CN115131027A - Suspicious risk client real-time monitoring method for identifying money laundering based on digital currency transaction - Google Patents
Suspicious risk client real-time monitoring method for identifying money laundering based on digital currency transaction Download PDFInfo
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- CN115131027A CN115131027A CN202210634951.9A CN202210634951A CN115131027A CN 115131027 A CN115131027 A CN 115131027A CN 202210634951 A CN202210634951 A CN 202210634951A CN 115131027 A CN115131027 A CN 115131027A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4014—Identity check for transactions
Abstract
The invention discloses a suspicious risk client real-time monitoring method for identifying money laundering based on digital currency transaction, which comprises the following steps; s1: when data transaction is carried out on the network, a system for measures is established for large-amount transaction or suspicious transaction, and the measures comprise real-name authentication, transaction termination, account freezing and the like; s2: establishing evaluation indexes of large-amount transaction and suspicious transaction, establishing a maximum amount of the digital currency, and carrying out a transaction rapid termination instruction aiming at the client which does not meet the transaction requirement, namely the transaction does not support the service for the client after reaching the limit. The suspicious risk client real-time monitoring method based on digital currency transaction recognition money laundering firstly establishes institutional measures about money laundering and evaluation indexes of large-amount transaction and suspicious transaction, quickly discriminates the true identity of the account of a suspicious client, and submits the suspicious client to a money laundering data transaction authentication center for centralized processing.
Description
Technical Field
The invention relates to the technical field of digital currency transactions, in particular to a suspicious risk client real-time monitoring method for identifying money laundering based on digital currency transactions.
Background
The existing suspicious risk customer real-time monitoring for identifying money laundering based on digital currency transaction has certain defects;
this prior art solution also presents the following problems when in use:
the real-time monitoring and tracking of the suspicious client information is inconvenient for quickly screening the identity of the suspicious client, the source of transaction data cannot be tracked timely, and relatively complete identification standard indexes are not established, so that the identity of the suspicious client cannot be quickly and accurately locked and monitored.
Improvements are needed to address the above problems.
Disclosure of Invention
The invention aims to provide a suspicious risk client real-time monitoring method for identifying money laundering based on digital currency transaction, which aims to solve the problems that the real-time monitoring and tracking of suspicious client information in the current market proposed by the background technology is inconvenient to quickly identify the identity of a suspicious client, the source of transaction data cannot be tracked timely, and relatively complete identification standard indexes are not established, so that the identity of the suspicious client cannot be locked and monitored quickly and accurately.
In order to achieve the purpose, the invention provides the following technical scheme: a suspicious risk customer real-time monitoring method for identifying money laundering based on digital currency transaction comprises the following steps;
s1: when data transaction is carried out on the network, a system for measures is established for large-amount transaction or suspicious transaction, and the measures comprise real-name authentication, transaction termination, account freezing and the like;
s2: establishing evaluation indexes of large-amount transaction and suspicious transaction, establishing a maximum amount-increasing value of digital currency, and then carrying out a transaction rapid termination instruction aiming at a client which does not meet transaction requirements, namely the transaction does not support providing service for the client after reaching the limit;
s3: the real-time KYC (know your customer) measures are taken, customer data are investigated, and if the customer is in abnormal operation, transaction data are rapidly reported to the central gateway unit;
s4: the information, data and data generated by the digital currency transaction identification are stored, so that each transaction can be completely reproduced and traced;
s5: big data tracking is carried out on suspicious risk customers meeting the identification characteristics, and the account identity of a transaction customer is quickly locked;
s6: tracking the source of transaction data in real time, processing mass transaction data, and analyzing the transaction data and tracking the capital flow direction by a system;
s7: analyzing and comparing the final result, carrying out file retention on the result, transmitting the structured data information to an anti-money laundering center on line for data archiving, and then uploading the information to an evaluation index in a classified manner.
