etc.) may include features enabling a view of particular user data with restrictions on making changes. Many more features of these user interfaces may be available to implement embodiments of the systems and/or procedures described throughout the present disclosure. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes and systems, and any such processes or systems may be considered a service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a user interface, can readily determine the purposes and use of a user interface in various embodiments and contexts disclosed herein. Certain considerations for the person of skill in the art, in determining whether a contemplated interface is a user interface and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: configurable views, ability to restrict manipulation or views, report functions, ability to manipulate user profile and data, implement regulatory requirements, provide the desired user features for borrowers, lenders, and 3rd parties, and the like.
[0214] Interfaces and dashboards as utilized herein may further be understood broadly to describe a component by which interaction or communication is achieved, such as a component of a computer, which may be embodied in software, hardware, or a combination thereof. Interfaces and dashboards may acquire, receive, present, or otherwise administrate an item, service, offering or other aspect of a transaction or loan. For example, interfaces and dashboards may serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: an application programming interface, a graphic user interface, user interface, software interface, marketplace interface, demand aggregation interface, crowdsourcing interface, secure access control interface, network interface, data integration interface or a cloud computing interface, or combinations thereof. An interface or dashboard may serve to act as a way to receive or display data, within the context of lending, refinancing, collection, consolidation, factoring, brokering or foreclosure, without limitation. An interface or dashboard may serve as an interface or dashboard for another interface or dashboard. Without limitation to any other aspect or description of the present disclosure, an interface may be used in conjunction with applications, circuits, controllers, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. In certain embodiments, an interface or dashboard may be embodied in computer readable instructions, hardware, or a combination thereof, as well as stored on a medium or in memory. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of interfaces and/or dashboards in various embodiments and contexts disclosed herein. [0215] The term domain as utilized herein may be understood broadly to describe a scope or context of a transaction and/or communications related to a transaction. For example, a domain may serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: a domain for execution, a domain for a digital asset, domains to which a request will be published, domains to which social network data collection and monitoring services will be applied, domains to which Internet of Things data collection and monitoring services will be applied, network domains, geolocation domains, jurisdictional location domains, and time domains. Without limitation to any other aspect or description of the present disclosure, one or more domains may be utilized relative to any applications, circuits, controllers, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. In certain embodiments, a domain may be embodied in computer readable instructions, hardware, or a combination thereof, as well as stored on a medium or in memory. One of skill in the art, having the benefit of the disclosure herein and knowledge about a domain, can readily determine the purposes and use of a domain in various embodiments and contexts disclosed herein.
[0216] The term request (and variations) as utilized herein may be understood broadly to describe the action or instance of initiating or asking for a thing (e.g. information, a response, an object, and the like) to be provided. A specific type of request may also serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: a formal legal request (e.g. a subpoena), a request to refinance (e.g. a loan), or a crowdsourcing request. Systems may be utilized to perform requests as well as fulfill requests. Requests in various forms may be included where discussing a legal action, a refinancing of a loan, or a crowdsourcing service, without limitation. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system, can readily determine the value of a request implemented in an embodiment. While specific examples of requests are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0217] The term reward (and variations) as utilized herein may be understood broadly to describe a thing or consideration received or provided in response to an action or stimulus. Rewards can be of a financial type, or non-financial type, without limitation. A specific type of reward may also serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: a reward event, claims for rewards, monetary rewards, rewards captured as a data set, rewards points, and other forms of rewards. Rewards may be triggered, allocated, generated for innovation, provided for the submission of evidence, requested, offered, selected, administrated, managed, configured, allocated, conveyed, identified, without limitation, as well as other actions. Systems may be utilized to perform the aforementioned actions. Rewards in various forms may be included where discussing a particular behavior, or encouragement of a particular behavior, without limitation. In certain embodiments herein, a reward may be utilized as a specific incentive (e.g., rewarding a particular person that responds to a crowdsourcing request) or as a general incentive (e.g., providing a reward responsive to a successful crowdsourcing request, in addition to or alternatively to a reward to the particular person that responded). One of skill in the art, having the benefit of the disclosure herein and knowledge about a reward, can readily determine the value of a reward implemented in an embodiment. While specific examples of rewards are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0218] The term robotic process automation system as utilized herein may be understood broadly to describe a system capable of performing tasks or providing needs for a system of the present disclosure. For example, a robotic process automation system, without limitation, can be configured for: negotiation of a set of terms and conditions for a loan, negotiation of refinancing of a loan, loan collection, consolidating a set of loans, managing a factoring loan, brokering a mortgage loan, training for foreclosure negotiations, configuring a crowdsourcing request based on a set of attributes for a loan, setting a reward, determining a set of domains to which a request will be published, configuring the content of a request, configuring a data collection and monitoring action based on a set of attributes of a loan, determining a set of domains to which the Internet of Things data collection and monitoring services will be applied, and iteratively training and improving based on a set of outcomes. A robotic process automation system may include: a set of data collection and monitoring services, an artificial intelligence system, and another robotic process automation system which is a component of the higher level robotic process automation system. The robotic process automation system may include: at least one of the set of mortgage loan activities and the set of mortgage loan interactions includes activities among marketing activity, identification of a set of prospective borrowers, identification of property, identification of collateral, qualification of borrower, title search, title verification, property assessment, property inspection, property valuation, income verification, borrower demographic analysis, identification of capital providers, determination of available interest rates, determination of available payment terms and conditions, analysis of existing mortgage, comparative analysis of existing and new mortgage terms, completion of application workflow, population of fields of application, preparation of mortgage agreement, completion of schedule to mortgage agreement, negotiation of mortgage terms and conditions with capital provider, negotiation of mortgage terms and conditions with borrower, transfer of title, placement of lien and closing of mortgage agreement. Example and non-limiting robotic process automation systems may include one or more user interfaces, interfaces with circuits and/or controllers throughout the system to provide, request, and/or share data, and/or one or more artificial intelligence circuits configured to iteratively improve one or more operations of the robotic process automation system. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated robotic process automation system, can readily determine the circuits, controllers, and/or devices to include to implement a robotic process automation system performing the selected functions for the contemplated system. While specific examples of robotic process automation systems are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood.
[0219] The term loan-related action (and other related terms such as loan-related event and loan- related activity) are utilized herein and may be understood broadly to describe one or multiple actions, events or activities relating to a transaction that includes a loan within the transaction. The action, event or activity may occur in many different contexts of loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, administration, negotiating, collecting, procuring, enforcing, and data processing (e.g. data collection), or combinations thereof, without limitation. A loan-related action may be used in the form of a noun (e.g. a notice of default has been communicated to the borrower with formal notice, which could be considered a loan-related action). A loan-related action, event, or activity may refer to a single instance, or may characterize a group of actions, events, or activities. For example, a single action such as providing a specific notice to a borrower of an overdue payment may be considered a loan-related action. Similarly, a group of actions from start to finish relating to a default may also be considered a single loan-related action. Appraisal, inspection, funding and recording, without limitation, may all also be considered loan-related actions that have occurred, as well as events relating to the loan, and may also be loan-related events. Similarly, these activities of completing these actions may also be considered loan-related activities (e.g. appraising, inspecting, funding, recording, etc.), without limitation. In certain embodiments, a smart contract or robotic process automation system may perform loan-related actions, loan-related events, or loan-related activities for one or more of the parties, and process appropriate tasks for completion of the same. In some cases the smart contract or robotic process automation system may not complete a loan-related action, and depending upon such outcome this may enable an automated action or may trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about loan-related actions, events, and activities can readily determine the purposes and use of this term in various forms and embodiments as described throughout the present disclosure.
[0220] The term loan-related action, events, and activities, as noted herein, may also more specifically be utilized to describe a context for calling of a loan. A calling of a loan is an action wherein the lender can demand the loan be repaid, usually triggered by some other condition or term, such as delinquent payment(s). For example, a loan-related action for calling of the loan may occur when a borrower misses three payments in a row, such that there is a severe delinquency in the loan payment schedule, and the loan goes into default. In such a scenario, a lender may be initiating loan-related actions for calling of the loan to protect its rights. In such a scenario, perhaps the borrower pays a sum to cure the delinquency and penalties, which may also be considered as a loan-related action for calling of the loan. In some circumstances a smart contract or robotic process automation system may initiate, administrate, or process loan-related actions for calling of the loan, which without limitation, may including providing notice, researching, and collecting payment history, or other tasks performed as a part of the calling of the loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about loan-related actions for calling of the loan, or other forms of the term and its various forms, can readily determine the purposes and use of this term in the context of an event or other various embodiments and contexts disclosed herein.
[0221] The term loan-related action, events, and activities, as noted herein, may also more specifically be utilized to describe a context for payment of a loan. Typically in transactions involving loans, without limitation, a loan is repaid on a payment schedule. Various actions may be taken to provide a borrower with information to pay back the loan, as well as actions for a lender to receive payment for the loan. For example, if a borrower makes a payment on the loan, a loan-related action for payment of the loan may occur. Without limitation, such a payment may comprise several actions that may occur with respect to the payment on the loan, such as: the payment being tendered to the lender, the loan ledger or accounting reflecting that a payment has been made, a receipt provided to the borrower of the payment made, and the next payment being requested of the borrower. In some circumstances a smart contract or robotic process automation system may initiate, administrate, or process such loan-related actions for payment of the loan, which without limitation, may including providing notice to the lender, researching, and collecting payment history, providing a receipt to the borrower, providing notice of the next payment due to the borrower, or other actions associated with payment of the loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about loan-related actions for payment of a loan, or other forms of the term and its various forms, can readily determine the purposes and use of this term in the context of an event or other various embodiments and contexts disclosed herein. [0222] The term loan-related action, events, and activities, as noted herein, may also more specifically be utilized to describe a context for a payment schedule or alternative payment schedule. Typically in transactions involving loans, without limitation, a loan is repaid on a payment schedule, which may be modified over time. Or, such a payment schedule may be developed and agreed in the alternative, with an alternative payment schedule. Various actions may be taken in the context of a payment schedule or alternate payment schedule for the lender or the borrower, such as: the amount of such payments, when such payments are due, what penalties or fees may attach to late payments, or other terms. For example, if a borrower makes an early payment on the loan, a loan-related action for payment schedule and alternative payment schedule of the loan may occur; in such case, perhaps the payment is applied as principal, with the regular payment still being due. Without limitation, loan-related actions for a payment schedule and alternative payment schedule may comprise several actions that may occur with respect to the payment on the loan, such as: the payment being tendered to the lender, the loan ledger or accounting reflecting that a payment has been made, a receipt provided to the borrower of the payment made, a calculation if any fees are attached or due, and the next payment being requested of the borrower. In certain embodiments, an activity to determine a payment schedule or alternative payment schedule may be a loan-related action, event, or activity. In certain embodiments, an activity to communicate the payment schedule or alternative payment schedule (e.g., to the borrower, the lender, or a 3rd party) may be a loan-related action, event, or activity. In some circumstances a smart contract circuit or robotic process automation system may initiate, administrate, or process such loan-related actions for payment schedule and alternative payment schedule, which without limitation, may include providing notice to the lender, researching and collecting payment history, providing a receipt to the borrower, calculating the next due date, calculating the final payment amount and date, providing notice of the next payment due to the borrower, determining the payment schedule or an alternate payment schedule, communicating the payment scheduler or an alternate payment schedule, or other actions associated with payment of the loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about loan-related actions for payment schedule and alternative payment schedule, or other forms of the term and its various forms, can readily determine the purposes and use of this term in the context of an event or other various embodiments and contexts disclosed herein.
[0223] The term regulatory notice requirement (and any derivatives) as utilized herein may be understood broadly to describe an obligation or condition to communicate a notification or message to another party or entity. The regulatory notice requirement may be required under one or more conditions that are triggered, or generally required. For example, a lender may have a regulatory notice requirement to provide notice to a borrower of a default of a loan, or change of an interest rate of a loan, or other notifications relating to a transaction or loan. The regulatory aspect of the term may be attributed to jurisdiction-specific laws, rules, or codes that require certain obligations of communication. In certain embodiments, a policy directive may be treated as a regulatory notice requirement - for example where a lender has an internal notice policy that may exceed the regulatory requirements of one or more of the jurisdictional locations related to a transaction. The notice aspect generally relates to formal communications, which may take many different forms, but may specifically be specified as a particular form of notice, such as a certified mail, facsimile, email transmission, or other physical or electronic form, a content for the notice, and/or a timing requirement related to the notice. The requirement aspect relates to the necessity of a party to complete its obligation to be in compliance with laws, rules, codes, policies, standard practices, or terms of an agreement or loan. In certain embodiments, a smart contract may process or trigger regulatory notice requirements and provide appropriate notice to a borrower. This may be based on location of at least one of: the lender, the borrower, the funds provided via the loan, the repayment of the loan, and the collateral of the loan, or other locations as designated by the terms of the loan, transaction, or agreement. In cases where a party or entity has not satisfied such regulatory notice requirements, certain changes in the rights or obligations between the parties may be triggered - for example where a lender provides a non-compliant notice to the borrower, an automated action or trigger based on the terms and conditions of the loan, and/or based on external information (e.g., a regulatory prescription, internal policy of the lender, etc.) may be effected by a smart contract circuit and/or robotic process automation system may be implemented. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of regulatory notice requirements in various embodiments and contexts disclosed herein.
[0224] The term regulatory notice requirement may also be utilized herein to describe an obligation or condition to communicate a notification or message to another party or entity based upon a general or specific policy, rather than based on a particular jurisdiction, or laws, rules, or codes of a particular location (as in regulatory notice requirement that may be jurisdiction- specific). The regulatory notice requirement may be prudent or suggested, rather than obligatory or required, under one or more conditions that are triggered, or generally required. For example, a lender may have a regulatory notice requirement that is policy based to provide notice to a borrower of a new informational website, or will experience a change of an interest rate of a loan in the future, or other notifications relating to a transaction or loan that are advisory or helpful, rather than mandatory (although mandatory notices may also fall under a policy basis). Thus, in policy based uses of the regulatory notice requirement term, a smart contract circuit may process or trigger regulatory notice requirements and provide appropriate notice to a borrower which may or may not necessarily be required by a law, rule, or code. The basis of the notice or communication may be out of prudence, courtesy, custom, or obligation.
[0225] The term regulatory notice may also be utilized herein to describe an obligation or condition to communicate a notification or message to another party or entity specifically, such as a lender or borrower. The regulatory notice may be specifically directed toward any party or entity, or a group of parties or entities. For example, a particular notice or communication may be advisable or required to be provided to a borrower, such as on circumstances of a borrower’s failure to provide scheduled payments on a loan resulting in a default. As such, such a regulatory notice directed to a particular user, such as a lender or borrower, may be as a result of a regulatory notice requirement that is jurisdiction-specific or policy-based, or otherwise. Thus, in some circumstances a smart contract may process or trigger a regulatory notice and provide appropriate notice to a specific party such as a borrower, which may or may not necessarily be required by a law, rule, or code, but may otherwise be provided out of prudence, courtesy or custom. In cases where a party or entity has not satisfied such regulatory notice requirements to a specific party or parties, it may create circumstances where certain rights may be forgiven by one or more parties or entities, or may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of regulatory notice requirements based in various embodiments and contexts disclosed herein.
[0226] The term regulatory foreclosure requirement (and any derivatives) as utilized herein may be understood broadly to describe an obligation or condition in order to trigger, process or complete default of a loan, foreclosure or recapture of collateral, or other related foreclosure actions. The regulatory foreclosure requirement may be required under one or more conditions that are triggered, or generally required. For example, a lender may have a regulatory foreclosure requirement to provide notice to a borrower of a default of a loan, or other notifications relating to the default of a loan prior to foreclosure. The regulatory aspect of the term may be attributed to jurisdiction-specific laws, rules, or codes, that require certain obligations of communication. The foreclosure aspect generally relates to the specific remedy of foreclosure, or a recapture of collateral property and default of a loan, which may take many different forms, but may be specified in the terms of the loan. The requirement aspect relates to the necessity of a party to complete its obligation in order to be in compliance or performance of laws, rules, codes, or terms of an agreement or loan. In certain embodiments, a smart contract circuit may process or trigger regulatory foreclosure requirements and process appropriate tasks relating to such a foreclosure action. Foreclosure action(s) may be based on a jurisdictional location of at least one of the lender, the borrower, the fund provided via the loan, the repayment of the loan, and the collateral of the loan, or other locations as designated by the terms of the loan, transaction, or agreement. In cases where a party or entity has not satisfied such regulatory foreclosure requirements, certain rights may be forgiven by the party or entity (e.g. a lender), or such a failure to comply with the regulatory notice requirement may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of regulatory foreclosure requirements in various embodiments and contexts disclosed herein.
[0227] The term regulatory foreclosure requirement may also be utilized herein to describe an obligation or to trigger, process, or complete default of a loan, foreclosure or recapture of collateral, or other related foreclosure actions, based upon a general or specific policy rather than based on a particular jurisdiction, or laws, rules, or codes of a particular location (as in regulatory foreclosure requirement that may be jurisdiction- specific). The regulatory foreclosure requirement may be prudent or suggested, rather than obligatory or required, under one or more conditions that are triggered, or generally required. For example, a lender may have a regulatory foreclosure requirement that is policy based to provide notice to a borrower of a default of a loan, or other notifications relating to a transaction or loan that are advisory or helpful, rather than mandatory (although mandatory notices may also fall under a policy basis). Thus, in policy based uses of the regulatory foreclosure requirement term, a smart contract may process or trigger regulatory foreclosure requirements and provide appropriate notice to a borrower which may or may not necessarily be required by a law, rule, or code. The basis of the notice or communication may be out of prudence, courtesy, custom, industry practice, or obligation.
[0228] The term regulatory foreclosure requirements may also be utilized herein to describe an obligation or condition that is to be performed with regard to a specific user, such as a lender or a borrower. The regulatory notice may be specifically directed toward any party or entity, or a group of parties or entities. For example, a particular notice or communication may be advisable or required to be provided to a borrower, such as on circumstances of a borrower’ s failure to provide scheduled payments on a loan resulting in a default. As such, such a regulatory foreclosure requirement is directed to a particular user, such as a lender or borrower, and may be a result of a regulatory foreclosure requirement that is jurisdiction-specific or policy-based, or otherwise. For example, the foreclosure requirement may be related to a specific entity involved with a transaction (e.g., the current borrower has been a customer for 30 years, so s/he receives unique treatment), or to a class of entities (e.g., “preferred” borrowers, or “first time default” borrowers). Thus, in some circumstances a smart contract circuit may process or trigger an obligation or action that must be taken pursuant to a foreclosure, where the action is directed or from a specific party such as a lender or a borrower, which may or may not necessarily be required by a law, rule, or code, but may otherwise be provided out of prudence, courtesy, or custom. In certain embodiments, the obligation or condition that is to be performed with regard to the specific user may form a part of the terms and conditions or otherwise be known to the specific user to which it applies (e.g., an insurance company or bank that advertises a specific practice with regard to a specific class of customers, such as first-time default customers, first-time accident customers, etc.), and in certain embodiments the obligation or condition that is to be performed with regard to the specific user may be unknown to the specific user to which it applies (e.g., a bank has a policy relating to a class of users to which the specific user belongs, but the specific user is not aware of the classification).
[0229] The terms value, valuation, and valuation model (and similar terms) as utilized herein should be understood broadly to describe an approach to evaluate and determine the estimated value for collateral. Without limitation to any other aspect or description of the present disclosure, a valuation model may be used in conjunction with: collateral (e.g. a secured property), artificial intelligence services (e.g. to improve a valuation model), data collection and monitoring services (e.g. to set a valuation amount), valuation services (e.g. the process of informing, using, and/or improving a valuation model), and/or outcomes relating to transactions in collateral (e.g. as a basis of improving the valuation model). “Jurisdiction- specific valuation model” is also used as a valuation model used in a specific geographic/jurisdictional area or region; wherein, the jurisdiction can be specific to jurisdiction of the lender, the borrower, the delivery of funds, the payment of the loan or the collateral of the loan, or combinations thereof. In certain embodiments, a jurisdiction-specific valuation model considers jurisdictional effects on a valuation of collateral, including at least: rights and obligations for borrowers and lenders in the relevant jurisdiction(s); jurisdictional effects on the ability to move, import, export, substitute, and/or liquidate the collateral; jurisdictional effects on the timing between default and foreclosure or collection of collateral; and/or jurisdictional effects on the volatility and/or sensitivity of collateral value determinations· In certain embodiments, a geolocation-specific valuation model considers geolocation effects on a valuation of the collateral, which may include a similar list of considerations of relative jurisdictional effects (although the jurisdictional location(s) may be distinct from the geolocation(s)), but may also include additional effects, such as: weather-related effects; distance of the collateral from monitoring, maintenance, or seizure services; and/or proximity of risk phenomenon (e.g., fault lines, industrial locations, a nuclear plant, etc.). A valuation model may utilize a valuation of offset collateral (e.g., a similar item of collateral, a generic value such as a market value of similar or fungible collateral, and/or a value of an item that correlates with a value of the collateral) as a part of the valuation of the collateral. In certain embodiments, an artificial intelligence circuit includes one or more machine learning and/or artificial intelligence algorithms, to improve a valuation model, including, for example, utilizing information over time between multiple transactions involving similar or offset collateral, and/or utilizing outcome information (e.g., where loan transactions are completed successfully or unsuccessfully, and/or in response to collateral seizure or liquidation events that demonstrate real- world collateral valuation determinations) from the same or other transactions to iteratively improve the valuation model. In certain embodiments, an artificial intelligence circuit is trained on a collateral valuation data set, for example previously determined valuations and/or through interactions with a trainer (e.g., a human, accounting valuations, and/or other valuation data). In certain embodiments, the valuation model and/or parameters of the valuation model (e.g., assumptions, calibration values, etc.) may be determined and/or negotiated as a part of the terms and conditions of the transaction (e.g., a loan, a set of loans, and/or a subset of the set of loans). One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine which aspects of the present disclosure will benefit a particular application for a valuation model, and how to choose or combine valuation models to implement an embodiment of a valuation model. Certain considerations for the person of skill in the art, or embodiments of the present disclosure in choosing an appropriate valuation model, include, without limitation: the legal considerations of a valuation model given the jurisdiction of the collateral; the data available for a given collateral; the anticipated transaction/loan type(s); the specific type of collateral; the ratio of the loan to value; the ratio of the collateral to the loan; the gross transaction/loan amount; the credit scores of the borrower; accounting practices for the loan type and/or related industry; uncertainties related to any of the foregoing; and/or sensitivities related to any of the foregoing. While specific examples of valuation models and considerations are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0230] The term market value data, or marketplace information, (and other forms or variations) as utilized herein may be understood broadly to describe data or information relating to the valuation of a property, asset, collateral or other valuable item which may be used as the subject of a loan, or transaction. Market value data or marketplace information may change from time to time, and may be estimated, calculated, or objectively or subjectively determined from various sources of information. Market value data or marketplace information may be related directly to an item of collateral or to an offset item of collateral. Market value data or marketplace information may include financial data, market ratings, product ratings, customer data, market research to understand customer needs or preferences, competitive intelligence regarding competitors, suppliers, and the like, entities sales, transactions, customer acquisition cost, customer lifetime value, brand awareness, churn rate, and the like. The term may occur in many different contexts of contracts or loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, and data processing (e.g. data collection), or combinations thereof, without limitation. Market value data or marketplace information may be used as a noun to identify a single figure or a plurality of figures or data. For example, market value data or marketplace information may be utilized by a lender to determine if a property or asset will serve as collateral for a secured loan, or may alternatively be utilized in the determination of foreclosure if a loan is in default, without limitation to these circumstances in use of the term. Marketplace value data or marketplace information may also be used to determine loan-to-value figures or calculations. In certain embodiments, a collection service, smart contract circuit, and/or robotic process automation system may estimate or calculate market value data or marketplace information from one or more sources of data or information. In some cases market data value or marketplace information, depending upon the data/information contained therein, may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system and available relevant marketplace information, can readily determine the purposes and use of this term in various forms, embodiments and contexts disclosed herein.
[0231] The terms similar collateral, similar to collateral, offset collateral, and other forms or variations as utilized herein may be understood broadly to describe a property, asset, or valuable item that may be like in nature to a collateral (e.g. an article of value held in security) regarding a loan or other transaction. Similar collateral may refer to a property, asset, collateral, or other valuable item which may be aggregated, substituted, or otherwise referred to in conjunction with other collateral, whether the similarity comes in the form of a common attribute such as type of item of collateral, category of the item of collateral, an age of the item of collateral, a condition of the item of collateral, a history of the item of collateral, an ownership of the item of collateral, a caretaker of the item of collateral, a security of the item of collateral, a condition of an owner of the item of collateral, a lien on the item of collateral, a storage condition of the item of collateral, a geolocation of the item of collateral, and a jurisdictional location of the item of collateral, and the like. In certain embodiments, an offset collateral references an item that has a value correlation with an item of collateral - for example an offset collateral may exhibit similar price movements, volatility, storage requirements, or the like for an item of collateral. In certain embodiments, similar collateral may be aggregated to form a larger security interest or collateral for an additional loan or distribution, or transaction. In certain embodiments, offset collateral may be utilized to inform a valuation of the collateral. In certain embodiments, a smart contract circuit or robotic process automation system may estimate or calculate figures, data or information relating to similar collateral, or may perform a function with respect to aggregating similar collateral. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of similar collateral, offset collateral, or related terms as they relate to collateral in various forms, embodiments, and contexts disclosed herein.
[0232] The term restructure (and other forms such as restructuring) as utilized herein may be understood broadly to describe a modification of terms or conditions, properties, collateral, or other considerations affecting a loan or transaction. Restructuring may result in a successful outcome where amended terms or conditions are adopted between parties, or an unsuccessful outcome where no modification or restructure occurs, without limitation. Restructuring can occur in many contexts of contracts or loans, such as application, lending, refinancing, collection, consolidation, factoring, brokering, foreclosure, and combinations thereof, without limitation. Debt may also be restructured, which may indicate that debts owed to a party are modified as to timing, amounts, collateral, or other terms. For example, a borrower may restructure debt of a loan to accommodate a change of financial conditions, or a lender may offer to a borrower the restructuring of a debt for its own needs or prudence. In certain embodiments, a smart contract circuit or robotic process automation system may automatically or manually restructure debt based on a monitored condition, or create options for restructuring a debt, administrate the process of negotiating or effecting the restructuring of a debt, or other actions in connection with restructuring or modifying terms of a loan or transaction. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of this term, whether in the context of debt or otherwise, in various embodiments and contexts disclosed herein.
[0233] The term social network data collection, social network monitoring services, and social network data collection and monitoring services (and its various forms or derivatives) as utilized herein may be understood broadly to describe services relating to the acquisition, organizing, observing, or otherwise acting upon data or information derived from one or more social networks. The social network data collection and monitoring services may be a part of a related system of services or a standalone set of services. Social network data collection and monitoring services may be provided by a platform or system, without limitation. Social network data collection and monitoring services may be used in a variety of contexts such as lending, refinancing, negotiation, collection, consolidation, factoring, brokering, foreclosure, and combinations thereof, without limitation. Requests of social network data collection and monitoring, with configuration parameters, may be requested by other services, automatically initiated, or automatically triggered to occur based on conditions or circumstances that occur. An interface may be provided to configure, initiate, display, or otherwise interact with social network data collection and monitoring services. Social networks, as utilized herein, reference any mass platform where data and communications occur between individuals and/or entities, where the data and communications are at least partially accessible to an embodiment system. In certain embodiments, the social network data includes publicly available (e.g., accessible without any authorization) information. In certain embodiments, the social network data includes information that is properly accessible to an embodiment system, but may include subscription access or other access to information that is not freely available to the public, but may be accessible (e.g., consistent with a privacy policy of the social network with its users). A social network may be primarily social in nature, but may additionally or alternatively include professional networks, alumni networks, industry related networks, academically oriented networks, or the like. In certain embodiments, a social network may be a crowdsourcing platform, such as a platform configured to accept queries or requests directed to users (and/or a subset of users, potentially meeting specified criteria), where users may be aware that certain communications will be shared and accessible to requestors, at least a portion of users of the platform, and/or publicly available. In certain embodiments, without limitation, social network data collection and monitoring services may be performed by a smart contract circuit or a robotic process automation system. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of social network data collection and monitoring services in various embodiments and contexts disclosed herein.
[0234] The term crowdsource and social network information as utilized herein may further be understood broadly to describe information acquired or provided in conjunction with a crowdsourcing model or transaction, or information acquired or provided on or in conjunction with a social network. Crowdsource and social network information may be provided by a platform or system, without limitation. Crowdsource and social network information may be acquired, provided, or communicated to or from a group of information suppliers and by which responses to the request may be collected and processed. Crowdsource and social network information may provide information, conditions, or factors relating to a loan or agreement. Crowdsource and social network information may be private or published, or combinations thereof, without limitation. In certain embodiments, without limitation, crowdsource and social network information may be acquired, provided, organized, or processed, without limitation, by a smart contract circuit, wherein the crowdsource and social network information may be managed by a smart contract circuit that processes the information to satisfy a set of configured parameters. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of this term in various embodiments and contexts disclosed herein.
[0235] The term negotiate (and other forms such as negotiating or negotiation) as utilized herein may be understood broadly to describe discussions or communications to bring about or obtain a compromise, outcome, or agreement between parties or entities. Negotiation may result in a successful outcome where terms are agreed between parties, or an unsuccessful outcome where the parties do not agree to specific terms, or combinations thereof, without limitation. A negotiation may be successful in one aspect or for a particular purpose, and unsuccessful in another aspect or for another purpose. Negotiation can occur in many contexts of contracts or loans, such as lending, refinancing, collection, consolidation, factoring, brokering, foreclosure, and combinations thereof, without limitation. For example, a borrower may negotiate an interest rate or loan terms with a lender. In another example, a borrower in default may negotiate an alternative resolution to avoid foreclosure with a lender. In certain embodiments, a smart contract circuit or robotic process automation system may negotiate for one or more of the parties, and process appropriate tasks for completing or attempting to complete a negotiation of terms. In some cases negotiation by the smart contract or robotic process automation system may not complete or be successful. Successful negotiation may enable automated action or trigger other conditions or terms to be implemented by the smart contract circuit or robotic process automation system. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of negotiation in various embodiments and contexts disclosed herein.
[0236] The term negotiate in various forms may more specifically be utilized herein in verb form (e.g. to negotiate) or in noun forms (e.g. a negotiation), or other forms to describe a context of mutual discussion leading to an outcome. For example, a robotic process automation system may negotiate terms and conditions on behalf of a party, which would be a use as a verb clause. In another example, a robotic process automation system may be negotiating terms and conditions for modification of a loan, or negotiating a consolidation offer, or other terms. As a noun clause, a negotiation (e.g. an event) may be performed by a robotic process automation system. Thus, in some circumstances a smart contract circuit or robotic process automation system may negotiate (e.g. as a verb clause) terms and conditions, or the description of doing so may be considered a negotiation (e.g. as a noun clause). One of skill in the art, having the benefit of the disclosure herein and knowledge about negotiating and negotiation, or other forms of the word negotiate, can readily determine the purposes and use of this term in various embodiments and contexts disclosed herein. [0237] The term negotiate in various forms may also specifically be utilized to describe an outcome, such as a mutual compromise or completion of negotiation leading to an outcome. For example, a loan may, by robotic process automation system or otherwise, be considered negotiated as a successful outcome that has resulted in an agreement between parties, where the negotiation has reached completion. Thus, in some circumstances a smart contract circuit or robotic process automation system may have negotiated to completion a set of terms and conditions, or a negotiated loan. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available for a contemplated system, can readily determine the purposes and use of this term as it relates to a mutually agreed outcome through completion of negotiation in various embodiments and contexts disclosed herein.
[0238] The term negotiate in various forms may also specifically be utilized to characterize an event such as a negotiating event, or an event negotiation, including reaching a set of agreeable terms between parties. An event requiring mutual agreement or compromise between parties may be considered a negotiating event, without limitation. For example, during the procurement of a loan, the process of reaching a mutually acceptable set of terms and conditions between parties could be considered a negotiating event. Thus, in some circumstances a smart contract circuit or robotic process automation system may accommodate the communications, actions, or behaviors of the parties for a negotiated event.
[0239] The term collection (and other forms such as collect or collecting) as utilized herein may be understood broadly to describe the acquisition of a tangible (e.g. physical item), intangible (e.g. data, a license, or a right), or monetary (e.g. payment) item, or other obligation or asset from a source. The term generally may relate to the entire prospective acquisition of such an item from related tasks in early stages to related tasks in late stages or full completion of the acquisition of the item. Collection may result in a successful outcome where the item is tendered to a party, or may or an unsuccessful outcome where the item is not tendered or acquired to a party, or combinations thereof (e.g., a late or otherwise deficient tender of the item), without limitation. Collection may occur in many different contexts of contracts or loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, and data processing (e.g. data collection), or combinations thereof, without limitation. Collection may be used in the form of a noun (e.g. data collection or the collection of an overdue payment where it refers to an event or characterizes an event), may refer as a noun to an assortment of items (e.g. a collection of collateral for a loan where it refers to a number of items in a transaction), or may be used in the form of a verb (e.g. collecting a payment from the borrower). For example, a lender may collect an overdue payment from a borrower through an online payment, or may have a successful collection of overdue payments acquired through a customer service telephone call. In certain embodiments, a smart contract circuit or robotic process automation system may perform collection for one or more of the parties, and process appropriate tasks for completing or attempting collection for one or more items (e.g. an overdue payment). In some cases negotiation by the smart contract or robotic process automation system may not complete or be successful, and depending upon such outcomes this may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of collection in various forms, embodiments, and contexts disclosed herein.
[0240] The term collection in various forms may also more specifically be utilized herein in noun form to describe a context for an event or thing, such as a collection event, or a collection payment. For example, a collection event may refer to a communication to a party or other activity that relates to acquisition of an item in such an activity, without limitation. A collection payment, for example, may relate to a payment made by a borrower that has been acquired through the process of collection, or through a collection department with a lender. Although not limited to an overdue, delinquent, or defaulted loan, collection may characterize an event, payment or department, or other noun associated with a transaction or loan, as being a remedy for something that has become overdue. Thus, in some circumstances a smart contract circuit or robotic process automation system may collect a payment or installment from a borrower, and the activity of doing so may be considered a collection event, without limitation.
[0241] The term collection in various forms may also more specifically be utilized herein as an adjective or other forms to describe a context relating to litigation, such as the outcome of a collection litigation (e.g. litigation regarding overdue or default payments on a loan). For example, the outcome of a collection litigation may be related to delinquent payments which are owed by a borrower or other party, and collection efforts relating to those delinquent payments may be litigated by parties. Thus, in some circumstances a smart contract circuit or robotic process automation system may receive, determine, or otherwise administrate the outcome of collection litigation.
[0242] The term collection in various forms may also more specifically be utilized herein as an adjective or other forms to describe a context relating to an action of acquisition, such as a collection action (e.g. actions to induce tendering or acquisition of overdue or default payments on a loan or other obligation). The terms collection yield, financial yield of collection, and/or collection financial yield may be used. The result of such a collection action may or may not have a financial yield. For example, a collection action may result in the payment of one or more outstanding payments on a loan, which may render a financial yield to another party such as the lender. Thus, in some circumstances a smart contract circuit or robotic process automation system may render a financial yield from a collection action, or otherwise administrate or in some manner assist in a financial yield of a collection action. In embodiments, a collection action may include the need for collection litigation.
[0243] The term collection in various forms (collection ROI, ROI on collection, ROI on collection activity, collection activity ROI, and the like) may also more specifically be utilized herein to describe a context relating to an action of receiving value, such as a collection action (e.g. actions to induce tendering or acquisition of overdue or default payments on a loan or other obligation), wherein there is a return on investment (ROI). The result of such a collection action may or may not have an ROI, either with respect to the collection action itself (as an ROI on the collection action) or as an ROI on the broader loan or transaction that is the subject of the collection action. For example, an ROI on a collection action may be prudent or not with respect to a default loan, without limitation, depending upon whether the ROI will be provided to a party such as the lender. A projected ROI on collection may be estimated, or may also be calculated given real events that transpire. In some circumstances a smart contract circuit or robotic process automation system may render an estimated ROI for a collection action or collection event, or may calculate an ROI for actual events transpiring in a collection action or collection event, without limitation. In embodiments, such a ROI may be a positive or negative figure, whether estimated or actual. [0244] The term reputation, measure of reputation, lender reputation, borrower reputation, entity reputation, and the like may include general, widely held beliefs, opinions, and/or perceptions that are generally held about an individual, entity, collateral, and the like. A measure for reputation may be determined based on social data including likes/dislikes, review of entity or products and services provided by the entity, rankings of the company or product, current and historic market and financial data include price, forecast, buy/sell recommendations, financial news regarding entity, competitors, and partners. Reputations may be cumulative in that a product reputation and the reputation of a company leader or lead scientist may influence the overall reputation of the entity. Reputation of an institute associated with an entity (e.g. a school being attended by a student) may influence the reputation of the entity. In some circumstances a smart contract circuit or robotic process automation system may collect or initiate collection of data related to the above and determine a measure or ranking of reputation. A measure or ranking of an entity’s reputation may be used by a smart contract circuit or robotic process automation system in determining whether to enter into an agreement with the entity, determination of terms and conditions of a loan, interest rates, and the like. In certain embodiments, indicia of a reputation determination may be related to outcomes of one or more transactions (e.g., a comparison of “likes” on a particular social media data set to an outcome index, such as successful payments, successful negotiation outcomes, ability to liquidate a particular type of collateral, etc.) to determine the measure or ranking of an entity’s reputation. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of the reputation, a measure or ranking of the reputation, and/or utilization of the reputation in negotiations, determination of terms and conditions, determination of whether to proceed with a transaction, and other various embodiments and contexts disclosed herein.
