CN113888337A

CN113888337A - Capital settlement method, device, equipment and storage medium based on big data

Info

Publication number: CN113888337A
Application number: CN202111150358.9A
Authority: CN
Inventors: 马位涛
Original assignee: Ping An Puhui Enterprise Management Co Ltd
Current assignee: Ping An Puhui Enterprise Management Co Ltd
Priority date: 2021-09-29
Filing date: 2021-09-29
Publication date: 2022-01-04

Abstract

The embodiment of the application belongs to the field of artificial intelligence and big data, and relates to a fund settlement method based on big data, which comprises the steps of inputting the common guarantee transaction information into a preset algorithm, and outputting corresponding transaction data; the method comprises the steps of obtaining common guarantee contracts in a preset period in a timing mode, and generating a reference transaction detail list according to the common guarantee contracts; when the transaction data of the historical transaction detail table is matched with the transaction data of the reference transaction detail table, sending the historical transaction detail table to the target server; and performing online settlement according to the historical transaction detail table. The application also provides a device, computer equipment and a storage medium. In addition, the present application also relates to blockchain techniques, where common vouch-for transaction information, common vouch-for contracts, and transaction data may be stored in blockchains. The method and the device have the advantages that online settlement is carried out by triggering each party, manpower resource consumption is reduced, settlement is accurate, efficiency is improved, and business is expanded.

Description

Capital settlement method, device, equipment and storage medium based on big data

Technical Field

The present application relates to the field of artificial intelligence and big data technologies, and in particular, to a method and an apparatus for fund settlement based on big data, a computer device, and a storage medium.

Background

In the field of credit insurance, there is a scenario in which two insurers guarantee a loan together, called "co-insurance" mode. The insurance company A is used as a main underwriting party, the insurance company B entrusts the insurance company A to collect and pay for others, and the insurance company A charges the insurance client with the full premium or pays the full settlement claim to the paying party. At present, insurance companies in a 'common insurance mode' still adopt a traditional offline settlement mode, and have the problems of high cost and low efficiency due to the consumption of great human resources.

Disclosure of Invention

The embodiment of the application aims to provide a fund settlement method based on big data so as to solve the technical problems that an insurance company in a 'common insurance mode' still adopts a traditional offline settlement mode, needs to consume great human resources, and is high in cost and low in efficiency.

In order to solve the above technical problem, an embodiment of the present application provides a fund settlement method based on big data, which adopts the following technical solutions:

acquiring a transaction record sent by a client, and extracting common guarantee transaction information in the transaction record;

inputting the common guarantee transaction information to a preset algorithm for calculation to obtain corresponding transaction data;

updating the transaction data to a corresponding historical transaction list, and sending the transaction data to a target server;

the method comprises the steps of obtaining common guarantee contracts in a preset period in a timing mode, and generating a reference transaction detail list according to the common guarantee contracts;

comparing the historical transaction list with the reference transaction list;

when the transaction data of the historical transaction detail table is matched with the transaction data of the reference transaction detail table, sending the historical transaction detail table to the target server for retention;

and performing online settlement according to the historical transaction detail table.

In order to solve the above technical problem, an embodiment of the present application further provides a fund settlement apparatus based on big data, including:

the acquisition module is used for acquiring a transaction record sent by a client and extracting common guarantee transaction information in the transaction record;

the calculation module is used for inputting the common guarantee transaction information to a preset algorithm for calculation to obtain corresponding transaction data;

the updating module is used for updating the transaction data to a corresponding historical transaction list and sending the transaction data to a target server;

the configuration module is used for acquiring common guarantee contracts in a preset period at regular time and generating a reference transaction detail list according to the common guarantee contracts;

the comparison module is used for comparing the historical transaction list with the reference transaction list;

the output module is used for sending the historical transaction list to the target server for storage when the historical transaction list corresponds to the reference transaction list;

and the settlement module is used for performing online settlement according to the historical transaction detail table.

In order to solve the above technical problem, an embodiment of the present application further provides a computer device, including:

a memory having computer readable instructions stored therein and a processor that when executed implement the steps of the big data based funds settlement method as described above.

In order to solve the above technical problem, an embodiment of the present application further provides a computer-readable storage medium, including:

the computer readable storage medium has stored thereon computer readable instructions which, when executed by a processor, implement the steps of the big data based funds settlement method as described above.

Compared with the prior art, the embodiment of the application mainly has the following beneficial effects:

the common guarantee transaction information is extracted, the common guarantee transaction information is input into a preset algorithm, corresponding transaction data are output, the transaction data are synchronized to a target server and a historical transaction detail table, common guarantee contracts in a preset period are obtained regularly, a reference transaction detail table is generated according to each common guarantee contract, the historical transaction detail table and the reference transaction detail table are compared through a comparison algorithm, when the historical transaction detail table and the reference transaction detail table correspond to each other, the historical transaction detail table is sent to trigger the self or the target server to conduct online settlement, the total amount payable is paid, the sub-accounting or the claim paying of the policy is completed, and the beneficial effects of reducing human resource consumption, accurately settling, improving efficiency and expanding business are achieved.

Drawings

In order to more clearly illustrate the solution of the present application, the drawings needed for describing the embodiments of the present application will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can be obtained by those skilled in the art without inventive effort.

FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;

FIG. 2 is a flow diagram of one embodiment of a big-data based funds settlement method according to the present application;

FIG. 3 is a flowchart of one embodiment of step S203 in FIG. 2;

FIG. 4 is a flowchart of one embodiment of step S204 of FIG. 2;

FIG. 5 is a schematic block diagram of one embodiment of a big-data based funds settlement apparatus according to the present application;

FIG. 6 is a block diagram illustrating one embodiment of an update module shown in FIG. 5;

FIG. 7 is a schematic block diagram of one embodiment of the configuration module shown in FIG. 5;

FIG. 8 is a schematic block diagram of one embodiment of a computer device according to the present application.

Detailed Description

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "including" and "having," and any variations thereof, in the description and claims of this application and the description of the above figures are intended to cover non-exclusive inclusions. The terms "first," "second," and the like in the description and claims of this application or in the above-described drawings are used for distinguishing between different objects and not for describing a particular order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

As shown in fig. 1, the system architecture 100 may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The

terminal devices

101, 102, 103 may have various communication client applications installed thereon, such as a web browser application, a shopping application, a search application, an instant messaging tool, a mailbox client, social platform software, and the like.

The

terminal devices

101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, E-book readers, MP3 players (Moving Picture E big data based fund settlement per Group Audio Layer III, mpeg compression standard Audio Layer 3), MP4(Moving Picture E big data based fund settlement per Group Audio Layer IV, mpeg compression standard Audio Layer 4) players, laptop portable computers, desktop computers, and the like.

The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the

terminal devices

101, 102, 103.

The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), and a big data and artificial intelligence platform.

It should be noted that the fund settlement method based on big data provided in the embodiments of the present application is generally executed by a server/terminal device, and accordingly, a fund settlement apparatus based on big data is generally disposed in the server/terminal device.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

With continued reference to FIG. 2, a flow diagram of one embodiment of a method for big data based funds settlement in accordance with the present application is shown. The fund settlement method based on the big data comprises the following steps:

step S201, acquiring a transaction record sent by a client, and extracting common guarantee transaction information in the transaction record.

In this embodiment, the electronic device (e.g., the server/terminal device shown in fig. 1) on which the big data based fund settlement method operates may receive the vouch-for transaction information transmitted by the client through a wired connection or a wireless connection. It should be noted that the wireless connection means may include, but is not limited to, a 3G/4G connection, a WiFi connection, a bluetooth connection, a wimax capital settlement connection based on big data, a Zigbee connection, a uwb (ultra wideband) connection, and other wireless connection means now known or developed in the future.

Further, the electronic device refers specifically to a server or a terminal where the primary security organization is located. The client can be a bank, a system where the insurance user is located or a terminal device. The transaction record can be a transaction carried out by a premium deducted by the client or a paid claim payment, and the transaction record can be transmitted to the server or the terminal in real time or at regular time; the transaction record includes one or more of a customer name, a payment account number, a number of vouching contracts paid, and a total amount paid. And determining whether the transaction related to the transaction record is a common guarantee transaction according to the key words or key information in the transaction record, for example, extracting a guarantee contract number in the transaction record, comparing the guarantee contract number with a guarantee contract pre-stored in a server or a terminal, determining whether the guarantee contract is a cooperative guarantee contract, and further acquiring common guarantee transaction information in the transaction record.

As an optional implementation, the step of refining of step S201 includes:

receiving a transaction record sent by a client;

extracting the guarantee contract identification in the transaction record to be associated with the corresponding guarantee contract;

and when the guarantee contract is a common guarantee contract, acquiring the common guarantee transaction information corresponding to the transaction record.

The transaction record may contain a guaranty contract identification, such as a guaranty contract number. The electronic equipment can acquire the guarantee contract identification in a mode of extracting key words from the transaction record, associate the guarantee contract identification with the corresponding guarantee contract, determine whether the guarantee contract is a common guarantee contract or not according to the type of the guarantee contract, and acquire common guarantee transaction information corresponding to the transaction record if the guarantee contract is the common guarantee contract. It is understood that the mapping table between the guaranty contract id and the guaranty contract is pre-stored in the electronic device, or the electronic device may call the mapping table between the guaranty contract id and the guaranty contract in the server. The mapping relationship table may include relationships between the guaranty contract identification, the type of guaranty contract, the guaranty amount of the guaranty contract, the payment period of the guaranty contract, and the like.

Step S202, inputting the common guarantee transaction information to a preset algorithm for calculation to obtain corresponding transaction data.

The cooperative guaranty transaction information includes one or more of a transaction type (premium payment or premium claim), a total amount of the transaction, a distribution ratio between the primary and cooperative guaranty institutions, a policy period or a pay ratio, and the like. The preset algorithm is designed according to the convention rule of the common guarantee contract, variable parameters such as transaction types, total transaction amount, distribution proportion between the main guarantee mechanism and the cooperative guarantee mechanism, policy period or paying proportion and the like are written into the model to obtain the preset algorithm, and the preset algorithm is called when the preset algorithm is used. And the cooperative guarantee transaction data is used as input data and is calculated by a preset algorithm to obtain corresponding transaction data, wherein the transaction data can comprise one or more of total transaction amount, guarantee amount of the main guarantee mechanism and guarantee amount of the cooperative guarantee mechanism.