Preferably, the step S1 and the step S2 relate to establishment of measure system and evaluation index of the large and suspicious transactions, and special compliance and risk control department are established for risk control.
Preferably, the customer having the sanctioned list is evaluated in step S2, and the service can be directly denied.
Preferably, the KYC measures in step S3 include customer identity background knowledge, customer occupation or business background knowledge, transaction purpose and nature knowledge, and knowledge of funding source channel.
Preferably, the suspicious customers identified in step S5 that meet the characteristics directly pass through the central office and the central operating agency, so as to grasp all user information, identify specific transaction characteristics through big data, and quickly compare the actual identities of the locked accounts.
Preferably, the tracking of the source of the transaction data in real time in step S6 relies on the central operating institution reporting the transaction request, and the transaction request is processed by the anti-money laundering data transaction authentication center in a centralized manner.
Preferably, the system analysis in step S6 makes the concealed money laundering activity transparent, enhances the control capability on the transaction information, and screens the source and the attribution of illegal funds in time.
Preferably, the archive information in step S7 should include the digital wallet address, IP address, and digital currency type and amount of each party and summary of each item of the suspicious customer.
Compared with the prior art, the invention has the beneficial effects that: the method for monitoring suspicious risk customers who identify money laundering based on digital currency transactions comprises the steps of firstly establishing institutional measures related to money laundering and establishing evaluation indexes of large-amount transactions and suspicious transactions, quickly screening the real account identities of the suspicious customers, and submitting the suspicious customers to centralized processing by a money laundering data transaction authentication center.
Firstly, establishing institutional measures about anti-money laundering and establishing evaluation indexes of large-amount transactions and suspicious transactions, tracing each transaction, tracking big data of suspicious risk customers according with identification characteristics, quickly locking account identities of transaction customers, directly mastering all user information by a central bank and a central operating organization after identifying suspicious customers according with the characteristics, identifying specific transaction characteristics through the big data, quickly comparing and locking real identities of the accounts, tracking sources of transaction data in real time, processing mass transaction data by using technologies such as big data, artificial intelligence and the like, systematically analyzing the transaction data and tracking fund flow direction, wherein the sources of the tracked transaction data depend on the central operating organization to report transaction requests, the anti-money laundering data transaction authentication center performs centralized processing, the final results are analyzed and compared, and the results are kept orderly, and transmitting the structured data information to an anti-money laundering center on line for data archiving, and finally uploading the information to an evaluation index in a classified manner, wherein the archive information comprises the digital wallet address, the IP address, the digital currency type and quantity of each party and all data summarization of suspicious customers.
Drawings
FIG. 1 is a schematic diagram of the principles of the present invention;
FIG. 2 is a schematic flow chart of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution: a suspicious risk customer real-time monitoring method for identifying money laundering based on digital currency transaction comprises the following steps;
s1: when data transaction is carried out on the network, a system for measures is established for large-amount transaction or suspicious transaction, and the measures comprise real-name authentication, transaction termination, account freezing and the like; s2: establishing evaluation indexes of large-amount transaction and suspicious transaction, establishing a maximum upper-amount numerical value of digital currency, and then carrying out a transaction rapid termination instruction aiming at a client which does not meet transaction requirements, namely the transaction does not support the provision of service for the client after reaching the limit; s3: the method comprises the steps of taking real-time KYC (know your customer) measures, investigating customer data, and rapidly reporting transaction data to a central gateway unit if the customer performs abnormal operation; s4: the information, data and data generated by the digital currency transaction identification are stored, so that each transaction can be completely reproduced and traced; s5: big data tracking is carried out on suspicious risk customers meeting the identification characteristics, and the account identity of a transaction customer is quickly locked; s6: tracking the source of transaction data in real time, processing mass transaction data, and analyzing the transaction data and tracking the capital flow direction by a system; s7: analyzing and comparing the final result, carrying out file retention on the result, transmitting the structured data information to an anti-money laundering center on line for data archiving, and then uploading the information to an evaluation index in a classified manner. The step S1 and the step S2 relate to the establishment of the measure system and the evaluation index of the large amount transaction and the suspicious transaction, and special compliance is established and a risk control department is set for risk control. The evaluation of the client containing the sanctioned list in step S2 may directly deny service. The KYC measures in step S3 include customer identity background knowledge, customer occupation or business background knowledge, transaction purpose and nature knowledge, and funding source channel knowledge. In step S5, the suspicious customer identified as meeting the feature in the step S may directly pass through central and central operating agencies to grasp all user information, identify the specific transaction feature through big data, and quickly compare the transaction feature with the real account identity. In the step S6, the source of the real-time tracking transaction data depends on the central operation institution reporting the transaction request, and is centrally processed by the anti-money laundering data transaction authentication center. In the step S6, the system analysis makes the concealed money laundering activity transparent, strengthens the control capability of transaction information, and screens the source and the attribution of illegal funds in time. The archive information in said step S7 should include the digital wallet address, IP address and digital currency type and amount of each party and summary of each item of the suspicious customer.