[0245] The term collection in various forms (e.g. collector) may also more specifically be utilized herein to describe a party or entity that induces, administrates, or facilitates a collection action, collection event, or other collection related context. The measure of reputation of a party involved, such as a collector, or during the context of a collection, may be estimated or calculated using objective, subjective, or historical metrics or data. For example, a collector may be involved in a collection action, and the reputation of that collector may be used to determine decisions, actions or conditions. Similarly, a collection may be also used to describe objective, subjective, or historical metrics or data to measure the reputation of a party involved, such as a lender, borrower, or debtor. In some circumstances a smart contract circuit or robotic process automation system may render a collection or measures, or implement a collector, within the context of a transaction or loan.
[0246] The term collection and data collection in various forms, including data collection systems, may also more specifically be utilized herein to describe a context relating to the acquisition, organization, or processing of data, or combinations thereof, without limitation. The result of such a data collection may be related or wholly unrelated to a collection of items (e.g., grouping of the items, either physically or logically), or actions taken for delinquent payments (e.g., collection of collateral, a debt, or the like), without limitation. For example, a data collection may be performed by a data collection system, wherein data is acquired, organized, or processed for decision-making, monitoring, or other purposes of prospective or actual transaction or loan. In some circumstances a smart contract or robotic process automation system may incorporate data collection or a data collection system, to perform portions or entire tasks of data collection, without limitation. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available for a contemplated system, can readily determine and distinguish the purposes and use of collection in the context of data or information as used herein.
[0247] The terms refinance, refinancing activity(ies), refinancing interactions, refinancing outcomes, and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure refinance and refinancing activities include replacing an existing mortgage, loan, bond, debt transaction, or the like with a new mortgage, loan, bond, or debt transaction that pays off or ends the previous financial arrangement. In certain embodiments, any change to terms and conditions of a loan, and/or any material change to terms and conditions of a loan, may be considered a refinancing activity. In certain embodiments, a refinancing activity is considered only those changes to a loan agreement that result in a different financial outcome for the loan agreement. Typically, the new loan should be advantageous to the borrower or issuer, and/or mutually agreeable (e.g., improving a raw financial outcome of one, and a security or other outcome for the other). Refinancing may be done to reduce interest rates, lower regular payments, change the loan term, change the collateral associated with the loan, consolidate debt into a single loan, restructure debt, change a type of loan (e.g. variable rate to fixed rate), pay off a loan that is due, in response to an improved credit score, to enlarge the loan, and/or in response to a change in market conditions (e.g. interest rates, value of collateral, and the like).
[0248] Refinancing activity may include initiating an offer to refinance, initiating a request to refinance, configuring a refinancing interest rate, configuring a refinancing payment schedule, configuring a refinancing balance in a response to the amount or terms of the refinanced loan, configuring collateral for a refinancing including changes in collateral used, changes in terms and conditions for the collateral, a change in the amount of collateral and the like, managing use of proceeds of a refinancing, removing or placing a lien on different items of collateral as appropriate given changes in terms and conditions as part of a refinancing, verifying title for a new or existing item of collateral to be used to secure the refinanced loan, managing an inspection process title for a new or existing item of collateral to be used to secure the refinanced loan, populating an application to refinance a loan, negotiating terms and conditions for a refinanced loan and closing a refinancing. Refinance and refinancing activities may be disclosed in the context of data collection and monitoring services that collect a training set of interactions between entities for a set of loan refinancing activities. Refinance and refinancing activities may be disclosed in the context of an artificial intelligence system that is trained using the collected training set of interactions that includes both refinancing activities and outcomes. The trained artificial intelligence may then be used to recommend a refinance activity, evaluate a refinance activity, make a prediction around an expected outcome of refinancing activity, and the like. Refinance and refinancing activities may be disclosed in the context of smart contract systems which may automate a subset of the interactions and activities of refinancing. In an example, a smart contract system may automatically adjust an interest rate for a loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system 120, a set of social network analytic services and a set of data collection and monitoring services. The interest rate may be adjusted based on rules, thresholds, model parameters that determine, or recommend, an interest rate for refinancing a loan based on interest rates available to the lender from secondary lenders, risk factors of the borrower (including predicted risk based on one or more predictive models using artificial intelligence), marketing factors (such as competing interest rates offered by other lenders), and the like. Outcomes and events of a refinancing activity may be recorded in a distributed ledger. Based on the outcome of a refinance activity, a smart contract for the refinance loan may be automatically reconfigured to define the terms and conditions for the new loan such as a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0249] One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine which aspects of the present disclosure will benefit from a particular application of a refinance activity, how to choose or combine refinance activities, how to implement systems, services, or circuits to automatically perform of one or more (or all) aspects of a refinance activity, and the like. Certain considerations for the person of skill in the art, for embodiments of the present disclosure in choosing an appropriate training sets of interactions with which to train an artificial intelligence to take action, recommend or predict the outcome of certain refinance activities. While specific examples of refinance and refinancing activities are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0250] The terms consolidate, consolidation activity(ies), loan consolidation, debt consolidation, consolidation plan, and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, consolidate, consolidation activity(ies), loan consolidation, debt consolidation, or consolidation plan are related to the use of a single large loan to pay off several smaller loans, and/or the use of one or more of a set of loans to pay off at least a portion of one or more of a second set of loans. In embodiments, loan consolidation may be secured (i.e. backed by collateral) or unsecured. Loans may be consolidated to obtain a lower interest rate than one or more of the current loans, to reduce total monthly loan payments, and/or to bring a debtor into compliance on the consolidated loans or other debt obligations of the debtor. Loans that may be classified as candidates for consolidation may be determined based on a model that processes attributes of entities involved in the set of loans including identity of a party, interest rate, payment balance, payment temls, payment schedule, type of loan, type of collateral, financial condition of party, payment status, condition of collateral, and value of collateral. Consolidation activities may include managing at least one of identification of loans from a set of candidate loans, preparation of a consolidation offer, preparation of a consolidation plan, preparation of content communicating a consolidation offer, scheduling a consolidation offer, communicating a consolidation offer, negotiating a modification of a consolidation offer, preparing a consolidation agreement, executing a consolidation agreement, modifying collateral for a set of loans, handling an application workflow for consolidation, managing an inspection, managing an assessment, setting an interest rate, deferring a payment requirement, setting a payment schedule, and closing a consolidation agreement. In embodiments, there may be systems, circuits, and/or services configured to create, configure (such as using one or more templates or libraries), modify, set, or otherwise handle (such as in a user interface) various rules, thresholds, conditional procedures, workflows, model parameters, and the like to determine, or recommend, a consolidation action or plan for a lending transaction or a set of loans based on one or more events, conditions, states, actions, or the like. In embodiments, a consolidation plan may be based on various factors, such as the status of payments, interest rates of the set of loans, prevailing interest rates in a platform marketplace or external marketplace, the status of the borrowers of a set of loans, the status of collateral or assets, risk factors of the borrower, the lender, one or more guarantors, market risk factors and the like. Consolidation and consolidation activities may be disclosed in the context of data collection and monitoring services that collect a training set of interactions between entities for a set of loan consolidation activities consolidation and consolidation activities may be disclosed in the context of an artificial intelligence system that is trained using the collected training set of interactions that includes both consolidation activities and outcomes associated with those activities. The trained artificial intelligence may then be used to recommend a consolidation activity, evaluate a consolidation activity, make a prediction around an expected outcome of consolidation activity, and the like based models including status of debt, condition of collateral or assets used to secure or back a set of loans, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences), and others. Debt consolidation, loan consolidation and associated consolidation activities may be disclosed in the context of smart contract systems which may automate a subset of the interactions and activities of consolidation. In embodiments, consolidation may include consolidation with respect to terms and conditions of sets of loans, selection of appropriate loans, configuration of payment terms for consolidated loans, configuration of payoff plans for pre-existing loans, communications to encourage consolidation, and the like. In embodiments the artificial intelligence of a smart contract may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended consolidation plan, which may specify a series of actions required to accomplish a recommended or desired outcome of consolidation (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the consolidation plan. Consolidation plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other lenders, values of collateral, and the like) as well as regulatory and/or compliance factors. Consolidation plans may be generated and/or executed for creation of new consolidated loans, for secondary loans related to consolidated loans, for modifications of existing loans related to consolidation, for refinancing terms of a consolidated loan, for foreclosure situations (e.g., changing from secured loan rates to unsecured loan rates), for bankruptcy or insolvency situations, for situations involving market changes (e.g., changes in prevailing interest rates) and others consolidation.
[0251] Certain of the activities related to loans, collateral, entities, and the like, may apply to a wide variety of loans and may not apply explicitly to consolidation activities. The categorization of the activities as consolidation activities may be based on the context of the loan for which the activities are taking place. However, one of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine which aspects of the present disclosure will benefit from a particular application of a consolidation activity, how to choose or combine consolidation activities, how to implement selected services, circuits, and/or systems described herein to perform certain loan consolidation operations, and the like. While specific examples of consolidation and consolidation activities are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0252] The terms factoring a loan, factoring a loan transaction, factors, factoring a loan interaction, factoring assets or sets of assets used for factoring and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure factoring may be applied to factoring assets such as invoices, inventory, accounts receivable, and the like, where the realized value of the item is in the future. For example, the accounts receivable is worth more when it has been paid and there is less risk of default. Inventory and Work in Progress (WIP) may be worth more as final product rather than components. References to accounts receivable should be understood to encompass these terms and not be limiting. Factoring may include a sale of accounts receivable at a discounted rate for value in the present (often cash). Factoring may also include the use of accounts receivable as collateral for a short term loan. In both cases the value of the accounts receivable or invoices may be discounted for multiple reasons including the future value of money, a term of the accounts receivable (e.g., 30 day net payment vs. 90 day net payment), a degree of default risk on the accounts receivable, a status of receivables, a status of work-in-progress (WIP), a status of inventory, a status of delivery and/or shipment, financial condition(s) of parties owing against the accounts receivable, a status of shipped and/or billed, a status of payments, a status of the borrower, a status of inventory, a risk factor of a borrower, a lender, one or more guarantors, market risk factors, a status of debt (are there other liens present on the accounts receivable or payment owed on the inventory, a condition of collateral assets (e.g. the condition of the inventory- is it current or out of date, are invoices in arrears), a state of a business or business operation, a condition of a party to the transaction (such as net worth, wealth, debt, location, and other conditions), a behavior of a party to the transaction (such as behaviors indicating preferences, behaviors indicating negotiation styles, and the like), current interest rates, any current regulatory and compliance issues associated with the inventory or accounts receivable (e.g. if inventory is being factored, has the intended product received appropriate approvals), and there legal actions against the borrower, and many others, including predicted risk based on one or more predictive models using artificial intelligence). A factor is an individual, business, entity, or groups thereof which agree to provide value inf exchange for either the outright acquisition of the invoices in a sale or the use of the invoices as collateral for a loan for the value. Factoring a loan may include the identification of candidates (both lenders and borrowers) for factoring, a plan for factoring specifying the proposed receivables (e.g. all, some, only those meeting certain criteria), and a proposed discount factor, communication of the plan to potential parties, proffering an offer and receiving an offer, verification of quality of receivables, conditions regarding treatment of the receivables for the term of the loan. While specific examples of factoring and factoring activities are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0253] The terms mortgage, brokering a mortgage, mortgage collateral, mortgage loan activities, and/or mortgage related activities as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a mortgage is an interaction where a borrower provides the title or a lien on the title of an item of value, typically property, to a lender as security in exchange for money or another item of value, to be repaid, typically with interest, to the lender. The exchange includes the condition that, upon repayment of the loan, the title reverts to the borrower and/or the lien on the property is removed. The brokering of a mortgage may include the identification of potential properties, lenders, and other parties to the loan, and arranging or negotiating the terms of the mortgage. Certain components or activities may not be considered mortgage related individually, but may be considered mortgage related when used in conjunction with a mortgage, act upon a mortgage, are related to an entity or party to a mortgage, and the like. For example, brokering may apply to the offering of a variety of loans including unsecured loans, outright sale of property and the like. Mortgage activities and mortgage interactions may include mortgage marketing activity, identification of a set of prospective borrowers, identification of property to mortgage, identification of collateral property to mortgage, qualification of borrower, title search and/or title verification for prospective mortgage property, property assessment, property inspection, or property valuation for prospective mortgage property, income verification, borrower demographic analysis, identification of capital providers, determination of available interest rates, determination of available payment terms and conditions, analysis of existing mortgage(s), comparative analysis of existing and new mortgage terms, completion of application workflow (e.g. keep the application moving forward by initiating next steps in the process as appropriate), population of fields of application, preparation of mortgage agreement, completion of schedule for mortgage agreement, negotiation of mortgage terms and conditions with capital provider, negotiation of mortgage terms and conditions with borrower, transfer of title, placement of lien on mortgaged property and closing of mortgage agreement, and similar terms, as utilized herein should be understood broadly. While specific examples of mortgages and mortgage brokering are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0254] The terms debt management, debt transactions, debt actions, debt terms and conditions, syndicating debt, consolidating debt, and/or debt portfolios, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure a debt includes something of monetary value that is owed to another. A loan typically results in the borrower holding the debt (e.g. the money that must be paid back according to the terms of the loan, which may include interest). Consolidation of debt includes the use of a new, single loan to pay back multiple loans (or various other configurations of debt structuring as described herein, and as understood to one of skill in the art). Often the new loan may have better terms or lower interest rates. Debt portfolios include a number of pieces or groups of debt, often having different characteristics including term, risk, and the like. Debt portfolio management may involve decisions regarding the quantity and quality of the debt being held and how best to balance the various debts to achieve a desired risk/reward position based on: investment policy, return on risk determinations for individual pieces of debt, or groups of debt. Debt may be syndicated where multiple lenders fund a single loan (or set of loans) to a borrower. Debt portfolios may be sold to a third party (e.g., at a discounted rate). Debt compliance includes the various measures taken to ensure that debt is repaid. Demonstrating compliance may include documentation of the actions taken to repay the debt.
[0255] Transactions related to a debt (debt transactions) and actions related to the debt (debt actions) may include offering a debt transaction, underwriting a debt transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating debt, and/or consolidating debt. Debt terms and conditions may include a balance of debt, a principal amount of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of assets that back the bond, a specification of substitutability of assets, a party, an issuer, a purchaser, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default. While specific examples of debt management and debt management activities are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0256] The terms condition, condition classification, classification models, condition management, and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure condition, condition classification, classification models, condition management, include classifying or determining a condition of an asset, issuer, borrower, loan, debt, bond, regulatory status, term or condition for a bond, loan or debt transaction that is specified and monitored in the contract, and the like. Based on a classified condition of an asset, condition management may include actions to maintain or improve a condition of the asset or the use of that asset as collateral. Based on a classified condition of an issuer, borrower, party regulatory status, and the like, condition management may include actions to alter the terms or conditions of a loan or bond. Condition classification may include various rules, thresholds, conditional procedures, workflows, model parameters, and the like to classify a condition of an asset, issuer, borrower, loan, debt, bond, regulatory status, term or condition for a bond, loan or debt transaction, and the like based on data from Internet of Things devices, data from a set of environmental condition sensors, data from a set of social network analytic services and a set of algorithms for querying network domains, social media data, crowdsourced data, and the like. Condition classification may include grouping or labeling entities, or clustering the entities, as similarly positioned with regard to some aspect of the classified condition (e.g., a risk, quality, ROI, likelihood for recovery, likelihood to default, or some other aspect of the related debt).
[0257] Various classification models are disclosed where the classification and classification model may be tied to a geographic location relating to the collateral, the issuer, the borrower, the distribution of the funds or other geographic locations. Classification and classification models are disclosed where artificial intelligence is used to improve a classification model (e.g. refine a model by making refinements using artificial intelligence data). Thus artificial intelligence may be considered, in some instances, as a part of a classification model and vice versa. Classification and classification models are disclosed where social media data, crowdsourced data, or IoT data is used as input for refining a model, or as input to a classification model. Examples of IoT data may include images, sensor data, location data, and the like. Examples of social media data or crowdsourced data may include behavior of parties to the loan, financial condition of parties, adherence to a parties to a term or condition of the loan, or bond, or the like. Parties to the loan may include issuers of a bond, related entities, lender, borrower, 3rd parties with an interest in the debt. Condition management may be discussed in connection with smart contract services which may include condition classification, data collection and monitoring, and bond, loan and debt transaction management. Data collection and monitoring services are also discussed in conjunction with classification and classification models which are related when classifying an issuer of a bond issuer, an asset or collateral asset related to the bond, collateral assets backing the bond, parties to the bond, and sets of the same. In some embodiments a classification model may be included when discussing bond types. Specific steps, factors or refinements may be considered a part of a classification model. In various embodiments, the classification model may change both in an embodiment, or in the same embodiment which is tied to a specific jurisdiction. Different classification models may use different data sets (e.g. based on the issuer, the borrower, the collateral assets, the bond type, the loan type, and the like) and multiple classification models may be used in a single classification. For example, one type of bond, such as a municipal bond, may allow a classification model that is based on bond data from municipalities of similar size and economic prosperity, whereas another classification model may emphasize data from IoT sensors associated with a collateral asset. Accordingly, different classification models will offer benefits or risks over other classification models, depending upon the embodiment and the specifics of the bond, loan or debt transaction. A classification model includes an approach or concept for classification. Conditions classified for a bond, loan, or debt transaction may include a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of assets that back the bond, loan or debt transaction, a specification of substitutability of assets, a party, an issuer, a purchaser, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and/or a consequence of default. Conditions classified may include type of bond issuer such as a municipality, a corporation, a contractor, a government entity, a non-governmental entity, and a non-profit entity. Entities may include a set of issuers, a set of bonds, a set of parties, and/or a set of assets. Conditions classified may include an entity condition such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences), and the like. Conditions classified may include an asset or type of collateral such as a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. Conditions classified may include a bond type where bond type may include a municipal bond, a government bond, a treasury bond, an asset-backed bond, and a corporate bond. Conditions classified may include a default condition, a foreclosure condition, a condition indicating violation of a covenant, a financial risk condition, a behavioral risk condition, a policy risk condition, a financial health condition, a physical defect condition, a physical health condition, an entity risk condition and an entity health condition. Conditions classified may include an environment where environment may include an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle. Actions based on the condition of an asset, issuer, borrower, loan, debt, bond, regulatory status and the like, may include managing, reporting on, syndicating, consolidating, or otherwise handling a set of bonds (such as municipal bonds, corporate bonds, performance bonds, and others), a set of loans (subsidized and unsubsidized, debt transactions and the like, monitoring, classifying, predicting, or otherwise handling the reliability, quality, status, health condition, financial condition, physical condition or other information about a guarantee, a guarantor, a set of collateral supporting a guarantee, a set of assets backing a guarantee, or the like. Bond transaction activities in response to a condition of the bond may include offering a debt transaction, underwriting a debt transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating debt, and/or consolidating debt.
[0258] One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine which aspects of the present disclosure will benefit a particular application for a classification model, how to choose or combine classification models to arrive at a condition, and/or calculate a value of collateral given the required data. Certain considerations for the person of skill in the art, or embodiments of the present disclosure in choosing an appropriate condition to manage, include, without limitation: the legality of the condition given the jurisdiction of the transaction, the data available for a given collateral, the anticipated transaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross transaction/loan amount, the credit scores of the borrower and the lender, and other considerations. While specific examples of conditions, condition classification, classification models, and condition management are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure. [0259] The terms classify, classifying, classification, categorization, categorizing, categorize (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, classifying a condition or item may include actions to sort the condition or item into a group or category based on some aspect, attribute, or characteristic of the condition or item where the condition or item is common or similar for all the items placed in that classification, despite divergent classifications or categories based on other aspects or conditions at the time. Classification may include recognition of one or more parameters, features, characteristics, or phenomena associated with a condition or parameter of an item, entity, person, process, item, financial construct, or the like. Conditions classified by a condition classifying system may include a default condition, a foreclosure condition, a condition indicating violation of a covenant, a financial risk condition, a behavioral risk condition, a contractual performance condition, a policy risk condition, a financial health condition, a physical defect condition, a physical health condition, an entity risk condition, and/or an entity health condition. A classification model may automatically classify or categorize items, entities, process, items, financial constructs or the like based on data received from a variety of sources. The classification model may classify items based on a single attribute or a combination of attributes, and/or may utilize data regarding the items to be classified and a model. The classification model may classify individual items, entities, financial constructs or groups of the same. A bond may be classified based on the type of bond ((e.g. municipal bonds, corporate bonds, performance bonds, and the like), rate of return, bond rating (3rd party indicator of bond quality with respect to bond issuer’s financial strength, and/or ability to bap bond’ s principal and interest, and the like. Lenders or bond issuers may be classified based on the type of lender or issuer, permitted attributes (e.g. based on income, wealth, location (domestic or foreign), various risk factors, status of issuers, and the like. Borrowers may be classified based on permitted attributes (e.g. income, wealth, total assets, location, credit history), risk factors, current status (e.g. employed, a student), behaviors of parties (such as behaviors indicating preferences, reliability, and the like), and the like. A condition classifying system may classify a student recipient of a loan based on progress of the student toward a degree, the student’s grades or standing in their classes, student’s status at the school (matriculated, on probation and the like), the participation of a student in a non-profit activity, a deferment status of the student, and the participation of the student in a public interest activity. Conditions classified by a condition classifying system may include a state of a set of collateral for a loan or a state of an entity relevant to a guarantee for a loan. Conditions classified by a condition classifying system may include a medical condition of a borrower, guarantor, subsidizer or the like. Conditions classified by a condition classifying system may include compliance with at least one of a law, a regulation, or a policy related to a lending transaction or lending institute. Conditions classified by a condition classifying system may include a condition of an issuer for a bond, a condition of a bond, a rating of a loan-related entity, and the like. Conditions classified by a condition classifying system may include an identify of a machine, a component, or an operational mode. Conditions classified by a condition classifying system may include a state or context (such as a state of a machine, a process, a workflow, a marketplace, a storage system, a network, a data collector, or the like). A condition classifying system may classify a process involving a state or context (e.g., a data storage process, a network coding process, a network selection process, a data marketplace process, a power generation process, a manufacturing process, a refining process, a digging process, a boring process, and/or other process described herein. A condition classifying system may classify a set of loan refinancing actions based on a predicted outcome of the set of loan refinancing actions. A condition classifying system may classify a set of loans as candidates for consolidation based on attributes such as identity of a party, an interest rate, a payment balance, payment terms, payment schedule, a type of loan, a type of collateral, a financial condition of party, a payment status, a condition of collateral, a value of collateral, and the like. A condition classifying system may classify the entities involved in a set of factoring loans, bond issuance activities, mortgage loans, and the like. A condition classifying system may classify a set of entities based on projected outcomes from various loan management activities. A condition classifying system may classify a condition of a set of issuers based on information from Internet of Things data collection and monitoring services, a set of parameters associated with an issuer, a set of social network monitoring and analytic services, and the like. A condition classifying system may classify a set of loan collection actions, loan consolidation actions, loan negotiation actions, loan refinancing actions and the like based on a set of projected outcomes for those activities and entities.
[0260] The term subsidized loan, subsidizing a loan, (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a subsidized loan is the loan of money or an item of value wherein payment of interest on the value of the loan may be deferred, postponed or delayed, with or without accrual, such as while the borrower is in school, is unemployed, is ill, and the like. In embodiments, a loan may be subsidized when the payment of interest on a portion or subset of the loan is borne or guaranteed by someone other than the borrower. Examples of subsidized loans may include a municipal subsidized loan, a government subsidized loan, a student loan, an asset-backed subsidized loan, and a corporate subsidized loan. An example of a subsidized student loan may include student loans which may be subsidized by the government and on which interest may be deferred or not accrue based on progress of the student toward a degree, the participation of a student in a non profit activity, a deferment status of the student, and the participation of the student in a public interest activity. An example of a government subsidized housing loan may include governmental subsidies which may exempt the borrower from paying closing costs, first mortgage payment and the like. Conditions for such subsidized loans may include location of the property (rural or urban), income of the borrower, military status of the borrower, ability of the purchased home to meet health and safety standards, a limit on the profits you can earn on the sale of your home, and the like. Certain usages of the word loan may not apply to a subsidized loan but rather to a regular loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit from consideration of a subsidized loan (e.g., in determining the value of the loan, negotiations related to the loan, terms and conditions related to the loan, etc.) wherein the borrower may be relieved of some of the loan obligations common for non- subsidized loans, where the subsidy may include forgiveness, delay or deferment of interest on a loan, or the payment of the interest by a third party. The subsidy may include the payment of closing costs including points, first payment and the like by a person or entity other than the borrower, and/or how to combine processes and systems from the present disclosure to enhance or benefit from title validation. [0261] The term subsidized loan management (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, subsidized loan management may include a plurality of activities and solutions for managing or responding to one or more events related to a subsidized loan wherein such events may include requests for a subsidized loan, offering a subsidized loan, accepting a subsidized loan, providing underwriting information for a subsidized loan, providing a credit report on a borrower seeking a subsidized loan, deferring a required payment as part of the loan subsidy, setting an interest rate for a subsidized loan where a lower interest rate may be part of the subsidy, deferring a payment requirement as part of the loan subsidy, identifying collateral for a loan, validating title for collateral or security for a loan, recording a change in title of property, assessing the value of collateral or security for a loan, inspecting property that is involved in a loan, identifying a change in condition of an entity relevant to a loan, a change in value of an entity that is relevant to a loan, a change in job status of a borrower, a change in financial rating of a lender, a change in financial value of an item offered as a security, providing insurance for a loan, providing evidence of insurance for property related to a loan, providing evidence of eligibility for a loan, identifying security for a loan, underwriting a loan, making a payment on a loan, defaulting on a loan, calling a loan, closing a loan, setting terms and conditions for a loan, foreclosing on property subject to a loan, modifying terms and conditions for a loan, for setting terms and conditions for a loan (such as a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default), or managing loan-related activities (such as, without limitation, finding parties interested in participating in a loan transaction, handling an application for a loan, underwriting a loan, forming a legal contract for a loan, monitoring performance of a loan, making payments on a loan, restructuring or amending a loan, settling a loan, monitoring collateral for a loan, forming a syndicate for a loan, foreclosing on a loan, collecting on a loan, consolidating a set of loans, analyzing performance of a loan, handling a default of a loan, transferring title of assets or collateral, and closing a loan transaction), and the like. In embodiments, a system for handling a subsidized loan may include classifying a set of parameters of a set of subsidized loans on the basis of data relating to those parameters obtained from an Internet of Things data collection and monitoring service. Classifying the set of parameters of the set of subsidized loans may also be on the bases of data obtained from one or more configurable data collection and monitoring services that leverage social network analytic services, crowd sourcing services, and the like for obtaining parameter data (e.g., determination that a person or entity is qualified for the subsidized loan, determining a social value of providing the subsidized loan or removing a subsidization from a loan, determining that a subsidizing entity is legitimate, determining appropriate subsidization terms based on characteristics of the buyer and/or subsidizer, etc.)·
[0262] The term foreclose, foreclosure, foreclose or foreclosure condition, default foreclosure collateral, default collateral, (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, foreclose condition, default and the like describe the failure of a borrower to meet the terms of a loan. Without limitation to any other aspect or description of the present disclosure foreclose and foreclosure include processes by which a lender attempts to recover, from a borrower in a foreclose or default condition, the balance of a loan or take away in lieu, the right of a borrower to redeem a mortgage held in security for the loan. Failure to meet the terms of the loan may include failure to make specified payments, failure to adhere to a payment schedule, failure to make a balloon payment, failure to appropriately secure the collateral, failure to sustain collateral in a specified condition (e.g. in good repair), acquisition of a second loan, and the like. Foreclosure may include a notification to the borrower, the public, jurisdictional authorities of the forced sale of an item collateral such as through a foreclosure auction. Upon foreclosure, an item of collateral may be placed on a public auction site (such as eBay™ or an auction site appropriate for a particular type of property. The minimum opening bid for the item of collateral may be set by the lender and may cover the balance of the loan, interest on the loan, fees associated with the foreclosure and the like. Attempts to recover the balance of the loan may include the transfer of the deed for an item of collateral in lieu of foreclosure (e.g. a real-estate mortgage where the borrower holds the deed for a property which acts as collateral for the mortgage loan). Foreclosure may include taking possession of or repossessing the collateral (e.g. a car, a sports vehicle such as a boat, ATV, ski- mobile, jewelry). Foreclosure may include securing an item of collateral associated with the loan (such as by locking a connected device, such as a smart lock, smart container, or the like that contains or secures collateral). Foreclosure may include arranging for the shipping of an item of collateral by a carrier, freight forwarder of the like. Foreclosure may include arranging for the transport of an item of collateral by a drone, a robot, or the like for transporting collateral. In embodiments, a loan may allow for the substitution of collateral or the shifting of the lien from an item of collateral initially used to secure the loan to a substitute collateral where the substitute collateral is of higher value (to the lender) than the initial collateral or is an item in which the borrower has a greater equity. The result of the substitution of collateral is that when the loan goes into foreclosure, it is the substitute collateral that may be the subject of a forced sale or seizure. Certain usages of the word default may not apply to such as to foreclose but rather to a regular or default condition of an item. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit from foreclosure, and/or how to combine processes and systems from the present disclosure to enhance or benefit from foreclosure. Certain considerations for the person of skill in the art, in determining whether the term foreclosure, foreclose condition, default and the like is referring to failure of a borrower to meet the terms of a loan and the related attempts by the lender to recover the balance of the loan or obtain ownership of the collateral.
[0263] The terms validation of title, title validation, validating title, and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure validation of title and title validation include any efforts to verify or confirm the ownership or interest by an individual or entity in an item of property such as a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. Efforts to verify ownership may include reference to bills of sale, government documentation of transfer of ownership, a legal will transferring ownership, documentation of retirement of liens on the item of property, verification of assignment of Intellectual Property to the proposed borrower in the appropriate jurisdiction, and the like. For real-estate property validation may include a review of deeds and records at a courthouse of a country, a state, a county or a district in which a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a vehicle, a ship, a plane, or a warehouse is located or registered. Certain usages of the word validation may not apply to validation of a title or title validation but rather to confirmation that a process is operating correctly, that an individual has been correctly identified using biometric data, that intellectual property rights are in effect, that data is correct and meaningful, and the like. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit from title validation, and/or how to combine processes and systems from the present disclosure to enhance or benefit from title validation. Certain considerations for the person of skill in the art, in determining whether the term validation is referring to title validation, are specifically contemplated within the scope of the present disclosure. [0264] Without limitation to any other aspect or description of the present disclosure, validation includes any validating system including, without limitation, validating title for collateral or security for a loan, validating conditions of collateral for security or a loan, validating conditions of a guarantee for a loan, and the like. For instance, a validation service may provide lenders a mechanism to deliver loans with more certainty, such as through validating loan or security information components (e.g., income, employment, title, conditions for a loan, conditions of collateral, and conditions of an asset). In a non- limiting example, a validation service circuit may be structured to validate a plurality of loan information components with respect to a financial entity configured to determine a loan condition for an asset. Certain components may not be considered a validating system individually, but may be considered validating in an aggregated system - for example, an Internet of Things component may not be considered a validating component on its own, however an Internet of Things component utilized for asset data collection and monitoring may be considered a validating component when applied to validating a reliability parameter of a personal guarantee for a load when the Internet of Things component is associated with a collateralized asset. In certain embodiments, otherwise similar looking systems may be differentiated in determining whether such systems are for validation. For example, a blockchain- based ledger may be used to validate identities in one instance and to maintain confidential information in another instance. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered a system for validation herein, while in certain embodiments a given system may not be considered a validating system herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a validating system and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: a lending platform having a social network monitoring system for validating the reliability of a guarantee for a loan; a lending platform having an Internet of Things data collection and monitoring system for validating reliability of a guarantee for a loan; a lending platform having a crowdsourcing and automated classification system for validating conditions of an issuer for a bond; a crowdsourcing system for validating quality, title, or other conditions of collateral for a loan; a biometric identify validation application such as utilizing DNA or fingerprints; IoT devices utilized to collectively validate location and identity of a fixed asset that is tagged by a virtual asset tag; validation systems utilizing voting or consensus protocols; artificial intelligence systems trained to recognize and validate events; validating information such as title records, video footage, photographs, or witnessed statements; validation representations related to behavior, such as to validate occurrence of conditions of compliance, to validate occurrence of conditions of default, to deter improper behavior or misrepresentations, to reduce uncertainty, or to reduce asymmetries of information; and the like.
[0265] The term underwriting (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, underwriting includes any underwriting, including, without limitation, relating to underwriters, providing underwriting information for a loan, underwriting a debt transaction, underwriting a bond transaction, underwriting a subsidized loan transaction, underwriting a securities transaction, and the like. Underwriting services may be provided by financial entities, such as banks, insurance or investment houses, and the like, whereby the financial entity guarantees payment in case of a determination of a loss condition (e.g., damage or financial loss) and accept the financial risk for liability arising from the guarantee. For instance, a bank may underwrite a loan through a mechanism to perform a credit analysis that may lead to a determination of a loan to be granted, such as through analysis of personal information components related to an individual borrower requesting a consumer loan (e.g., employment history, salary and financial statements publicly available information such as the borrower's credit history), analysis of business financial information components from a company requesting a commercial load (e.g., tangible net worth, ratio of debt to worth (leverage), and available liquidity (current ratio)), and the like. In a non limiting example, an underwriting services circuit may be structured to underwrite a financial transaction including a plurality of financial information components with respect to a financial entity configured to determine a financial condition for an asset. In certain embodiments, underwriting components may be considered underwriting for some purposes but not for other purposes - for example, an artificial intelligence system to collect and analyze transaction data may be utilized in conjunction with a smart contract platform to monitor loan transactions, but alternately used to collect and analyze underwriting data, such as utilizing a model trained by human expert underwriters. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered underwriting herein, while in certain embodiments a given system may not be considered underwriting herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is underwriting and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: a lending platform having an underwriting system for a loan with a set of data- integrated microservices such as including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions; underwriting processes, operations, and services; underwriting data, such as data relating to identities of prospective and actual parties involved insurance and other transactions, actuarial data, data relating to probability of occurrence and/or extent of risk associated with activities, data relating to observed activities and other data used to underwrite or estimate risk; an underwriting application, such as, without limitation, for underwriting any insurance offering, any loan, or any other transaction, including any application for detecting, characterizing or predicting the likelihood and/or scope of a risk, an underwriting or inspection flow about an entity serving a lending solution, an analytics solution, or an asset management solution; underwriting of insurance policies, loans, warranties, or guarantees; a blockchain and smart contract platform for aggregating identity and behavior information for insurance underwriting, such as with an optional distributed ledger to record a set of events, transactions, activities, identities, facts, and other information associated with an underwriting process; a crowdsourcing platform such as for underwriting of various types of loans, and guarantees; an underwriting system for a loan with a set of data- integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions; an underwriting solution to create, configure, modify, set or otherwise handle various rules, thresholds, conditional procedures, workflows, or model parameters; an underwriting action or plan for management a set of loans of a given type or types based on one or more events, conditions, states, actions, secondary loans or transactions to back loans, for collection, consolidation, foreclosure, situations of bankruptcy of insolvency, modifications of existing loans, situations involving market changes, foreclosure activities; adaptive intelligent systems including artificial intelligent models trained on a training set of underwriting activities by experts and/or on outcomes of underwriting actions to generate a set of predictions, classifications, control instructions, plans, models; underwriting system for a loan with a set of data- integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions; and the like.