The preset algorithm has a calculation function and can calculate transaction data according to transaction types, total transaction amount, distribution proportion between the main insurance mechanism and the cooperative insurance mechanism, policy period or pay proportion and the like in the common insurance transaction information. For example, the calculation rule of the preset algorithm is as follows: the premium (pay-per-view) of the primary vouching authority is equal to the product of the total amount charged (paid) in the month and the allotment.

Step S203, updating the transaction data to a corresponding historical transaction list, and sending the transaction data to a target server.

In this embodiment, the electronic device updates the transaction data obtained by processing to a historical transaction list of the local server, where the historical transaction list corresponds to different time periods, for example, a historical transaction list is generated every month, and the transaction data obtained by performing a common guarantee transaction for the month is stored in the historical transaction list corresponding to the month; the historical transaction list may be an editable document, with transaction data added.

Compressing the transaction data into a file packet with a preset format and sending the file packet to a target server, wherein the target server is a server or a terminal where a cooperation guarantee mechanism is located in cooperation guarantee transaction; the cooperative guaranty organization decompresses the received file package, updates transaction data contained in the file package to a system where the cooperative guaranty organization is located, and records each common guaranty transaction for reconciliation.

When a common guarantee transaction is carried out, the transaction data is sent to a server or a terminal of the cooperative guarantee mechanism, and the records are carried out in multiple ways, so that the main guarantee mechanism can be effectively prevented from being forged in finance, and the beneficial effects of real bookkeeping and account checking are realized.

Step S204, regularly acquiring common guarantee contracts in a preset period, and generating a reference transaction detail list according to each common guarantee contract.

The timing may be monthly, e.g., No. 5 per month, or the first working day of each month, and may be custom set according to user needs. The preset period may be set according to the actual performance of the warranty agency, such as monthly, semi-annually, or the like; the common guarantee contract is a contract which is signed by two guarantee institutions and the same insurer together, and information such as benefit distribution proportion of the main guarantee institution and the cooperative guarantee institution and pay proportion during pay is specified in the contract. The common guarantee contract may be a contract newly signed in a preset period, or a payment period agreed by the contract, for example, after the user pays a premium for a certain amount every month after the user pays the premium for the first time, the payment period of the user may be included in the preset period. And obtaining the total transaction amount in a preset period according to each common guarantee contract, the respective guarantee amounts of the main guarantee institution and the cooperative guarantee institution, generating a reference transaction detail table by the total transaction amount, the respective guarantee amounts of the main guarantee institution and the cooperative guarantee contract identification according to the transaction time of the transaction data, and outputting the reference transaction detail table in a word or excel form.

Step S205, comparing the historical transaction statement with the reference transaction statement.

In this embodiment, the historical transaction detail table and the reference transaction detail table are compared one by one through a comparison algorithm, such as a Needleman-Wunsch comparison algorithm, and whether the transaction data obtained by each common guaranty contract in the reference transaction detail table in a preset period corresponds to each transaction record in the historical transaction detail table is determined. And identifying whether the transaction data in the reference transaction list and the historical transaction list correspond or not by using parameters such as the common guarantee contract identifier as a matching identifier.

As an alternative implementation, the step of refining of step S205 includes:

calling a comparison algorithm to traverse each transaction data in the reference transaction list;

and matching each transaction data with the historical transaction list.

The comparison algorithm can be a Needleman-Wunsch comparison algorithm or a match algorithm, each transaction data in the reference detailed tables is traversed, the transaction data in each history detailed table and the transaction data in the history transaction detailed tables are matched one by one, and after the matching is successful, the next transaction data in the reference detailed tables is skipped to, and the matching process is continued; and if the transaction data in the reference transaction detail list and all transaction data in the historical transaction detail list are failed to be paired, marking the transaction data, generating an error report record, writing the error report record into the running log, and jumping to the matching process of the next transaction data.

And step S206, when the transaction data of the historical transaction list is matched with the transaction data of the reference transaction list, sending the historical transaction list to the target server for retention.

When the reference transaction list is matched with the transaction data in the historical transaction list, the historical transaction list is packaged into a file package, the file package is sent to a target server in the form of the file package, so that the cooperation guarantee mechanism can keep the file package, and the internal reconciliation is further carried out; the main guarantee mechanism accurately obtains the settlement amount in a preset period through internal account checking so as to improve the efficiency.

It is emphasized that the transaction data and the historical transaction detail table may also be stored in a node of a blockchain in order to further ensure the privacy and security of the transaction data.

The block chain referred by the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

And step S207, performing online settlement according to the historical transaction list.