Firstly, establishing institutional measures about money laundering and establishing evaluation indexes of large-amount transaction and suspicious transaction, quickly screening the true identity of the account of a suspicious customer, submitting the true identity to a centralized processing by a money laundering data transaction authentication center, regulating the archive retention of the result, and transmitting the regulated data information to the money laundering center on line for data archiving.
The working principle is as follows: as shown in fig. 1-2, when using the suspicious risk client real-time monitoring method for identifying money laundering based on digital currency transaction, firstly, establishing institutional measures related to money laundering and establishing evaluation indexes of large-amount transaction and suspicious transaction, then setting special compliance and risk control departments to carry out risk control according to different measures and indexes, adopting real-name authentication before institutional measures require large-amount transaction on line, specifying whether the non-compliant transaction is terminated, freezing account on line when suspicious risk client exists, wherein the evaluation indexes contain information of risk client not compliant with transaction requirement and range exceeding transaction limit, carrying out transaction fast termination instruction according to client not compliant with transaction requirement, namely, the transaction does not support providing service for the client after reaching the limit, if identifying client of sanctioned list, the service may be denied directly. The method is characterized in that customer data are rapidly investigated aiming at suspicious customers, if the customers have abnormal operation, transaction data are rapidly reported to a central host gateway unit, and the investigation comprises customer identity background knowledge, customer occupation or operation background knowledge, transaction purpose and property knowledge and fund source channel knowledge. The method is characterized in that information, data and data generated by on-line digital currency transaction identification are stored, each transaction can be completely reproduced, each transaction is traced, suspicious risk customers meeting identification characteristics are tracked by big data, the account identities of transaction customers are quickly locked, the suspicious customers meeting the characteristics can directly master all user information by central authorities and central operating institutions, specific transaction characteristics are identified by the big data, the real identities of accounts are quickly compared and locked, the sources of transaction data are tracked in real time, massive transaction data can be processed by utilizing technologies such as big data, artificial intelligence and the like, the transaction data and the fund flow direction are systematically analyzed, wherein the sources of the tracked transaction data rely on the central operating institutions to report transaction requests, the transaction requests are centrally processed by a money laundering data transaction authentication center to analyze and compare final results, and the result is normalized for file retention, the normalized data information is transmitted to an anti-money laundering center for data archiving on line, and finally the information is classified and uploaded to an evaluation index, the retained information should include the digital wallet address, the IP address, the type and the quantity of the digital currency of each party and various data summarization of suspicious customers, and the content which is not described in detail in the description belongs to the prior art which is known by technical personnel in the field.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.