[0266] The term insuring (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, insuring includes any insuring, including, without limitation, providing insurance for a loan, providing evidence of insurance for an asset related to a loan, a first entity accepting a risk or liability for another entity, and the like. Insuring, or insurance, may be a mechanism through which a holder of the insurance is provided protection from a financial loss, such as in a form of risk management against the risk of a contingent or uncertain loss. The insuring mechanism may provide for an insurance, determine the need for an insurance, determine evidence of insurance, and the like, such as related to an asset, transaction for an asset, loan for an asset, security, and the like. An entity which provides insurance may be known as an insurer, insurance company, insurance carrier, underwriter, and the like. For instance, a mechanism for insuring may provide a financial entity with a mechanism to determine evidence of insurance for an asset related to a loan. In a non limiting example, an insurance service circuit may be structured to determine an evidence condition of insurance for an asset based on a plurality of insurance information components with respect to a financial entity configured to determine a loan condition for an asset. In certain embodiments, components may be considered insuring for some purposes but not for other purposes - for example a blockchain and smart contract platform may be utilized to manage aspects of a loan transaction such as for identity and confidentiality, but may alternately be utilized to aggregate identity and behavior information for insurance underwriting. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered insuring herein, while in certain embodiments a given system may not be considered insuring herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is insuring and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: insurance facilities such as branches, offices, storage facilities, data centers, underwriting operations and others; insurance claims, such as for business interruption insurance, product liability insurance, insurance on goods, facilities, or equipment, flood insurance, insurance for contract-related risks, and many others, as well as claims data relating to product liability, general liability, workers compensation, injury and other liability claims and claims data relating to contracts, such as supply contract perfom lance claims, product delivery requirements, contract claims, claims for damages, claims to redeem points or rewards, claims of access rights, warranty claims, indemnification claims, energy production requirements, delivery requirements, timing requirements, milestones, key performance indicators and others; insurance-related lending; an insurance service, an insurance brokerage service, a life insurance service, a health insurance service, a retirement insurance service, a property insurance service, a casualty insurance service, a finance and insurance service, a reinsurance service; a blockchain and smart contract platform for aggregating identity and behavior information for insurance underwriting; identities of applicants for insurance, identities of parties that may be willing to offer insurance, information regarding risks that may be insured (of any type, without limitation, such as property, life, travel, infringement, health, home, commercial liability, product liability, auto, fire, flood, casualty, retirement, unemployment; distributed ledger may be utilized to facilitate offering and underwriting of microinsurance, such as for defined risks related to defined activities for defined time periods that are narrower than for typical insurance policies; providing insurance for a loan, providing evidence of insurance for property related to a loan; and the like.
[0267] The term aggregation (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, an aggregation or to aggregate includes any aggregation including, without limitation, aggregating items together, such as aggregating or linking similar items together (e.g., collateral to provide collateral for a set of loans, collateral items for a set of loans is aggregated in real time based on a similarity in status of the set of items, and the like), collecting data together (e.g., for storage, for communication, for analysis, as training data for a model, and the like), summarizing aggregated items or data into a simpler description, or any other method for creating a whole formed by combining several (e.g., disparate) elements. Further, an aggregator may be any system or platform for aggregating, such as described. Certain components may not be considered aggregation individually but may be considered aggregation in an aggregated system - for example a collection of loans may not be considered an aggregation of loans of itself but may be an aggregation if collected as such. In a non-limiting example, an aggregation circuit may be structured to provide lenders a mechanism to aggregate loans together from a plurality of loans, such as based on a loan attribute, parameter, term or condition, financial entity, and the like, to become an aggregation of loans. In certain embodiments, an aggregation may be considered an aggregation for some purposes but not for other purposes - for example for example, an aggregation of asset collateral conditions may be collected for the purpose of aggregating loans together in one instance and for the purpose of determining a default action in another instance. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such systems are aggregators, and/or which type of aggregating systems. For example, a first and second aggregator may both aggregate financial entity data, where the first aggregator aggregates for the sake of building a training set for an analysis model circuit and where the second aggregator aggregates financial entity data for storage in a blockchain-based distributed ledger. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered as aggregation herein, while in certain embodiments a given system may not be considered aggregation herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is aggregation and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation forward market demand aggregation (e.g., blockchain and smart contract platform for forward market demand aggregation, interest expressed or committed in a demand aggregation interface, blockchain used to aggregate future demand in a forward market with respect to a variety of products and services, process a set of potential configurations having different parameters for a subset of configurations that are consistent with each other and the subset of configurations used to aggregate committed future demand for the offering that satisfies a sufficiently large subset at a profitable price, and the like); correlated aggregated data (including trend information) on worker ages, credentials, experience (including by process type) with data on the processes in which those workers are involved; demand for accommodations aggregated in advance and conveniently fulfilled by automatic recognition of conditions that satisfy pre-configured commitments represented on a blockchain (e.g., distributed ledger); transportation offerings aggregated and fulfilled (e.g., with a wide range of pre-defined contingencies); aggregation of goods and services on the blockchain (e.g., a distributed ledger used for demand planning); with respect to a demand aggregation interface (e.g., presented to one or more consumers); aggregation of multiple submissions; aggregating identity and behavior information (e.g., insurance underwriting); accumulation and aggregation of multiple parties; aggregation of data for a set of collateral; aggregated value of collateral or assets (e.g., based on real time condition monitoring, real- time market data collection and integration, and the like); aggregated tranches of loans; collateral for smart contract aggregated with other similar collateral; and the like.
[0268] The term linking (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, linking includes any linking, including, without limitation, linking as a relationship between two things or situations (e.g., where one thing affects the other). For instance, linking a subset of similar items such as collateral to provide collateral for a set of loans. Certain components may not be considered linked individually, but may be considered in a process of linking in an aggregated system - for example, a smart contracts circuit may be structured to operate in conjunction with a blockchain circuit as part of a loan processing platform but where the smart contracts circuit processes contracts without storing information through the blockchain circuit, however the two circuits could be linked through the smart contracts circuit linking financial entity information through a distributed ledger on the blockchain circuit. In certain embodiments, linking may be considered linking for some purposes but not for other purposes - for example, linking goods and services for users and radio frequency linking between access points are different forms of linking, where the linking of goods and services for users links things together while an RF link is a communications link between transceivers. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such system are linking, and/or which type of linking. For example, linking similar data together for analysis is different from linking similar data together for graphing. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered linking herein, while in certain embodiments a given system may not be considered a linking herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is linking and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation linking marketplaces or external marketplaces with a system or platform; linking data (e.g., data cluster including links and nodes); storage and retrieval of data linked to local processes; links (e.g. with respect to nodes) in a common knowledge graph; data linked to proximity or location (e.g., of the asset); linking to an environment (e.g., goods, services, assets, and the like); linking events (e.g., for storage such as in a blockchain, for communication or analysis); linking ownership or access rights; linking to access tokens (e.g., travel offerings linked to access tokens); links to one or more resources (e.g., secured by cryptographic or other techniques); linking a message to a smart contract; and the like.
[0269] The term indicator of interest (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, an indicator of interest includes any indicator of interest including, without limitation, an indicator of interest from a user or plurality of users or parties related to a transaction and the like (e.g., parties interested in participating in a loan transaction), the recording or storing of such an interest (e.g., a circuit for recording an interest input from a user, entity, circuit, system, and the like), a circuit analyzing interest related data and setting an indicator of interest (e.g., a circuit setting or communicating an indicator based on inputs to the circuit, such as from users, parties, entities, systems, circuits, and the like), a model trained to determine an indicator of interest from input data related to an interest by one of a plurality of inputs from users, parties, or financial entities, and the like. Certain components may not be considered indicators of interest individually, but may be considered an indicator of interest in an aggregated system - for example, a party may seek information relating to a transaction such as though a translation marketplace where the party is interested in seeking information, but that may not be considered an indicator of interest in a transaction. However, when the party asserts a specific interest (e.g., through a user interface with control inputs for indicating interest) the party’s interest may be recorded (e.g., in a storage circuit, in a blockchain circuit), analyzed (e.g., through an analysis circuit, a data collection circuit), monitored (e.g., through a monitoring circuit), and the like. In a non-limiting example, indicators of interest may be recorded (e.g., in a blockchain through a distributed ledger) from a set of parties with respect to the product, service, or the like, such as ones that define parameters under which a party is willing to commit to purchase a product or service. In certain embodiments, an indicator of interest may be considered an indicator of interest for some purposes but not for other purposes - for example, a user may indicate an interest for a loan transaction but that does not necessarily mean the user is indicating an interest in providing a type of collateral related to the loan transaction. For instance, a data collection circuit may record an indicator of interest for the transaction but may have a separate circuit structure for determining an indication of interest for collateral. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such system are determining an indication of interest, and/or which type of indicator of interest exists. For example, one circuit or system may collect data from a plurality of parties to determine an indicator of interest in securing a loan and a second circuit or system may collect data from a plurality of parties to determine an indicator of interest in a determining ownership rights related to a loan. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered an indicator of interest herein, while in certain embodiments a given system may not be considered an indicator of interest herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is an indicator of interest and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation parties indicating an interest in participating in a transaction (e.g., a loan transaction), parties indicating an interest in securing in a product or service, recording or storing an indication of interest (e.g., through a storage circuit or blockchain circuit), analyzing an indication of interest (e.g., through a data collection and/or monitoring circuit), and the like. [0270] The term accommodations (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, an accommodation includes any service, activity, event, and the like such as including, without limitation, a room, group of rooms, table, seating, building, event, shared spaces offered by individuals (e.g., airbnb™ spaces), bed-and-breakfasts, workspaces, conference rooms, convention spaces, fitness accommodations, health and wellness accommodations, dining accommodations, and the like, in which someone may live, stay, sit, reside, participate, and the like. As such, an accommodation may be purchased (e.g., a ticket through a sports ticketing application), reserved or booked (e.g., a reservation through a hotel reservation application), provided as a reward or gift, traded or exchanged (e.g., through a marketplace), provided as an access right (e.g., offering by way of an aggregation demand), provided based on a contingency (e.g., a reservation for a room being contingent on the availability of a nearby event), and the like. Certain components may not be considered an accommodation individually but may be considered an accommodation in an aggregated system - for example, a resource such as a room in a hotel may not in itself be considered an accommodation but a reservation for the room may be. For instance, a blockchain and smart contract platform for forward market rights for accommodations may provide a mechanism to provide access rights with respect to accommodations· In a non limiting example, a blockchain circuit may be structured to store access rights in a forward demand market, where the access rights may be stored in a distributed ledger with related shared access to a plurality of actionable entities. In certain embodiments, an accommodation may be considered an accommodation for some purposes but not for other purposes - for example, a reservation for a room may be an accommodation on its own, but may not be accommodation that is satisfied if a related contingency is not met as agreed upon at the time of the e.g. reservation. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such systems are related to an accommodation, and/or which type of accommodation· For example, an accommodation offering may be made based on different systems, such as one where the accommodation offering is determined by a system collecting data related to forward demand and a second one where the accommodation offering is provided as a reward based on a system processing a performance parameter. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered as related to an accommodation herein, while in certain embodiments a given system may not be considered related to an accommodation herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is related to accommodation and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation an accommodations provided as determined through a service circuit, trading or exchanging services (e.g., through an application and/or user interface), as an accommodation offering such as with respect to a combination of products, services, and access rights, processed (e.g., aggregation demand for the offering in a forward market), accommodation through booking in advance, accommodation through booking in advance upon meeting a certain condition (e.g., relating to a price within a given time window), and the like.
[0271] The term contingencies (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a contingency includes any contingency including, without limitation, any action that is dependent upon a second action. For instance, a service may be provided as contingent on a certain parameter value, such as collecting data as condition upon an asset tag indication from an Internet of Things circuit. In another instance, an accommodation such as a hotel reservation may be contingent upon a concert (local to the hotel and at the same time as the reservation) proceeding as scheduled. Certain components may not be considered as relating to a contingency individually, but may be considered related to a contingency in an aggregated system - for example, a data input collected from a data collection service circuit may be stored, analyzed, processed, and the like, and not be considered with respect to a contingency, however a smart contracts service circuit may apply a contract term as being contingent upon the collected data. For instance, the data may indicate a collateral status with respect to a loan transaction, and the smart contracts service circuit may apply that data to a term of contract that depends upon the collateral. In certain embodiments, a contingency may be considered contingency for some purposes but not for other purposes - for example, a delivery of contingent access rights for a future event may be contingent upon a loan condition being satisfied, but the loan condition on its own may not be considered a contingency in the absence of the contingency linkage between the condition and the access rights. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such systems are related to a contingency, and/or which type of contingency. For example, two algorithms may both create a forward market event access right token, but where the first algorithm creates the token free of contingencies and the second algorithm creates a token with a contingency for delivery of the token. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered a contingency herein, while in certain embodiments a given system may not be considered a contingency herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a contingency and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation a forward market operated within or by the platform may be a contingent forward market, such as one where a future right is vested, is triggered, or emerges based on the occurrence of an event, satisfaction of a condition, or the like; a blockchain used to make a contingent market in any form of event or access token by securely storing access rights on a distributed ledger; setting and monitoring pricing for contingent access rights, underlying access rights, tokens, fees and the like; optimizing offerings, timing, pricing, or the like, to recognize and predict patterns, to establish rules and contingencies; exchanging contingent access rights or underlying access rights or tokens access tokens and/or contingent access tokens; creating a contingent forward market event access right token where a token may be created and stored on a blockchain for contingent access right that could result in the ownership of a ticket; discovery and delivery of contingent access rights to future events; contingencies that influence or represent future demand for an offering, such as including a set of products, services, or the like; pre-defined contingencies; optimized offerings, timing, pricing, or the like, to recognize and predict patterns, to establish rules and contingencies; creation of a contingent future offering within the dashboard; contingent access rights that may result in the ownership of the virtual good or each smart contract to purchase the virtual good if and when it becomes available under defined conditions; and the like.
[0272] The term level of service (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a level of service includes any level of service including, without limitation, any qualitative or quantitative measure of the extent to which a service is provided, such as, and without limitation, a first class vs. business class service (e.g., travel reservation or postal delivery), the degree to which a resource is available (e.g., service level A indicating that the resource is highly available vs. service level C indicating that the resource is constrained, such as in terms of traffic flow restrictions on a roadway), the degree to which an operational parameter is performing (e.g., a system is operating at a high state of service vs a low state of service, and the like. In embodiments, level of service may be multi-modal such that the level of service is variable where a system or circuit provides a service rating (e.g., where the service rating is used as an input to an analytical circuit for determining an outcome based on the service rating). Certain components may not be considered relative to a level of service individually, but may be considered relative to a level of service in an aggregated system - for example a system for monitoring a traffic flow rate may provide data on a current rate but not indicate a level of service, but when the determined traffic flow rate is provided to a monitoring circuit the monitoring circuit may compare the determined traffic flow rate to past traffic flow rates and determine a level of service based on the comparison. In certain embodiments, a level of service may be considered a level of service for some purposes but not for other purposes - for example, the availability of first class travel accommodation may be considered a level of service for determining whether a ticket will be purchased but not to project a future demand for the flight. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such system utilizes a level of service, and/or which type of level of service. For example, an artificial intelligence circuit may be trained on past level of service with respect to traffic flow patterns on a certain freeway and used to predict future traffic flow patterns based on current flow rates, but a similar artificial intelligence circuit may predict future traffic flow patterns based on the time of day. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered with respect to levels of service herein, while in certain embodiments a given system may not be considered with respect to levels of service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a level of service and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation transportation or accommodation offerings with predefined contingencies and parameters such as with respect to price, mode of service, and level of service; warranty or guarantee application, transportation marketplace, and the like.
[0273] The term payment (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a payment includes any payment including, without limitation, an action or process of paying (e.g., a payment to a loan) or of being paid (e.g., a payment from insurance), an amount paid or payable (e.g., a payment of $1000 being made), a repayment (e.g., to pay back a loan), a mode of payment (e.g., use of loyalty programs, rewards points, or particular currencies, including cryptocurrencies) and the like. Certain components may not be considered payments individually, but may be considered payments in an aggregated system - for example, submitting an amount of money may not be considered a payment as such, but when applied to a payment to satisfy the requirement of a loan may be considered a payment (or repayment). For instance, a data collection circuit may provide lenders a mechanism to monitor repayments of a loan. In a non-limiting example, the data collection circuit may be structured to monitor the payments of a plurality of loan components with respect to a financial loan contract configured to determine a loan condition for an asset. In certain embodiments, a payment may be considered a payment for some purposes but not for other purposes - for example a payment to a financial entity may be for a repayment amount to pay back the loan, or it may be to satisfy a collateral obligation in a loan default condition. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such system are related to a payment, and/or which type of payment. For example, funds may be applied to reserve an accommodation or to satisfy the delivery of services after the accommodation has been satisfied. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered a payment herein, while in certain embodiments a given system may not be considered a payment herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a payment and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation, deferring a required payment; deferring a payment requirement; payment of a loan; a payment amount; a payment schedule; a balloon payment schedule; payment performance and satisfaction; modes of payment; and the like.
[0274] The term location (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a location includes any location including, without limitation, a particular place or position of a person, place, or item, or location information regarding the position of a person, place, or item, such as a geolocation (e.g., geolocation of a collateral), a storage location (e.g., the storage location of an asset), a location of a person (e.g., lender, borrower, worker), location information with respect to the same, and the like. Certain components may not be considered with respect to location individually, but may be considered with respect to location in an aggregated system - for example, a smart contract circuit may be structured to specify a requirement for a collateral to be stored at a fixed location but not specify the specific location for a specific collateral. In certain embodiments, a location may be considered a location for some purposes but not for other purposes - for example, the address location of a borrower may be required for processing a loan in one instance, and a specific location for processing a default condition in another instance. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such system are a location, and/or which type of location. For example, the location of a music concert may be required to be in a concert hall seating 10,000 people in one instance but specify the location of an actual concert hall in another. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered with respect to a location herein, while in certain embodiments a given system may not be considered with respect to a location herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is considered with respect to a location and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation a geolocation of an item or collateral; a storage location of item or asset; location information; location of a lender or a borrower; location-based product or service targeting application; a location-based fraud detection application; indoor location monitoring systems (e.g., cameras, IR systems, motion-detection systems); locations of workers (including routes taken through a location); location parameters; event location; specific location of an event; and the like.
[0275] The term route (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a route includes any route including, without limitation, a way or course taken in getting from a starting point to a destination, to send or direct along a specified course, and the like. Certain components may not be considered with respect to a route individually, but may be considered a route in an aggregated system - for example a mobile data collector may specify a requirement for a route for collecting data based on an input from a monitoring circuit, but only in receiving that input does the mobile data collector determine what route to take and begin traveling along the route. In certain embodiments, a route may be considered a route for some purposes but not for other purposes - for example possible routes through a road system may be considered differently than specific routes taken through from one location to another location. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such system are specified with respect to a location, and/or which types of locations. For example, routes depicted on a map may indicate possible routes or actual routes taken by individuals. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered with respect to a route herein, while in certain embodiments a given system may not be considered with respect to a route herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is utilizing a route and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation delivery routes; routes taken through a location; heat map showing routes traveled by customers or workers within an environment; determining what resources are deployed to what routes or types of travel; direct route or multi-stop route, such as from the destination of the consumer to a specific location or to wherever an event takes place; a route for a mobile data collector; and the like.
[0276] The term future offering (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a future offing includes any offer of an item or service in the future including, without limitation, a future offer to provide an item or service, a future offer with respect to a proposed purchase, a future offering made through a forward market platform, a future offering determined by a smart contract circuit, and the like. Further, a future offering may be a contingent future offer or an offer based on conditions resulting on the offer being a future offering, such as where the future offer is contingent upon or with the conditions imposed by a predetermined condition (e.g., a security may be purchased for $1000 at a set future date contingent upon a predetermine state of a market indicator). Certain components may not be considered a future offering individually, but may be considered a future offering in an aggregated system - for example, an offer for a loan may not be considered a future offering if the offer is not authorized through a collective agreement amongst a plurality of parties related to the offer, but may be considered a future offer once a vote has been collected and stored through a distributed ledger, such as through a blockchain circuit. In certain embodiments, a future offering may be considered a future offering for some purposes but not for other purposes - for example, a future offering may be contingent upon a condition being meet in the future, and so the future offering may not be considered a future offer until the condition is met. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such system are future offerings, and/or which type of future offerings. For example, two security offerings may be determined to be offerings to be made at a future time, however, one may have immediate contingences to be met and thus may not be considered to be a future offering but rather an immediate offering with future declarations. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered in association with a future offering herein, while in certain embodiments a given system may not be considered in association with a future offering herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is in association with a future offering and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation a forward offering, a contingent forward offering, a forward offing in a forward market platform (e.g., for creating a future offering or contingent future offering associated with identifying offering data from a platform-operated marketplace or external marketplace); a future offering with respect to entering into a smart contract (e.g., by executing an indication of a commitment to purchase, attend, or otherwise consume a future offering), and the like.
[0277] The term access right (and derivatives or variations) as utilized herein may be understood broadly to describe an entitlement to acquire or possess a property, article, or other thing of value. A contingent access right may be conditioned upon a trigger or condition being met before such an access right becomes entitled, vested or otherwise defensible. An access right or contingent access right may also serve specific purposes or be configured for different applications or contexts, such as, without limitation, loan-related actions or any service or offering. Without limitation, notices may be required to be provided to the owner of a property, article or item of value before such access rights or contingent access rights are exercised. Access rights and contingent access rights in various forms may be included where discussing a legal action, a delinquent or defaulted loan or agreement, or other circumstances where a lender may be seeking remedy, without limitation. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the value of such rights implemented in an embodiment. While specific examples of access rights and contingent access rights are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0278] The term smart contract (and other forms or variations) as utilized herein may be understood broadly to describe a method, system, connected resource or wide area network offering one or more resources useful to assist or perform actions, tasks or things by embodiments disclosed herein. A smart contract may be a set of steps or a process to negotiate, administrate, restructure or implement an agreement or loan between parties. A smart contract may also be implemented as an application, website, FTP site, server, appliance or other connected component or Internet related system that renders resources to negotiate, administrate, restructure or implement an agreement or loan between parties. A smart contract may be a self contained system, or may be part of a larger system or component that may also be a smart contract. For example, a smart contract may refer to a loan or an agreement itself, conditions or terms, or may refer to a system to implement such a loan or agreement. In certain embodiments, a smart contract circuit or robotic process automation system may incorporate or be incorporated into automatic robotic process automation system to perform one or more purposes or tasks, whether part of a loan or transaction process, or otherwise. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of this term as it relates to a smart contract in various forms, embodiments and contexts disclosed herein.
[0279] The term allocation of reward (and variations) as utilized herein may be understood broadly to describe a thing or consideration allocated or provided as consideration, or provided for a purpose. The allocation of rewards can be of a financial type, or non-financial type, without limitation. A specific type of allocation of reward may also serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: a reward event, claims for rewards, monetary rewards, rewards captured as a data set, rewards points, and other forms of rewards. Thus an allocation of rewards may be provided as a consideration within the context of a loan or agreement. Systems may be utilized to allocate rewards. The allocation of rewards in various forms may be included where discussing a particular behavior, or encouragement of a particular behavior, without limitation. An allocation of a reward may include an actual dispensation of the award, and/or a recordation of the reward. The allocation of rewards may be performed by a smart contract circuit or a robotic processing automation system. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the value of the allocation of rewards in an embodiment. While specific examples of the allocation of rewards are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.
[0280] The term satisfaction of parameters or conditions (and other derivatives, forms, or variations) as utilized herein may be understood broadly to describe completion, presence or proof of parameters or conditions that have been met. The term generally may relate to a process of determining such satisfaction of parameters or conditions, or may relate to the completion of such a process with a result, without limitation. Satisfaction may result in a successful outcome of other triggers or conditions or terms that may come into execution, without limitation. Satisfaction of parameters or conditions may occur in many different contexts of contracts or loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, and data processing (e.g. data collection), or combinations thereof, without limitation. Satisfaction of parameters or conditions may be used in the form of a noun (e.g. the satisfaction of the debt repayment), or may be used in a verb form to describe the process of determining a result to parameters or conditions. For example, a borrower may have satisfaction of parameters by making a certain number of payments on time, or may cause satisfaction of a condition allowing access rights to an owner if a loan defaults, without limitation. In certain embodiments, a smart contract or robotic process automation system may perform or determine satisfaction of parameters or conditions for one or more of the parties and process appropriate tasks for satisfaction of parameters or conditions. In some cases satisfaction of parameters or conditions by the smart contract or robotic process automation system may not complete or be successful, and depending upon such outcomes, this may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of this term in various forms, embodiments and contexts disclosed herein.
[0281] The term information (and other forms such as info or informational, without limitation) as utilized herein may be understood broadly in a variety of contexts with respect to an agreement or a loan. The term generally may relate to a larger context, such as information regarding an agreement or loan, or may specifically relate to a finite piece of information (e.g. a specific detail of an event that happened on a specific date). Thus, information may occur in many different contexts of contracts or loans, and may be used in the contexts, without limitation of evidence, transactions, access, and the like. Or, without limitation, information may be used in conjunction with stages of an agreement or transaction, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, and information processing (e.g. data or information collection), or combinations thereof. For example, information as evidence, transaction, access, etc. may be used in the form of a noun (e.g. the information was acquired from the borrower), or may refer as a noun to an assortment of informational items (e.g. the information about the loan may be found in the smart contract), or may be used in the form of characterizing as an adjective (e.g. the borrower was providing an information submission). For example, a lender may collect an overdue payment from a borrower through an online payment, or may have a successful collection of overdue payments acquired through a customer service telephone call. In certain embodiments, a smart contract circuit or robotic process automation system may perform collection, administration, calculating, providing, or other tasks for one or more of the parties and process appropriate tasks relating to information (e.g. providing notice of an overdue payment). In some cases information by the smart contract circuit or robotic process automation system may be incomplete, and depending upon such outcomes this may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of information as evidence, transaction, access, etc. in various forms, embodiments and contexts disclosed herein. [0282] Information may be linked to external information (e.g. external sources). The term more specifically may relate to the acquisition, parsing, receiving, or other relation to an external origin or source, without limitation. Thus, information linked to external information or sources may be used in conjunction with stages of an agreement or transaction, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, and information processing (e.g. data or information collection), or combinations thereof. For example, information linked to external information may change as the external information changes, such as a borrower’s credit score, which is based on an external source. In certain embodiments, a smart contract circuit or robotic process automation system may perform acquisition, administration, calculating, receiving, updating, providing or other tasks for one or more of the parties and process appropriate tasks relating to information that is linked to external information. In some cases information that is linked to external information by the smart contract or robotic process automation system may be incomplete, and depending upon such outcomes this may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of this term in various forms, embodiments and contexts disclosed herein.
[0283] Information that is a part of a loan or agreement may be separated from information presented in an access location. The term more specifically may relate to the characterization that information can be apportioned, split, restricted, or otherwise separated from other information within the context of a loan or agreement. Thus, information presented or received on an access location may not necessarily be the whole information available for a given context. For example, information provided to a borrower may be different information received by a lender from an external source, and may be different than information received or presented from an access location. In certain embodiments, a smart contract circuit or robotic process automation system may perform separation of information or other tasks for one or more of the parties and process appropriate tasks. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of this term in various forms, embodiments and contexts disclosed herein.
[0284] The term encryption of information and control of access (and other related terms) as utilized herein may be understood broadly to describe generally whether a party or parties may observe or possess certain information, actions, events or activities relating to a transaction or loan. Encryption of information may be utilized to prevent a party from accessing, observing or receiving information, or may alternatively be used to prevent parties outside the transaction or loan from being able to access, observe or receive confidential (or other) information. Control of access to information relates to the determination of whether a party is entitled to such access of information. Encryption of information or control of access may occur in many different contexts of loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, administration, negotiating, collecting, procuring, enforcing, and data processing (e.g. data collection), or combinations thereof, without limitation. An encryption of information or control of access to information may refer to a single instance, or may characterize a larger amount of information, actions, events or activities, without limitation. For example, a borrower or lender may have access to information about a loan, but other parties outside the loan or agreement may not be able to access the loan information due to encryption of the information, or a control of access to the loan details. In certain embodiments, a smart contract circuit or robotic process automation system may perform encryption of information or control of access to information for one or more of the parties and process appropriate tasks for encryption or control of access of information. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of this term in various forms, embodiments and contexts disclosed herein.
[0285] The term potential access party list (and other related terms) as utilized herein may be understood broadly to describe generally whether a party or parties may observe or possess certain information, actions, events, or activities relating to a transaction or loan. A potential access party list may be utilized to authorize one or more parties to access, observe or receive information, or may alternatively be used to prevent parties from being able to do so. A potential access party list information relates to the determination of whether a party (either on the potential access party list or not on the list) is entitled to such access of information. A potential access party list may occur in many different contexts of loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, administration, negotiating, collecting, procuring, enforcing and data processing (e.g. data collection), or combinations thereof, without limitation. A potential access party list may refer to a single instance, or may characterize a larger amount of parties or information, actions, events or activities, without limitation. For example, a potential access party list may grant (or deny) access to information about a loan, but other parties outside potential access party list may not be able to (or may be granted) access the loan information. In certain embodiments, a smart contract circuit or robotic process automation system may perform administration or enforcement of a potential access party list for one or more of the parties and process appropriate tasks for encryption or control of access of information. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of this term in various forms, embodiments and contexts disclosed herein.
[0286] The term offering, making an offer, and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, an offering includes any offer of an item or service including, without limitation, an insurance offering, a security offering, an offer to provide an item or service, an offer with respect to a proposed purchase, an offering made through a forward market platform, a future offering, a contingent offering, offers related to lending (e.g. lending, refinancing, collection, consolidation, factoring, brokering, foreclosure), an offering determined by a smart contract circuit, an offer directed to a customer/debtor, an offering directed to a provider/lender, a 3rd party offer (e.g. regulator, auditor, partial owner, tiered provider) and the like. Offerings may include physical goods, virtual goods, software, physical services, access rights, entertainment content, accommodations, or many other items, services, solutions, or considerations. In an example, a third party offer may be to schedule a band instead of just an offer of tickets for sale. Further, an offer may be based on pre-determined conditions or contingencies. Certain components may not be considered an offering individually, but may be considered an offering in an aggregated system - for example, an offer for insurance may not be considered an offering if the offer is not approved by one or more parties related to the offer, however once approval has been granted, it may be considered an offer. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered in association with an offering herein, while in certain embodiments a given system may not be considered in association with an offering herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and/or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is in association with an offering and/or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation the item or service being offered, a contingency related to the offer, a way of tracking if a contingency or condition has been met, an approval of the offering, an execution of an exchange of consideration for the offering, and the like.
[0287] The term artificial intelligence (AI) solution should be understood broadly. Without limitation to any other aspect of the present disclosure, an AI solution includes a coordinated group of AI related aspects to perform one or more tasks or operations as set forth throughout the present disclosure. An example AI solution includes one or more AI components, including any AI components set forth herein, including at least a neural network, an expert system, and/or a machine learning component. The example AI solution may include as an aspect the types of components of the solution, such as a heuristic AI component, a model based AI component, a neural network of a selected type (e.g., recursive, convolutional, perceptron, etc.), and/or an AI component of any type having a selected processing capability (e.g., signal processing, frequency component analysis, auditory processing, visual processing, speech processing, text recognition, etc.). Without limitation to any other aspect of the present disclosure, a given AI solution may be formed from the number and type of AI components of the AI solution, the connectivity of the AI components (e.g., to each other, to inputs from a system including or interacting with the AI solution, and/or to outputs to the system including or interacting with the AI solution). The given AI solution may additionally be formed from the connection of the AI components to each other within the AI solution, and to boundary elements (e.g., inputs, outputs, stored intermediary data, etc.) in communication with the AI solution. The given AI solution may additionally be formed from a configuration of each of the AI components of the AI solution, where the configuration may include aspects such as: model calibrations for an AI component; connectivity and/or flow between AI components (e.g., serial and/or parallel coupling, feedback loops, logic junctions, etc.); the number, selected input data, and/or input data processing of inputs to an AI component; a depth and/or complexity of a neural network or other component; a training data description of an AI component (e.g., training data parameters such as content, amount of training data, statistical description of valid training data, etc.); and/or a selection and/or hybrid description of a type for an AI component. An AI solution includes a selection of AI elements, flow connectivity of those AI elements, and/or configuration of those AI elements.
[0288] One of skill in the art, having the benefit of the present disclosure, can readily determine an AI solution for a given system, and/or configure operations to perform a selection and/or configuration operation for an AI solution for a given system. Certain considerations to determining an AI solution, and/or configuring operations to perform a selection and/or configuration operation for an AI solution include, without limitation: an availability of AI components and/or component types for a given implementation; an availability of supporting infrastructure to implement given AI components (e.g., data input values available, including data quality, level of service, resolution, sampling rate, etc.; availability of suitable training data for a given AI solution; availability of expert inputs, such as for an expert system and/or to develop a model training data set; regulatory and/or policy based considerations including permitted action by the AI solution, requirements for acquisition and/or retention of sensitive data, difficult to obtain data, and/or expensive data); operational considerations for a system including or interacting with the AI solution, including response time specifications, safety considerations, liability considerations, etc.; available computing resources such as processing capability, network communication capability, and/or memory storage capability (e.g., to support initial data, training data, input data such as cached, buffered, or stored input data, iterative improvement state data, output data such as cached, buffered, or stored output data, and/or intermediate data storage, such as data to support ongoing calculations, historical data, and/or accumulation data); the types of tasks to be performed by the AI solution, and the suitability of AI components for those tasks, sensitivity of AI components performing the tasks (e.g., variability of the output space relative to a disturbance size of the input space); the interactions of AI components within the entire AI solution (e.g., a low capability rationality AI component may be coupled with a higher capability AI component that may provide high sensitivity and/or unbounded response to inputs); and/or model implementation considerations (e.g., requirements to re-calibrate, aging constraints of a model, etc.).
[0289] A selected and/or configured AI solution may be utilized with any of the systems, procedures, and/or aspects of embodiments as set forth throughout the present disclosure. For example, a system utilizing an expert system may include the expert system as all or a part of a selected, configured AI solution. In another example, a system utilizing a neural network, and/or a combination of neural networks, may include the neural network(s) as all or a part of a selected, configured AI solution. The described aspects of an AI solution, including the selection and configuration of the AI solution, are non-limiting illustrations.
[0290] Referring to Fig. 1, an embodiment 100 of a financial, transactional and marketplace enablement system is illustrated wherein a lending enablement platform 100 is enabled and wherein a platform-oriented marketplace 132 may comprise a lending application 144. The lending enablement platform 100 may include a set of systems, applications, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, and other elements (collectively referred in the alternative, except where context indicates otherwise, as the “platform,” the “lending platform,” the “system,” and the like) working in coordination (such as by data integration and organization in a services oriented architecture) to enable intelligent management of a set of entities 198 that may occur, operate, transact or the like within, or own, operate, support or enable, one or more applications, services, solutions, programs or the like of the lending application 144 or external marketplaces 188 that involve lending transactions or lending-related entities, or that may otherwise be part of, integrated with, linked to, or operated on by the lending enablement platform 100. References to a set of services herein should be understood, except where context indicates otherwise, these and other various systems, applications, processes, modules, services, layers, devices, components, machines, products, sub systems, interfaces, connections, and other types of elements. Fig. 1 includes a management application platform 126 comprising a lending application 144, adaptive intelligence systems 158, monitoring systems 164, data collection system 166, data storage systems 186, all interfacing with data handling layers 168. Fig. 1 also depicts the disclosed systems having process and application outputs and outcomes 151 and in communication with entities 198. Components of the lending application 144 may include underwriting 103, risk management 122, analytics 130, pricing 131, tax 124, crowdsourcing system 120, smart contract 134, blockchain 136, lending model 108, trust and custody 150, platform marketplace 132, fraud 138, regulatory 142, payments 146, and security 148. A set may include multiple members or a single member. The adaptive intelligence systems 158 may include opportunity miners 153, robotic process automation (RPA) 154, artificial intelligence 156, artificial intelligence store 157, and clustering 104. The monitoring systems 164 and data collection system 166 may include software interaction observation 160, functional imaging 161, and physical process observation 162. The data storage system 186 may include access data 170, pricing data 178, asset and facility data 172, claims data 180, worker data 174, accounting data 182, event data 176, and underwriting data 184. Entities 198 may include external marketplaces 188, collateral 102, facilities 190, collaborative robotics 193, workers 194, wearable/portable devices 195, processes 196, and machines 197. As with other embodiments, the lending enablement platform 100 may have various data handling layers, with components, modules, systems, services, components, functions and other elements described in connection with other embodiments described throughout this disclosure and the documents incorporated herein by reference. This may include various adaptive intelligent systems 158, monitoring systems 164, data collection systems 166, and data storage systems 186, as well as a set of interfaces 187 of, to, and/or among each of those systems and/or the various other elements of the lending enablement platform 100. In embodiments the interfaces 187 may include application programming interfaces 112; data integration technologies for extracting, transforming, cleansing, normalizing, deduplicating, loading and the like as data is moved among various services using various protocols and formats (collectively referred to as ETL systems 114); and various ports, portals, connectors, gateways, wired connections, sockets, virtual private networks, containers, secure channels and other connections configured among elements on a one-to-one, one-to-many, or many-to-one basis, such as in unicast, broadcast and multi-cast transmission (collectively referred to as ports 118). Interfaces 187 may include, be enabled by, integrate with, or interface with a real time operating system (RTOS) 110, such as the FreeRTOS™ operating system, that has a deterministic execution pattern in which a user may define an execution pattern, such as based on assignment of a priority to each thread of execution. An instance of the RTOS 110 may be embedded, such as on a microcontroller of an Internet of Things device, such as one used to monitor various entities 198. The RTOS 110 may provide real-time scheduling (such as scheduling of data transmissions to monitoring systems 164 and data collection systems 166, scheduling of inter-task communication among various service elements, and other timing and synchronization elements). In embodiments the interfaces 187 may use or include a set of libraries that enable secure connection between small, low-power edge devices, such as Internet of Things devices used to monitor various entities 198, and various cloud-deployed services of the lending enablement platform 100, as well as a set of edge devices and the systems that enable them, such as ones running local data processing and computing systems such as AWS IoT Greengrass™ and/or AWS Lambda™ functions, such as to allow local calculation, configuration of data communication, execution of machine learning models (such as for prediction or classification), synchronization of devices or device data, and communication among devices and services. This may include use of local device resources such as serial ports, GPUs, sensors and cameras. In embodiments, data may be encrypted for secure end-to-end communication.