The bill detail list comprises the total amount due (paid) of the main bearing security mechanism and the total amount due (paid) of the cooperation security mechanism, and the online settlement is completed according to the total amount due (paid) and the bank card information, namely the main bearing security mechanism conducts the online transfer according to the total amount due (paid). It can be understood that when the payment for the guarantee needs to be paid to the cooperative guaranty organization after the historical transaction list is sent, the transfer instruction is triggered, and the transfer is carried out according to the settlement amount in the historical transaction list. Similarly, the target server generates a corresponding reference transaction detail table according to a common guarantee contract associated with the main insurance mechanism, when the historical transaction detail table of the main insurance mechanism is received, firstly, a comparison process is started, the reference transaction detail table obtained by self processing is compared with the historical transaction detail table received from the main insurance mechanism, when data are matched and the main insurance mechanism needs to pay for the claim protection, a transfer instruction is triggered, and transfer is carried out according to the settlement amount in the historical transaction detail table. It should be noted that, the execution subject is a local server, and the settlement is determined according to the size between the premium and the fee to be paid, and if the premium is greater than the fee to be paid, the local server performs the payment; if the premium is less than the reimbursement fee, the target server pays the premium.

As an optional implementation manner, after step S205, the method further includes:

updating the historical transaction statement according to the reference transaction statement when the transaction data of the historical transaction statement does not match the transaction data of the reference transaction statement;

and re-comparing the updated historical transaction list with the reference transaction list.

According to the comparison result, if the transaction data of the historical transaction list is not matched with the transaction data of the reference detailed transaction list, error marking is carried out in the operation log, errors are marked, such as omission, errors and the like, data of a client are called according to the common guarantee contract in the reference detailed transaction list, whether the transaction record corresponding to the common guarantee contract really exists is judged, if yes, the omitted transaction record is added into the historical transaction list, or the wrong transaction record in the historical transaction list is corrected; if not, marking is carried out in the reference transaction list, and when the historical transaction list is compared with the reference transaction list again, the record is skipped, so that the data comparison is completed.

The common guarantee transaction information is extracted, the common guarantee transaction information is input into a preset algorithm, corresponding transaction data are output, the transaction data are synchronized to a target server and a historical transaction detail table, common guarantee contracts in a preset period are obtained regularly, a reference transaction detail table is generated according to the common guarantee contracts, the historical transaction detail table and the reference transaction detail table are compared through a comparison algorithm, and when the historical transaction detail table and the reference transaction detail table correspond to each other, the historical transaction detail table is sent to trigger each party to conduct online settlement, the total amount payable is paid, the account distribution or loss payment of the insurance policy is completed, and the beneficial effects of reducing human resources, accurately settling, improving efficiency and expanding business are achieved.

In an embodiment, the electronic device may further perform the step of refining in step 203, including:

step S2031, carrying out format conversion on the transaction data, and adding the transaction data after format conversion to the historical transaction list to obtain an updated historical transaction list;

step 2032, compressing the transaction data into a target file packet, and acquiring a data transmission interface corresponding to the target server;

step 2033, sending the target file package to the target server through the data transmission interface.

And performing format processing on the transaction data, setting the transaction data into corresponding formats, such as text formats, numerical value formats and the like, and calling an add method to respectively add the transaction data after format conversion to rows corresponding to the historical transaction list so as to update the historical transaction list.

And compressing the unprocessed transaction data into a target file packet with a specific format, wherein the target file packet is used for network transmission and can be analyzed by a target server to obtain the transaction data. The transaction data can be compressed by calling a compression program to obtain a compressed file package, wherein the compression program can be WinRAR, 7-Aip. The electronic equipment and the target server are provided with communicated data transmission interfaces, and data are transmitted through the data transmission interfaces. And the server or the terminal sends the target file packet to the target server through the data transmission interface.

The transaction data are compressed into the target file package, the target file package is sent to the corresponding target server, and the transaction data are updated into the historical transaction record table, so that the transaction data are updated to the cooperation guarantee mechanism and the system of the electronic equipment in time to be stored, the recording is carried out according to the time of the transaction record, the data are real and can be verified, and the beneficial effects of later-stage account checking and account checking are facilitated.

In some optional implementations of this embodiment, the electronic device may further perform a refinement step of step 204, including:

step S2041, calling a common guarantee contract in the system in a fixed time within the preset period;

step S2042, extracting feature data in each of the common guaranty contracts;

step S2043, writing the feature data into a preset template file, and generating the reference transaction list.

The electronic device is provided with a warranty contract database. The guarantee contracts can be stored in different positions in a guarantee contract database according to guarantee types, each guarantee contract has a fixed communication address, and the common guarantee contract in a preset period in the system is called through the communication address. And filtering out unqualified products by setting a screening condition to obtain the common guarantee contract in a preset period, wherein the screening condition comprises a contract type and a time period obtained according to the preset period, such as 7/1/2021 to 7/31/2021. It should be noted that the common guarantee contract may be a contract that charges the client for a premium period, for example, from 5/1/2021 to 4/30/2022, and the contract is also required to be included in the preset period from 7/1/2021 to 7/31/2021.

The characteristic data in each common guarantee contract is extracted, wherein the characteristic data comprises one or more of guarantee amount in a preset period, distribution proportion of a main guarantee mechanism and a cooperative guarantee mechanism, preferential discount, latest payment time and the like.

The electronic equipment is provided with a preset template file in advance, after a command of generating a reference transaction detail list is started, the preset template file is started, characteristic data are written into a position corresponding to the preset template file according to a preset rule, a cache file of the processed preset template file is obtained after the characteristic data are processed, the cache file is further converted into a specific file format, such as Excel, Word or Notepad, and the reference transaction detail list is generated, wherein the file format of the reference transaction detail list is the same as that of the historical transaction detail list.