Claims (8)
1. A suspicious risk customer real-time monitoring method for identifying money laundering based on digital currency transaction is characterized by comprising the following steps;
s1: when data transaction is carried out on the network, a system for measures is established for large-amount transaction or suspicious transaction, and the measures comprise real-name authentication, transaction termination, account freezing and the like;
s2: establishing evaluation indexes of large-amount transaction and suspicious transaction, establishing a maximum amount-increasing value of digital currency, and then carrying out a transaction rapid termination instruction aiming at a client which does not meet transaction requirements, namely the transaction does not support providing service for the client after reaching the limit;
s3: the real-time KYC (know your customer) measures are taken, customer data are investigated, and if the customer is in abnormal operation, transaction data are rapidly reported to the central gateway unit;
s4: the information, data and data generated by the digital currency transaction identification are stored, so that each transaction can be completely reproduced and traced;
s5: big data tracking is carried out on suspicious risk customers meeting the identification characteristics, and the account identity of a transaction customer is quickly locked;
s6: tracking the source of transaction data in real time, processing mass transaction data, and analyzing the transaction data and tracking the capital flow direction by a system;
s7: analyzing and comparing the final result, carrying out file retention on the result, transmitting the structured data information to an anti-money laundering center on line for data archiving, and then uploading the information to an evaluation index in a classified manner.
2. The method of claim 1, wherein the method comprises the steps of identifying suspicious risk customers of money laundering based on digital currency transactions, and the method comprises the following steps: the step S1 and the step S2 relate to establishment of measure system and evaluation index of large amount transaction and suspicious transaction, and special compliance and risk control department are established for risk control.
3. The method of claim 1, wherein the method comprises the steps of identifying suspicious risk customers who have washed money based on digital currency transactions, wherein the method comprises the following steps: the customer having the sanction list evaluated in step S2 can directly refuse the service.
4. The method of claim 1, wherein the method comprises the steps of identifying suspicious risk customers of money laundering based on digital currency transactions, and the method comprises the following steps: the KYC measures in step S3 include customer identity background knowledge, customer occupation or business background knowledge, transaction purpose and nature knowledge, and funding source channel knowledge.
5. The method of claim 1, wherein the method comprises the steps of identifying suspicious risk customers who have washed money based on digital currency transactions, wherein the method comprises the following steps: in step S5, the suspicious customers identified in accordance with the characteristics in the step S can directly pass through the central office and the central operating organization to grasp all user information, identify specific transaction characteristics through big data, and quickly compare the transaction characteristics with the real identities of the locked accounts.
6. The method of claim 1, wherein the method comprises the steps of identifying suspicious risk customers of money laundering based on digital currency transactions, and the method comprises the following steps: in the step S6, the source of the real-time tracking transaction data depends on the central operation institution reporting the transaction request, and is centrally processed by the anti-money laundering data transaction authentication center.
7. The method of claim 1, wherein the method comprises the steps of identifying suspicious risk customers of money laundering based on digital currency transactions, and the method comprises the following steps: in the step S6, the system analysis makes the concealed money laundering activity transparent, strengthens the control capability of transaction information, and screens the source and the attribution of illegal funds in time.
8. The method of claim 1, wherein the method comprises the steps of identifying suspicious risk customers of money laundering based on digital currency transactions, and the method comprises the following steps: the archive information in said step S7 should include the digital wallet address, IP address and digital currency type and amount of each party and summary of each item of the suspicious customer.
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| CN202210634951.9A CN115131027A (en) | 2022-06-06 | 2022-06-06 | Suspicious risk client real-time monitoring method for identifying money laundering based on digital currency transaction |
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| CN202210634951.9A CN115131027A (en) | 2022-06-06 | 2022-06-06 | Suspicious risk client real-time monitoring method for identifying money laundering based on digital currency transaction |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116596532A (en) * | 2022-11-07 | 2023-08-15 | 北京天德科技有限公司 | Supervision method based on real-time suspicious transaction identification and supervision blockchain wallet |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116596532A (en) * | 2022-11-07 | 2023-08-15 | 北京天德科技有限公司 | Supervision method based on real-time suspicious transaction identification and supervision blockchain wallet |
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