[0291] In the context of a lending enablement platform 100 and set of lending application 144, various entities 198 may include any of the wide variety of assets, systems, devices, machines, facilities, individuals or other entities mentioned throughout this disclosure or in the documents incorporated herein by reference, such as, without limitation: machines 197 and their components (e.g., machines that are the subject of a loan or collateral for a loan, such as various vehicles and equipment, as well as machines used to conduct lending transactions, such as automated teller machines, point of sale machines, vending machines, kiosks, smart-card-enabled machines, and many others, including ones used to enable microloans, payday loans and others); financial and transactional processes 196 (such as lending processes, inspection processes, collateral tracking processes, valuation processes, credit checking processes, creditworthiness processes, syndication processes, interest rate-setting processes, software processes (including applications, programs, services, and others), production processes, collection processes, banking processes (e.g., lending processes, underwriting processes, investing processes, and many others), financial service processes, diagnostic processes, security processes, safety processes, assessment processes, payment processes, valuation processes, issuance processes, factoring processes, consolidation processes, syndication processes, collection processes, foreclosure processes, title transfer processes, title verification processes, collateral monitoring processes, and many others); wearable and portable devices 195 (such as mobile phones, tablets, dedicated portable devices for financial applications, data collectors (including mobile data collectors), sensor-based devices, watches, glasses, hearables, head-worn devices, clothing-integrated devices, arm bands, bracelets, neck- worn devices, AR/VR devices, headphones, and many others); workers 194 (such as banking workers, loan officers, financial service personnel, managers, inspectors, brokers (e.g., mortgage brokers), attorneys, underwriters, regulators, assessors, appraisers, process supervisors, security personnel, safety personnel and many others); robotic systems 192 (e.g., physical robots, collaborative robots (e.g., “cobots”), software bots and others); and facilities 190 (such as banking facilities, inventory warehousing facilities, factories, homes, buildings, storage facilities (such as for loan-related collateral, property that is the subject of a loan, inventory (such as related to loans on inventory), personal property, components, packaging materials, goods, products, machinery, equipment, and other items), banking facilities (such as for commercial banking, investing, consumer banking, lending and many other banking activities) and others. In embodiments, various entities 198 may include external marketplaces 188, such as financial, commodities, e- commerce, advertising, and other external marketplaces 188 (including current and futures markets), such as ones within which transactions occur in various goods and services, such that monitoring of the external marketplaces 188 and various entities 198 within them may provide lending-relevant information, such as with respect to the price or value of items, the liquidity of items, the characteristics of items, the rate of depreciation of items, or the like. For example, for various entities that may comprise collateral 102 or assets for asset-backed lending, a monitoring system 164 may monitor not only the collateral 102 or assets, such as by cameras, sensors, or other monitoring systems 164, but may also collect data, such as via data collection systems 166 of various types, with respect to the value, price, or other condition of the collateral 102 or assets, such as by determining market conditions for collateral 102 or assets that are in similar condition, of similar age, having similar specifications, having similar location, or the like. In embodiments, an adaptive intelligent system 158 may include a clustering circuit 104, such as one that groups or clusters various entities 198, including collateral 102, parties, assets, or the like by similarity of attributes, such as a k-means clustering system, self-organizing map system, or other system as described herein and in the documents incorporated herein by reference. The clustering system may organize collections of collateral, collections of assets, collections of parties, and collections of loans, for example, such that they may be monitored and analyzed based on common attributes, such as to enable performance of a subset of transactions to be used to predict performance of others, which in turn may be used for underwriting 122, pricing 131, fraud prevention applications 138, or other applications, including any of the services, solutions, or applications described in connection with Fig. 1 and Fig. 2 or elsewhere throughout this disclosure or the documents incorporated herein by reference. In embodiments condition information about collateral 102 or assets is continuously monitored by a monitoring system 164, such as a set of sensors on the collateral 102 or assets, a set of sensors or cameras in the environment of the collateral 102 or assets, or the like, and market information is collected in real time by a data collection system 166, such that the condition and market information may be time- aligned and used as a basis for real time estimation of the value of the collateral or assets and forward prediction of the future value of the collateral or assets. Present and predicted value for the collateral 102 or assets may be based on a model, which may be accessed and used, such as in a smart contract, to enable automated, or machine-assisted lending on the collateral or assets, such as the underwriting or offering of a microloan on the collateral 102 or assets. Aggregation of data for a set of collateral 102 or set of assets, such as a collection or fleet of collateral 102 or fleet of assets owned by an entity 198 may allow real time portfolio valuation and larger scale lending, including via smart contracts that automatically adjust interest rates and other terms and conditions based on the individual or aggregated value of collateral 102 or assets based on real time condition monitoring and real-time market data collection and integration. Transactions, party information, transfers of title, changes in terms and conditions, and other information may be stored in a blockchain 136, including loan transactions and information (such as condition information for collateral 102 or assets and marketplace data) about the collateral 102 or assets. The smart contract may be configured to require a party to confirm condition information and/or market value information, such as by representations and warranties that are supported or verified by the monitoring systems 164 (which may flag fraud in a fraud prevention application 138). A lending model 108 may be used to value collateral 102 or assets, to determine eligibility for lending based on the condition and/or value of collateral 102 or assets, to set pricing (e.g., interest rates), to adjust terms and conditions, and the like. The lending model 108 may be created by a set of experts, such as using calculated analytics 130 on past lending transactions. The lending model 108 may be populated by data from monitoring systems 164 and data collection systems 166, may pull data from data storage systems 186, and the like. The lending model 108 may be used to configure parameters of a smart contract, such that smart contract terms and conditions automatically adjust based on adjustments in the lending model 108. The lending model 108 may be configured to be improved by artificial intelligence 156, such as by training it on a set of outcomes, such as outcomes from lending transactions (e.g., payment outcomes, default outcomes, performance outcomes, and the like), outcomes on collateral 102 or assets (such as prices or value patterns of collateral or assets over time), outcomes on entities (such as defaults, foreclosures, performance results, on time payments, late payments, bankruptcies, and the like), and others. Training may be used to adjust and improve model parameters and performance, including for classification of collateral or assets (such as automatic classification of type and/or condition, such as using vision-based classification from camera-based monitoring systems 164), prediction of value of collateral 102 or assets, prediction of defaults, prediction of performance, and the like. In embodiments, configuration or handling of smart contracts for lending on collateral 102 or assets may be learned and automated in a robotic process automation (RPA) system 154, such as by training the RPA system 154 to create smart contracts, configure parameters of smart contracts, confirm title to collateral 102 or assets, set terms and conditions of smart contracts, initiate security interests on collateral 102 for smart contracts, monitor status or performance of smart contracts, terminate or initiate termination for default of smart contracts, close smart contracts, foreclose on collateral 102 or assets, transfer title, or the like, such as by using monitoring systems 164 to monitor expert entities 198, such as human managers, as they undertake a training set of similar tasks and actions in the creation, configuration, title confirmation, initiation of security interests, monitoring, termination, closing, foreclosing, and the like for a training set of smart contracts. Once an RPA system 154 is trained, it may efficiently create the ability to provide lending at scale across a wide range of entities and assets that may serve as collateral 102, that may provide guarantees or security, or the like, thereby making loans more readily available for a wider range of situations, entities 198, and collateral 102. The RPA system 154 may itself be improved by artificial intelligence 156, such as by continuously adjusting model parameters, weights, configurations, or the like based on outcomes, such as loan performance outcomes, collateral valuation outcomes, default outcomes, closing rate outcomes, interest rate outcomes, yield outcomes, return-on-investment outcomes, or others. Smart contracts may include or be used for direct lending, syndicated lending, and secondary lending contracts, individual loans or aggregated tranches of loans, and the like.
[0292] In embodiments, the lending application 144 of the management application platform 128 may, in various optional embodiments, include, integrate with, or interact with (such as within other embodiments of the lending enablement platform ) a set of applications, such as ones by which a lender, a borrower, a guarantor, an operator or owner of a transactional or financial entity, or other user, may manage, monitor, control, analyze, or otherwise interact with one or more elements related to a loan, such as an entity 198 that is a party to a loan, the subject of a loan, the collateral for a loan, or otherwise relevant to the loan. This may include any of the elements noted above in connection with Fig. 1. The set of applications may include a lending application 144 (such as, without limitation, for personal lending, commercial lending, collateralized lending, microlending, peer-to-peer lending, insurance-related lending, asset-backed lending, secured debt lending, corporate debt lending, student loans, subsidized loans, mortgage lending, municipal lending, sovereign debt, automotive lending, pay day loans, loans against receivables, factoring transactions, loans against guaranteed or assured payments (such as tax refunds, annuities, and the like), and many others). The lending application 144 may include, integrate with, or link with one or more of any of a wide range of other types of applications that may be relevant to lending, such as an investment application (such as, without limitation, for investment in tranches of loans, corporate debt, bonds, syndicated loans, municipal debt, sovereign debt, or other types of debt- related securities); an asset management application (such as, without limitation, for managing assets that may be the subject of a loan, the collateral for a loan, assets that back a loan, the collateral for a loan guarantee, or evidence of creditworthiness, assets related to a bond, investment assets, real property, fixtures, personal property, real estate, equipment, intellectual property, vehicles, and other assets); a risk management solution 122 (such as, without limitation, for managing risk or liability with respect to subject of a loan, a party to a loan, or an activity relevant to the performance of a loan, such as a product, an asset, a person, a home, a vehicle, an item of equipment, a component, an information technology system, a security system, a security event, a cybersecurity system, an item of property, a health condition, mortality, fire, flood, weather, disability, business interruption, injury, damage to property, damage to a business, breach of a contract, and others); a marketing application 202 (such as, without limitation, an application for marketing a loan or a tranche of loans, a customer relationship management application for lending, a search engine optimization application for attracting relevant parties, a sales management application, an advertising network application, a behavioral tracking application, a marketing analytics application, a location-based product or service targeting application, a collaborative filtering application, a recommendation engine for loan-related product or service, and others); a trading application (such as, without limitation, an application for trading a loan, a tranche of loans, a portion of a loan, a loan-related interest, or the like, such as a buying application, a selling application, a bidding application, an auction application, a reverse auction application, a bid/ask matching application, or others); a tax application 262 (such as, without limitation, for managing, calculating, reporting, optimizing, or otherwise handling data, events, workflows, or other factors relating to a tax-related impact of a loan); a fraud prevention application 138 (such as, without limitation, one or more of an identity verification application, a biometric identity validation application, a transactional pattern-based fraud detection application, a location-based fraud detection application, a user behavior-based fraud detection application, a network address-based fraud detection application, a black list application, a white list application, a content inspection-based fraud detection application, or other fraud detection application; a security application, solution or service (referred to herein as a security application 148, such as, without limitation, any of the fraud prevention applications 138 noted above, as well as a physical security system (such as for an access control system (such as using biometric access controls, fingerprinting, retinal scanning, passwords, and other access controls), a safe, a vault, a cage, a safe room, or the like), a monitoring system (such as using cameras, motion sensors, infrared sensors and other sensors), a cyber security system (such as for virus detection and remediation, intrusion detection and remediation, spam detection and remediation, phishing detection and remediation, social engineering detection and remediation, cyberattack detection and remediation, packet inspection, traffic inspection, DNS attack remediation and detection, and others) or other security application); an underwriting application 122 (such as, without limitation, for underwriting any loan, guarantee, or other loan-related transaction or obligation, including any application for detecting, characterizing or predicting the likelihood and/or scope of a risk, including underwriting based on any of the data sources, events or entities noted throughout this disclosure or the documents incorporated herein by reference); a blockchain application for storing information as a blockchain 136 (such as, without limitation, a distributed ledger capturing a series of transactions, such as debits or credits, purchases or sales, exchanges of in kind consideration, smart contract events, or the like, a cryptocurrency application, or other blockchain-based application); a real estate application (such as, without limitation, a real estate brokerage application, a real estate valuation application, a real estate mortgage or lending application, a real estate assessment application, or other); a regulatory and/or compliance solution 142 (such as, without limitation, an application for regulating the terms and conditions of a loan, such as the permitted parties, the permitted collateral, the permitted terms for repayment, the permitted interest rates, the required disclosures, the required underwriting process, conditions for syndication, and many others); a platform-oriented marketplace 500 such as marketplace application, solution or service (referred to as a marketplace application, such as, without limitation, a loan syndication marketplace, a blockchain-based marketplace, a cryptocurrency marketplace, a token-based marketplace, a marketplace for items used as collateral, or other marketplace); a warranty or guarantee application (such as, without limitation, an application for a warranty or guarantee with respect to an item that is the subject of a loan, collateral for a loan, or the like, such as a product, a service, an offering, a solution, a physical product, software, a level of service, quality of service, a financial instrument, a debt, an item of collateral, performance of a service, or other item); an analyst application 130 (such as, without limitation, an analytic application with respect to any of the data types, applications, events, workflows, or entities mentioned throughout this disclosure or the documents incorporated by reference herein, such as a big data application, a user behavior application, a prediction application, a classification application, a dashboard, a pattern recognition application, an econometric application, a financial yield application, a return on investment application, a scenario planning application, a decision support application, and many others); a pricing application 131 (such as, without limitation, for pricing of interest rates and other terms and conditions for a loan). Thus, the management application platform 128 may host and enable interaction among a wide range of disparate applications (such term including the above-referenced and other financial or transactional applications, services, solutions, and the like), such that by virtue of shared microservices, shared data infrastructure, and shared intelligence, any pair or larger combination or permutation of such services may be improved relative to an isolated application of the same type.
[0293] In embodiments the data collection systems 166 and the monitoring systems 164 may monitor one or more events related to a loan, debt, bond, factoring agreement, or other lending transaction, such as events related to requesting a loan, offering a loan, accepting a loan, providing underwriting information for a loan, providing a credit report, deferring a required payment, setting an interest rate for a loan, deferring a payment requirement, identifying collateral or assets for a loan, validating title for collateral or security for a loan, recording a change in title of property, assessing the value of collateral or security for a loan, inspecting property that is involved in a loan, a change in condition of an entity relevant to a loan, a change in value of an entity that is relevant to a loan, a change in job status of a borrower, a change in financial rating of a lender, a change in financial value of an item offered as a security, providing insurance for a loan, providing evidence of insurance for property related to a loan, providing evidence of eligibility for a loan, identifying security for a loan, underwriting a loan, making a payment on a loan, defaulting on a loan, calling a loan, closing a loan, setting terms and conditions for a loan, foreclosing on property subject to a loan, and modifying terms and conditions for a loan. Microservices Lending Platform with Data Collection Services, Blockchain and Smart Contracts
[0294] In embodiments, provided herein is a platform, consisting of various services, components, modules, programs, systems, devices, algorithms, and other elements, for lending. In embodiments, the platform or system includes a set of microservices having a set of application programming interfaces that facilitate connection among the microservices and to the microservices by programs that are external to the platform, wherein the microservices include (a) a multi-modal set of data collection services that collect information about and monitor entities related to a lending transaction; (b) a set of blockchain services for maintaining a secure historical ledger of events related to a loan, the blockchain services having access control features that govern access by a set of parties involved in a loan; (c) a set of application programming interfaces, data integration services, data processing workflows and user interfaces for handling loan-related events and loan-related activities; and (d) a set of smart contract services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan-related events and loan-related activities.
[0295] In embodiments the entities relevant to lending include a set of entities among lenders, borrowers, guarantors, equipment, goods, systems, fixtures, buildings, storage facilities, and items of collateral. [0296] In embodiments collateral items are monitored and the collateral items are selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0297] In embodiments the multi-modal set of data collection services include services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0298] In embodiments the events related to a loan are selected from requesting a loan, offering a loan, accepting a loan, providing underwriting information for a loan, providing a credit report, deferring a required payment, setting an interest rate for a loan, deferring a payment requirement, identifying collateral for a loan, validating title for collateral or security for a loan, recording a change in title of property, assessing the value of collateral or security for a loan, inspecting property that is involved in a loan, a change in condition of an entity relevant to a loan, a change in value of an entity that is relevant to a loan, a change in job status of a borrower, a change in financial rating of a lender, a change in financial value of an item offered as a security, providing insurance for a loan, providing evidence of insurance for property related to a loan, providing evidence of eligibility for a loan, identifying security for a loan, underwriting a loan, making a payment on a loan, defaulting on a loan, calling a loan, closing a loan, setting terms and conditions for a loan, foreclosing on property subject to a loan, and modifying terms and conditions for a loan.
[0299] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0300] In embodiments a set of parties to the loan is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0301] In embodiments loan-related activities include activities selected from the set of finding parties interested in participating in a loan transaction, an application for a loan, underwriting a loan, forming a legal contract for a loan, monitoring performance of a loan, making payments on a loan, restructuring or amending a loan, settling a loan, monitoring collateral for a loan, forming a syndicate for a loan, foreclosing on a loan, and closing a loan transaction.
[0302] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0303] In embodiments smart contract services configure at least one smart contract to automatically undertake a loan-related action based on based on information collected by the multi-modal set of data collection services.
[0304] In embodiments the loan-related action is selected from among offering a loan, accepting a loan, underwriting a loan, setting an interest rate for a loan, deferring a payment requirement, modifying an interest rate for a loan, validating title for collateral, recording a change in title, assessing the value of collateral, initiating inspection of collateral, calling a loan, closing a loan, setting terms and conditions for a loan, providing notices required to be provided to a borrower, foreclosing on property subject to a loan, and modifying terms and conditions for a loan.
[0305] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of items of collateral and undertakes an action related to a loan to which the collateral is subject.
[0306] In embodiments the loan-related action is selected from among offering a loan, accepting a loan, underwriting a loan, setting an interest rate for a loan, deferring a payment requirement, modifying an interest rate for a loan, validating title for collateral, recording a change in title, assessing the value of collateral, initiating inspection of collateral, calling a loan, closing a loan, setting terms and conditions for a loan, providing notices required to be provided to a borrower, foreclosing on property subject to a loan, and modifying terms and conditions for a loan.
[0307] Referring to Fig. 2, additional applications, solutions, programs, systems, services and the like that may be present in a lending application 144 are depicted, which may be interchangeably included in the management application platform 128 with other elements noted in connection with Fig. 1 and elsewhere throughout this disclosure and the documents incorporated herein by reference. Also depicted are additional entities 198, which should be understood to be interchangeable with the other entities 198 described in connection with various embodiments described herein. In addition to elements already noted above, the lending application 144 may include a set of applications, solutions, programs, systems, services and the like that include one or more of a social network analytics application 204 that may find and analyze information about various entities 198 as depicted in one or more social networks (such as, without limitation, information about parties, behavior of parties, conditions of assets, events relating to parties or assets, conditions of facilities, location of collateral 102 or assets, and the like), such as by allowing a user to configure queries that may be initiated and managed across a set of social network sites using data collection systems 166 and monitoring systems 164; a crowdsourcing solution 250; a loan management solution 149 (such as for managing or responding to one or more events related to a loan (such events including, among others, requests for a loan, offering a loan, accepting a loan, providing underwriting information for a loan, providing a credit report, deferring a required payment, setting an interest rate for a loan, deferring a payment requirement, identifying collateral for a loan, validating title for collateral or security for a loan, recording a change in title of property, assessing the value of collateral or security for a loan, inspecting property that is involved in a loan, a change in condition of an entity relevant to a loan, a change in value of an entity that is relevant to a loan, a change in job status of a borrower, a change in financial rating of a lender, a change in financial value of an item offered as a security, providing insurance for a loan, providing evidence of insurance for property related to a loan, providing evidence of eligibility for a loan, identifying security for a loan, underwriting a loan, making a payment on a loan, defaulting on a loan, calling a loan, closing a loan, setting terms and conditions for a loan, foreclosing on property subject to a loan, and modifying terms and conditions for a loan) for setting terms and conditions for a loan (such as a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default), or managing loan-related activities (such as, without limitation, finding parties interested in participating in a loan transaction, handling an application for a loan, underwriting a loan, forming a legal contract for a loan, monitoring performance of a loan, making payments on a loan, restructuring or amending a loan, settling a loan, monitoring collateral for a loan, forming a syndicate for a loan, foreclosing on a loan, collecting on a loan, consolidating a set of loans, analyzing performance of a loan, handling a default of a loan, transferring title of assets or collateral, and closing a loan transaction)); a rating solution 2102 (such as for rating an entity 198 (such as a party 210, collateral 102, asset 218 or the like), such as involving rating of creditworthiness, financial health, physical condition, status, value, presence or absence of defects, quality, or other attribute); regulatory and/or compliance solution 142 (such as for enabling specification, application and/or monitoring of one or more policies, rules, regulations, procedures, protocols, processes, or the like, such as ones that relate to terms and conditions of loan transactions, steps required in forming lending transactions, steps required in performing lending transactions, steps required with respect to security or collateral, steps required for underwriting, steps required for setting prices, interest rates, or the like, steps required to provide required legal disclosures and notices (e.g., presenting annualized percentage rates) and others ); a custodial solution or set of custodial solution 1802 (such as for taking custody of a set of assets 218, collateral 102, or the like (including cryptocurrencies, currency, securities, stocks, bonds, agreements evidencing ownership interests, and many other items), such as on behalf of a party 210, client, or other entity 198 that needs assistance in maintaining security of the items, or in order to provide security, backing, or a guarantee for an obligation, such as one involved in a lending transaction); a loan marketing solution 2002 (such as for enabling a lender to market availability of a loan to a set of prospective borrowers, to target a set of borrowers who are appropriate for a type of transaction, to configure marketing or promotional messages (including placement and timing of the message), to configure advertisement and promotional channels for lending transactions, to configure promotional or loyalty program parameters, and many others); a brokering solution 244 (such as for brokering a set of loan transactions among a set of parties, such as a mortgage loan), which may allow a user to configure a set of preferences, profiles, parameters, or the like to find a set of prospective counterparties to a lending transaction; a bond management solution 234 such as for managing, reporting on, syndicating, consolidating, or otherwise handling a set of bonds (such as municipal bonds, corporate bonds, performance bonds, and others); a guarantee and/or security monitoring solution 230, such as for monitoring, classifying, predicting, or otherwise handling the reliability, quality, status, health condition, financial condition, physical condition or other information about a guarantee, a guarantor, a set of collateral supporting a guarantee, a set of assets backing a guarantee, or the like; a negotiation solution 232, such as for assisting, monitoring, reporting on, facilitating and/or automating negotiation of a set of terms and conditions for a lending transaction (such as, without limitation, a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclosure condition, a default condition, and a consequence of default), which may include a set of user interfaces for configuration of parameters, profiles, preferences, or the like for negotiation, such as ones that use or are informed by the lending model 108 and ones that use, are informed by, or that are automated by or with the assistance of a set of artificial intelligence 156 services and systems, by robotic process automation (RPA) 154, or other adaptive intelligent systems 158; a collection solution 238 for collecting on a loan, which may optionally use, be informed by, or be automated by or with the assistance of a set of artificial intelligence 156 services and systems, by robotic process automation 154, or other adaptive intelligent systems 158, such as based on monitoring the status or condition of various entities 198 with the monitoring systems 164 and data collection systems 166 in order to trigger collection, such as when one or more covenants has not been met, when collateral is in poor condition, when financial health of party is below a threshold, or the like; a consolidation solution 240 for consolidating a set of loans, such as using a lending model 108 that is configured for modeling a consolidated set of loans and such as using or being automated by one or more adaptive intelligent systems 158; a custodial solution 258; a factoring solution 242, such as for monitoring, managing, automating or otherwise handling a set of factoring transactions, such as using a lending model 108 that is configured for modeling factoring transactions and such as using or being automated by one or more adaptive intelligent systems 158; a debt restructuring solution 228, such as for restructuring a set of loans or debt, such as using a lending model 108 that is configured for modeling alternative scenarios for restructuring a set of loans or debt and such as using or being automated by one or more adaptive intelligent systems 158; and/or an interest rate automation solution 224, such as for setting or configuring a set of rules or a model for a set of interest rates for a set of lending transactions or for automating interest rate setting based on information collected by data collection systems 166 or monitoring systems 164 (such as information about conditions, status, health, location, geolocation, storage condition, or other relevant information about any of the entities 198), which may set interest rates or facilitate setting of interest rates for a set of loans, such as using a lending model 108 that is configured for modeling interest rate scenarios for a set of loans and such as using or being automated by one or more of the adaptive intelligent systems 158. As with the solutions referenced in connection with Fig. 1, the various solutions may share the adaptive intelligent systems 158, the monitoring systems 164, the data collection systems 166 and the data storage systems 186, such as by being integrated into the lending enablement platform 100 in a microservices architecture having various appropriate data integration services, APIs 112, and interfaces.
[0308] As with the entities 198 described in connection with Fig. 2, entities 198 may further include a range of entities that are involved with loans, debt transactions, bonds, factoring agreements, and other lending transactions, such as: collateral 102 and assets 218 that are used to secure, guarantee, or back a payment obligation (such as vehicles, ships, planes, buildings, homes, real estate, undeveloped land, farms, crops, facilities 190(such as municipal facilities, factories, warehouses, storage facilities, treatment facilities, plants, and others), systems, a set of inventory, commodities, securities, currencies, tokens of value, tickets, cryptocurrencies, consumables, edibles, beverages, precious metals, jewelry, gemstones, intellectual property, intellectual property rights, contractual rights, legal rights, antiques, fixtures, equipment, furniture, tools, machinery and personal property); a set of parties 210 (such as one or more of a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, a bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, an agent, an attorney, a valuation professional, a government official, and/or an accountant); a set of lending agreements 220 (such as loans, bonds 212, lending agreements, corporate debt agreements, subsidized loan agreements, factoring agreements, consolidation agreements, syndication agreements, guarantee agreements, underwriting agreements, and others, which may include a set of terms and conditions that may be searched, collected, monitored, modified or otherwise handled by the lending enablement platform 100, such as interest rates, payment schedules, payment amounts, principal amounts, representations and warranties, indemnities, covenants, and other terms and conditions); a set of guarantees 214 (such as provided by personal guarantors, corporate guarantors, government guarantors, municipal guarantors and others to secure or back a payment obligation or other obligation of a lending agreement 220); a set of performance activities 222 (such as making payments of principal and/or interest, maintaining required insurance, maintaining title, satisfying covenants, maintaining condition of collateral 102 or assets 218, conducting business as required by an agreement; and many others); and devices 252 (such as Internet of Things devices that may be disposed on or in goods, equipment or other items, such as ones that are collateral 102 or assets 218 used to back a payment obligation or to satisfy a covenant or other requirement, or that may be disposed on or in packaging for goods, as well as ones disposed in facilities 190or other environments where entities 198 may be located). In embodiments a lending agreement 220 may be for a bond, a factoring agreement, a syndication agreement, a consolidation agreement, a settlement agreement, or a loan, such as one or more of an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0309] As noted elsewhere herein and in documents incorporated by reference, artificial intelligence (such as any of the techniques or systems described throughout this disclosure) in connection with various transactional and marketplace entities 198 and related processes and applications may be used to facilitate, among other things: (a) the optimization, automation and/or control of various functions, workflows, applications, features, resource utilization and other factors, (b) recognition or diagnosis of various states, entities, patterns, events, contexts, behaviors, or other elements; and/or (c) the forecasting of various states, events, contexts or other factors. As artificial intelligence improves, a large array of domain- specific and/or general artificial intelligence systems have become available and are likely to continue to proliferate. As developers seek solutions to domain-specific problems, such as ones relevant to entities 198 and applications of the platform 126 described throughout this disclosure they face challenges in selecting artificial intelligence models (such as what set of neural networks, machine learning systems, expert systems, or the like to select) and in discovering and selecting what inputs may enable effective and efficient use of artificial intelligence for a given problem. As noted above, opportunity miners 153 may assist with the discovery of opportunities for increased automation and intelligence; however, once opportunities are discovered, selection and configuration of an artificial intelligence solution still presents a significant challenge, one that is likely to continue to grow as artificial intelligence solutions proliferate.
[0310] One set of solutions to these challenges is an artificial intelligence store 157 that is configured to enable collection, organization, recommendation and presentation of relevant sets of artificial intelligence systems based on one or more attributes of a domain and/or a domain- related problem. In embodiments, an artificial intelligence store 157 may include a set of interfaces to artificial intelligence systems, such as enabling the download of relevant artificial intelligence applications, establishment of links or other connections to artificial intelligence systems (such as links to cloud-deployed artificial intelligence systems via APIs, ports, connectors, or other interfaces) and the like. The artificial intelligence store 157 may include descriptive content with respect to each of a variety of artificial intelligence systems, such as metadata or other descriptive material indicating suitability of a system for solving particular types of problems (e.g., forecasting, NLP, image recognition, pattern recognition, motion detection, route optimization, or many others) and/or for operating on domain- specific inputs, data or other entities. In embodiments, the artificial intelligence store 157 may be organized by category, such as domain, input types, processing types, output types, computational requirements and capabilities, cost, energy usage, and other factors. In embodiments, an interface to the application store 157 may take input from a developer and/or from the platform (such as from an opportunity miner 153) that indicates one or more attributes of a problem that may be addressed through artificial intelligence and may provide a set of recommendations, such as via an artificial intelligence attribute search engine, for a subset of artificial intelligence solutions that may represent favorable candidates based on the developer’s domain- specific problem.
[0311] In embodiments, a criteria for determining the recommendation may include level of anticipated human oversight. This may include, among others, understanding the level and types of decisions delegated to human workers (such as a decision to purchase a security, taking a market decision, taking a license on Intellectual property, financial limits on actions and ordering (e.g. is the RPA able to order or commit to transactions below a certain amount, above which a human is involved), the level and type of anticipated human supervision of robotic process automation operations, anticipated extent of human supervision and/or governance of model training and training data set selection. A further consideration may be the level and type of anticipated human involvement in the curation of model versions (such as identifying historical break points where input data should be discarded); and others.
[0312] In embodiments, criteria for determining the recommendation may include security considerations such as adversarial training and complex environments such as network attacks, viruses, and the like. Additional security considerations may include the security and management of historic training datasets, including audit trails. Security considerations may include the model traceability and accuracy - how will the model or controlling parameters be updated, who will have authority to update the model, how will the updates be documented, how will results be correlated with model updates, and the like. How will version control be implemented and documented. Another security consideration will be documentation of the results of the AI for audit trails including financial results and performance results.
[0313] In embodiments, criteria for determining the recommendation may include the availability of different AI types, models, algorithms, or systems (including heuristic/model-based AI, neural networks, and others). Availability may be limited by the computational environment that the user intends to use such as a given cloud platform, an on-premises IT system, or in a network (edge or other network), and the like and whether a given type, model, or algorithm will run in the client’s environment. In embodiments, computational factors and configurations may be criteria. For example, the available processor types for running the AI solution in the client’ s environment may be a factor including: chipsets, modules, device, cloud components, number, and architecture of processor types (e.g. multi-core processor availability, GPU availability, CPU availability, FPGA availability, custom ASIC availability, and the like), and the like. Additionally, computational factors, which may be expressed as minimum capability criteria, may include available processing capacity, both for solution training (for example utilizing a cloud computing resource) and solution operation deployment environment/capacity (e.g. IoT, in-vehicle, edge, mesh network, on-premises IT solution, stand along, or other deployment environments). Additional criteria may include software and interface criteria such as software environment such as operating systems (Linux, Mac, PC, and the like), languages and protocols used for APIs for access to input data sources for solution training as well as access to runtime data and data integration and output.
[0314] In embodiments, criteria may include various network factors such as available network type, available network bandwidth (input and output) for both AI solution and AI operation, network uptime, network redundance, variability of delivery times (sequencing of data may vary), as well as any of the other networks and network criteria described herein.
[0315] In embodiments, criteria may include performance or quality of service factors, either in absolute terms or relative to other AI and/or non-AI solutions (e.g. conventional models or rule- based solutions. Criteria may include speed/latency, time to train/configure and an AI solution, time for the AI solution to provide result in an operations situation, accuracy, reliability (e.g. ability to resolve to a result), consistency, absence of bias, outcome-based measures of quality such as return on investment (ROI), yield (e.g. output from an AI-governed operation), profitability, revenue and other economic measures, performance on safety measures, performance on security measures, energy consumption (e.g. overall consumption, timing-based consumption (e.g. ability to shift processing from peak to off-peak hours), ability to access renewable or low-carbon energy for model training and/or operation, management of cost of new model training initiatives (power costs, latency and validation of new models), and the like. [0316] In embodiments, criteria may include the ability of the client to access a given type or model due to license requirements and limitations, client policies (described elsewhere herein), regulations (including in the client’ s jurisdiction, the jurisdiction of the data source (e.g. European data privacy laws and Safe Harbor), a jurisdiction governing a particular model, algorithm, or the like (e.g. export controls on technology), permissions (e.g. training data or operational data), and the like. Additionally, the recommendation may be influenced by the type of problem to be solved and whether there are specialized algorithms or methods that are optimized for the type of problem (e.g. quantum annealing based traveling salesperson solver or even classic heuristic methods that provide for reasonable baseline results).
[0317] In embodiments, criteria may include conformance or adherence to governance principles and policies. There may be policies regarding what input data sources may be used to train the AI solution. There may be policies regarding what input sources may be used during operation. For example, input data sources may be reviewed for potential bias, appropriate representation (either demographically or of the problem space), scope, and the like. There may be criteria regarding accreditation or approval of the solution by a regulatory body, certification organization, internal IT review, and the like. There may be policies and procedures that must be in place or implemented with respect to security (e.g. physical security of the system, cybersecurity, and the like), safety requirements (e.g. the safety of the user, the safety of output product, and the like), and the like.
[0318] In embodiments, the criteria for recommending an AI solution may include criteria regarding data availability such as the availability of data sources of adequate size, granularity, quality, reliability, location, time zones, accuracy, or the like for effective model training. Additional criteria regarding data availability may include the cost of data for: inputs for the model training, input for model operation. Additional criteria may include the availability of data for operation of the AI solution, and the like. Criteria for AI selection may further include upstream data processing requirements, master data management considerations such as dimensional cleanup and data validation, and the like.
[0319] In embodiments, criteria for solution selection may include applicability of the model or solution to the given task or workflow of the “problem” Criteria may include benchmark performance of a given model relative to other models performing a known task type (e.g. a convolutional neural network for 2D object classification, a gated recurrent neural network for tasks that tend to produce exploding errors, or the like). In embodiments, selection of a solution may be based on the solution having a configuration that is similar or analogous to how a biological brain solves a similar task (e.g. where a sequence of neural network models are arranged to mimic a sequence or flow which may include serial elements, parallel elements, feedback loops, conditional logic junctions, graph-driven elements and other flow characteristics), such as a flow of modular or quasi-modular processes, such as ones involved in the brain of a human or other species, such as for in visual or auditory processing, language recognition, speech, motion tracking, image recognition, facial recognition, motion coordination, tactile recognition, spatial orientation, and the like. Criteria may include application of class AI heuristic methods to function as guard rails or operations in less impactful areas.
[0320] In embodiments, criteria may include model deployment considerations such as requirements for model updates (e.g. frequency and requirement for retirement of models), management of historic models and maintaining historical decision engine, potential for distributed decision making capabilities, model curation rules (e.g. how long a model or input data are considered valid for training), and the like.
[0321] Search results or recommendations may, in embodiments, be based at least in part on collaborative filtering, such as by asking developers to indicate or select elements of favorable models, as well as by clustering, such as by using similarity matrices, k-means clustering, or other clustering techniques that associate similar developers, similar domain- specific problems, and/or similar artificial intelligence solutions. The artificial intelligence store 157 may include e- commerce features, such as ratings, reviews, links to relevant content, and mechanisms for provisioning, licensing, delivery and payment (including allocation of payments to affiliates and or contributors), including ones that operate using smart contract and/or blockchain features to automate purchasing, licensing, payment tracking, settlement of transactions, or other features. [0322] In embodiments, once a solution has been selected or recommended, the solution must be configured for the specific client and problem to be solved. Without limitation, configuration may include any of the factors mentioned in connection with the selection of a solution model above. Configuration of a set of neural network types (e.g., modules) in a flow (with options for serial elements, parallel elements, feedback loops, conditional logic junctions, graph-driven flows and the like) that recognizes the relative strengths and weaknesses of each type of AI solution (based on any or the selection factors noted above) for the specific task involved in the flow is critical. In an illustrative and non-limiting example of a flow, a) identify something by visual classification (such as with a CNN), b) predict its future state (such as with a gated RNN), c) optimize the future state (using a feed forward neural network). Configuration options include selection of neural network type(s) (including hybrids of different neural networks and/or other model types in various flows as noted above); selection of input model type; setting of initial model weights; setting model size (e.g., number of layers in a deep neural network); selection of computational deployment environment; selection of input data sources for training; selection of input data sources for operation; selection of feedback function/outcome measures; selection of data integration language(s) for inputs and outputs; configuration of APIs for model training; configuration of APIs for model inputs; configuration of APIs for outputs; configuration of access controls (role-based, user-based, policy-based and others); configuration of security parameters; configuration of network protocols; configuration of storage parameters (type, location, duration); configuration of economic factors (e.g., pricing for access; cost-allocation; and others); and others. Additional configuration options may include configuration of data flows (e.g. flows from multiple security exchanges into centralized decision engines), configuration of high availability, fault tolerance environments (e.g. trading systems are required to fail down to operation state that meets services levels requirements), price based data acquisition strategies (e.g. detailed financial data may require additional spending), combination with heuristic methods, coordination of massively parallel decision making environments (e.g. distributed vision systems), and the like. Additional configurations may include making decision models if there is an area that requires further consideration (e.g. pushing a decision to the edge to monitor for a specific event). [0323] In embodiments, another set of solutions, which may be deployed alone or in connection with other elements of the platform, including the artificial intelligence store 157, may include a set of functional imaging capabilities 161, which may comprise monitoring systems 164 and data collection systems 166 and, in some cases, physical process observation systems 162 and/or software interaction observation systems 160, such as for monitoring various transactional and marketplace entities 198. Functional imaging systems 161 may, in embodiments, provide considerable insight into the types of artificial intelligence that are likely to be most effective in solving particular types of problems most effectively. As noted elsewhere in this disclosure and in the documents incorporated by reference herein, computational and networking systems, as they grow in scale, complexity and interconnections, manifest problems of information overload, noise, network congestion, energy waste, and many others. As the Internet of Things grows to hundreds of billions of devices, and virtually countless potential interconnections, optimization becomes exceedingly difficult. One source for insight is the human brain, which faces similar challenges and has evolved, over millennia, reasonable solutions to a wide range of very difficult optimization problems. The human brain operates with a massive neural network organized into interconnected modular systems, each of which has a degree of adaptation to solve particular problems, from regulation of biological systems and maintenance of homeostasis to detection of a wide range of static and dynamic patterns, to recognition of threats and opportunities, among many others.