In one embodiment, the step of refining of step S2043 includes:

acquiring a target row corresponding to the characteristic data;

carrying out standardization processing on the value of the characteristic data according to the target row corresponding to the characteristic data;

and writing the value of the standardized feature data into a target row corresponding to the preset template file to obtain the reference transaction list.

The preset target file is provided with a target row, and the target row can correspond to a contract number row, a total insurance premium row, a total reimbursement amount row, a main insurance party amount row, a cooperation insurance party amount row, a summary row and the like in a common guarantee contract. The target line is provided with different formats, such as a contract number behavior text format and a total insurance premium behavior numerical value format.

The feature data are classified to determine a target line corresponding to the feature data, the target line can be determined according to a keyword corresponding to the feature data, the value of the feature data is determined to be subjected to standardization processing according to the target line, for example, decimal point digit conversion, unit conversion and the like are performed on a numerical format, word number reduction and the like can be performed on a text format, and the feature data are unified in format and convenient for later summarization. For example, if the characteristic data is 56.78 ten thousand yuan, then the corresponding target action total guarantee amount row has a corresponding value of 56.78 ten thousand yuan, and the value of the characteristic data is standardized according to the format requirement of the target row, and if the processed value is 56.780, the value 56.780 is written into the total guarantee amount row in the preset template file. And converting the preset template file after data processing into a reference transaction list in a preset format.

In the embodiment, the characteristic data in the common guarantee contract in the preset period is automatically processed in batches through the preset template file to generate the readable reference transaction detail table, so that the method has the advantages of high data processing efficiency and high accuracy, and the data processing capacity and efficiency are improved.

The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware associated with computer readable instructions, which can be stored in a computer readable storage medium, and when executed, the processes of the embodiments of the methods described above can be included. The storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a Random Access Memory (RAM).

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.

The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.

With further reference to fig. 5, as an implementation of the method shown in fig. 2, the present application provides an embodiment of a big data based fund settlement apparatus, which corresponds to the embodiment of the method shown in fig. 2, and which is particularly applicable to various electronic devices.

As shown in fig. 5, the big-data-based fund settlement apparatus 500 according to the present embodiment includes: the system comprises an acquisition module 501, a calculation module 502, an update module 503, a configuration module 504, a comparison module 505, an output module 506 and a settlement module 507. Wherein:

the obtaining module 501 is configured to obtain a transaction record sent by a client, and extract common guarantee transaction information in the transaction record;

the calculation module 502 is configured to input the common guarantee transaction information to a preset algorithm for calculation to obtain corresponding transaction data;

the updating module 503 is configured to update the transaction data to a corresponding historical transaction list, and send the transaction data to a target server;

the configuration module 504 is configured to obtain common guaranty contracts in a preset period at regular time, and generate a reference transaction detail table according to each common guaranty contract;

the comparison module 505 is configured to compare the historical transaction statement with the reference transaction statement;

the output module 506 is configured to send the historical transaction detail table to the target server for retention when the transaction data of the historical transaction detail table matches the transaction data of the reference transaction detail table;

the settlement module 507 is used for performing online settlement according to the historical transaction detail table.

In this embodiment, the obtaining module 501 is configured to receive a transaction record sent by a client. The client can be a bank, a system where the insurance user is located or a terminal device. The transaction record can be a transaction carried out by a premium deducted by the client or a paid claim payment, and the transaction record can be transmitted to the server or the terminal in real time or at regular time; the transaction record includes one or more of a customer name, a payment account number, a number of vouching contracts paid, and a total amount paid. And determining whether the transaction related to the transaction record is a common guarantee transaction according to the key words or key information in the transaction record, for example, extracting a guarantee contract number in the transaction record, comparing the guarantee contract number with a guarantee contract pre-stored in a server or a terminal, determining whether the guarantee contract is a cooperative guarantee contract, and further acquiring common guarantee transaction information in the transaction record.

As an optional implementation, the obtaining module 501 specifically includes the following sub-modules:

the receiving submodule is used for receiving the transaction record sent by the client;

the extraction submodule is used for extracting the guarantee contract identification in the transaction record to be associated with the corresponding guarantee contract;

and the acquisition sub-module is used for acquiring the common guarantee transaction information corresponding to the transaction record when the guarantee contract is a common guarantee contract.

The transaction record may contain a guaranty contract identification, such as a guaranty contract number. The electronic equipment can acquire the guarantee contract identification in a mode of extracting the key words from the transaction record, associate the guarantee contract identification with the corresponding guarantee contract, determine whether the guarantee contract is a common guarantee contract or not according to the type of the guarantee contract, and if the guarantee contract is the common guarantee contract, the transaction record is common guarantee transaction information or contains the common guarantee transaction information. It is understood that the mapping table between the guaranty contract id and the guaranty contract is pre-stored in the electronic device, or the electronic device may call the mapping table between the guaranty contract id and the guaranty contract in the server. The mapping relationship table may include relationships between the guaranty contract identification, the type of guaranty contract, the guaranty amount of the guaranty contract, the payment period of the guaranty contract, and the like.

