Closed-loop management method and system for data element and block chain fusion

Abstract

The invention discloses a closed-loop management method and system for data element and block chain fusion, and belongs to the technical field of closed-loop management systems. The system comprises a financial data block chain management platform, and the financial data block chain management platform is in communication connection with a multi-source financial data collection module used for collecting and deploying a supervision area, marking original data according to time nodes, and classifying and screening the original data; according to the invention, through collection, preprocessing and intelligent ownership verification of multi-source financial data, full-process compliance and risk prevention and control are realized by relying on a block chain intelligent contract, the right confirmation efficiency is improved, disputes are reduced, the risk joint defense module combines multiple data and a historical library to realize second-level response of abnormal transaction risks, and the prevention and control capability of a financial institution is enhanced; the problem of heterogeneous chain value islanding is solved through a cross-chain protocol and a risk mapping table, different chain security protocols are adapted, sensitive data desensitization, dynamic right adjustment and blocking of unauthorized right are performed at the same time, the information sovereignty of authorized users is guaranteed, and the leakage risk is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of closed-loop management systems, and specifically to a closed-loop management method and system that integrates data elements with blockchain. Background Art

[0002] In today's digital age, data elements have become one of the key production factors that promote economic and social development. Compared with other traditional production factors, data elements have significant characteristics such as reproducibility and repeatability, which enables the value of data in economic activities to be continuously amplified; however, it is these characteristics that also bring a series of serious problems. For example, financial market data is extremely easy to be intercepted, illegally used, tampered with, denied and leaked during circulation, which seriously threatens data security and the rights and interests of relevant parties. In addition, the consensus algorithm, ledger structure, encryption mechanism and other technologies of each chain are different, resulting in heterogeneity between blockchains; there is a lack of a unified interconnection mechanism between heterogeneous chains, making it difficult to achieve value intercommunication, which forms a value island effect in the blockchain ecosystem.

[0003] As an emerging distributed ledger technology, blockchain technology integrates multiple advanced technologies such as encryption technology, distributed networks, and smart contracts, providing new ideas and directions for solving the problems in the application of the above-mentioned data elements; the tamper-proof nature of blockchain can be used for data storage and to ensure the authenticity and integrity of data. Its distributed network structure can improve the reliability and availability of data, and smart contracts can realize automated business processes and rule execution.

[0004] However, current blockchain-based data element-related applications are mainly concentrated in limited aspects such as data notarization. They can only trace data elements after circulation, and cannot conduct comprehensive control before and during the circulation of data elements. They fail to cover the entire life cycle of data element circulation and have not yet achieved controllable management of the entire process of data element circulation. Therefore, there is an urgent need for an innovative closed-loop management method and system to deeply integrate data elements with blockchain technology, build a compliant, efficient, secure and reliable data element circulation system, and realize closed-loop management of data elements, so as to give full play to the value of data elements, protect the rights and interests of all parties, and promote the healthy and orderly development of the data element market. Summary of the Invention

[0005] The purpose of this invention is to provide a closed-loop management method and system for the integration of data elements and blockchain to solve the problems raised.

[0006] To achieve the above objectives, the present invention provides the following technical solutions: a closed-loop management system integrating data elements and blockchain, including a financial data blockchain management platform, wherein the financial data blockchain management platform is communicatively connected to a multi-source financial data acquisition module for collecting and deploying regulatory areas, marking the original data according to time nodes and classifying and filtering it, and generating a financial data set F with timestamps and risk tags. t And send it to the data element rights confirmation analysis module and the blockchain risk joint defense module;

[0007] Data element ownership analysis module: for the received financial data set F t Conduct ownership verification, combining financial regulatory rules with historical ownership records r , generate a compliance dataset F t / anon , compliance authorization signal S a or overriding warning signal S u And send it to the blockchain risk joint defense module;

[0008] Blockchain risk joint defense module: Based on financial data set F t , compliance authorization signal S a / Override warning signal S u and historical risk event database H f , analyze cross-institutional circulation risks and generate risk warning signals S w And send it to the distributed compliance control module;

[0009] Distributed compliance control module: Automatically matches and triggers preset stored financial regulatory policies based on received risk signals, generates compliance control plans, executes them through smart contracts and feeds them back to the financial data blockchain management platform.

[0010] Furthermore, the multi-source financial data collection module performs the following processing based on the original data collected by the deployment supervision area:

[0011] According to the financial data blockchain management platform, the deployment supervision area intercepts the time period for key data processing instructions, extends it to the intercepted time period according to the historical collection time frequency, and constructs a new extended time node to give a timestamp mark to the collected original data. The deployment supervision area includes the financial data area connecting to the internal database, the external information source connection port, and the third-party information aggregation port, constructing the precise target of original data collection and constructing a tag file for the target type, such as retail transaction files, corporate business files, cross-border payment files and multiple groups of data storage tag files.