[0324] Setting up a robotic process automation (RPA) system includes selection of the best AI solution and configuration. There may be goals to train the RPA system, typically on human interactions with software and or hardware (e.g., tools) and to use the system in operation, both of which be enhanced by understanding what is going on in the human brain as it solves a problem. In a single neural network solution (using one network to solve a problem in a single step, like single-step translation), the process would likely involve setting initial weights for inputs, selection of input data sources, selection of the type of network (e.g., convolutional or not, gated or not, deep or not, among others), the number of layers, and what inputs are provided to it (and outputs if there are complex outputs). The idea would be to pick inputs and weights that are the ones the human brain tends to use to solve the same problem. For hybrids of multiple AI modules/systems and/or AI combined with more conventional software systems (like control systems, analytic models, rule-based systems, conditional logic systems, and others), the value would likely be the above, plus configuring with awareness of time sequences of processing, such as reflecting patterns of brain activity as visual, auditory, tactile and other sensory information is processed to recognize situation, context, motion, objects, etc. and then other regions (that behave differently) to do things like solve a logic puzzle, calculate, follow an algorithm, proliferate possibilities, and many others. For these, a series of “lego blocks”, each consisting of a different neural network or other AI type, can be sequenced, set in parallel, linked by conditional logic, etc. to achieve a solution that automate the process.
[0325] In embodiments, identification of a type of reasoning and/or a type of processing may be informed by undertaking brain imaging, such as functional MRI or other magnetic imaging, electroencephalogram (EEG), or other imaging, such as by identifying broad brain activity (e.g., wave bands of activity, such as delta, theta, alpha and gamma waves), by identifying a set of brain regions that are activated and/or inactive during the set interactions of the user that are being used for training of the intelligent agent (such as neocortex regions, such as Fpl (involved in judgment and decision making), F7 (involved in imagination and mimicry), F3 (involved in analytic deduction), T3 (involved in speech), C3 (involved in storage of facts), T5 (involved in mediation and empathy), P3 (involved in tactical navigation), 01 (involved in visual engineering), Fp2 (involved in process management), F8 (involved in belief systems), F4 (involved in expert classification), T4 (involved in listening and intuition), C4 (involved in artistic creativity), T6 (involved in prediction), P4 (involved in strategic gaming), 02 (involved in abstraction), and/or combinations of the foregoing) or by other neuroscientific, psychological, or similar techniques that provide insight into how humans upon which the intelligent agent is trained are solving particular types of problems that are involved in workflows for which intelligent agents are deployed. In embodiments, an intelligent agent may be configured with a neural network type, or combination of types, that is selected to replicate or simulate a processing activity that is similar to the activity of the brain regions of a human expert that is performing a set of activities for which the intelligent agent is to be trained. As one example among many possible, a trader may be shown to use visual processing region 01 and strategic gaming region P4 of the neocortex when making successful trades, and a neural network may be configured with a convolutional neural network to provide effective replication of visual pattern recognition and a gated recurrent neural network to replicate strategic gaming. In embodiments, a library of neural network resources representing combinations of neural network types that mimic or simulate neocortex activities may be configured to allow selection and implementation of modules that replicate the combinations used by human experts to undertake various activities that are subjects of development of intelligent agents, such as involving robotic process automation. In embodiments, various neural network types from the library may be configured in series and/or in parallel configurations to represent processing flows, which may be arranged to mimic or replicate flows of processing in the brain, such as based on spatiotemporal imaging of the brain when involved in the activity that is the subject of automation. In embodiments, an intelligent software agent for agent development may be trained, such as using any of the training techniques described herein, to select a set of neural network resource types, to arrange the neural network resource types according to a processing flow, to configure input data sources for the set of neural network resources, and/or to automatically deploy the set of neural network types on available computational resources to initiate training of the configured set of neural network resources to perform a desired intelligent agent/automation workflows. In embodiments, the intelligent software agent used for agent development operates on an input data set of spatiotemporal imaging data of a human brain, such as an expert who is performing the workflows that is the subject of development of a further, and uses the spatiotemporal imaging data to automatically select and configure the selection and arrangement of the set of neural network types to initiate learning. Thus, a system for developing an intelligent agent may be configured for (optionally automatic) selection of neural network types and/or arrangements based on spatiotemporal neocortical activity patterns of human users involved in workflows for which the agent is trained. Once developed, the resulting intelligent agent/process automation system may be trained as described throughout this disclosure.
[0326] In embodiments, a system for developing an intelligent agent (including the aforementioned agent for development of intelligent agents) may use information from brain imaging of human users to infer (optionally automatically) what data sources should be selected as inputs for an intelligent agent. For example, for processes where neocortex region 01 is highly active (involving visual processing), visual inputs (such as available information from cameras, or visual representations of information like price patterns, among many others) may be selected as favorable data sources. Similarly, for processes involving region C3 (involving storage and retrieval of facts), data sources providing reliable factual information (such as blockchain-based distributed ledgers) may be selected. Thus, a system for developing an intelligent agent may be configured for (optionally automatic) selection of input data types and sources based on spatiotemporal neocortical activity patterns of human users involved in workflows for which the agent is trained.
[0327] Functional imaging 161, such as functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), computed tomography (CT) and other brain imaging systems have improved to the point that patterns of brain activity can be recognized in real time and temporally associated with other information, such behaviors, stimulus information, environmental condition data, gestures, eye movements, and other information, such that via functional imaging 161, either alone or in combination with other information collected by monitoring systems 164, the platform may determine and classify what brain modules, operations, systems, and/or functions are employed during the undertaking of a set of tasks or activities, such as ones involving software interaction observation systems 160, physical process observations 162, or a combination thereof. This classification may assist in selection and/or configuration of a set of artificial intelligence solutions, such as from an artificial intelligence store 157, that includes a similar set of capabilities and/or functions to the set of modules and functions of the human brain when undertaking an activity, such as for the initial configuration of a robotic process automation (RPA) system 154 that automates a task performed by an expert human.
[0328] In embodiments, a system may receive and/or monitor a set of inputs relating to a user, including image/video feeds, audio feeds, motion sensors, heartbeat monitor, other relevant biosensors, and the like. In embodiments, the system may also receive input relating to actions taken by the monitored user, such as input to a computing device or actions taken with respect to a physical environment in which the user is working. In embodiments, all the collected data is time stamped, so that, for example, a video feed may capture a series of images of a user while the user is performing a task and may concurrently capture the eye movements of the user (e.g. eye gaze tracking) to determine what the user is focusing on (e.g., what is the user looking at on a screen). During this time the system may also track the user’s heart rate or other biological sensor measurements to determine whether the user is engaged in a task that requires intense concentration or less focused concentration. The system may also track the actions taken and may further determine the amount of time taken between actions. An RPA solution can then distribute processing, such as to a heavier, more computationally intensive activity to an AI solution on a cloud platform (like a deep neural network with many layers) and placing less computationally intensive tasks, such as ones where a human makes very quick decisions on minimal input data, on an edge or IoT device platform using a much more compact model, such as a TinyML(™) model.
[0329] In embodiments, the system may determine the relative amount of time taken between actions, such that long periods of inaction may indicate that the user is involved in work that requires lots of thought, while short periods of inaction may indicate that the user is engaged in work that requires less thought and more action. The system may also monitor an audio feed and/or state of the computing device that a user is working on when the period of inaction occur, which may be indicative of a user being distracted rather than focusing. Assuming that the user is actively working and not exhibiting distraction, then the system can generate a feature vector relating to the work being performed by the user that indicates the time-stamped data entries, which can be then fed into a machine-learned model. In embodiments, the machine-learned model may determine a brain region (or multiple brain regions) from the set of brain regions that were likely engaged during the work period. In embodiments, the machine-learned model may be trained using a training data set that includes labeled training vectors, where the label of each training vector indicates the brain region (or regions) that were being engaged by a subject when the training vector was generated. For example, each training vector may be labeled with one or more of: Fpl (involved in judgment and decision making), F7 (involved in imagination and mimicry), F3 (involved in analytic deduction), T3 (involved in speech), C3 (involved in storage of facts), T5 (involved in mediation and empathy), P3 (involved in tactical navigation), 01 (involved in visual engineering), Fp2 (involved in process management), F8 (involved in belief systems), F4 (involved in expert classification), T4 (involved in listening and intuition), C4 (involved in artistic creativity), T6 (involved in prediction), P4 (involved in strategic gaming), 02 (involved in abstraction)). In some embodiments, the training vector may indicate additional data, such as the type of task being performed, whether the subject was successful in completing the task, or other suitable information.
[0330] In embodiments, these machine-learned models may be trained on different types of work tasks, such as negotiating, drafting, data entry, responding to emails, analyzing data, reviewing documents, or the like. Furthermore, in some embodiments, such machine-learned models may be trained by one party but leveraged by other parties. In these embodiments, the machine-learned models (and/or the training data vectors) may be bought and sold via a marketplace. Such machine-learned models may be used in a broader RPA system, such that the output of the models may be used as a specific signal in an RPA learning process.
[0331] In general, using data from organizations for predicting positioning of organization in market and adjusting processes within organization accordingly. In example embodiments, robotic imaging may be used to capture data of users (e.g., employees or workers) within the organization as they complete various tasks and processes while also correlating this information with completion of these tasks/processes. Obtaining various analytics regarding success of completion of tasks (e.g., efficiency). Then, using data obtained from tracking/monitoring users to determine what factors indicate some users as being more successful than other users in completion of tasks (e.g., based on physical movements of users in doing tasks correctly, brain regions activated, physical strength of users, etc.). This may be based on scanning/monitoring of users as they complete tasks. In some example embodiments, using system to segregate data relating to users with successful task completions versus data relating to users with less successful completions. The system may analyze biological data of workers to determine what makes one worker more successful than other workers. In some example embodiments, this analysis may also be combined with data from machines to determine whether workers are using machines accurately/efficiently. This biological data from workers may also be used to determine whether more workers may be needed to improve efficiency. Using historical data and results from process competitions to look at what improvements should be made whether by training, selecting workers who are better are some tasks vs. others, etc. The resulting analytics on outcomes, and contributions to outcomes, may be used, for example, as a feedback function for weighting the value of particular capabilities for design of an AI solution that is intended to perform the same or similar tasks. In some example embodiments, various data and analysis as described above may be used with respect to determining whether improvements made based on the analysis also improves the market positioning of the organization.
[0332] An operator skilled in a task may develop strong memory connections to muscle functions - muscle memory - which translates into easily accomplished actions that, without this connection, would be difficult or at least require repeated attempts, slower operation, and the like. A system that can distinguish between actions accomplished using muscle memory and others may better identify which actions are worth following/ repeating/leaming.
[0333] Understanding the mechanisms of muscle memory - e.g., understanding the pathways from cognition (visual, auditory, etc.) inputs to develop muscle memory may be a basis for understanding how to automate human actions. This may involve repetition type actions, association of one type of action with another type of action based on similarities, such as body positioning, expected result (dropping the hammer in the holster, etc.).
[0334] Additional value might be in understanding how two individuals can develop a form of muscle memory that allows them to “get into a rhythm”, such as when exchanging physical items. What cues are they exchanging, visually recognizable actions (placement of hand / orientation) and how are those interpreted.
[0335] In embodiments, an imaging system may analyze brain images of multiple members of a team for a set of tasks or workflows that involve different types of expertise. Team performance can be tracked, and AI solutions may be configured to replicate the types of neural processing that are undertaken by different team members, such as motion tracking and coordination by one team member and executive decision making by another.
[0336] In embodiments, an imaging system may analyze brain images of multiple members of a mock trial or negotiation practice sessions for a set of verbal exchanges regarding an argument, point-count-point, and the like for negotiations, and the like. In addition to brain images, audio capture and bio-indicators of response to exchanges could also be harvested to increase the range of multi-dimensional data useful for learning how to automate human actions associated with successful negotiation and the like.
[0337] Given the level of abstraction humans use to trigger actions, e.g. recognizing an alarm tone or recognizing an action from a fellow worker, we can get less abstract in machine-machine communication, e.g. the input that triggered the alarm tone can trigger a direct machine-machine communication or, if the fellow worker is now a machine, they can indicate their positioning in their routine indicating they’re ready to hand-off their work. This is similar to how less intelligent robots have been automated, even with simple macros where the “intelligence” is wrung out of the process to make it more robust, and there are strategies and methods for this that could be applied to these biologic-type inputs which are a level of abstraction beyond what is needed. This down-shift in complexity can, itself, be trained into the system as they recognize what myriad of “soft” triggers (e.g. image recognition) can be turned into “hard” triggers.)
[0338] Using systems like Fpl (involved in judgment and decision making), P3 (involved in tactical navigation), 01 (involved in visual engineering), Fp2 (involved in process management), F8 (involved in belief systems), and T4 (involved in listening and intuition), the training vectors may indicate, in some embodiments, a system of mixed audio and visual concepts. The system may use an expert system to monitor a set of inputs and reconfigure those inputs to monitor an asset including image feeds at various electromagnetic frequencies (such as visual light, thermal, UV, and the like), and audio feeds from those frequencies to determine use, sounds of use, and possible sounds of concerns. When examples include fixed assets (those that cannot move), ambient measurement of the environment may be measured along with signatures of use or non use of the product such as lack of motion, thermal imprints, or lack thereof. The changing environment in the room, the contact with asset by user or other fixtures, can cause reconfiguration of the sensors looking to appreciate the space. When fixed in a room, such systems may determine that ambient conditions could be detrimental to the asset such as strong outside lighting (too rich of UV content) relative to more appropriate lighting. Also included is sensing the motion of use. In more moveable assets, detection and parsing of benign motion rather than motion that may have a higher propensity to age or damage an asset can be recorded and characterized as an aggregated feed.
[0339] Risk Management - Combination of F3 (analytic deduction) and Fpl(judgement and decision making)- Analytics and decision making in the human brain are informed by experience and knowledge, which may be partial, limited, negative, positive, factual, emotional, etc. AI can possibly recognize a situation (sensors, image recognition, proximity, text and conversation analysis, etc.), and apply better risk management in decision making using stored fact-based outcomes for similar situations. This could be applied to enable consumers to make better purchasing and financial decisions. In other applications, it could be applied to emergency response, policing actions, etc.
[0340] In embodiments, an AI solution may be configured as a companion risk manager for a main operational AI solution, such as sharing common inputs and resources, but focused on identifying risks, externalities, and other factors that are not required for the core process automation, but may improve governance, safety, emergency response, and other aspects. [0341] In embodiments, an AI solution may be configured as a companion risk manager for a main operational AI solution, such as sharing common inputs and resources, but focused on identifying risks, externalities, and other factors that are not required for the core process automation, but may improve governance, safety, emergency response, and other aspects.
[0342] Thus, the platform may include a system that takes input from a functional imaging system to configure, optionally automatically based on matching of attributes between one or more biological systems, such as brain systems, and one or more artificial intelligence systems, a set of artificial intelligence capabilities for a robotic process automation system. Selection and configuration may further comprise selection of inputs to robotic process automation and/or artificial intelligence that are configured at least in part based on functional imaging of the brain while workers undertake tasks, such as selection of visual inputs (such as images from cameras) where vision systems of the brain are highly activated, selection of acoustic inputs where auditory systems of the brain are highly activated, selection of chemical inputs (such as chemical sensors) where olfactory systems of the brain are highly activated, or the like. Thus, a biologically aware robotic process automation system may be improved by having initial configuration, or iterative improvement, be guided, either automatically or under developer control, by imaging-derived information collected as workers perform expert tasks that may benefit from automation.
[0343] Functional imaging may provide insight into which tasks involve serial processing versus parallel processing, providing insight into the type of AI solution that may be best suited to a similar tasks (e.g. is it best to receive language and visual data/inputs at once (in parallel) or sequentially). Is there an order in which a user takes in data that might suggest an optimal ordering for performance? Analysis of functional images may enable identification of which computations tasks are most quickly processed through visual inputs versus textual (language processing) and may enable improved matching of task to best input/stimulus.
[0344] Functional imaging may enable determining efficiencies resulting from the pairing or multiple combinations of stimuli (e.g., is a task/command most efficiently communicated by providing multiple, diverse inputs at once, and/or is it best to omit certain stimuli from inputs/commands .
[0345] Functional imaging may enable ranking tasks or events to perform/solve based on the probabilistic improvement in the performance of a subsequent task (where task could be a computation or an actual action performed by a device based on a data/stimulus input).
[0346] Functional imaging may enable measuring negative impacts on performance/computation based on “noise,” where noise may be unneeded data, irrelevant data, or overwhelming data sizes - similar to determining “negative stimuli” (in the human context this could be ambient noise in distinguishing a human voice within a cascade of auditory inputs, or ambient lighting in image recognition, or movement in counting objects in a region and so forth.
[0347] As one example among many possible, a marketplace host may be shown to use prediction region T6 and judgment and decision making region Fpl when configuring a new marketplace, such as to predict favorable marketplace configuration parameters (such as to optimize marketplace efficiency profitability, and/or fairness) and to generate decisions related to marketplace parameters, and a neural network may be configured with a neural network to provide effective replication of prediction and a neural network to replicate decision making. The marketplace configuration parameters may include, but are not limited to, assets, asset types, description of assets, method for verification of ownership, method for delivery of traded goods, estimated size of marketplace, methods for advertising the marketplace, methods for controlling the marketplace, regulatory constraints, data sources, insider trading detection techniques, liquidity requirements, access requirements (such as whether to implement dealer-to-dealer trading, dealer- to-customer trading, or customer- to-customer trading), anonymity (such as determining whether counterparty identities are disclosed), continuity of order handling (e.g., continuous or periodic order handling), interaction (e.g., bilateral or multilateral), price discovery, pricing drivers (e.g., order-driven pricing or quote-driven pricing), price formation (e.g., centralized price formation or fragmented price formation), custodial requirements, types of orders allowed (such as limit orders, stop orders, market orders, and off-market orders), supported market types (such as dealer markets, auction markets, absolute auction markets, minimum bid auction markets, reverse auction markets, sealed bid auction markets, Dutch auction markets, multi-step auction markets (e.g., two-step, three-step, n-step, etc.), forward markets, futures markets, secondary markets, derivatives markets, contingent markets, markets for aggregates (e.g., mutual funds), and the like), trading rules (e.g., tick size, trading halts, open/close hours, escrow requirements, liquidity requirements, geographic rules, jurisdictional rules, rules on publicity, insider trading prohibitions, conflict of interest rules, timing rules (e.g., involving spot- market trading, futures trading and the like) and many others), asset listing requirements (e.g., financial reporting requirements, auditing requirements, minimum capital requirements), deposit minimums, trading minimums, verification rules, commission rules, fee rules, marketplace lifetime rules (e.g., short-term marketplace with timing constraints vs. long-term marketplace), and transparency (e.g., the amount and extent of information disseminated).
[0348] An RPA system may use AI systems related to biological brain functions F3 (involved in analytic deduction) and 01 (involved in visual engineering) in conjunction with one another to perform tasks related to visual calculus. The tasks related to visual calculus may include, for example, processing image sensor data via the 01 visual engineering system to determine what the RPA system “sees,” and how to interpret, classify, identify, etc. what is “seen.” Then, the F3 analytic deduction system may perform 1) deductions to determine what has led to the current state of what is “seen,” and 2) prediction to determine a future state of what is “seen” based on the current state of visual data. The RPA system may use the T6 prediction function to assist in performing such predictions. The deductions may be useful in determining a cause of an issue, inefficiency, or problem in a system being analyzed. The predictions may be useful in determining solutions to problems and/or potential efficiency improvements. The AI system using F3, 01, and/or T6 may then also be used to choose a machine learned model suitable for performing the problem solving and/or efficiency improvement. For example, in a manufacturing environment, the RPA system and AI system may intake data from a plurality of visual IoT sensors, the visual data being from one or more sites on the manufacturing floor. The 01 visual engineering system may determine and/or classify what the visual data is seeing, such as one or more machines, products, assembly lines, etc. The F3 analytic deduction system may determine whether one or more of the machines, products, assembly lines, etc. are indicative of issues or inefficiencies. The T6 system may then make predictions and forward the predictions to a suitable machine learned model for determining solutions to problems and/or improvements to efficiencies.
IoT and Onboard Sensor Platform for Monitoring Collateral for a Loan [0349] In embodiments, provided herein is a platform, consisting of various services, components, modules, programs, systems, devices, algorithms, and other elements, for monitoring collateral for a loan. In embodiments, the platform or system includes (a) a set of Internet of Things services for monitoring an environment for the collateral; a set of sensors positioned on at least one of the collateral, a container for the collateral, and a package for the collateral, the set of sensors configured to associate sensor information sensed by the set of sensors with a unique identifier for the collateral; and a set of blockchain services for taking information from the set of Internet of Things services and the set of sensors and storing the information in a blockchain, wherein access to the blockchain is provided via a secure access control interface for a secured lender for a loan to which the collateral is subject.
[0350] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan. [0351] In embodiments the collateral items are selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0352] In embodiments the set of Internet of Things services monitors an environment selected from among a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.
[0353] In embodiments the set of sensors is selected from the group consisting of image, temperature, pressure, humidity, velocity, acceleration, rotational, torque, weight, chemical, magnetic field, electrical field, and position sensors.
[0354] In embodiments the platform or system may further include a set of services for reporting on events relevant to at least one of the value, the condition and the ownership of the collateral. [0355] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of the collateral and undertakes an action related to a loan to which the collateral is subject.
[0356] In embodiments the loan-related action is selected from among offering a loan, accepting a loan, underwriting a loan, setting an interest rate for a loan, deferring a payment requirement, modifying an interest rate for a loan, validating title for collateral, recording a change in title, assessing the value of collateral, initiating inspection of collateral, calling a loan, closing a loan, setting terms and conditions for a loan, providing notices required to be provided to a borrower, foreclosing on property subject to a loan, and modifying terms and conditions for a loan.
[0357] In embodiments the platform or system may further include a market value data collection service that monitors and reports on marketplace information relevant to the value of the collateral. In embodiments the collateral items are selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. [0358] In embodiments the market value data collection service monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace.
[0359] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral. In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
[0360] In embodiments the platform or system may further include a set of smart contract services for managing a smart contract for the loan. In embodiments the smart contract services set terms and conditions for the loan. In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
Allocate collateral for a loan using distributed ledger and smart contract
[0361] In embodiments, provided herein is a system for handling a loan having a set of computational services. In embodiments, the platform or system includes (a) a set of blockchain services for supporting a distributed ledger; (b) a set of data collection and monitoring services for monitoring a set of items that provide collateral for a loan; (c) a set of valuation services that use a valuation model to set a value for collateral based on information from the data collection and monitoring services; and (d) a set of smart contract services for establishing a smart lending contract, wherein the smart contract services process output from the set of valuation services and assigns items of collateral sufficient to provide security for the loan to the loan on a distributed ledger that records events relevant to the loan.
[0362] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0363] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0364] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0365] In embodiments the collateral items are selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0366] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0367] In embodiments the valuation services include artificial intelligence services that iteratively improve the valuation model based on outcome data relating to transactions in collateral.
[0368] In embodiments the valuation services further include a set of market value data collection services that monitor and report on marketplace information relevant to the value of collateral. [0369] In embodiments the set of market value data collection services monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace.
[0370] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral.
[0371] In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
Smart contract that sets primary and secondary priority for lenders on same collateral [0372] In embodiments, provided herein is a system for handling a loan having a set of computational services. In embodiments, the platform or system includes (a) a set of blockchain services for supporting a distributed ledger; (b) a set of data collection and monitoring services for monitoring a set of items that provide collateral for a loan; and (c) a set of smart contract services for establishing a smart lending contract, wherein the smart contract services assign collateral to a loan on a distributed ledger that records events relevant to the loan and record priority among a set of lending entities with respect to the collateral.
[0373] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0374] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0375] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0376] In embodiments the set of the collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0377] In embodiments the platform or system may further include a set of valuation services that use a valuation model to set a value for collateral based on information from a set of data collection and monitoring services that monitor items of collateral. [0378] In embodiments the valuation services include artificial intelligence services that iteratively improve the valuation model based on outcome data relating to transactions in collateral.
[0379] In embodiments the valuation services further include a set of market value data collection services that monitor and report on marketplace information relevant to the value of collateral. [0380] In embodiments the set of market value data collection services monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace.
[0381] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral.
[0382] In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
[0383] In embodiments output from the set of valuation services is used by the smart contract services to apportion value for an item of collateral among a set of lenders.
[0384] In embodiments the apportionment of value is based on priority information for the lenders that is recorded in the distributed ledger.
[0385] Referring to Fig. 3, in embodiments, devices 252 may be connected devices that connect (such as through any of the wide range of interfaces 187) to a set of Internet of Things (IoT) data collection services 208, which may be part of or integrated with the data collection systems 166 and monitoring systems 164 of the lending enablement platform 100. The interfaces 187 may include network interfaces, APIs, SDKs, ports, brokers, connectors, gateways, cellular network facilities, data integration interfaces, data migration systems, cloud computing interfaces (including ones that include computational capabilities, such as AWS IoT Greengrass™, Amazon™ Lambda™ and similar systems), and others. For example, the IoT data collection services 208 may be configured to take data from a set of edge data collection devices in the Internet of Things, such as low-power sensor devices (e.g., for sensing movement of entities, for sensing, temperatures, pressures or other attributes about entities 198 or their environments, or the like), cameras that capture still or video images of entities 198, more fully enabled edge devices (such as Raspberry Pi™ or other computing devices, Unix™ devices, and devices running embedded systems, such as including microcontrollers, FPGAs, ASICs and the like), and many others. The IoT data collection services 208 may, in embodiments, collect data about collateral 102 or assets 218, such as, for example, regarding the location, condition (health, physical, or otherwise), quality, security, possession, or the like. For example, an item of personal property, such as a gemstone, vehicle, item of artwork, or the like, may be monitored by a motion sensor and/or a camera having a known location (or having a location confirmed by GPS or other location system), to ensure that it remains in a safe, designated location. The camera can provide evidence that the item remains in undamaged condition and in the possession of a party 210, such as to indicate that it remains appropriate and adequate collateral 102 for a loan. In embodiments this may include items of collateral for microloans, such as clothing, collectibles, and other items. [0386] In embodiments the lending enablement platform 100 has a set of data-integrated microservices including data collection services 166, monitoring services 164, blockchain services for storing data as a blockchain 136, and smart contract services 134 for handling lending entities and transactions. The smart contract services 134 may take data from the data collection systems 166 and monitoring systems 164 (such as from IOT devices) and automatically execute a set of rules or conditions that embody the smart contract based on the collected data. For example, upon recognition that collateral 102 for a loan has been damaged (such as evidenced by a camera or sensor), the smart contract services 134 may automatically initiate a demand for payment of a loan, automatically initiate a foreclosure process, automatically initiate an action to claim substitute or backup collateral, automatically initiate an inspection process, automatically change a payment or interest rate term that is based on the collateral (such as setting an interest rate at a level for an unsecured loan, rather than a secured loan), or the like. Smart contract events may be recorded on a blockchain 136 by the blockchain services, such as in a distributed ledger. Automated monitoring of collateral 102 and assets 218 and handling of loans via smart contract services 134 may facilitate lending to a much wider range of parties 210 and undertaking of loans based on a much wider range of collateral 102 and assets 218 than for conventional loans, as lenders may have greater certainty as to the condition of collateral. Monitoring systems 164 and data collection systems 166 may also monitor and collect data from external marketplaces 188 or for marketplaces operated with the lending enablement platform 100 to maintain awareness of the value of collateral 102 and assets 218, such as to ensure that items remain of adequate value and liquidity to assure repayment of a loan. For example, public e-commerce auction sites like eBay™ can be monitored to confirm that personal property items are of a type and condition likely to be disposed of easily by a lender in a liquid public market, so that the lender is sure to receive payment if the borrower defaults. This may allow loans to be made and administered on a wide range of personal property that is normally difficult to use as collateral. In embodiments an automated foreclosure process may be initiated by a smart contract, which may, upon occurrence of a condition of default that permits foreclosure (such as uncured failure to make payments) include a process for automatically initiating placement of an item of collateral on a public auction site (such as eBay™ or an auction site appropriate for a particular type of property), automatically securing collateral (such as by locking a connected device, such as a smart lock, smart container, or the like that contains or secures collateral), automatically configuring a set of instructions to a carrier, freight forwarder, or the like for shipping collateral, automatically configuring a set of instructions for a drone, a robot, or the like for transporting collateral, or the like.
[0387] In embodiments a system is provided for facilitating foreclosure on collateral. The system may include a set of data collection and monitoring services for monitoring at least one condition of a lending agreement; and a set of smart contract services establishing terms and conditions of the lending agreement that include terms and conditions for foreclosure on at least one item that provides collateral securing a repayment obligation of the lending agreement, wherein upon detection of a default based on data collected by the data collection and monitoring services, the set of smart contract services automatically initiates a foreclosure process on the collateral. In embodiments, the set of smart contract services initiates a signal to at least one of a smart lock and a smart container to lock the collateral. In embodiments, the set of smart contract services configures and initiates a listing of the collateral on a public auction site. In embodiments, the set of smart contract services configures and delivers a set of transport instructions for the collateral. In embodiments, the set of smart contract services configures a set of instructions for a drone to transport the collateral. In embodiments, the set of smart contract services configures a set of instructions for a robot to transport the collateral. In embodiments, the set of smart contract services initiates a process for automatically substituting a set of substitute collateral. In embodiments, the set of smart contract services initiates a message to a borrower initiating a negotiation regarding the foreclosure. In embodiments, the negotiation is managed by a robotic process automation system that is trained on a training set of foreclosure negotiations. In embodiments, the negotiation relates to modification of at least one of the interest rate, the payment terms, and the collateral for the lending transaction.
[0388] Referring to Fig. 4, in embodiments the lending enablement platform 100 is provided having Internet of Things (IoT) data collection services 208 (with various IoT and edge devices as described throughout this disclosure) for monitoring at least one of a set of assets 218 and a set of collateral 102 for a loan, a bond, or a debt transaction. The lending enablement platform 100 may include a guarantee and/or security monitoring solution 230 for monitoring assets 218 and/or collateral 102 based on the data collected by the IoT data collection services 208, such as where the guarantee and/or security monitoring solution 230 uses various adaptive intelligent systems 158, such as ones that may use model (which may be adjusted, reinforced, trained, or the like, such as using artificial intelligence 156) that determines the condition or value of items based on images, sensor data, location data, or other data of the type collected by the IoT data collection services 208. Monitoring may include monitoring of location of collateral 102 or assets 218, behavior of parties 210, financial condition of parties 210, or the like. The guarantee and/or security monitoring solution 230 may include a set of interfaces by which a user may configure parameters for monitoring, such as rules or thresholds regarding conditions, behaviors, attributes, financial values, locations, or the like, in order to obtain alerts regarding collateral 102 or assets 218. For example, a user may set a rule that collateral must remain in a given jurisdiction, a threshold value of the collateral as a percentage of a loan balance, a minimum status condition (e.g., freedom from damage or defects), or the like. Configured parameters may be used to provide alerts to personnel responsible for monitoring loan compliance and/or used or embodied into one or more smart contract contracts that may take input from the interface of the guarantee and/or security monitoring solution 230 to configure conditions for foreclosure, conditions for changing interest rates, conditions for accelerating payments, or the like. The lending enablement platform 100 may have a loan management solution 248 that allows a loan manager to access information from the IoT data collection services 208 and/or the guarantee and/or security monitoring solution 230, such that a user may manage various actions with respect to a loan (of the many types describe herein, such as setting interest rates, foreclosing, sending notices, and the like) based on the condition of collateral 102 or assets 218, based on events involving entities 198, based on behaviors, based on loan-related actions (such as payments) and other factors. The loan management solution 248 may include a set of interfaces, workflows, models (including adaptive intelligent systems 158) that are configured for a particular type of loan (of the many types described herein) and that allow a user to configure parameters, set rules, set thresholds, design workflows, configure smart contract services, configure blockchain services, and the like in order to facilitate automated or assisted management of a loan, such as enabling automated handing of loan actions by a smart contract in response to collected data from the IoT data collection services 208 or enabling generation of a set of recommended actions for a human user based on that data. [0389] In embodiments a lending platform is provided having a smart contract and distributed ledger platform for managing at least one of ownership of a set of collateral and a set of events related to a set of collateral. A set of smart contract services 134 may, for example, transfer ownership of the collateral 102 or other assets 218 upon recognition of an event of failure to make payment or other default, occurrence of a foreclosure condition (such as failure to satisfy with a covenant or failure to comply with an obligation), or the like, where the ownership transfer and related events are recorded by the set of blockchain services in a distributed ledger, such as one that provides a secure record of title to the assets 218 or collateral 102. As an example, a covenant of a loan embodied in a smart contract may require that collateral 102 have a value that exceeds a minimum fraction (or multiple) of the remaining balance of a loan. Based on data collected about the value of collateral (such as by monitoring one or more external marketplaces 188 or marketplaces of the lending enablement platform 100), a smart contract may calculate whether the covenant is satisfied and record the outcome on a blockchain. If the covenant is not satisfied, such as if market factors indicate that the type of collateral has diminished, while the loan balance remains high, the smart contract may initiate a foreclosure, including recording an ownership transfer on a distributed ledger via the blockchain services. A smart contract may also process events related to an entity 198 such as a party 210. For example, a covenant of a loan may require the party to maintain a level of debt below a threshold or ratio, to maintain a level of income, to maintain a level of profit, or the like. The monitoring systems 164 or data collection systems 166 may provide data used by the smart contract services 134 to determine covenant compliance and to enable automated action, including recording events like foreclosure and ownership transfers on a distributed ledger. In another example, a covenant may relate to a behavior of a party 210 or a legal status of a party 210, such as requiring the party to refrain from taking a particular action with respect to an item of property. For example, a covenant may require a party to comply with zoning regulations that prohibit certain usage of real property. IoT data collection services 208 may be used to monitor the party 210, the property, or other items to confirm compliance with the covenant or to trigger alerts or automated actions in cases of non-compliance.
Smart contract with automatic foreclosure based on collateral value falling below covenant requirement
[0390] In embodiments, provided herein is a system for handling a loan having a set of computational services. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for monitoring a set of items that provide collateral for a loan; (b) a set of valuation services that uses a valuation model to set a value for collateral based on information from the data collection and monitoring services; and (c) a set of smart contract services for managing a smart lending contract, wherein the set of smart contract services processes output from the set of valuation services, compares the output to a covenant of the loan that is specified in a smart contract and automatically initiates at least one of a notice of default and a foreclosure action when the value of the collateral is insufficient to satisfy the covenant. [0391] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0392] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan. [0393] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0394] In embodiments the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0395] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0396] In embodiments the set of valuation services includes artificial intelligence services that iteratively improve the valuation model based on outcome data relating to transactions in collateral.
[0397] In embodiments the set of valuation services further includes a set of market value data collection services that monitor and report on marketplace information relevant to the value of collateral.
[0398] In embodiments the set of market value data collection services monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace.
[0399] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral.
[0400] In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
Collateral for smart contract aggregated with other similar collateral [0401] In embodiments, provided herein is a smart contract system for handling a loan having a set of computational services. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for identifying a set of items that provide collateral for a set of loans and collecting information with respect to the collateral items; (b) a set of clustering services for grouping the collateral items based on similarity of attributes of the collateral items; and (c) a set of smart contract services for managing a smart lending contract, wherein the set of smart contract services processes output from the set of clustering services and aggregates and links a subset of similar items of collateral to provide collateral for a set of loans. The clustering circuit 104 may be part of the adaptive intelligent systems 158 and may use any of a wide range of clustering models and techniques, such as ones that are based on attributes of entities 198 that are collected by the monitoring systems 164 or data collection systems 166 and/or stored in the data storage system 186.