The cooperative guaranty transaction information includes one or more of a transaction type (premium payment or premium claim), a total amount of the transaction, a distribution ratio between the primary and cooperative guaranty institutions, a policy period or a pay ratio, and the like. The preset algorithm is designed according to the convention rule of the common guarantee contract, variable parameters such as transaction types, total transaction amount, distribution proportion between the main guarantee mechanism and the cooperative guarantee mechanism, policy period or paying proportion and the like are written into the model to obtain the preset algorithm, and the preset algorithm is called when the preset algorithm is used. The calculation module 502 calculates the cooperative guaranty transaction data as input data by a preset algorithm to obtain transaction data, wherein the transaction data may include one or more of a total transaction amount, a principal guaranty amount of a primary guaranty organization, and a cooperation guaranty amount of a cooperative guaranty organization.

The updating module 503 compresses the transaction data into a file packet with a preset format and sends the file packet to a target server, wherein the target server is a server or a terminal where a cooperation guarantee mechanism is located in the cooperation guarantee transaction; the cooperative guaranty organization decompresses the received file package, updates transaction data contained in the file package to a system where the cooperative guaranty organization is located, and records each common guaranty transaction for reconciliation. The configuration module 504 updates the processed transaction data to a historical transaction list of the local server, where the historical transaction list corresponds to different time periods, for example, a historical transaction list is generated every month, and the transaction data obtained by the common guarantee transaction performed in the month is stored in the historical transaction list corresponding to the month; the historical transaction list may be an editable document, with transaction data added. When a common guarantee transaction is carried out, the transaction data is sent to a server or a terminal of the cooperative guarantee mechanism, and the records are carried out in multiple ways, so that the main guarantee mechanism can be effectively prevented from being forged in finance, and the beneficial effects of real bookkeeping and account checking are realized.

The timing may be monthly, e.g., No. 5 per month, or the first working day of each month, and may be custom set according to user needs. The preset period may be set according to the actual performance of the warranty agency, such as monthly, semi-annually, or the like; the common guarantee contract may be a contract newly signed in a preset period, or a payment period agreed by the contract, for example, after the user pays a premium for a certain amount every month after the user pays the premium for the first time, the payment period of the user may be included in the preset period. And obtaining the total transaction amount in a preset period according to each common guarantee contract, the respective guarantee amounts of the main guarantee institution and the cooperative guarantee institution, generating a reference transaction detail table by the total transaction amount, the respective guarantee amounts of the main guarantee institution and the cooperative guarantee contract identification according to the transaction time of the transaction data, and outputting the reference transaction detail table in a word or excel form.

The comparison module 505 compares the historical transaction detail table with the reference transaction detail table one by one through a comparison algorithm, such as a Needleman-Wunsch comparison algorithm, and determines whether the transaction data obtained by each common guaranty contract in the reference transaction detail table in a preset period corresponds to each transaction record in the historical transaction detail table one by one. And identifying whether the transaction data in the reference transaction list and the historical transaction list correspond or not by using parameters such as the common guarantee contract identifier as a matching identifier.

As an optional embodiment, the alignment module 505 may specifically include the following sub-modules:

the traversal submodule is used for calling a comparison algorithm and traversing each transaction data in the reference transaction list;

and the matching sub-module is used for matching each transaction data with the historical transaction detail table.

The comparison algorithm can be a Needleman-Wunsch comparison algorithm or a match algorithm, and the traversing sub-module traverses each transaction data in the reference detailed list. The matching submodule matches the transaction data in each historical statement with the transaction data in the historical transaction statement one by one, and after the matching is successful, the matching submodule jumps to the next transaction data in the reference statement and continues the matching process; and if the transaction data in the reference transaction detail list and all transaction data in the historical transaction detail list are failed to be paired, marking the transaction data, generating an error report record, writing the error report record into the running log, and jumping to the matching process of the next transaction data.

When the reference transaction list corresponds to the transaction data in the history transaction list, the output module 506 packs the history transaction list into a file package, sends the file package to the target server in the form of the file package, so that the file package can be stored by the target server and is further subjected to internal reconciliation; the main guarantee mechanism accurately obtains the settlement amount in a preset period through internal account checking so as to improve the efficiency.

The bill detail list comprises the total amount due (paid) of the main bearing security mechanism and the total amount due (paid) of the cooperation security mechanism, and the online settlement is completed according to the total amount due (paid) and the bank card information, namely the main bearing security mechanism conducts the online transfer according to the total amount due (paid). It can be understood that when the payment for the guarantee needs to be paid to the cooperative guaranty organization after the historical transaction list is sent, the transfer instruction is triggered, and the transfer is carried out according to the settlement amount in the historical transaction list. Similarly, the target server generates a corresponding reference transaction detail table according to a common guarantee contract associated with the main insurance mechanism, when a historical transaction detail table of the main insurance party is received, firstly, a comparison process is started, the reference transaction detail table obtained by self processing is compared with the historical transaction detail table received from the main insurance mechanism, when data are matched and the main insurance mechanism needs to pay for the insurance of the insurance claim, a transfer instruction is triggered, and transfer is carried out according to the settlement amount in the historical transaction detail table.