[0402] In embodiments the loan for which collateral is aggregated may be any of an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0403] In embodiments the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0404] In embodiments clustering the collateral is performed by a clustering algorithm that groups collateral based on attributes collected by the data collection and monitoring services.
[0405] In embodiments attributes used for grouping are selected from among a type of item, a category of item, a specification of an item, a product feature set of an item, a model of item, a brand of item, a manufacturer of item, a status of item, a context of item, a state of item, a value of item, a storage location of item, a geolocation of item, an age of item, a maintenance history of item, a usage history of item, an accident history of item, a fault history of item, an ownership of item, an ownership history of item, a price of a type of item, a value of a type of item, an assessment of an item, and a valuation of an item. [0406] In embodiments the set of smart contract services allocates a group of similar items as collateral across a set of loans among different parties, thereby diversifying risk across the loans. [0407] In embodiments the platform or system may further include a set of valuation services that uses a valuation model to set a value for collateral based on information from the data collection and monitoring services, wherein the set of smart contract services automatically rebalances items of collateral for a set of loans based on the value of the collateral.
[0408] In embodiments a set of similar collateral items for a set of loans is aggregated in real time based on a similarity in status of the set of items.
[0409] In embodiments the similarity in status is based on the items being in transit during a defined time period.
[0410] In embodiments a set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0411] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0412] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
Smart contract that manages, in a blockchain and distributed ledger, a lien on an asset based on status of a loan for which the asset is collateral
[0413] In embodiments, provided herein is a smart contract system for managing a lien on collateral for a loan having a set of computational services. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for monitoring the status of a loan and an associated set of items of collateral for the loan; (b) a set of blockchain services for maintaining a secure historical ledger of events related to the loan, the blockchain services having access control features that govern access by a set of parties involved in a loan; and (c)a set of smart contract services for managing a smart lending contract, wherein the set of smart contract services processes information from the set of data collection and monitoring services and automatically at least one of initiates and terminates a lien on at least one item in the set of collateral based on the status of the loan, wherein the action on the lien is recorded in the distributed ledger for the loan.
[0414] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0415] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0416] In embodiments the status of the loan is determined based on the status of at least one of an entity related to the loan and a state of performance of a condition for the loan.
[0417] In embodiments the performance of a condition relates to at least one of a payment performance and satisfaction of a covenant.
[0418] In embodiments the set of data collection and monitoring services monitors an entity to determine compliance with a covenant.
[0419] In embodiments the entity is a party, and the set of data collection and monitoring services monitors the financial condition of an entity that is a party to the loan.
[0420] In embodiments the financial condition is determined based on a set of attributes of the entity selected from among a publicly stated valuation of the entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity.
[0421] In embodiments the party is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0422] In embodiments the entity is a set of collateral for the loan and the set of data collection and monitoring services monitor the status of the collateral.
[0423] In embodiments the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0424] In embodiments the platform or system may further include a set of valuation services that uses a valuation model to set a value for a set of collateral based on information from the data collection and monitoring services.
[0425] In embodiments the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0426] In embodiments the set of valuation services includes artificial intelligence services that iteratively improve the valuation model based on outcome data relating to transactions in collateral.
[0427] In embodiments the set of valuation services further includes a set of market value data collection services that monitor and report on marketplace information relevant to the value of collateral.
[0428] In embodiments the set of market value data collection services monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace. [0429] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral.
[0430] In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
[0431] In embodiments terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0432] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0433] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0434] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
Smart contract/blockchain that allows substitution of collateral for a loan based on validated information about the collateral (ownership, condition, value)
[0435] In embodiments, provided herein is a smart contract system for managing collateral for a loan having a set of computational services. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for monitoring the status of a loan and of an associated set of items of collateral for the loan; (b) a set of blockchain services for maintaining a secure historical ledger of events related to the loan, the blockchain services having access control features that govern access by a set of parties involved in a loan; and (c) a set of smart contract services for managing a smart lending contract, wherein the set of smart contract services processes information from the set of data collection and monitoring services and automatically initiates at least one of substitution, removal, or addition of a set of items to the set of collateral for the loan based on an outcome of the processing, wherein the change in the set of collateral is recorded in the distributed ledger for the loan.
[0436] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0437] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0438] In embodiments the status of the loan is determined based on the status of at least one of an entity related to the loan and a state of performance of a condition for the loan.
[0439] In embodiments the performance of a condition relates to at least one of a payment performance and satisfaction of a covenant.
[0440] In embodiments the set of data collection and monitoring services monitors an entity to determine compliance with a covenant.
[0441] In embodiments the entity is a party, and the set of data collection and monitoring services monitors the financial condition of an entity that is a party to the loan.
[0442] In embodiments the financial condition is determined based on a set of attributes of the entity selected from among a publicly stated valuation of the entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity.
[0443] In embodiments the party is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0444] In embodiments the entity is a set of collateral for the loan and the set of data collection and monitoring services monitors the status of the collateral.
[0445] In embodiments the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0446] In embodiments the platform or system may further include a set of valuation services that uses a valuation model to set a value for a set of collateral based on information from the data collection and monitoring services.
[0447] In embodiments the smart contract initiates substitution, removal or addition of collateral items to the set of collateral for the loan to maintain a value of collateral within a stated range. [0448] In embodiments the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0449] In embodiments the set of valuation services includes artificial intelligence services that iteratively improve the valuation model based on outcome data relating to transactions in collateral.
[0450] In embodiments the set of valuation services further includes a set of market value data collection services that monitor and report on marketplace information relevant to the value of collateral. [0451] In embodiments the set of market value data collection services monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace.
[0452] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral.
[0453] In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
[0454] In embodiments terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0455] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0456] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0457] In embodiments a lending platform is provided having a smart contract that automatically adjusts an interest rate for a loan based on at least one of a regulatory factor and a market factor for a specific jurisdiction.
[0458] Referring to Fig. 55, in embodiments a lending platform is provided having a crowdsourcing system for obtaining information about at least one of a state of a set of collateral for a loan and a state of an entity relevant to a guarantee for a loan. Thus, in embodiments, a platform is provided herein, with systems, methods, processes, services, components and other elements for enabling a blockchain and smart contract platform 500 for crowdsourcing information relevant to lending. As with other embodiments described above in connection with sourcing innovation, product demand, or the like, a blockchain 136, such as optionally embodying a distributed ledger, may be configured with a set of smart contracts to administer a reward 512 for the submission of loan information 518, such as evidence of ownership of property, evidence of title, information about ownership of collateral, information about condition of collateral, information about the location of collateral, information about a party’s identity, information about a party’s creditworthiness, information about a party’s activities or behavior, information about a party’s business practices, information about the status of performance of a contract, information about accounts receivable, information about accounts payable, information about the value of collateral, and many other types of information. In embodiments, a blockchain 136, such as optionally distributed in a distributed ledger, may be used to configure a request for information 518 along with terms and conditions 510 related to the information, such as a reward 512 for submission of the information 518, a set of terms and conditions 510 related to the use of the information 518), and various parameters 508, such as timing parameters, the nature of the information required (such as independently validated information like title records, video footage, photographs, witnessed statements, or the like), and other parameters 508.
[0459] The platform 500 may include a crowdsourcing interface 520, which may be included in or provided in coordination with a website, application, dashboard, communications system (such as for sending emails, texts, voice messages, advertisements, broadcast messages, or other message), by which a message may be presented in the crowdsourcing interface 520 or sent to relevant individuals (whether targeted, such as in the case of a request to a particular individual, or broadcast, such as to individuals in a given location, company, organization, or the like) with an appropriate link to the smart contract and associated blockchain 136, such that a reply message submitting information 518, with relevant attachments, links, or other information, can be automatically associated (such as via an API 112 or data integration system) with the blockchain 136, such that the blockchainl36, and any optionally associated distributed ledger, maintains a secure, definitive record of information 518 submitted in response to the request. Where a reward 512 is offered, the blockchain 136 and/or smart contract may be used to record time of submission, the nature of the submission, and the party submitting, such that at such time as a submission satisfies the conditions for a reward 512 (such as, for example, upon completion of a loan transaction in which the information 518 was useful), the blockchain 136 and any distributed ledger stored thereby can be used to identify the submitter and, by execution of the smart contract, convey the reward 512 (which may take any of the forms of consideration noted throughout this disclosure. In embodiments, the blockchain 136 and any associated ledger may include identifying information for submissions of information 518 without containing actual information 518, such that information may be maintained secret (such as being encrypted or being stored separately with only identifying information), subject to satisfying or verifying conditions for access (such as identification or verification of a person who has legitimate access rights, such as by an identity or security application 148). Rewards 512 may be provided based on outcomes of cases or situations to which information 518 relates, based on a set of rules (which may be automatically applied in some cases, such as using a smart contract in concert with an automation system, a rule processing system, an artificial intelligence system 156 or other expert system, which in embodiments may comprise one that is trained on a training data set created with human experts. For example, a machine vision system may be used to evaluate evidence of the existence and/or condition of collateral based on images of items, and parties submitting information about collateral may be rewarded, such as via tokens or other consideration, via distribution of rewards 512 through the smart contract, blockchain 136 and any distributed ledger. Thus, the platform 500 may be used for a wide variety of fact-gathering and information-gathering purposes, to facilitate validation of collateral, to validate representations about behavior, to validate occurrence of conditions of compliance, to validate occurrence of conditions of default, to deter improper behavior or misrepresentations, to reduce uncertainty, to reduce asymmetries of information, or the like.
[0460] In embodiments, information may relate to fact-gathering or data-gathering for a variety of applications and solutions that may be supported by a lending enablement platform 100, including the crowdsourcing platform 500, such as for an underwriting solution 103 (e.g., of various types of loans, guarantees, and other items), risk management solutions 122 (such as managing a wide variety of risks noted throughout this disclosure, such as risks associated with individual loans, packages of loans, tranches of loans and the like); lending applications 144 (such as evidence of the ownership and or value of collateral, evidence of the veracity of representations, evidence of performance or compliance with loan covenants, and the like); regulatory and/or compliance solutions 142 (such as with respect to compliance with a wide range of regulations that may govern entities 198 and processes, behaviors or activities of or by entities 198); and fraud prevention applications 138 (such as to detect fraud, misrepresentation, improper behavior, libel, slander, and the like). For example, a capital loan for a building may include a covenant regarding the use of the property, such as permitting certain uses and prohibiting others, permitting a given occupancy, or the like, and the crowdsourcing platform 500 may solicit and provide consideration for compliance information about the building (e.g., requesting confirmation from the crowd that a building is in fact being used for its intended use as permitted by zone regulations). Crowdsourced information may be combined with information from monitoring systems 164. In embodiments, an adaptive intelligent system 158 may, for example, continuously monitor a property, an item of collateral 102 or other entity 198 and, upon recognition (such as by an AI system, such as a neural network classifier) of a suspicious event (e.g., one that may indicate violation of a loan covenant), the adaptive intelligent system 158 may provide a signal to the crowdsourcing system 520 indicating that a crowdsourcing process should be initiated to verify the presence or absence of the violation. In embodiments, this may include classifying the covenant-related condition that using a machine classifier, providing the classification along with identifying data about an entity, and automatically configuring, such as based on a model or set of rules, a crowdsource request that identifies what information is requested about what entity 198 and what reward 512 is provided. In embodiment, rewards 512 may be configured by experts, rewards 512 may be based on a set of rules (such as ones that operate on parameters of the loan, the terms and conditions of a covenant in a smart contract (such as loan value, remaining term, and the like), the value of collateral 102, or the like), and/or reward 512 may be set by robotic process automation (RPA) 154, such as where an RPA 154 system is trained on a training set of expert activities in setting rewards in various contexts that collectively show what rewards are appropriate in given situations. Robotic process automation (RPA) 154 of reward configuration may be continuously improved by artificial intelligence 156, such as based on a continuous feedback of outcomes of crowdsourcing, such as outcomes of success (e.g., verification of covenant defaults, yield outcomes, and the like).
[0461] Information gathering may include information gathering with respect to entities 198 and their identities, assertions, claims, actions or behaviors, among many other factors and may be accomplished by crowdsourcing in the platform 500 or by data collection systems 166 and monitoring systems 164, optionally with automation via robotic process automation (RPA) 154 and adaptive intelligence, such as using an artificial intelligence system 156.
[0462] Referring to Fig. 6, a platform-operated marketplace crowdsourcing system 500 may be configured, such as in a crowdsourcing dashboard interface 618 or other user interface for an operator of the platform-operated marketplace crowdsourcing system 500, using the various enabling capabilities of the lending enablement platform 100 described throughout this disclosure. The operator may use the user interface or dashboard 514 to undertake a series of steps to perform or undertake an algorithm to create a crowdsourcing request for information 518 as described in connection with Fig. 5. In embodiments, one or more of the steps of the algorithm to create a reward 512 within the dashboard 514 may include, at a step 602, identifying potential rewards 512, such as what information 518 is likely to be of value in a given situation (such as may be indicated through various communication channels by stakeholders or representatives of an entity, such as an individual or enterprise, such as attorneys, agents, investigators, parties, auditors, detectives, underwriters, inspectors, and many others).
[0463] The dashboard 514 may be configured with a crowdsourcing dashboard interface 618, such as with elements (including application programming elements, data integration elements, messaging elements, and the like) that allow a crowdsourcing request to be managed in the platform marketplace 500 and/or in one or more external marketplaces 188. In the dashboard 514, at a step 604 the user may configure one or more parameters 508 or conditions 510, such as comprising or describing the conditions (of the type described herein) for the crowdsourcing request, such as by defining a set of conditions 510 that trigger the reward 512 and determine allocation of the reward 512 to a set of submitters of information 518. The user interface of the dashboard 514, which may include or be associated with the crowdsourcing dashboard interface 620, may include a set of drop down menus, tables, forms, or the like with default, templated, recommended, or pre-configured conditions, parameters 508, conditions 510 and the like, such as ones that are appropriate for various types of crowdsourcing requests. Once the conditions and other parameters of the request are configured, at a step 608 a smart contract and blockchain 136 may be configured to maintain, such as via a ledger, the data required to provision, allocate, and exchange data related to the request and to submissions of information 518. The smart contract and blockchainl36 may be configured to identity information 518, transaction information (such as for exchanges of information), technical information, other evidence data of the type described in connection with Fig. 5, including any data, testimony, photo or video content or other information that may be relevant to a submission of information 518 or the conditions 510 for a reward 512. At a step 610 a smart contract may be configured to embody the conditions 510 that were configured at the step 604 and to operate on the blockchain 136 that was created at the step 608, as well as to operate on other data, such as data indicating facts, conditions, events, or the like in the platform-operated marketplace 500 and/or an external marketplace 188 or other information site or resource, such as ones related to submission information 518, such as sites indicating outcomes of legal cases or portions of cases, sites reporting on investigations, and the like. The smart contract may be configured at the step 610 to apply one or more rules, execute one or more conditional operations, or the like upon data, such as evidence data 518 and data indicating satisfaction of parameters 508 or conditions 510, as well as identity data, transactional data, timing data, and other data. Once configuration of one or more blockchains 136 and one or more smart contracts is complete, at a step 612 the blockchain 136 and smart contract may be deployed in the platform-operated marketplace 500, external marketplace 188 or other site or environment, such as for interaction by one or more submitters or other users, who may, such as in a crowdsourcing dashboard interface 620, such as a website, application, or the like, enter into the smart contract, such as by submitting a submission of information 518 and requesting the reward 512, at which point the platform 500, such as using the adaptive intelligent systems 158 or other capabilities, may store relevant data, such as submission data 518, identity data for the party or parties entering the smart contract on the blockchain 136 or otherwise on the platform 500. At a step 614, once the smart contract is executed, the platform 500 may monitor, such as by the monitoring systems 164 layer, the platform-operated marketplace 500 and/or one or more external marketplaces 188 or other sites for submission data 518, event data 176, or other data that may satisfy or indicate satisfaction of one or more conditions 510 or trigger application of one or more rules of the smart contract, such as to trigger a reward 512.
[0464] At a step 616, upon satisfaction of conditions 510, smart contracts may be settled, executed, or the like, resulting updates or other operations on the blockchain 136, such as by transferring consideration (such as via a payments system) and transferring access to information 518. Thus, via the above-referenced steps, an operator of the platform-operated marketplace 500 may discover, configure, deploy and have executed a set of smart contracts that crowdsource information relevant to a loan (such as information about value or condition of collateral 102, compliance with covenants, fraud or misrepresentation, and the like) and that are cryptographically secured and transferred on a blockchain 136 from information gatherers to parties seeking information. In embodiments, the adaptive intelligent systems 158 layer may be used to monitor the steps of the algorithm described above, and one or more artificial intelligence systems may be used to automate, such as by robotic process automation (RPA) 154, the entire process or one or more sub-steps or sub-algorithms. This may occur as described above, such as by having an artificial intelligence system 156 learn on a training set of data resulting from observations, such as monitoring software interactions of human users as they undertake the above-referenced steps. Once trained, the adaptive intelligent systems 158 layer may thus enable the lending enablement platform 100 to provide a fully automated platform for crowdsourcing of loan information.
Crowdsourcing system for validating quality, title, or other conditions of collateral for a loan
[0465] In embodiments, provided herein is a crowdsourcing system for validating conditions of collateral 102 or assets 218 for a loan. In embodiments, the platform or system includes (a) a set of crowdsourcing services by which a crowdsourcing request is communicated to a group of information suppliers and by which responses to the request are collected and processed to provide a reward to at least one successful information supplier; (b) an interface to the set of crowdsourcing services that enables configuration of parameters of the request, wherein the request and parameters are configured to obtain information related to the condition of a set of collateral for a loan; and (c) a set of publishing services that publish the crowdsourcing request.
[0466] In embodiments the reward is managed by a smart contract that processes responses to the crowdsourcing request and automatically allocates a reward to information that satisfies a set of parameters configured for the crowdsourcing request.
[0467] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0468] In embodiments the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0469] In embodiments condition of collateral 102 or assets 218 includes condition attributes selected from the group consisting of the quality of the collateral, the condition of the collateral, the status of title to the collateral, the status of possession of the collateral, the status of a lien on the collateral, a new or used status of item, a type of item, a category of item, a specification of an item, a product feature set of an item, a model of item, a brand of item, a manufacturer of item, a status of item, a context of item, a state of item, a value of item, a storage location of item, a geolocation of item, an age of item, a maintenance history of item, a usage history of item, an accident history of an item, a fault history of an item, an ownership of an item, an ownership history of an item, a price of a type of item, a value of a type of item, an assessment of an item, and a valuation of an item.
[0470] In embodiments the platform or system may further include a set of blockchain services that record identifying information and parameters of the request, responses to the crowdsourcing request, and rewards in a distributed ledger for the crowdsourcing request.
[0471] In embodiments the interface is a graphical user interface configured to enable a workflow by which a human user enters parameters to establish the crowdsourcing request.
[0472] In embodiments the parameters include a type of requested information, a reward, and a condition for receiving the reward.
[0473] In embodiments the parameter is a reward, and the reward is selected from among a financial reward, a token, a ticket, a contractual right, a cryptocurrency, a set of reward points, a currency, a discount on a product or service, and an access right.
[0474] In embodiments the platform or system may further include a set of smart contract services 134 that administer a smart lending contract, wherein the smart contract services 134 process information from the set of crowdsourcing services and automatically undertake an action related to the loan. [0475] In embodiments the action is at least one of a foreclosure action, a lien administration action, an interest-rate setting action, a default initiation action, a substitution of collateral, and a calling of the loan.
[0476] In embodiments the platform or system may further include a robotic process automation system (RPA) 154 that is trained, based on a training set of interactions of human users with the interface to the set of crowdsourcing services, to configure a crowdsourcing request based on a set of attributes of a loan. In embodiments the attributes of the loan are obtained from a set of smart contract services that manage the loan. In embodiments the robotic process automation system is configured to be iteratively trained and improved based on a set of outcomes from a set of crowdsourcing requests. In embodiments training includes training the robotic process automation system to set a reward. In embodiments training includes training the robotic process automation system to determine a set of domains to which the request will be published. In embodiments training includes training the robotic process automation system to configure the content of a request.
Crowdsourcing system for validating the quality of a personal guarantee for a loan
[0477] In embodiments, provided herein is a crowdsourcing system 520 for validating conditions of collateral 102 or assets 218 for a loan. In embodiments, the platform or system includes (a) a set of crowdsourcing services by which a crowdsourcing request is communicated to a group of information suppliers and by which responses to the request are collected and processed to provide a reward to at least one successful information supplier; (b) an interface to the set of crowdsourcing services that enables configuration of parameters of the request, wherein the request and parameters are configured to obtain information related to the condition of guarantor for a loan; and (c) a set of publishing services that publish the crowdsourcing request.
[0478] In embodiments the set of crowdsourcing systems 520 obtains information about the financial condition of an entity that is the guarantor for the loan.
[0479] In embodiments the financial condition is determined at least in part based on information about the entity selected from among a publicly stated valuation of the entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity. [0480] In embodiments the reward is managed by a smart contract that processes responses to the crowdsourcing request and automatically allocates a reward to information that satisfies a set of parameters configured for the crowdsourcing request.
[0481] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0482] In embodiments the platform or system may further include an interface of the crowdsourcing services In embodiments a request is configured to obtain information about condition of a set of collateral for the loan, wherein the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0483] In embodiments condition of collateral includes condition attributes selected from the group consisting of the quality of the collateral, the condition of the collateral, the status of title to the collateral, the status of possession of the collateral, the status of a lien on the collateral, a new or used status of item, a type of item, a category of item, a specification of an item, a product feature set of an item, a model of item, a brand of item, a manufacturer of item, a status of item, a context of item, a state of item, a value of item, a storage location of item, a geolocation of item, an age of item, a maintenance history of item, a usage history of item, an accident history of an item, a fault history of an item, an ownership of an item, an ownership history of an item, a price of a type of item, a value of a type of item, an assessment of an item, and a valuation of an item. [0484] In embodiments the platform or system may further include a set of blockchain services that record identifying information and parameters of the request, responses to the crowdsourcing request, and rewards in a distributed ledger for the crowdsourcing request.
[0485] In embodiments the interface is a graphical user interface configured to enable a workflow by which a human user enters parameters to establish the crowdsourcing request.
[0486] In embodiments the parameters include a type of requested information, a reward, and a condition for receiving the reward. [0487] In embodiments the parameter is a reward, and the reward is selected from among a financial reward, a token, a ticket, a contractual right, a cryptocurrency, a set of reward points, a currency, a discount on a product or service, and an access right.
[0488] In embodiments the platform or system may further include a set of smart contract services that administer a smart lending contract, wherein the smart contract services process information from the set of crowdsourcing services and automatically undertake an action related to the loan. [0489] In embodiments the action is at least one of a foreclosure action, a lien administration action, an interest-rate setting action, a default initiation action, a substitution of collateral, and a calling of the loan.
[0490] In embodiments the platform or system may further include a robotic process automation system that is trained, based on a training set of interactions of human users with the interface to the set of crowdsourcing services, to configure a crowdsourcing request based on a set of attributes of a loan.
[0491] In embodiments the attributes of the loan are obtained from a set of smart contract services that manage the loan.
[0492] In embodiments the robotic process automation system is configured to be iteratively trained and improved based on a set of outcomes from a set of crowdsourcing requests.
[0493] In embodiments training includes training the robotic process automation system to set a reward, to determine a set of domains to which the request will be published or to configure the content of a request.
[0494] Referring to Fig. 7, in embodiments a lending platform is provided having smart contract services 134 that automatically adjusts an interest rate for a loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analytic services and a set of data collection and monitoring services. The lending enablement platform 100 may include an interest rate automation solution 224 that may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of the setting of interest rates based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others). For example, a user of the interest rate automation solution 224 may set (such as in a user interface) rules, thresholds, model parameters, and the like that determine, or recommend, an interest rate for a loan based on the above, such as based on interest rates available to the lender from secondary lenders, risk factors of the borrower (including predicted risk based on one or more predictive models using artificial intelligence 156), or the system may automatically recommend or set such rules, thresholds, parameters and the like (optionally by learning to do so based on a training set of outcomes over time). Interest rates may be determined based on marketing factors (such as competing interest rates offered by other lenders). Interest rates may be calculated for new loans, for modifications of existing loans, for refinancing, for foreclosure situations (e.g., changing from secured loan rates to unsecured loan rates), and the like.
[0495] In embodiments, provided herein is a smart contract system for modifying a loan having a set of computational services. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for monitoring a set of entities involved in a loan; and (b) a set of smart contract services for managing a smart lending contract, wherein the set of smart contract services processes information from the set of data collection and monitoring services and automatically initiates a change in an interest rate for the loan based on the information.
[0496] In embodiments the change in interest rate is based on the condition of a set of collateral for the loan that is monitored by the set of data collection and monitoring services.
[0497] In embodiments the change in interest rate is based on an attribute of a party that is monitored by the set of data collection and monitoring services.
[0498] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0499] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0500] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0501] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0502] In embodiments the platform or system may further include a set of valuation services that uses a valuation model to set a value for a set of collateral based on information from the data collection and monitoring services.
[0503] In embodiments the change in interest rate is based on the valuation of a set of collateral for the loan that is monitored by the set of data collection and monitoring services.
[0504] In embodiments a set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0505] In embodiments the set of valuation services includes artificial intelligence services that iteratively improve the valuation model based on outcome data relating to transactions in collateral.
[0506] In embodiments the set of valuation services further includes a set of market value data collection services that monitor and report on marketplace information relevant to the value of collateral.
[0507] In embodiments the set of market value data collection services monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace.
[0508] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral.
[0509] In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
[0510] In embodiments, provided herein is a smart contract system for modifying a loan having a set of computational services. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for monitoring public sources of information about a set of entities involved in a loan, wherein the public sources of information are selected from among website information, news article information, social network information and crowdsourced information; and (b) a set of smart contract services for managing a smart lending contract, wherein the set of smart contract services processes information from the set of data collection and monitoring services and automatically initiates a change in an interest rate for the loan based on the information·
[0511] In embodiments the set of data collection and monitoring services monitor the financial condition of an entity that is a party to the loan.
[0512] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0513] In embodiments the financial condition is determined based on a set of attributes of the entity selected from among a publicly stated valuation of the entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity.
[0514] In embodiments the party is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0515] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of items of collateral and undertakes an action related to a loan to which the collateral is subject.
[0516] In embodiments the loan-related action is selected from among offering a loan, accepting a loan, underwriting a loan, setting an interest rate for a loan, deferring a payment requirement, modifying an interest rate for a loan, validating title for collateral, recording a change in title, assessing the value of collateral, initiating inspection of collateral, calling a loan, closing a loan, setting terms and conditions for a loan, providing notices required to be provided to a borrower, foreclosing on property subject to a loan, and modifying terms and conditions for a loan.
[0517] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0518] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0519] In embodiments the monitored entity is a set of collateral items that is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0520] In embodiments, provided herein is a smart contract system for modifying a loan, the system having a set of computational services. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for monitoring a set of entities involved in a loan In embodiments the entities are located in a plurality of different jurisdictions; and (b) a set of smart contract services for managing a smart lending contract, wherein the set of smart contract services processes location information about the entities from the set of data collection and monitoring services and automatically undertakes a loan-related action for the loan based at least in part on the location information.
[0521] In embodiments the loan-related action is selected from among offering a loan, accepting a loan, underwriting a loan, setting an interest rate for a loan, deferring a payment requirement, modifying an interest rate for a loan, validating title for collateral, recording a change in title, assessing the value of collateral, initiating inspection of collateral, calling a loan, closing a loan, setting terms and conditions for a loan, providing notices required to be provided to a borrower, foreclosing on property subject to a loan, and modifying terms and conditions for a loan.
[0522] In embodiments the smart contract is configured to process a set of jurisdiction- specific regulatory notice requirements and to provide an appropriate notice to a borrower based on location of at least one of the lender, the borrower, the funds provided via the loan, the repayment of the loan, and the collateral for the loan.
[0523] In embodiments the smart contract is configured to process a set of jurisdiction- specific regulatory foreclosure requirements and to provide an appropriate foreclosure notice to a borrower based on jurisdiction of at least one of the lender, the borrower, the funds provided via the loan, the repayment of the loan, and the collateral for the loan.
[0524] In embodiments the smart contract is configured to process a set of jurisdiction- specific rules for setting terms and conditions of the loan and to configure the smart contract based on the location of at least one of the borrower, the funds provided via the loan, the repayment of the loan, and the collateral for the loan.
[0525] In embodiments the smart contract is configured to set the interest rate for the loan to cause the loan to comply with maximum interest rate limitations applicable in a jurisdiction.
[0526] In embodiments the change in interest rate is based on the condition of a set of collateral for the loan that is monitored by the set of data collection and monitoring services.
[0527] In embodiments the change in interest rate is based on an attribute of a party that is monitored by the set of data collection and monitoring services.
[0528] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0529] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0530] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0531] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0532] In embodiments the platform or system may further include a set of valuation services that uses a valuation model to set a value for a set of collateral based on information from the data collection and monitoring services.
[0533] In embodiments the valuation model is a jurisdiction-specific valuation model that is based on the jurisdiction of at least one of the lender, the borrower, the delivery of funds provided via loan, the payment of the loan and collateral for the loan.
[0534] In embodiments at least one of the terms and conditions for the loan is based on the valuation of a set of collateral for the loan that is monitored by the set of data collection and monitoring services.
[0535] In embodiments a set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0536] In embodiments the set of valuation services includes artificial intelligence services that iteratively improve the valuation model based on outcome data relating to transactions in collateral.
[0537] In embodiments the set of valuation services further includes a set of market value data collection services that monitor and report on marketplace information relevant to the value of collateral.
[0538] In embodiments the set of market value data collection services monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace.
[0539] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral.
[0540] In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
[0541] Referring to Fig. 8, in embodiments a lending platform is provided having a smart contract that automatically restructures debt based on a monitored condition. The lending enablement platform 100 may include a debt restructuring solution 228 that may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of the restructuring of debt based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others). For example, a user of the debt restructuring solution 228 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the debt restructuring solution 228) various rules, thresholds, procedures, workflows, model parameters, and the like that determine, or recommend, a debt restructuring action for a loan based on one or more events, conditions, states, actions, or the like, where restructuring may be based on various factors, such as prevailing market interest rates, interest rates available to the lender from secondary lenders, risk factors of the borrower (including predicted risk based on one or more predictive models using artificial intelligence 156), status of other debt (such as new debt of a borrower, elimination of debt of a borrower, or the like), condition of collateral 102 or assets 218 used to secure or back a loan, state of a business or business operation (e.g., receivables, payables, or the like), and many others. Restructuring may include changes in interest rate, changes in priority of secured parties, changes in collateral 102 or assets 218 used to back or secure debt, changes in parties, changes in guarantors, changes in payment schedule, changes in principal balance (e.g., including forgiveness or acceleration of payments), and others. In embodiments the debt restructuring solution 228 may automatically recommend or set such rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended restructuring plan, which may specify a series of actions required to accomplish a recommended restructuring, which may be automated and may be involved conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the debt restructuring plan. Restructuring plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other lenders, values of collateral, and the like) as well as regulatory and/or compliance factors. Restructuring plans may be generated and/or executed for modifications of existing loans, for refinancing, for foreclosure situations (e.g., changing from secured loan rates to unsecured loan rates), for bankruptcy or insolvency situations, for situations involving market changes (e.g., changes in prevailing interest rates) and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of restructuring activities by experts and/or on outcomes of restructuring actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a restructuring plan.
[0542] In embodiments, provided herein is a smart contract system for modifying a loan, the system having a set of computational services. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for monitoring a set of entities involved in a loan; and (b) a set of smart contract services for managing a smart lending contract, wherein the set of smart contract services processes information from the set of data collection and monitoring services and automatically restructures debt based on a monitored condition.
[0543] In embodiments the restructuring is based on the condition of a set of collateral for the loan that is monitored by the set of data collection and monitoring services.
[0544] In embodiments the restructuring is according to a set of rules that are based on a covenant of the loan, wherein the restructuring occurs upon an event that is determined with respect to at least one of the monitored entities that relates to the covenant.
[0545] In embodiments the event is the failure of collateral for a loan to exceed a required fractional value of the remaining balance of the loan.
[0546] In embodiments the event is a default of the buyer with respect to a loan covenant.
[0547] In embodiments the restructuring is based on an attribute of a party that is monitored by the set of data collection and monitoring services.
[0548] In embodiments the set of smart contract services further includes services for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan- related events and loan-related activities.
[0549] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0550] In embodiments the set of terms and conditions for the loan that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default. [0551] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0552] In embodiments the platform or system may further include a set of valuation services that uses a valuation model to set a value for a set of collateral based on information from the data collection and monitoring services.
[0553] In embodiments the restructuring of the debt is based on the valuation of a set of collateral for the loan that is monitored by the set of data collection and monitoring services.
[0554] In embodiments a set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0555] In embodiments the set of valuation services includes artificial intelligence services that iteratively improve the valuation model based on outcome data relating to transactions in collateral.
[0556] In embodiments the set of valuation services further includes a set of market value data collection services that monitor and report on marketplace information relevant to the value of collateral.
[0557] In embodiments the set of market value data collection services monitors pricing or financial data for items that are similar to the collateral in at least one public marketplace.
[0558] In embodiments a set of similar items for valuing an item of collateral is constructed using a similarity clustering algorithm based on the attributes of the collateral.
[0559] In embodiments the attributes are selected from among a category of the collateral, an age of the collateral, a condition of the collateral, a history of the collateral, a storage condition of the collateral and a geolocation of the collateral.
[0560] Referring to Fig. 9, in embodiments a lending enablement platform 100 is provided having a social network analytics application 204 for monitoring social media, collecting data and determining analytics for validating the reliability of a guarantee for a loan. The lending enablement platform 100 may include a guarantee and/or security monitoring solution 230 that may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable monitoring of a guarantee and/or security for a lending transaction based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others). For example, a user of the guarantee and/or security monitoring solution 230 may set (such as in a user interface) rules, thresholds, model parameters, and the like that determine, or recommend, a monitoring plan for lending transaction such as based on risk factors of the borrower, risk factors of the lender, market risk factors, and/or risk factors of collateral 102 or assets 218 (including predicted risk based on one or more predictive models using artificial intelligence 156), or the lending enablement platform 100 may automatically recommend or set such rules, thresholds, parameters and the like (optionally by learning to do so based on a training set of outcomes over time). The guarantee and/or security monitoring solution 230 may configure a set of social network analytics services 204 and/or other monitoring systems 164 and/or data collection systems 166 to search, parse, extract, and process data from one or more social networks, website, or the like, such as ones that may contain information about collateral 102 or assets 218 (e.g., photos that show a vehicle, boat, or other personal property of a party 210, photos of a home or other real property, photos or text that describes activities of a party 210 (including ones that indicate financial risk, physical risk, health risk, or other risk that may be relevant to the quality of the guarantor and/or the guarantee for a payment obligation and/or the ability of the borrower to repay a loan when due). For example a photo showing a borrower driving a regular passenger vehicle in off-road conditions may be flagged as indicating that the vehicle cannot be fully relied upon as collateral for an automobile loan that has a high remaining balance.
[0561] Thus, in embodiments, provided herein is a social network monitoring system for validating conditions of a guarantee for a loan. In embodiments, the platform or system includes (a) a set of social network data collection and monitoring services by which data is collected by a set of algorithms that are configured to monitor social network information about entities involved in a loan; and (b) an interface to the set of social networking services that enables configuration of parameters of the social network data collection and monitoring services to obtain information related to the condition of guarantee.
[0562] In embodiments the set of social network data collection and monitoring services obtains information about the financial condition of an entity that is the guarantor for the loan. [0563] In embodiments the financial condition is determined at least in part based on information contained in a social network about the entity selected from among a publicly stated valuation of the entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity.
[0564] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0565] In embodiments the platform or system may further include an interface of the social network data collection and monitoring services In embodiments the data collection and monitoring service is configured to obtain information about condition of a set of collateral for the loan, wherein the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0566] In embodiments condition of collateral includes condition attributes selected from the group consisting of the quality of the collateral, the condition of the collateral, the status of title to the collateral, the status of possession of the collateral, the status of a lien on the collateral, a new or used status of item, a type of item, a category of item, a specification of an item, a product feature set of an item, a model of item, a brand of item, a manufacturer of item, a status of item, a context of item, a state of item, a value of item, a storage location of item, a geolocation of item, an age of item, a maintenance history of item, a usage history of item, an accident history of an item, a fault history of an item, an ownership of an item, an ownership history of an item, a price of a type of item, a value of a type of item, an assessment of an item, and a valuation of an item. [0567] In embodiments the interface is a graphical user interface configured to enable a workflow by which a human user enters parameters to establish the social network data collection and monitoring request.
[0568] In embodiments the platform or system may further include a set of smart contract services that administer a smart lending contract, wherein the smart contract services process information from the set of social network data collection and monitoring services and automatically undertake an action related to the loan.
[0569] In embodiments the action is at least one of a foreclosure action, a lien administration action, an interest-rate setting action, a default initiation action, a substitution of collateral, and a calling of the loan.
[0570] In embodiments the platform or system may further include a robotic process automation system that is trained, based on a training set of interactions of human users with the interface to the set of social network data collection and monitoring services, to configure a data collection and monitoring action based on a set of attributes of a loan.
[0571] In embodiments the attributes of the loan are obtained from a set of smart contract services that manage the loan.
[0572] In embodiments the robotic process automation system is configured to be iteratively trained and improved based on a set of outcomes from a set of social network data collection and monitoring requests.
[0573] In embodiments training includes training the robotic process automation system to determine a set of domains to which the social network data collection and monitoring services will applied.
[0574] In embodiments training includes training the robotic process automation system to configure the content of a social network data collection and monitoring search.
[0575] Referring still to Fig. 9, in embodiments a lending platform is provided having an Internet of Things data collection and monitoring system for validating reliability of a guarantee for a loan. The guarantee and/or security monitoring solution 230 may include the capability to use data from, and configure collection activities by, a set of Internet of Things services 208 (which may include various IoT devices, edge devices, edge computation and processing capabilities, and the like as described in connection with various embodiments), such as ones that monitor various entities 198 and their environments involved in lending transactions.
[0576] In embodiments, provided herein is a monitoring system for validating conditions of a guarantee for a loan. For example, a set of algorithms may be configured to initiate data collection by IoT devices, to manage data collection, and the like such as based on the conditions referenced above, including conditions that relate to risk factors of the borrower or lender, market risk factors, physical risk factors, or the like. For example, an IoT system may be configured to capture video or images of a home during periods of bad weather, such as to determine whether the home is at risk of a flood, wind damage, or the like, in order to confirm whether the home can be predicted to serve as adequate collateral for a home loan, a line of credit, or other lending transaction. [0577] In embodiments, the platform or system includes (a) a set of Internet of Things data collection and monitoring services by which data is collected by a set of algorithms that are configured to monitor Internet of Things information collected from and about entities involved in a loan; and (b) an interface to the set of Internet of Things data collection and monitoring services that enables configuration of parameters of the social network data collection and monitoring services to obtain information related to the condition of guarantee.
[0578] In embodiments the set of Internet of Things data collection and monitoring services obtains information about the financial condition of an entity that is the guarantor for the loan. [0579] In embodiments the financial condition is determined at least in part based on information collected by an Internet of Things device about the entity selected from among a publicly stated valuation of the entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity.
[0580] In embodiments the loan is of at least one type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0581] In embodiments the platform or system may further include an interface of the set of Internet of Things data collection and monitoring services In embodiments the set of data collection and monitoring services is configured to obtain information about condition of a set of collateral for the loan, wherein the set of collateral items is selected from among a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0582] In embodiments condition of collateral includes condition attributes selected from the group consisting of the quality of the collateral, the condition of the collateral, the status of title to the collateral, the status of possession of the collateral, the status of a lien on the collateral, a new or used status of item, a type of item, a category of item, a specification of an item, a product feature set of an item, a model of item, a brand of item, a manufacturer of item, a status of item, a context of item, a state of item, a value of item, a storage location of item, a geolocation of item, an age of item, a maintenance history of item, a usage history of item, an accident history of an item, a fault history of an item, an ownership of an item, an ownership history of an item, a price of a type of item, a value of a type of item, an assessment of an item, and a valuation of an item. [0583] In embodiments the interface is a graphical user interface configured to enable a workflow by which a human user enters parameters to establish an Internet of Things data collection and monitoring services monitoring action.
[0584] In embodiments the platform or system may further include a set of smart contract services that administer a smart lending contract, wherein the set of smart contract services process information from the set of Internet of Things data collection and monitoring services and automatically undertakes an action related to the loan.
[0585] In embodiments the action is at least one of a foreclosure action, a lien administration action, an interest-rate setting action, a default initiation action, a substitution of collateral, and a calling of the loan.
[0586] In embodiments the platform or system may further include a robotic process automation system that is trained, based on a training set of interactions of human users with the interface to the set of Internet of Things data collection and monitoring services, to configure a data collection and monitoring action based on a set of attributes of a loan.
[0587] In embodiments the attributes of the loan are obtained from a set of smart contract services that manage the loan.
[0588] In embodiments the robotic process automation system is configured to be iteratively trained and improved based on a set of outcomes from a set of Internet of Things data collection and monitoring services activities. [0589] In embodiments training includes training the robotic process automation system to determine a set of domains to which the Internet of Things data collection and monitoring services will applied.
[0590] In embodiments training includes training the robotic process automation system to configure the content of Internet of Things data collection and monitoring services activities. [0591] Referring to Fig. 10, in embodiments a lending platform is provided having a robotic process automation system (RPA) 154 for negotiation of a set of terms and conditions for a loan. The RPA system 154 may provide automation for one or more aspects of a negotiation solution 232 that enables automated negotiation and/or provides a recommendation or plan for a negotiation relevant to a lending transaction. The negotiation solution 232 and/or RPA system 154 for negotiation may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a negotiation of one or more terms and conditions of a lending transaction, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others). For example, a user of the negotiation solution 232 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the negotiation solution 232 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a negotiation action or plan for a lending transaction negotiation based on one or more events, conditions, states, actions, or the like, where the negotiation plan may be based on various factors, such as prevailing market interest rates, interest rates available to the lender from secondary lenders, risk factors of the borrower, the lender, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 used to secure or back a loan, state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating negotiation styles), and many others. Negotiation may include negotiation of lending transaction terms and conditions, debt restructuring, foreclosure activities, setting interest rates, changes in interest rate, changes in priority of secured parties, changes in collateral 102 or assets 218 used to back or secure debt, changes in parties, changes in guarantors, changes in payment schedule, changes in principal balance (e.g., including forgiveness or acceleration of payments), and many other transactions or terms and conditions. In embodiments the negotiation solution 232 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended negotiation plan, which may specify a series of actions required to accomplish a recommended or desired outcome of negotiation (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the negotiation plan. Negotiation plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other lenders, values of collateral, and the like) as well as regulatory and/or compliance factors. Negotiation plans may be generated and/or executed for creation of new loans, for creation of guarantees and security, for secondary loans, for modifications of existing loans, for refinancing, for foreclosure situations (e.g., changing from secured loan rates to unsecured loan rates), for bankruptcy or insolvency situations, for situations involving market changes (e.g., changes in prevailing interest rates) and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of negotiation activities by experts and/or on outcomes of negotiation actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a negotiation plan.
[0592] In embodiments, provided herein is a robotic process automation system for negotiating a loan. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for collecting a training set of interactions among entities for a set of loan transactions; (b) an artificial intelligence system that is trained on the training set of interactions to classify a set of loan negotiation actions; and (c) a robotic process automation system that is trained on a set of loan transaction interactions and a set of loan transaction outcomes to negotiate the terms and conditions of a loan on behalf of a party to a loan.
[0593] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0594] In embodiments the entities are a set of parties to a loan transaction.
[0595] In embodiments the set of parties is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0596] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0597] In embodiments the robotic process automation is trained on a set of interactions of parties with a set of user interfaces involved in a set of lending processes.
[0598] In embodiments upon completion of negotiation a smart contract for a loan is automatically configured by a set of smart contract services based on the outcome of the negotiation.
[0599] In embodiments at least one of an outcome and a negotiating event of the negotiation is recorded in a distributed ledger associated with the loan.
[0600] In embodiments the loan is of a type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0601] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0602] In embodiments, provided herein is a robotic process automation system for negotiating refinancing of a loan. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for collecting a training set of interactions between entities for a set of loan refinancing activities; an artificial intelligence system that is trained on the training set of interactions to classify a set of loan refinancing actions; and (c) a robotic process automation system that is trained on a set of loan refinancing interactions and a set of loan refinancing outcomes to undertake a loan refinancing activity on behalf of a party to a loan.
[0603] In embodiments the loan refinancing activity includes initiating an offer to refinance, initiating a request to refinance, configuring a refinancing interest rate, configuring a refinancing payment schedule, configuring a refinancing balance, configuring collateral for a refinancing, managing use of proceeds of a refinancing, removing or placing a lien associated with a refinancing, verifying title for a refinancing, managing an inspection process, populating an application, negotiating terms and conditions for a refinancing and closing a refinancing.
[0604] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0605] In embodiments the entities are a set of parties to a loan transaction.
[0606] In embodiments the set of parties is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0607] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0608] In embodiments the robotic process automation is trained on a set of interactions of parties with a set of user interfaces involved in a set of lending processes.
[0609] In embodiments upon completion of a refinancing process a smart contract for a refinance loan is automatically configured by a set of smart contract services based on the outcome of the refinancing activity.
[0610] In embodiments at least one of an outcome and an event of the refinancing is recorded in a distributed ledger associated with the refinancing loan.
[0611] In embodiments the loan is of a type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan. [0612] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0613] Referring to Fig. 11, in embodiments a lending platform is provided having a robotic process automation system for loan collection. The RPA system 154 may provide automation for one or more aspects of a collection solution 238 that enables automated collection and/or provides a recommendation or plan for a collection activity relevant to a lending transaction. The collection solution 238 and/or RPA system 154 for collection may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a collection action of one or more terms and conditions of a collection process for a lending transaction, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others). For example, a user of the collection solution 238 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the collection solution 238 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a collection action or plan for a lending transaction or loan monitoring solution based on one or more events, conditions, states, actions, or the like, where the collection plan may be based on various factors, such as the status of payments, the status of the borrower, the status of collateral 102 or assets 218, risk factors of the borrower, the lender, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 used to secure or back a loan, state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating how borrowers respond to communication styles, communication cadence, and the like), and many others. Collection may include collection with respect to loans, communications to encourage payments, and the like. In embodiments the collection solution 238 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended collection plan, which may specify a series of actions required to accomplish a recommended or desired outcome of collection (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the collection plan. Collection plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other lenders, values of collateral, and the like) as well as regulatory and/or compliance factors. Collection plans may be generated and/or executed for creation of new loans, for secondary loans, for modifications of existing loans, for refinancing, for foreclosure situations (e.g., changing from secured loan rates to unsecured loan rates), for bankruptcy or insolvency situations, for situations involving market changes (e.g., changes in prevailing interest rates) and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of collection activities by experts and/or on outcomes of collection actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a collection plan.
[0614] In embodiments, provided herein is a robotic process automation system for handling collection of a loan. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for collecting a training set of interactions among entities for a set of loan transactions that involve collection of a set of payments for a set of loans; (b) an artificial intelligence system that is trained on the training set of interactions to classify a set of loan collection actions; and (c) a robotic process automation system that is trained on a set of loan transaction interactions and a set of loan collection outcomes to undertake a loan collection action on behalf of a party to a loan.
[0615] In embodiments the loan collection action undertaken by the robotic process automation system is selected from among initiation of a collection process, referral of a loan to an agent for collection, configuration of a collection communication, scheduling of a collection communication, configuration of content for a collection communication, configuration of an offer to settle a loan, termination of a collection action, deferral of a collection action, configuration of an offer for an alternative payment schedule, initiation of a litigation, initiation of a foreclosure, initiation of a bankruptcy process, a repossession process, and placement of a lien on collateral.
[0616] In embodiments the set of loan collection outcomes is selected from among a response to a collection contact event, a payment of a loan, a default of the borrower on a loan, a bankruptcy of a borrower of a loan, an outcome of a collection litigation, a financial yield of a set of collection actions, a return on investment on collection and a measure of reputation of a party involved in collection.
[0617] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities. In embodiments the entities are set of parties to a loan transaction. In embodiments the set of parties is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0618] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0619] In embodiments the robotic process automation is trained on a set of interactions of parties with a set of user interfaces involved in a set of lending processes.
[0620] In embodiments upon completion of negotiation of a collection process a smart contract for a loan is automatically configured by a set of smart contract services based on the outcome of the negotiation.
[0621] In embodiments at least one of a collection outcome and a collection event is recorded in a distributed ledger associated with the loan.
[0622] In embodiments the loan is of a type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0623] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0624] Referring to Fig. 12, in embodiments a lending platform is provided having a robotic process automation system for consolidating a set of loans. The RPA system 154 may provide automation for one or more aspects of a consolidation solution 240 that enables automated consolidation and/or provides a recommendation or plan for a consolidation activity relevant to a lending transaction. The consolidation solution 240 and/or RPA system 154 for consolidation may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a consolidation action or a consolidation process for a lending transaction, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others). For example, a user of the consolidation solution 240 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the consolidation solution 240 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a consolidation action or plan for a lending transaction or a set of loans based on one or more events, conditions, states, actions, or the like, where the consolidation plan may be based on various factors, such as the status of payments, interest rates of the set of loans, prevailing interest rates in a platform marketplace or external marketplace, the status of the borrowers of a set of loans, the status of collateral 102 or assets 218, risk factors of the borrower, the lender, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 used to secure or back a set of loans, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences), and many others. Consolidation may include consolidation with respect to terms and conditions of sets of loans, selection of appropriate loans, configuration of payment terms for consolidated loans, configuration of payoff plans for pre-existing loans, communications to encourage consolidation, and the like. In embodiments the consolidation solution 240 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended consolidation plan, which may specify a series of actions required to accomplish a recommended or desired outcome of consolidation (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the consolidation plan. Consolidation plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other lenders, values of collateral, and the like) as well as regulatory and/or compliance factors. Consolidation plans may be generated and/or executed for creation of new consolidated loans, for secondary loans related to consolidated loans, for modifications of existing loans related to consolidation, for refinancing terms of a consolidated loan, for foreclosure situations (e.g., changing from secured loan rates to unsecured loan rates), for bankruptcy or insolvency situations, for situations involving market changes (e.g., changes in prevailing interest rates) and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of consolidation activities by experts and/or on outcomes of consolidation actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a consolidation plan.
[0625] In embodiments, provided herein is a robotic process automation system for consolidating a set of loans. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for collecting information about a set of loans and for collecting a training set of interactions between entities for a set of loan consolidation transactions; (b) an artificial intelligence system that is trained on the training set of interactions to classify a set of loans as candidates for consolidation; and (c) a robotic process automation system that is trained on a set of loan consolidation interactions to manage consolidation of at least a subset of the set of loans on behalf of a party to the consolidation.
[0626] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0627] In embodiments the set of loans that are classified as candidates for consolidation are determined based on a model that processes attributes of entities involved in the set of loans, wherein the attributes selected from among identity of a party, interest rate, payment balance, payment terms, payment schedule, type of loan, type of collateral, financial condition of party, payment status, condition of collateral, and value of collateral. [0628] In embodiments managing consolidation includes managing at least one of identification of loans from a set of candidate loans, preparation of a consolidation offer, preparation of a consolidation plan, preparation of content communicating a consolidation offer, scheduling a consolidation offer, communicating a consolidation offer, negotiating a modification of a consolidation offer, preparing a consolidation agreement, executing a consolidation agreement, modifying collateral for a set of loans, handling an application workflow for consolidation, managing an inspection, managing an assessment, setting an interest rate, deferring a payment requirement, setting a payment schedule, and closing a consolidation agreement. In embodiments the entities are a set of parties to a loan transaction. In embodiments the set of parties is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0629] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0630] In embodiments the robotic process automation is trained on a set of interactions of parties with a set of user interfaces involved in a set of consolidation processes. In embodiments upon completion of negotiation a smart contract for a consolidated loan is automatically configured by a set of smart contract services based on the outcome of the negotiation. In embodiments at least one of an outcome and a negotiating event of the negotiation is recorded in a distributed ledger associated with the loan.
[0631] In embodiments the loan is of a type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0632] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system. [0633] Referring to Fig. 13, in embodiments a lending platform is provided having a robotic process automation system for managing a factoring transaction. The RPA system 154 may provide automation for one or more aspects of a factoring solution 242 that enables automated factoring and/or provides a recommendation or plan for a factoring activity relevant to a lending transaction, such as one involving factoring of receivables. The factoring solution 242 and/or RPA system 154 for factoring may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a factoring action of one or more terms and conditions of a factoring transaction, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, accounts receivable, and inventory, among others). For example, a user of the factoring solution 242 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the factoring solution 242 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a factoring action or plan for a factoring transaction or monitoring solution based on one or more events, conditions, states, actions, or the like, where the factoring plan may be based on various factors, such as the status of receivables, the status of work-in-progress, the status of inventory, the status of delivery and/or shipment, the status of payments, the status of the borrower, the status of collateral 102 or assets 218, risk factors of the borrower, the lender, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 used to secure or back a loan, state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating negotiation styles, and the like), and many others. Factoring may include factoring with respect to loans, communications to encourage payments, and the like. In embodiments the factoring solution 242 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended factoring plan, which may specify a series of actions required to accomplish a recommended or desired outcome of factoring (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the factoring plan. Factoring plans may be determined and executed based at least one part on market factors (such as competing interest rates or other terms and conditions offered by other lenders, values of collateral, values of accounts receivable, interest rates, and the like) as well as regulatory and/or compliance factors. Factoring plans may be generated and/or executed for creation of new factoring arrangements, for modifications of existing factoring arrangements, and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of factoring activities by experts and/or on outcomes of factoring actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a factoring plan.
[0634] In embodiments, provided herein is a robotic process automation system for consolidating a set of loans. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for collecting information about entities involved in a set of factoring loans and for collecting a training set of interactions between entities for a set of factoring loan transactions; (b) an artificial intelligence system that is trained on the training set of interactions to classify the entities involved in the set of factoring loans; and (c) a robotic process automation system that is trained on the set of factoring loan interactions to manage a factoring loan.
[0635] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0636] In embodiments the artificial intelligence system uses a model that processes attributes of entities involved in the set of factoring loans, wherein the attributes selected from assets used for factoring, identity of a party, interest rate, payment balance, payment terms, payment schedule, type of loan, type of collateral, financial condition of party, payment status, condition of collateral, and value of collateral.
[0637] In embodiments the assets used for factoring include a set of accounts receivable.
[0638] In embodiments managing a factoring loan includes managing at least one of a set of assets for factoring, identification of loans for factoring from a set of candidate loans, preparation of a factoring offer, preparation of a factoring plan, preparation of content communicating a factoring offer, scheduling a factoring offer, communicating a factoring offer, negotiating a modification of a factoring offer, preparing a factoring agreement, executing a factoring agreement, modifying collateral for a set of factoring loans, handing transfer of a set of accounts receivable, handling an application workflow for factoring, managing an inspection, managing an assessment of a set of assets to be factored, setting an interest rate, deferring a payment requirement, setting a payment schedule, and closing a factoring agreement.
[0639] In embodiments the entities are a set of parties to a loan transaction.
[0640] In embodiments the set of parties is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0641] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0642] In embodiments the robotic process automation is trained on a set of interactions of parties with a set of user interfaces involved in a set of factoring processes.
[0643] In embodiments upon completion of negotiation a smart contract for a factoring loan is automatically configured by a set of smart contract services based on the outcome of the negotiation.
[0644] In embodiments at least one of an outcome and a negotiating event of the negotiation is recorded in a distributed ledger associated with the loan.
[0645] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0646] Referring to Fig. 14, in embodiments a lending platform is provided having a robotic process automation system for brokering a loan. The loan may be, for example, a mortgage loan. [0647] The RPA system 154 may provide automation for one or more aspects of a brokering solution 244 that enables automated brokering and/or provides a recommendation or plan for a brokering activity relevant to a lending transaction, such as for brokering a set of mortgage loans, home loans, lines of credit, automobile loans, construction loans, or other loans of any of the types described herein. The brokering solution 244 and/or RPA system 154 for brokering may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a brokering action or a brokering process for a lending transaction, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others, as well as of interest rates, available lenders, available terms and the like). For example, a user of the brokering solution 244 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the brokering solution 244 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a brokering action or plan for brokering a set of loans of a given type or types based on one or more events, conditions, states, actions, or the like, where the brokering plan may be based on various factors, such as the interest rates of the set of loans available from various primary and secondary lenders, permitted attributes of borrowers (e.g., based on income, wealth, location, or the like) prevailing interest rates in a platform marketplace or external marketplace, the status of the borrowers of a set of loans, the status or other attributes of collateral 102 or assets 218, risk factors of the borrower, the lender, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 available to secure or back a set of loans, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences), and many others. Brokering may include brokering with respect to terms and conditions of sets of loans, selection of appropriate loans, configuration of payment terms for consolidated loans, configuration of payoff plans for pre-existing loans, communications to encourage borrowing, and the like. In embodiments the brokering solution 244 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended brokering plan, which may specify a series of actions required to accomplish a recommended or desired outcome of brokering (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the brokering plan. Brokering plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other lenders, property values, attributes of borrowers, values of collateral, and the like) as well as regulatory and/or compliance factors. Brokering plans may be generated and/or executed for creation of new loans, for secondary loans, for modifications of existing loans, for refinancing terms, for situations involving market changes (e.g., changes in prevailing interest rates or property values) and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of brokering activities by experts and/or on outcomes of brokering actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a brokering plan.
[0648] In embodiments, provided herein is a robotic process automation system for automating brokering of a mortgage. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for collecting information about entities involved in a set of mortgage loan activities and for collecting a training set of interactions between entities for a set of mortgage loan transactions; (b) an artificial intelligence system that is trained on the training set of interactions to classify the entities involved in the set of mortgage loans; and (c) a robotic process automation system that is trained on at least one of the set of mortgage loan activities and the set of mortgage loan interactions to broker a mortgage loan.
[0649] In embodiments at least one of the set of mortgage loan activities and the set of mortgage loan interactions includes activities among marketing activity, identification of a set of prospective borrowers, identification of property, identification of collateral, qualification of borrower, title search, title verification, property assessment, property inspection, property valuation, income verification, borrower demographic analysis, identification of capital providers, determination of available interest rates, determination of available payment terms and conditions, analysis of existing mortgage, comparative analysis of existing and new mortgage terms, completion of application workflow, population of fields of application, preparation of mortgage agreement, completion of schedule to mortgage agreement, negotiation of mortgage terms and conditions with capital provider, negotiation of mortgage terms and conditions with borrower, transfer of title, placement of lien and closing of mortgage agreement.
[0650] In embodiments the set of data collection and monitoring services includes services selected from among a set of Internet of Things systems that monitor the entities, a set of cameras that monitor the entities, a set of software services that pull information related to the entities from publicly available information sites, a set of mobile devices that report on information related to the entities, a set of wearable devices worn by human entities, a set of user interfaces by which entities provide information about the entities and a set of crowdsourcing services configured to solicit and report information related to the entities.
[0651] In embodiments the artificial intelligence system uses a model that processes attributes of entities involved in the set of mortgage loans, wherein the attributes are selected from properties that are subject to mortgages, assets used for collateral, identity of a party, interest rate, payment balance, payment terms, payment schedule, type of mortgage, type of property, financial condition of party, payment status, condition of property, and value of property.
[0652] In embodiments managing a mortgage loan includes managing at least one of a property that is subject to a mortgage, identification of candidate mortgages from a set of borrower situations, preparation of a mortgage offer, preparation of content communicating a mortgage offer, scheduling a mortgage offer, communicating a mortgage offer, negotiating a modification of a mortgage offer, preparing a mortgage agreement, executing a mortgage agreement, modifying collateral for a set of mortgage loans, handing transfer of a lien, handling an application workflow, managing an inspection, managing an assessment of a set of assets to be subject to a mortgage, setting an interest rate, deferring a payment requirement, setting a payment schedule, and closing a mortgage agreement. In embodiments the entities are a set of parties to a loan transaction. In embodiments the set of parties is selected from among a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, and an accountant.
[0653] In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0654] In embodiments the robotic process automation is trained on a set of interactions of parties with a set of user interfaces involved in a set of mortgage-related activities. In embodiments upon completion of negotiation a smart contract for a mortgage loan is automatically configured by a set of smart contract services based on the outcome of the negotiation. In embodiments at least one of an outcome and a negotiating event of the negotiation is recorded in a distributed ledger associated with the loan. In embodiments the artificial intelligence system includes at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0655] Referring to Fig. 15, in embodiments a lending platform is provided having a crowdsourcing and automated classification system for validating condition of an issuer for a bond. The RPA system 154 may provide automation for one or more aspects of a bond management solution 234 that enables automated bond management and/or provides a recommendation or plan for a bond management activity relevant to a bond transaction, such as for municipal bonds, corporate bonds, government bonds, or other bonds that may be backed by assets, collateral, or commitments of a bond issuer. The bond management solution 234 and/or RPA system 154 for bond management may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a bond management action or a management process for a bond transaction, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others, as well as of interest rates, available lenders, available terms and the like). For example, a user of the bond management solution 234 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the bond management solution 234 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a bond management action or plan for management a set of bonds of a given type or types based on one or more events, conditions, states, actions, or the like, where the bond management plan may be based on various factors, such as the interest rates available from various primary and secondary lenders or issuers, permitted attributes of issuers and buyers (e.g., based on income, wealth, location, or the like) prevailing interest rates in a platform marketplace or external marketplace, the status of the issuers of a set of bonds, the status or other attributes of collateral 102 or assets 218, risk factors of the issuer, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 available to secure or back a set of bonds, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences), and many others. Bond management may include management with respect to terms and conditions of sets of bonds, selection of appropriate bonds, communications to encourage transactions, and the like. In embodiments the bond management solution 234 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended bond management plan, which may specify a series of actions required to accomplish a recommended or desired outcome of bond management (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the bond management plan. Bond management plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other issuers, property values, attributes of issuers, values of collateral or assets, and the like) as well as regulatory and/or compliance factors. Bond management plans may be generated and/or executed for creation of new bonds, for secondary loans or transactions to back bonds, for modifications of existing bonds, for situations involving market changes (e.g., changes in prevailing interest rates or property values) and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of bond management activities by experts and/or on outcomes of bond management actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a bond management plan.
[0656] In embodiments, provided herein is a platform, consisting of various services, components, modules, programs, systems, devices, algorithms, and other elements, for monitoring condition of an issuer for a bond. In embodiments, the platform or system includes (a) a set of crowdsourcing systems 520 for collecting information about a set of entities involved in a set of bond transactions; and (b) a condition classifying system having a model and a set of artificial intelligence services for classifying the condition of the set of issuers using information from the set of crowdsourcing services, wherein the model is trained using a training data set of outcomes related to the issuers. [0657] In embodiments the set of entities includes entities among a set of issuers, a set of bonds, a set of parties, and a set of assets.
[0658] In embodiments a set of issuers includes at least one of a municipality, a corporation, a contractor, a government entity, a non-governmental entity, and a non-profit entity.
[0659] In embodiments the set of bonds includes at least one of a municipal bond, a government bond, a treasury bond, an asset-backed bond, and a corporate bond.
[0660] In embodiments the condition classified by the condition classifying system is among a default condition, a foreclosure condition, a condition indicating violation of a covenant, a financial risk condition, a behavioral risk condition, a policy risk condition, a financial health condition, a physical defect condition, a physical health condition, an entity risk condition and an entity health condition.
[0661] In embodiments the set of crowdsourcing services enables a user interface by which a user may configure a crowdsourcing request for information relevant to the condition about the set of issuers.
[0662] In embodiments the platform or system may further include a set of configurable data collection and monitoring services for monitoring the issuers that includes at least one of a set of Internet of Things devices, a set of environmental condition sensors, a set of social network analytic services and a set of algorithms for querying network domains.
[0663] In embodiments the set of configurable data collection and monitoring services monitors an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.
[0664] In embodiments the set of bonds is backed by a set of assets.
[0665] In embodiments the set of assets includes assets among municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0666] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of the assets and undertakes an action related to a debt transaction to which the asset is related.
[0667] In embodiments the action is selected from among offering a debt transaction, underwriting a debt transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating debt, and consolidating debt.
[0668] In embodiments the artificial intelligence services include at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0669] In embodiments the platform or system may further include an automated bond management system that manages an action related to the bond, wherein the automated bond management system is trained on a training set of bond management activities.
[0670] In embodiments the automated bond management system is trained on a set of interactions of parties with a set of user interfaces involved in a set of bond transaction activities. [0671] In embodiments the set of bond transaction activities includes activities among offering a debt transaction, underwriting a debt transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating debt, and consolidating debt.
[0672] In embodiments the platform or system may further include a market value data collection service that monitors and reports on marketplace information relevant to the value of at least one of the issuer and a set of assets.
[0673] In embodiments reporting is on a set of assets that includes at least one of a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0674] In embodiments the market value data collection service monitors pricing or financial data for items that are similar to the assets in at least one public marketplace.
[0675] In embodiments a set of similar items for valuing the assets is constructed using a similarity clustering algorithm based on the attributes of the assets.
[0676] In embodiments the attributes are selected from among a category of the assets, asset age, asset condition, asset history, asset storage, and geolocation of assets.
[0677] In embodiments the platform or system may further include a set of smart contract services for managing a smart contract for the bond transaction.
[0678] In embodiments the smart contract services set terms and conditions for the bond.
[0679] In embodiments the set of terms and conditions for the debt transaction that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of assets that back the bond, a specification of substitutability of assets, a party, an issuer, a purchaser, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0680] In embodiments the lending platform is provided having a social network monitoring system with artificial intelligence for classifying a condition about a bond. [0681] In embodiments, provided herein is a platform, consisting of various services, components, modules, programs, systems, devices, algorithms, and other elements, for monitoring condition of an issuer for a bond. In embodiments, the platform or system includes (a) a set of social network analytics applications 204 for collecting information about a set of entities involved in a set of bond transactions; and (b) a condition classifying system having a model and a set of artificial intelligence services for classifying the condition of the set of issuers based on information from the set of social network monitoring and analytic services, wherein the model is trained using a training data set of outcomes related to the issuers.
[0682] In embodiments the set of entities includes entities among a set of issuers, a set of bonds, a set of parties, and a set of assets.
[0683] In embodiments a set of issuers includes at least one of a municipality, a corporation, a contractor, a government entity, a non-governmental entity, and a non-profit entity.
[0684] In embodiments the set of bonds includes at least one of a municipal bond, a government bond, a treasury bond, an asset-backed bond, and a corporate bond.
[0685] In embodiments the condition classified by the condition classifying system is among a default condition, a foreclosure condition, a condition indicating violation of a covenant, a financial risk condition, a behavioral risk condition, a policy risk condition, a financial health condition, a physical defect condition, a physical health condition, an entity risk condition and an entity health condition.
[0686] In embodiments the set of social network monitoring and analytic services enables a user interface by which a user may configure a query for information about the set of entities.
[0687] In embodiments the platform or system may further include a set of data collection and monitoring services for monitoring the entities that includes at least one of a set of Internet of Things devices, a set of environmental condition sensors, a set of crowdsourcing services, and a set of algorithms for querying network domains.
[0688] In embodiments the set of data collection and monitoring services monitors an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.
[0689] In embodiments the set of bonds is backed by a set of assets. In embodiments the set of assets includes assets among municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0690] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of the assets and undertakes an action related to a bond transaction to which the asset is related.
[0691] In embodiments the action is selected from among offering a bond transaction, underwriting a bond transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating bonds, and consolidating bonds.
[0692] In embodiments the artificial intelligence services include at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0693] In embodiments the platform or system may further include an automated bond management system that manages an action related to the bond, wherein the automated bond management system is trained on a training set of bond management activities.
[0694] In embodiments the automated bond management system is trained on a set of interactions of parties with a set of user interfaces involved in a set of bond transaction activities.
[0695] In embodiments the set of bond transaction activities includes activities among offering a bond transaction, underwriting a bond transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating bonds, and consolidating bonds.
[0696] In embodiments the platform or system may further include a market value data collection service that monitors and reports on marketplace information relevant to the value of at least one of the issuer, a set of bonds, and a set of assets.
[0697] In embodiments reporting is on a set of assets that includes at least one of a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0698] In embodiments the market value data collection service monitors pricing or financial data for items that are similar to the assets in at least one public marketplace.
[0699] In embodiments a set of similar items for valuing the assets is constructed using a similarity clustering algorithm based on the attributes of the assets.
[0700] In embodiments the attributes are selected from among a category of the assets, asset age, asset condition, asset history, asset storage, and geolocation of assets.
[0701] In embodiments the platform or system may further include a set of smart contract services for managing a smart contract for the bond transaction.
[0702] In embodiments the smart contract services set terms and conditions for the bond.
[0703] In embodiments the set of terms and conditions for the debt transaction that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of assets that back the bond, a specification of substitutability of assets, a party, an issuer, a purchaser, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0704] In embodiments a lending platform is provided having an Internet of Things data collection and monitoring system with artificial intelligence for classifying a condition about a bond.
[0705] In embodiments, provided herein is a platform, consisting of various services, components, modules, programs, systems, devices, algorithms, and other elements, for monitoring condition of an issuer for a bond. In embodiments, the platform or system includes (a) a set of Internet of Things data collection and monitoring services for collecting information about a set of entities involved in a set of bond transactions; and (b) a condition classifying system having a model and a set of artificial intelligence services for classifying the condition of the set of issuers based on information from IoT data collection services 208, wherein the model is trained using a training data set of outcomes related to the issuers.
[0706] In embodiments the set of entities includes entities among a set of issuers, a set of bonds, a set of parties, and a set of assets.
[0707] In embodiments a set of issuers includes at least one of a municipality, a corporation, a contractor, a government entity, a non-governmental entity, and a non-profit entity. [0708] In embodiments the set of bonds includes at least one of a municipal bond, a government bond, a treasury bond, an asset-backed bond, and a corporate bond.
[0709] In embodiments the condition classified by the condition classifying system is among a default condition, a foreclosure condition, a condition indicating violation of a covenant, a financial risk condition, a behavioral risk condition, a policy risk condition, a financial health condition, a physical defect condition, a physical health condition, an entity risk condition and an entity health condition.
[0710] In embodiments the set of Internet of Things data collection and monitoring services enables a user interface by which a user may configure a query for information about the set of entities.
[0711] In embodiments the platform or system may further include a set of configurable data collection and monitoring services for monitoring the entities that includes at least one of a set of social network analytic services, a set of environmental condition sensors, a set of crowdsourcing services, and a set of algorithms for querying network domains.
[0712] In embodiments the set of configurable data collection and monitoring services monitors an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.
[0713] In embodiments the set of bonds is backed by a set of assets.
[0714] In embodiments the set of assets includes assets among municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0715] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of the assets and undertakes an action related to a bond transaction to which the asset is related.
[0716] In embodiments the action is selected from among offering a bond transaction, underwriting a bond transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating bonds, and consolidating bonds.
[0717] In embodiments the artificial intelligence services include at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0718] In embodiments the platform or system may further include an automated bond management system that manages an action related to the bond, wherein the automated bond management system is trained on a training set of bond management activities.
[0719] In embodiments the automated bond management system is trained on a set of interactions of parties with a set of user interfaces involved in a set of bond transaction activities.
[0720] In embodiments the set of bond transaction activities includes activities among offering a bond transaction, underwriting a bond transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating bonds, and consolidating bonds.
[0721] In embodiments the platform or system may further include a market value data collection service that monitors and reports on marketplace information relevant to the value of at least one of the issuer, a set of bonds, and a set of assets.
[0722] In embodiments reporting is on a set of assets that includes at least one of a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0723] In embodiments the market value data collection service monitors pricing or financial data for items that are similar to the assets in at least one public marketplace.
[0724] In embodiments a set of similar items for valuing the assets is constructed using a similarity clustering algorithm based on the attributes of the assets.
[0725] In embodiments the attributes are selected from among a category of the assets, asset age, asset condition, asset history, asset storage, and geolocation of assets. [0726] In embodiments the platform or system may further include a set of smart contract services for managing a smart contract for the bond transaction.
[0727] In embodiments the smart contract services set terms and conditions for the bond.
[0728] In embodiments the set of terms and conditions for the debt transaction that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of assets that back the bond, a specification of substitutability of assets, a party, an issuer, a purchaser, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0729] In embodiments, provided herein is a platform, consisting of various services, components, modules, programs, systems, devices, algorithms, and other elements, for monitoring condition of an entity and managing debt related to the entity. In embodiments, the platform or system includes (a) a set of data collection and monitoring services for collecting information about entities involved in a set of debt transactions; (b) a condition classifying system having a model and a set of artificial intelligence services for classifying the condition of the set of entities, wherein the model is trained using a training data set of outcomes related to the entities; and [0730] (c) an automated debt management system that manages an action related to the debt, wherein the automated debt management system is trained on a training set of debt management activities.
[0731] In embodiments the data collection and monitoring services includes at least one of a set of Internet of Things devices, a set of environmental condition sensors, a set of crowdsourcing services, a set of social network analytic services and a set of algorithms for querying network domains.
[0732] In embodiments the set of data collection and monitoring services monitors an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.
[0733] In embodiments the debt transaction is of a type selected from among an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, and a subsidized loan.
[0734] In embodiments the entities involved in the set of debt transactions include a set of parties and a set of assets.
[0735] In embodiments the set of assets includes assets among municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0736] In embodiments the platform or system may further include a set of sensors positioned on at least one of the assets, on a container for the asset and on a package for the asset, the set of sensors configured to associate sensor information sensed by the set of sensors with a unique identifier for the asset and a set of blockchain services for taking information from the data collection and monitoring services and the set of sensors and storing the information in a blockchain, wherein access to the blockchain is provided via a secure access control interface for a party for a debt transaction involving the asset.
[0737] In embodiments the set of sensors is selected from the group consisting of image, temperature, pressure, humidity, velocity, acceleration, rotational, torque, weight, chemical, magnetic field, electrical field, and position sensors.
[0738] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of the assets and undertakes an action related to a debt transaction to which the asset is related.
[0739] In embodiments the action is selected from among offering a debt transaction, underwriting a debt transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating debt, and consolidating debt.