As an alternative embodiment, the big data based fund settlement apparatus further comprises:

the updating submodule is used for updating the historical transaction list according to the reference transaction list when the transaction data of the historical transaction list is not matched with the transaction data of the reference transaction list;

and the re-comparison submodule is used for re-comparing the updated historical transaction list with the reference transaction list.

According to the comparison result, if the transaction data of the historical transaction detail table is not matched with the transaction data of the reference detail transaction table, the updating sub-module carries out error marking in the operation log, marks errors, such as omission, errors and the like, and judges whether the transaction record corresponding to the common guarantee contract actually exists or not according to the data of the common guarantee contract calling client in the reference detail transaction table, if so, the omitted transaction record is added into the historical transaction detail table, or the wrong transaction record in the historical transaction detail table is corrected; if not, marking is carried out in the reference transaction list, and when the sub-module is compared again to compare the historical transaction list with the reference transaction list, the record is skipped to complete data comparison.

The common guarantee transaction information is extracted, the common guarantee transaction information is input into a preset algorithm for calculation to obtain corresponding transaction data, the transaction data are synchronized to a target server and a historical transaction detail table, common guarantee contracts in a preset period are obtained regularly, a reference transaction detail table is generated according to the common guarantee contracts, the historical transaction detail table and the reference transaction detail table are compared through a comparison algorithm, and when the historical transaction detail table and the reference transaction detail table are in one-to-one correspondence, the historical transaction detail table is sent to trigger all parties to conduct online settlement, the total amount payable is paid, the account division or the claim payment of the policy is completed, and the beneficial effects of reducing human resource loss, accurately settling, improving efficiency and expanding business are achieved.

Referring to fig. 6, which is a schematic structural diagram of an embodiment of the computing module, the update module 503 includes a first update sub-module 5031, a second update sub-module 5032, and a third update sub-module 5033.

The first updating sub-module 5031 is configured to perform format conversion on the transaction data, add the transaction data after format conversion to the historical transaction list, and obtain an updated historical transaction list;

the second updating sub-module 5032 is configured to compress the transaction data into a target file package, and obtain a data transmission interface corresponding to the target server;

a third update sub-module 5033, which sends the target file packet to the target server through the data transmission interface.

The first updating sub-module 5031 performs format processing on the transaction data, sets the transaction data into a corresponding format, such as a text format and a numerical value format, and respectively adds the transaction data after format conversion to rows corresponding to the historical transaction list by calling an add method, thereby updating the historical transaction list.

The second update sub-module 5032 compresses the transaction data into a target file package with a specific format, wherein the target file package is used for network transmission and can be analyzed by a target server to obtain the transaction data. The transaction data can be compressed by calling a compression program to obtain a compressed file package, wherein the compression program can be WinRAR, 7-Aip. The third update sub-module 5033 is connected to the target server via a data transmission interface, and transmits data via the data transmission interface. And sending the target file packet to the target server through the data transmission interface.

Referring to fig. 7, a schematic diagram of an embodiment of a configuration module, the configuration module 504 includes a first configuration sub-module 5041, a second configuration sub-module 5042, and a third configuration sub-module 5043.

The first configuration submodule 5041 is configured to call the common guaranty contract in the system periodically within the preset period;

a second configuration sub-module 5042 for extracting feature data in each of said common guaranty contracts;

and the third configuration sub-module 5043 is configured to write the feature data into a preset template file, and generate the reference transaction list.

The capital settlement device based on big data is provided with a guarantee contract database. The guarantee contracts can be stored in different positions in a guarantee contract database according to guarantee types, each guarantee contract has a fixed communication address, and the common guarantee contract in a preset period in the system is called through the communication address. The first configuration sub-module 5041 may be configured to filter out the non-compliant contract to obtain the common guaranty contract within the predetermined period by setting a filtering condition, where the filtering condition includes a contract type and a time period obtained according to the predetermined period, such as 7/1/2021 to 7/31/2021. It should be noted that the common guarantee contract may be a contract that charges the client for a premium period, for example, from 5/1/2021 to 4/30/2022, and the contract is also required to be included in the preset period from 7/1/2021 to 7/31/2021.

The second configuration sub-module 5042 extracts feature data from each of the common guaranty contracts, wherein the feature data includes one or more of the guaranty amount in a predetermined period, the distribution ratio of the primary and cooperative guaranty agencies, discount offers, and the latest payment time.

The third configuration sub-module 5043 pre-configures a preset template file, starts the preset template file after starting the command of generating the reference transaction detail list, writes the feature data into a position corresponding to the preset template file according to a preset rule, processes the feature data to obtain a cache file of the processed preset template file, converts the cache file into a specific file format, such as Excel, Word or Notepad, and generates the reference transaction detail list, wherein the file format of the reference transaction detail list is the same as that of the historical transaction detail list.

In an embodiment, the third configuration sub-module 5043 may further include the following sub-modules:

the searching submodule is used for acquiring a target row corresponding to the characteristic data;

the standardization processing submodule is used for carrying out standardization processing on the value of the characteristic data according to the target line corresponding to the characteristic data;

and the writing sub-module is used for writing the value of the standardized feature data into a target row corresponding to the preset template file to obtain the reference transaction list.

The feature data are classified, a target line corresponding to the feature data is determined, the searching submodule can determine the target line according to a keyword corresponding to the feature data, the standardization processing submodule determines to standardize the value of the feature data according to the target line, for example, decimal point digit conversion, unit conversion and the like are carried out on a numerical value format, word number reduction and the like can be carried out on a text format, and the uniform format is convenient for later-stage summarization. For example, if the characteristic data is 56.78 ten thousand yuan, the corresponding target action total guarantee amount row has a corresponding value of 56.78 ten thousand yuan, the normalization processing sub-module normalizes the value of the characteristic data according to the format requirement of the target row, and if the processed value is 56.780, the writing sub-module writes the value 56.780 into the total guarantee amount row in the preset template file. And converting the preset template file after data processing into a reference transaction list in a preset format.

In order to solve the technical problem, an embodiment of the present application further provides a computer device. Referring to fig. 8, fig. 8 is a block diagram of a basic structure of a computer device according to the present embodiment.

The computer device 8 comprises a memory 81, a processor 82, a network interface 83 communicatively connected to each other via a system bus. It is noted that only computer device 8 having components 81-83 is shown, but it is understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead. As will be understood by those skilled in the art, the computer device is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and the hardware includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.

The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer equipment can carry out man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch panel or voice control equipment and the like.

The memory 81 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or D big data based fund settlement memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the storage 81 may be an internal storage unit of the computer device 8, such as a hard disk or a memory of the computer device 8. In other embodiments, the memory 81 may also be an external storage device of the computer device 8, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the computer device 8. Of course, the memory 81 may also comprise both an internal storage unit of the computer device 8 and an external storage device thereof. In this embodiment, the memory 81 is generally used for storing an operating system installed in the computer device 8 and various types of application software, such as computer readable instructions of a big data based fund settlement method. Further, the memory 81 may also be used to temporarily store various types of data that have been output or are to be output.

The processor 82 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 82 is typically used to control the overall operation of the computer device 8. In this embodiment, the processor 82 is configured to execute computer readable instructions stored in the memory 81 or process data, such as computer readable instructions for executing the big data based fund settlement method.

The network interface 83 may comprise a wireless network interface or a wired network interface, and the network interface 83 is generally used for establishing communication connections between the computer device 8 and other electronic devices.

The present application further provides another embodiment, which is to provide a computer-readable storage medium storing computer-readable instructions executable by at least one processor to cause the at least one processor to perform the steps of the big-data based funds settlement method as described above.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.

It is to be understood that the above-described embodiments are merely illustrative of some, but not restrictive, of the broad invention, and that the appended drawings illustrate preferred embodiments of the invention and do not limit the scope of the invention. This application is capable of embodiments in many different forms and is provided for the purpose of enabling a thorough understanding of the disclosure of the application. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to one skilled in the art that the present application may be practiced without modification or with equivalents of some of the features described in the foregoing embodiments. All equivalent structures made by using the contents of the specification and the drawings of the present application are directly or indirectly applied to other related technical fields and are within the protection scope of the present application.

Claims

1. A fund settlement method based on big data is characterized by comprising the following steps:

comparing the historical transaction list with the reference transaction list;

2. The big-data based funds settlement method of claim 1, wherein the step of extracting the common vouching transaction information in the transaction record sent by the acquisition client comprises:

receiving a transaction record sent by a client;

extracting a guarantee contract identifier in the transaction record;

associating to a corresponding guaranty contract according to the guaranty contract identifier;

3. The big data based funds settlement method of claim 1, wherein the step of updating the transaction data to a corresponding historical transaction schedule and sending the transaction data to a target server comprises:

carrying out format conversion on the transaction data, and adding the transaction data subjected to format conversion to the historical transaction list to obtain an updated historical transaction list;

compressing the transaction data into a target file packet, and acquiring a data transmission interface corresponding to the target server;

and sending the target file packet to the target server through the data transmission interface.

4. The big-data based fund settlement method according to claim 1, wherein the step of periodically acquiring common guaranty contracts within a preset period and generating a reference transaction schedule from each of the common guaranty contracts comprises:

calling a common guarantee contract in the system at regular time within the preset period;

extracting feature data in each of the common guaranty contracts;

and writing the characteristic data into a preset template file to generate the reference transaction list.

5. The big data based funds settlement method of claim 1, wherein the step of writing the characteristic data into a preset template file to generate the reference transaction schedule comprises:

acquiring a target row corresponding to the characteristic data;

6. The big data based funds settlement method of claim 1, wherein the step of comparing the historical transaction schedule with the reference transaction schedule comprises:

and matching each transaction data with the historical transaction list.

7. The big data based funds settlement method of any one of claims 1 to 6, further comprising, after the step of comparing the historical transaction schedule with the reference transaction schedule:

8. A big data based funds settlement apparatus, comprising:

the output module is used for sending the historical transaction detail table to the target server for retention when the transaction data of the historical transaction detail table is matched with the transaction data of the reference transaction detail table;

9. A computer device comprising a memory having computer readable instructions stored therein and a processor that when executed performs the steps of the big-data based funds settlement method of any of claims 1 to 7.

10. A computer readable storage medium having computer readable instructions stored thereon which, when executed by a processor, implement the steps of the big data based funds settlement method of any of claims 1 to 7.