[0740] In embodiments the artificial intelligence services include at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0741] In embodiments the automated debt management system is trained on a set of interactions of parties with a set of user interfaces involved in a set of debt transaction activities.
[0742] In embodiments the set of debt transaction activities includes activities among offering a debt transaction, underwriting a debt transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating debt, and consolidating debt.
[0743] In embodiments the platform or system may further include a market value data collection service that monitors and reports on marketplace information relevant to the value of a set of assets.
[0744] In embodiments the set of assets includes assets among municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0745] In embodiments the market value data collection service monitors pricing or financial data for items that are similar to the assets in at least one public marketplace.
[0746] In embodiments a set of similar items for valuing the assets is constructed using a similarity clustering algorithm based on the attributes of the assets.
[0747] In embodiments the attributes are selected from among a category of the assets, asset age, asset condition, asset history, asset storage, and geolocation of assets.
[0748] In embodiments the platform or system may further include a set of smart contract services for managing a smart contract for the debt transaction.
[0749] In embodiments the smart contract services set terms and conditions for the transaction. [0750] In embodiments the set of terms and conditions for the debt transaction that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0751] Referring to Fig. 16, in embodiments a lending platform is provided having a system that varies the terms and conditions of loan based on a parameter monitored by the IoT. The loan may be a subsidized loan. The RPA system 154 may provide automation for one or more aspects of a loan management solution 248 that enables automated loan management and/or provides a recommendation or plan for a loan management activity relevant to a loan transaction, such as for personal loans, corporate loans, subsidized loans, student loans, or other loans, including ones that may be backed by assets, collateral, or commitments of a borrower. The loan management solution 248 and/or RPA system 154 for loan management may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a loan management action or a management process for a loan transaction, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others, as well as of interest rates, available lenders, available terms and the like). For example, a user of the loan management solution 248 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the loan management solution 248 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a loan management action or plan for management a set of loans of a given type or types based on one or more events, conditions, states, actions, or the like, where the loan management plan may be based on various factors, such as the interest rates available from various primary and secondary lenders or issuers, permitted attributes of borrowers (e.g., based on income, wealth, location, or the like) prevailing interest rates in a platform marketplace or external marketplace, the status of the parties of a set of loans, the status or other attributes of collateral 102 or assets 218, risk factors of the borrower, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 available to secure or back a set of loans, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences, payment preferences, or communication preferences), and many others. Loan management may include management with respect to terms and conditions of sets of loans, selection of appropriate loans, communications to encourage transactions, and the like. In embodiments the loan management solution 248 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended loan management plan, which may specify a series of actions required to accomplish a recommended or desired outcome of loan management (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the loan management plan. Loan management plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other issuers, property values, attributes of issuers, values of collateral or assets, and the like) as well as regulatory and/or compliance factors. Loan management plans may be generated and/or executed for creation of new loans, for secondary loans or transactions to back loans, for collection, for consolidation, for foreclosure, for situations of bankruptcy of insolvency, for modifications of existing loans, for situations involving market changes (e.g., changes in prevailing interest rates or property values) and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of loan management activities by experts and/or on outcomes of loan management actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a loan management plan.
[0752] In embodiments, provided herein is a system for automating handling of a subsidized loan. In embodiments, the platform or system includes (a) a set of Internet of Things data collection and monitoring services for collecting information about a set of entities involved in a set of subsidized loan transactions; (b) a condition classifying system having a model and a set of artificial intelligence services for classifying a set of parameters of the set of subsidized loans involved in the transactions based on information from the set of IoT data collection services 208, wherein the model is trained using a training data set of outcomes related to subsidized loans; and (c) a set of smart contract for automatically modifying the terms and conditions of a subsidized loan based on the classified set of parameters from the condition classifying system.
[0753] In embodiments the set of entities includes entities among a set of subsidized loans, a set of parties, a set of subsidies, a set of guarantors, a set of subsidizing parties, and a set of collateral. [0754] In embodiments a set of subsidizing parties includes at least one of a municipality, a corporation, a contractor, a government entity, a non-governmental entity, and a non-profit entity. [0755] In embodiments the set of subsidized loans includes at least one of a municipal subsidized loan, a government subsidized loan, a student loan, an asset-backed subsidized loan, and a corporate subsidized loan. [0756] In embodiments the condition classified by the condition classifying system is among a default condition, a foreclosure condition, a condition indicating violation of a covenant, a financial risk condition, a behavioral risk condition, a contractual performance condition, a policy risk condition, a financial health condition, a physical defect condition, a physical health condition, an entity risk condition and an entity health condition.
[0757] In embodiments the loan is a student loan and the condition classifying system classifies at least one of the progress of a student toward a degree, the participation of a student in a non profit activity, and the participation of the student in a public interest activity.
[0758] In embodiments the set of Internet of Things data collection and monitoring services enables a user interface by which a user may configure a query for information about the set of entities.
[0759] In embodiments the platform or system may further include a set of configurable data collection and monitoring services for monitoring the entities that includes at least one of a set of social network analytic services, a set of environmental condition sensors, a set of crowdsourcing services, and a set of algorithms for querying network domains.
[0760] In embodiments the set of configurable data collection and monitoring services monitors an environment selected from among a municipal environment, an educational environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.
[0761] In embodiments the set of subsidized loans is backed by a set of assets.
[0762] In embodiments the set of assets includes assets among municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0763] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of the assets and undertakes an action related to a subsidized loan transaction to which the asset is related. [0764] In embodiments the action is selected from among offering a subsidized loan transaction, underwriting a subsidized loan transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating subsidized loans, and consolidating subsidized loans.
[0765] In embodiments the artificial intelligence services include at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0766] In embodiments the platform or system may further include an automated subsidized loan management system that manages an action related to the subsidized loan, wherein the automated subsidized loan management system is trained on a training set of subsidized loan management activities.
[0767] In embodiments the automated subsidized loan management system is trained on a set of interactions of parties with a set of user interfaces involved in a set of subsidized loan transaction activities.
[0768] In embodiments the set of subsidized loan transaction activities includes activities among offering a subsidized loan transaction, underwriting a subsidized loan transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating subsidized loans, and consolidating subsidized loans.
[0769] In embodiments the platform or system may further include a set of blockchain services for recording the modified set of terms and conditions for the set of subsidized loans in a distributed ledger.
[0770] In embodiments the platform or system may further include a market value data collection service that monitors and reports on marketplace information relevant to the value of at least one of the issuer, a set of subsidized loans, and a set of assets.
[0771] In embodiments reporting is on a set of assets that includes at least one of a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. [0772] In embodiments the market value data collection service monitors pricing or financial data for items that are similar to the assets in at least one public marketplace.
[0773] In embodiments a set of similar items for valuing the assets is constructed using a similarity clustering algorithm based on the attributes of the assets.
[0774] In embodiments the attributes are selected from among a category of the assets, asset age, asset condition, asset history, asset storage, and geolocation of assets.
[0775] In embodiments the platform or system may further include a set of smart contract services for managing a smart contract for the subsidized loan transaction.
[0776] In embodiments the smart contract services set terms and conditions for the subsidized loan.
[0777] In embodiments the set of terms and conditions for the debt transaction that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of assets that back the subsidized loan, a specification of substitutability of assets, a party, an issuer, a purchaser, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0778] In embodiments a lending platform is provided having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored in a social network.
[0779] In embodiments, provided herein is a system for automating handling of a subsidized loan. In embodiments, the platform or system includes (a) a set of social network analytic data collection and monitoring services for collecting information about a set of entities involved in a set of subsidized loan transactions; (b) a condition classifying system having a model and a set of artificial intelligence services for classifying a set of parameters of the set of subsidized loans involved in the transactions based on information from the set of social network analytics applications 204 which include data collection, monitoring, and analysis, wherein the model is trained using a training data set of outcomes related to subsidized loans; and (c) a set of smart contract for automatically modifying the terms and conditions of a subsidized loan based on the classified set of parameters from the condition classifying system.
[0780] In embodiments the set of entities includes entities among a set of subsidized loans, a set of parties, a set of subsidies, a set of guarantors, a set of subsidizing parties, and a set of collateral. [0781] In embodiments a set of subsidizing parties includes at least one of a municipality, a corporation, a contractor, a government entity, a non-governmental entity, and a non-profit entity. [0782] In embodiments the set of subsidized loans includes at least one of a municipal subsidized loan, a government subsidized loan, a student loan, an asset-backed subsidized loan, and a corporate subsidized loan.
[0783] In embodiments the condition classified by the condition classifying system is among a default condition, a foreclosure condition, a condition indicating violation of a covenant, a financial risk condition, a behavioral risk condition, a contractual performance condition, a policy risk condition, a financial health condition, a physical defect condition, a physical health condition, an entity risk condition and an entity health condition.
[0784] In embodiments the loan is a student loan and the condition classifying system classifies at least one of the progress of a student toward a degree, the participation of a student in a non profit activity, and the participation of the student in a public interest activity.
[0785] In embodiments the set of social network analytic data collection and monitoring services enables a user interface by which a user may configure a query for information about the set of entities and the social network analytic data collection and monitoring services initiates a set of algorithms that search and retrieve data from social networks based on the query.
[0786] In embodiments the platform or system may further include a set of configurable data collection and monitoring services for monitoring the entities that includes at least one of a set of Internet of Things services, a set of environmental condition sensors, a set of crowdsourcing services, and a set of algorithms for querying network domains.
[0787] In embodiments the set of configurable data collection and monitoring services monitors an environment selected from among a municipal environment, an educational environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.
[0788] In embodiments the set of subsidized loans is backed by a set of assets.
[0789] In embodiments the set of assets includes assets among municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0790] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of the assets and undertakes an action related to a subsidized loan transaction to which the asset is related. [0791] In embodiments the action is selected from among offering a subsidized loan transaction, underwriting a subsidized loan transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating subsidized loans, and consolidating subsidized loans.
[0792] In embodiments the artificial intelligence services include at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0793] In embodiments the platform or system may further include an automated subsidized loan management system that manages an action related to the subsidized loan, wherein the automated subsidized loan management system is trained on a training set of subsidized loan management activities.
[0794] In embodiments the automated subsidized loan management system is trained on a set of interactions of parties with a set of user interfaces involved in a set of subsidized loan transaction activities.
[0795] In embodiments the set of subsidized loan transaction activities includes activities among offering a subsidized loan transaction, underwriting a subsidized loan transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating subsidized loans, and consolidating subsidized loans.
[0796] In embodiments the platform or system may further include a set of blockchain services for recording the modified set of terms and conditions for the set of subsidized loans in a distributed ledger.
[0797] In embodiments the platform or system may further include a market value data collection service that monitors and reports on marketplace information relevant to the value of at least one of a party, a set of subsidized loans, and a set of assets.
[0798] In embodiments reporting is on a set of assets that includes at least one of a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0799] In embodiments the market value data collection service monitors pricing or financial data for items that are similar to the assets in at least one public marketplace.
[0800] In embodiments a set of similar items for valuing the assets is constructed using a similarity clustering algorithm based on the attributes of the assets.
[0801] In embodiments the attributes are selected from among a category of the assets, asset age, asset condition, asset history, asset storage, and geolocation of assets.
[0802] In embodiments the platform or system may further include a set of smart contract services for managing a smart contract for the subsidized loan transaction.
[0803] In embodiments the smart contract services set terms and conditions for the subsidized loan.
[0804] In embodiments the set of terms and conditions for the debt transaction that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of assets that back the subsidized loan, a specification of substitutability of assets, a party, an issuer, a purchaser, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0805] In embodiments a lending platform is provided having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored by crowdsourcing.
[0806] In embodiments, provided herein is a system for automating handling of a subsidized loan. In embodiments, the platform or system includes (a) a set of crowdsourcing systems 520 for collecting information about a set of entities involved in a set of subsidized loan transactions; (b) a condition classifying system having a model and a set of artificial intelligence services for classifying a set of parameters of the set of subsidized loans involved in the transactions based on information from the set of crowdsourcing services, wherein the model is trained using a training data set of outcomes related to subsidized loans; and (c) a set of smart contract for automatically modifying the terms and conditions of a subsidized loan based on the classified set of parameters from the condition classifying system.
[0807] In embodiments the set of entities includes entities among a set of subsidized loans, a set of parties, a set of subsidies, a set of guarantors, a set of subsidizing parties, and a set of collateral. [0808] In embodiments a set of subsidizing parties includes at least one of a municipality, a corporation, a contractor, a government entity, a non-governmental entity, and a non-profit entity. [0809] In embodiments the set of subsidized loans includes at least one of a municipal subsidized loan, a government subsidized loan, a student loan, an asset-backed subsidized loan, and a corporate subsidized loan.
[0810] In embodiments the condition classified by the condition classifying system is among a default condition, a foreclosure condition, a condition indicating violation of a covenant, a financial risk condition, a behavioral risk condition, a contractual performance condition, a policy risk condition, a financial health condition, a physical defect condition, a physical health condition, an entity risk condition and an entity health condition.
[0811] In embodiments the loan is a student loan and the condition classifying system classifies at least one of the progress of a student toward a degree, the participation of a student in a non profit activity, and the participation of the student in a public interest activity.
[0812] In embodiments the set of crowdsourcing services enables a user interface by which a user may configure a query for information about the set of entities and the set of crowdsourcing services automatically configures initiates a crowdsourcing request based on the query.
[0813] In embodiments the platform or system may further include a set of configurable data collection and monitoring services for monitoring the entities that includes at least one of a set of Internet of Things services, a set of environmental condition sensors, a set of social network analytic services, and a set of algorithms for querying network domains.
[0814] In embodiments the set of configurable data collection and monitoring services monitors an environment selected from among a municipal environment, an educational environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle.
[0815] In embodiments the set of subsidized loans is backed by a set of assets.
[0816] In embodiments the set of assets includes assets among municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. [0817] In embodiments the platform or system may further include an automated agent that processes events relevant to at least one of the value, the condition and the ownership of the assets and undertakes an action related to a subsidized loan transaction to which the asset is related. [0818] In embodiments the action is selected from among offering a subsidized loan transaction, underwriting a subsidized loan transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating subsidized loans, and consolidating subsidized loans.
[0819] In embodiments the artificial intelligence services include at least one of a machine learning system, a model-based system, a rule-based system, a deep learning system, a hybrid system, a neural network, a convolutional neural network, a feed forward neural network, a feedback neural network, a self-organizing map, a fuzzy logic system, a random walk system, a random forest system, a probabilistic system, a Bayesian system, and a simulation system.
[0820] In embodiments the platform or system may further include an automated subsidized loan management system that manages an action related to the subsidized loan, wherein the automated subsidized loan management system is trained on a training set of subsidized loan management activities.
[0821] In embodiments the automated subsidized loan management system is trained on a set of interactions of parties with a set of user interfaces involved in a set of subsidized loan transaction activities.
[0822] In embodiments the set of subsidized loan transaction activities includes activities among offering a subsidized loan transaction, underwriting a subsidized loan transaction, setting an interest rate, deferring a payment requirement, modifying an interest rate, validating title, managing inspection, recording a change in title, assessing the value of an asset, calling a loan, closing a transaction, setting terms and conditions for a transaction, providing notices required to be provided, foreclosing on a set of assets, modifying terms and conditions, setting a rating for an entity, syndicating subsidized loans, and consolidating subsidized loans.
[0823] In embodiments the platform or system may further include a set of blockchain services for recording the modified set of terms and conditions for the set of subsidized loans in a distributed ledger.
[0824] In embodiments the platform or system may further include a market value data collection service that monitors and reports on marketplace information relevant to the value of at least one of a party, a set of subsidized loans, and a set of assets. [0825] In embodiments reporting is on a set of assets that includes at least one of a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property.
[0826] In embodiments the market value data collection service monitors pricing or financial data for items that are similar to the assets in at least one public marketplace.
[0827] In embodiments a set of similar items for valuing the assets is constructed using a similarity clustering algorithm based on the attributes of the assets.
[0828] In embodiments the attributes are selected from among a category of the assets, asset age, asset condition, asset history, asset storage, and geolocation of assets.
[0829] In embodiments the platform or system may further include a set of smart contract services for managing a smart contract for the subsidized loan transaction.
[0830] In embodiments the smart contract services set terms and conditions for the subsidized loan.
[0831] In embodiments the set of terms and conditions for the debt transaction that are specified and managed by the set of smart contract services is selected from among a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of assets that back the subsidized loan, a specification of substitutability of assets, a party, an issuer, a purchaser, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.
[0832] Referring to Fig. 17, in embodiments a lending platform is provided having an automated blockchain custody service and solution for managing a set of custodial assets. The RPA system 154 may provide automation for one or more aspects of a custodial solution 1802 that enables automated custodial management and/or provides a recommendation or plan for a custodial activity relevant to a set of assets, such as ones involved in or backing a lending transaction or ones for which clients seek custodial for security or administrative purposes, such as for assets of any of the types described herein, including cryptocurrencies and other currencies, stock certificates and other evidence of ownership, securities, and many others. The custodial solution 1802 and/or RPA system 154 for handling custodial activity may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a custodial action or a management process for trust or custody of a set of assets 218, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others, and the like). For example, a user of the custodial solution 1802 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the custodial solution 1802 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a custodial action or plan for management a set of assets of a given type or types based on one or more events, conditions, states, actions, status or the like, where the custodial plan may be based on various factors, such as the storage options available, the basis for retrieval of assets, the basis for transfer of ownership of assets, and the like, condition of assets 218 for which custodial services will be required, behaviors of parties (such as behaviors indicating preferences), and many others. Custodial services may include management with respect to terms and conditions of sets of assets, selection of appropriate terms and conditions for trust and custody 150, selection of parameters for transfer of ownership, selection and provision of storage, selection and provision of secure infrastructure for data storage, and others. In embodiments the custodial solution 1802 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended custodial plan, which may specify a series of actions required to accomplish a recommended or desired outcome of custodial services (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the custodial plan. Custodial plans may be determined and executed based at least one part on market factors (such as competing terms and conditions offered by other custodians, property values, attributes of clients, values of collateral or assets, costs of physical storage, costs of data storage, and the like) as well as regulatory and/or compliance factors. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of custodial activities by experts and/or on outcomes of custodial actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a custodial plan. In embodiments, actions with respect to custody of a set of assets may be stored in a blockchain 136, such as in a distributed ledger. [0833] In embodiments, provided herein is a system for handling trust and custody 150 for a set of assets. The platform or system may include (a) a set of asset identification services for identifying a set of assets for which a financial institution is responsible for taking custody; (b) a set of identity management services by which the financial institution verifies identities and credentials of a set of entities entitled to take action with respect to the assets; and (c) set of blockchain services wherein at least one of the set of assets and identifying information for the set of assets is stored in a blockchain and wherein events related to the set of assets are recorded in a distributed ledger.
[0834] In embodiments the credentials include owner credentials, agent credentials, beneficiary credentials, trustee credentials, and custodian credentials.
[0835] In embodiments the events related to the set of assets include transfer of title, death of an owner, disability of an owner, bankruptcy of an owner, foreclosure, placement of a lien, use of assets as collateral, designation of a beneficiary, undertaking a loan against assets, providing a notice with respect to assets, inspection of assets, assessment of assets, reporting on assets for taxation purposes, allocation of ownership of assets, disposal of assets, sale of assets, purchase of assets, and designation of an ownership status.
[0836] In embodiments the platform or system further includes a set of data collection and monitoring services for monitoring at least one of the set of assets, a set of entities, and a set of events related to the assets.
[0837] In embodiments the set of entities includes at least one of an owner, a beneficiary, an agent, a trustee and a custodian.
[0838] In embodiments the platform or system further includes a set of smart contract services for managing the custody of the set of assets, wherein at least one event related to the set of assets is managed automatically by the smart contract based on a set of terms and conditions embodied in the smart contract and based on information collected by the set of data collection and monitoring services.
[0839] In embodiments the events related to the set of assets include transfer of title, death of an owner, disability of an owner, bankruptcy of an owner, foreclosure, placement of a lien, use of assets as collateral, designation of a beneficiary, undertaking a loan against assets, providing a notice with respect to assets, inspection of assets, assessment of assets, reporting on assets for taxation purposes, allocation of ownership of assets, disposal of assets, sale of assets, purchase of assets, and designation of an ownership status.
[0840] Referring to Fig. 18, in embodiments a lending platform is provided having an underwriting system for a loan with a set of data- integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions. The RPA system 154 may provide automation for one or more aspects of an underwriting solution 122 that enables automated underwriting and/or provides a recommendation or plan for an underwriting activity relevant to a loan transaction, such as for personal loans, corporate loans, subsidized loans, student loans, or other loans, including ones that may be backed by assets, collateral, or commitments of a borrower. The underwriting solution 122 and/or RPA system 154 for underwriting may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a underwriting action or a management process for a loan transaction, such as based on a set of conditions, which may include smart contract terms and conditions, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others, as well as of interest rates, available lenders, available terms and the like)). For example, a user of the underwriting solution 122 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the underwriting solution 122 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a underwriting action or plan for management a set of loans of a given type or types based on one or more events, conditions, states, actions, or the like, where the underwriting plan may be based on various factors, such as the interest rates available from various primary and secondary lenders or issuers, permitted attributes of borrowers (e.g., based on income, wealth, location, or the like), prevailing interest rates in a platform marketplace or external marketplace, the status of the parties of a set of loans, the status or other attributes of collateral 102 or assets 218, risk factors of the borrower, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 available to secure or back a set of loans, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences, payment preferences, or communication preferences), and many others. Underwriting may include management with respect to terms and conditions of sets of loans, selection of appropriate loans, communications relevant to underwriting processes, and the like. In embodiments the underwriting solution 122 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended underwriting plan, which may specify a series of actions required to accomplish a recommended or desired outcome of underwriting (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the underwriting plan. Underwriting plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other issuers, property values, borrower behavior, demographic trends, payment trends, attributes of issuers, values of collateral or assets, and the like) as well as regulatory and/or compliance factors. Underwriting plans may be generated and/or executed for new loans, for secondary loans or transactions to back loans, for collection, for consolidation, for foreclosure, for situations of bankruptcy of insolvency, for modifications of existing loans, for situations involving market changes (e.g., changes in prevailing interest rates or property values), for foreclosure activities, and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of underwriting activities by experts and/or on outcomes of underwriting actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of an underwriting plan. In embodiments events and outcomes of underwriting may be recorded in a blockchain 136, such as in a distributed ledger, for secure access and retrieval by authorized users. Adaptive intelligent systems 158 may, such as using various artificial intelligence 156 or expert systems disclosed herein and in the documented incorporated by reference herein, may improve or automated one or more aspects of underwriting, such as by training a model, a neural net, a deep learning system, or the like based on a training set of expert interactions and/or a training set of outcomes from underwriting activities.
[0841] Referring to Fig. 19, in embodiments a lending platform is provided having a loan marketing system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services and smart contract services for marketing a loan to a set of prospective parties. The lending enablement platform 100 may enable one or more aspects of a loan marketing solution 2002 that enables automated loan marketing and/or provides a recommendation or plan for a loan marketing activity relevant to a loan transaction, such as for personal loans, corporate loans, subsidized loans, student loans, or other loans, including ones that may be backed by assets, collateral, or commitments of a borrower. The loan marketing solution 2002 (which in embodiments may include or use an RPA system 154 configured for loan marketing) may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a loan marketing action or a management process for a loan transaction, such as based on a set of conditions, which may include smart contract terms and conditions (which may be configured, e.g., for a marketed set of loans), available capital for lending, regulatory factors, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others, as well as of interest rates, available lenders, available terms and the like)), and others. For example, a user of the loan marketing solution 2002 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the loan marketing solution 2002 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a loan marketing action or plan for management a set of loans of a given type or types based on one or more events, conditions, states, actions, or the like, where the loan marketing plan may be based on various factors, such as the interest rates available from various primary and secondary lenders or issuers, returns on the capital that is made available for loans, permitted or desired attributes of borrowers (e.g., based on income, wealth, location, or the like), prevailing interest rates in a platform marketplace or external marketplace, the status of the parties of a set of loans, the status or other attributes of collateral 102 or assets 218, risk factors of the borrower, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 available to secure or back a set of loans, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences, payment preferences, or communication preferences), and many others. Loan marketing may include management with respect to terms and conditions of sets of loans, selection of appropriate loans, communications relevant to loan marketing processes, and the like. In embodiments the loan marketing solution 2002 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended loan marketing plan, which may specify a series of actions required to accomplish a recommended or desired outcome of loan marketing (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the loan marketing plan. Loan marketing plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other issuers, property values, borrower behavior, demographic trends, payment trends, attributes of issuers, values of collateral or assets, and the like) as well as regulatory and/or compliance factors. Loan marketing plans may be generated and/or executed for new loans, for secondary loans or transactions to back loans, for collection, for consolidation, for foreclosure situations (e.g., as an alternative to foreclosure), for situations of bankruptcy of insolvency, for modifications of existing loans, for situations involving market changes (e.g., changes in prevailing interest rates, available capital, or property values), and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of loan marketing activities by experts and/or on outcomes of loan marketing actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a loan marketing plan. In embodiments events and outcomes of loan marketing may be recorded in a blockchain 136, such as in a distributed ledger, for secure access and retrieval by authorized users. Adaptive intelligent systems 158 may, such as using various artificial intelligence 156 or expert systems disclosed herein and in the documented incorporated by reference herein, may improve or automated one or more aspects of entity rating, such as by training a model, a neural net, a deep learning system, or the like based on a training set of expert interactions and/or a training set of outcomes from loan marketing activities.
[0842] Referring to Fig. 20, in embodiments a lending platform is provided having a rating system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for rating a set of loan-related entities. The lending enablement platform 100 may enable one or more aspects of an entity rating solution 206 that enables automated entity rating and/or provides a recommendation or plan for an entity rating activity relevant to a loan transaction, such as for personal loans, corporate loans, subsidized loans, student loans, or other loans, including ones that may be backed by assets, collateral, or commitments of a borrower. The entity rating solution 206 (which in embodiments may include or use an RPA system 154 configured for entity rating) may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of an entity rating action or a rating process for a loan transaction, such as based on a set of conditions, attributes, events, or the like, which may include attributes of entities 198 (such as value, quality, location, net worth, price, physical condition, health condition, security, safety, ownership and the like), smart contract terms and conditions (which may be configured or populated, e.g., based on ratings for a rated set of loans), regulatory factors, marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets 218, among others, as well as of interest rates, available lenders, available terms and the like)), and others. For example, a user of the entity rating solution 206 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the entity rating solution 206 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, an entity rating action or plan for rating a set of loans of a given type or types based on one or more events, attributes, parameters, characteristics, conditions, states, actions, or the like, where the entity rating plan may be based on various factors (e.g., based on income, wealth, location, or the like or parties 210, relative to others, or based on condition of collateral 102 or assets 218, or the like), prevailing conditions of a platform marketplace or external marketplace, the status of the parties of a set of loans, the status or other attributes of collateral 102 or assets 218, risk factors of the borrower, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 available to secure or back a set of loans, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences, payment preferences, or communication preferences), and many others. Entity rating may include management with respect to terms and conditions of sets of loans, selection of appropriate loans, communications relevant to entity rating processes, and the like. In embodiments the entity rating solution 206 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended entity rating plan, which may specify a series of actions required to accomplish a recommended or desired outcome of entity rating (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the entity rating plan. Entity rating plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other issuers, property values, borrower behavior, demographic trends, payment trends, attributes of issuers, values of collateral or assets, and the like) as well as regulatory and/or compliance factors. Entity rating plans may be generated and/or executed for new loans, for secondary loans or transactions to back loans, for collection, for consolidation, for foreclosure situations (e.g., as an alternative to foreclosure), for situations of bankruptcy of insolvency, for modifications of existing loans, for situations involving market changes (e.g., changes in prevailing interest rates, available capital, or property values), and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of entity rating activities by experts and/or on outcomes of entity rating actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of an entity rating plan. In embodiments events and outcomes of entity rating may be recorded in a blockchain 136, such as in a distributed ledger, for secure access and retrieval by authorized users. Adaptive intelligent systems 158 may, such as using various artificial intelligence 156 or expert systems disclosed herein and in the documented incorporated by reference herein, may improve or automated one or more aspects of entity rating, such as by training a model, a neural net, a deep learning system, or the like based on a training set of expert interactions and/or a training set of outcomes from entity rating activities.
[0843] Referring to Fig. 21, in embodiments a lending platform is provided having a regulatory and/or compliance solution 142 with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for automatically facilitating compliance with at least one of a law, a regulation and a policy that applies to a lending transaction. The lending enablement platform 100 may enable one or more aspects of a regulatory and compliance solution 142 that enables automated regulatory and compliance and/or provides a recommendation or plan for a regulatory and compliance activity relevant to a loan transaction, such as for personal loans, corporate loans, subsidized loans, student loans, or other loans, including ones that may be backed by assets, collateral, or commitments of a borrower. The regulatory and compliance solution 142 (which in embodiments may include or use an RPA system 154 configured for automating regulatory and compliance activities based on a training set of interactions by experts in regulatory and/or compliance activities) may include a set of interfaces, workflows, and models (which may include, use or be enabled by various adaptive intelligent systems 158) and other components that are configured to enable automation of one or more aspects of a regulatory and compliance action or a regulatory and/or compliance process for a loan transaction, such as based on a set of policies, regulations, laws, requirements, specifications, conditions, attributes, events, or the like, which may include attributes of or applicable to entities 198 involved in a lending transaction and/or the terms and conditions of loans (including smart contract terms and conditions (which may be configured or populated, e.g., based on terms and conditions that are permitted for a given set of loans)), as well as various marketplace conditions (of platform marketplaces and/or external marketplaces 188, conditions monitored by monitoring systems 164 and data collection systems 166, and the like (such as of entities 198, including without limitation parties 210, collateral 102 and assets LPX218, among others, as well as of interest rates, available lenders, available terms and the like)), and others. For example, a user of the regulatory and compliance solution 142 may create, configure (such as using one or more templates or libraries), modify, set or otherwise handle (such as in a user interface of the regulatory and/or compliance solution 142 and/or RPA system 154) various rules, thresholds, conditional procedures, workflows, model parameters, and the like that determine, or recommend, a regulatory and compliance action or plan for governing a set of loans of a given type or types based on one or more events, attributes, parameters, characteristics, conditions, states, actions, or the like, where the regulatory and compliance plan may be based on various factors (e.g., based on permitted interest rates, required notices (e.g., regarding annualized percentage rate reporting), permitted borrowers (e.g., students for federally subsidized student loans), permitted lenders, permitted issuers, income (e.g., for low-income loans), wealth (e.g., for loans that are permitted by policy to be provided only to adequately capitalized parties), location (e.g., for geographically governed lending programs, such as for municipal development), conditions of a platform marketplace or external marketplace (such as where loans are required to have interest rates that do not exceed a threshold that is calculated based on prevailing interest rates), the status of the parties of a set of loans, the status or other attributes of collateral 102 or assets 218, risk factors of the borrower, one or more guarantors, market risk factors and the like (including predicted risk based on one or more predictive models using artificial intelligence 156), status of debt, condition of collateral 102 or assets 218 available to secure or back a set of loans, the state of a business or business operation (e.g., receivables, payables, or the like), conditions of parties 210 (such as net worth, wealth, debt, location, and other conditions), behaviors of parties (such as behaviors indicating preferences, behaviors indicating debt preferences, payment preferences, or communication preferences), and many others. Regulatory and compliance may include governance with respect to terms and conditions of sets of loans, selection of appropriate loans, notices required to be provided, underwriting policies, communications relevant to regulatory and compliance processes, and the like. In embodiments the regulatory and compliance solution 142 may automatically recommend or set rules, thresholds, actions, parameters and the like (optionally by learning to do so based on a training set of outcomes over time), resulting in a recommended regulatory and compliance plan, which may specify a series of actions required to accomplish a recommended or desired outcome of regulatory and compliance (such as within a range of acceptable outcomes), which may be automated and may involve conditional execution of steps based on monitored conditions and/or smart contract terms, which may be created, configured, and/or accounted for by the regulatory and compliance plan. Regulatory and compliance plans may be determined and executed based at least one part on market factors (such as competing interest rates offered by other issuers, property values, borrower behavior, demographic trends, payment trends, attributes of issuers, values of collateral or assets, and the like) as well as regulatory and/or compliance factors. Regulatory and compliance plans may be generated and/or executed for new loans, for secondary loans or transactions to back loans, for collection, for consolidation, for foreclosure situations (e.g., as an alternative to foreclosure), for situations of bankruptcy of insolvency, for modifications of existing loans, for situations involving market changes (e.g., changes in prevailing interest rates, available capital, or property values), and others. In embodiments, adaptive intelligent systems 158, including artificial intelligence 156 may be trained on a training set of regulatory and compliance activities by experts and/or on outcomes of regulatory and compliance actions to generate a set of predictions, classifications, control instructions, plans, models, or the like for automated creation, management and/or execution of one or more aspects of a regulatory and compliance plan. In embodiments events and outcomes of regulatory and compliance may be recorded in a blockchain 136, such as in a distributed ledger, for secure access and retrieval by authorized users. Adaptive intelligent systems 158 may, such as using various artificial intelligence 156 or expert systems disclosed herein and in the documented incorporated by reference herein, may improve or automate one or more aspects of regulatory and compliance, such as by training a model, a neural net, a deep learning system, or the like based on a training set of expert interactions and/or a training set of outcomes from regulatory and compliance activities.
[0844] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction.
[0845] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a smart contract and distributed ledger platform for managing at least one of ownership of a set of collateral and a set of events related to a set of collateral.
[0846] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a smart contract system that automatically adjusts an interest rate for a loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analytic services and a set of data collection and monitoring services.
[0847] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a crowdsourcing system for obtaining information about at least one of a state of a set of collateral for a loan and a state of an entity relevant to a guarantee for a loan. [0848] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a smart contract that automatically adjusts an interest rate for a loan based on at least one of a regulatory factor and a market factor for a specific jurisdiction.
[0849] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a smart contract that automatically restructures debt based on a monitored condition.
[0850] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a social network monitoring system for validating the reliability of a guarantee for a loan.
[0851] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having an Internet of Things data collection and monitoring system for validating reliability of a guarantee for a loan.
[0852] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a robotic process automation system for negotiation of a set of terms and conditions for a loan.
[0853] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a robotic process automation system for loan collection.
[0854] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a robotic process automation system for consolidating a set of loans.
[0855] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a robotic process automation system for managing a factoring loan.
[0856] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a robotic process automation system for brokering a mortgage loan.
[0857] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a crowdsourcing and automated classification system for validating condition of an issuer for a bond.
[0858] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a social network monitoring system with artificial intelligence for classifying a condition about a bond.
[0859] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having an Internet of Things data collection and monitoring system with artificial intelligence for classifying a condition about a bond.
[0860] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored by the IoT.
[0861] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored in a social network. [0862] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored by crowdsourcing. [0863] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having an automated blockchain custody service for managing a set of custodial assets.
[0864] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having an underwriting system for a loan with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions.
[0865] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a loan marketing system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services and smart contract services for marketing a loan to a set of prospective parties.
[0866] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a rating system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for rating a set of loan-related entities.
[0867] In embodiments a lending platform is provided herein having a set of data-integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions and having a compliance system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for automatically facilitating compliance with at least one of a law, a regulation and a policy related to a lending transaction.
[0868] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a smart contract and distributed ledger platform for managing at least one of ownership of a set of collateral and a set of events related to a set of collateral.
[0869] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a smart contract system that automatically adjusts an interest rate for a loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analytic services and a set of data collection and monitoring services.
[0870] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a crowdsourcing system for obtaining information about at least one of a state of a set of collateral for a loan and a state of an entity relevant to a guarantee for a loan.
[0871] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a smart contract that automatically adjusts an interest rate for a loan based on at least one of a regulatory factor and a market factor for a specific jurisdiction. [0872] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a smart contract that automatically restructures debt based on a monitored condition.
[0873] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a social network monitoring system for validating the reliability of a guarantee for a loan.
[0874] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having an Internet of Things data collection and monitoring system for validating reliability of a guarantee for a loan.
[0875] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a robotic process automation system for negotiation of a set of terms and conditions for a loan.
[0876] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a robotic process automation system for loan collection. [0877] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a robotic process automation system for consolidating a set of loans.
[0878] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a robotic process automation system for managing a factoring loan.
[0879] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a robotic process automation system for brokering a mortgage loan.
[0880] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a crowdsourcing and automated classification system for validating condition of an issuer for a bond.
[0881] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a social network monitoring system with artificial intelligence for classifying a condition about a bond.
[0882] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having an Internet of Things data collection and monitoring system with artificial intelligence for classifying a condition about a bond.
[0883] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored by the IoT.
[0884] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored in a social network.
[0885] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a system that varies the terms and conditions of a subsidized loan based on a parameter monitored by crowdsourcing.
[0886] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having an automated blockchain custody service for managing a set of custodial assets.
[0887] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having an underwriting system for a loan with a set of data- integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions.
[0888] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a loan marketing system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services and smart contract services for marketing a loan to a set of prospective parties.
[0889] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a rating system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for rating a set of loan-related entities.
[0890] In embodiments a lending platform is provided herein having an Internet of Things and sensor platform for monitoring at least one of a set of assets and a set of collateral for a loan, a bond, or a debt transaction and having a compl