[0012] Furthermore, the multi-source financial data acquisition module performs risk screening on the marked files based on historical records as follows:

[0013] Retrieve the pre-stored high-risk reference template from the financial data blockchain management platform and compare it with the marked files. If the cross-border payment file is greater than the pre-stored cross-border risk threshold, the cross-border payment file data will be marked as high-risk cross-border risk. tag / a If the corporate business file is greater than the pre-stored transfer upper limit, the corporate business file data will be marked as high risk. tag / b If the retail transaction file is greater than the pre-stored credit threshold, the retail transaction file data is marked as high risk credit risk. tag / c , and construct the classified financial dataset F t Stored on the financial data blockchain management platform.

[0014] Furthermore, the multi-source financial data acquisition module performs risk screening on the marked files based on historical records as follows:

[0015] For the financial dataset F t Copy and generate the retrieved folder-sub-page, perform compliance pre-processing on the data in the retrieved folder-sub-page, remove the un-masked customer biometric data, convert the sensitive fields in the personal information into anonymous identification characters through a hash algorithm or masking method, and generate a compliant data set F t / anon , retrieve the pre-stored compliance verification code from the financial data blockchain management platform and locate it in the compliance data set F t / anon Multi-type data is supplemented with collection source identification and compliance verification code to form a compliance data set F t / anon Build multi-level protection, and archive pre-processed data into three-dimensional indexes based on time, business, and risk level.

[0016] Furthermore, the data element rights confirmation analysis module analyzes the compliance data set F t / anon The analysis process is as follows:

[0017] Receive the compliance dataset F t / anon Then, the data usage simulation scenarios are restored one by one based on the multiple data types in the collection, and the pre-stored authorizer agreement threshold, financial institution data sharing agreement threshold and compliance data set F are retrieved from the financial data blockchain management platform. t / anon Analyze multiple types of data one by one: If a single retail transaction file data is marked as high-risk cross-border risk tag / a , and only the “domestic use” style mark is marked in the authorization agreement threshold range, then an unauthorized warning signal S is generated. u , with an unauthorized "cross-border use without authorization" style mark; if there is a protocol-permitted query / verification mark in the multi-type data, and the purpose of use is within the query scope and verification scope, a compliance authorization signal S is generated. a , construct the ownership confirmation mark and compliance dataset F based on the multiple analysis results t / anonBind to the chain to form an unalterable record of ownership H r When a batch of unauthorized data is detected, the module automatically triggers an early warning work order and pushes it to the compliance department for manual review.

[0018] Furthermore, the blockchain risk joint defense module t / anon The further analysis process is as follows:

[0019] Receive the compliance dataset F t / anon , compliance authorization signal S a and over-authority warning signal S u Then, the pre-stored historical risk event database H is retrieved from the financial data blockchain management platform. f Conduct joint risk analysis and analyze the historical risk event database H f The ratio of compliance and unauthorized values ​​in the above table generates the upper limit of the compliance risk index. If the unauthorized warning signal S u > compliance risk index upper limit, then generate compliance risk warning S w1 ;Analyze the historical risk event database H f Medium-to-high risk swap tag / b The mean number of IP address distributions is used to generate the cross-border risk threshold. If the compliance dataset F t / anon Medium-to-high risk swap tag / b If the number of IP address distributions is greater than the cross-border risk threshold, a cross-border operation abnormality signal S is generated. w2 ;Analyze the historical risk event database H f Medium to high risk credit risk tag / c Matching blacklist database, if high risk credit risk tag / c If it is in the blacklist database, a potential abnormal trustless association S is generated. w3 , retrieve the risk signal level low, medium and high from the financial data blockchain management platform. If the compliance data set F t / anon If the analysis generates a single set of risk signals, it is judged as low risk. If two or three sets are generated at the same time, they are judged as medium risk or high risk respectively, triggering the cross-institutional joint defense mechanism signal and sharing the risk characteristics in real time with all financial institutions in the alliance chain.

[0020] Furthermore, the risk agreement of the financial data area connection internal database, external information source connection port, and third-party information aggregation port is retrieved from the financial data blockchain management platform, and the financial field cross-chain risk mapping threshold table M is constructed in combination with the internal risk determination scheme. c , when the high risk of internal database cross-border risk tag / a When there is duplication or transfer of shared information between data and external information source connection port, call the compliant data set F t / anon Generate relevant compliance dataset F t / anonCompare the original data to generate a comparison duplication percentage value, and compare it with the cross-chain risk mapping threshold table M in the financial field c Perform a reference comparison. If the comparison duplication percentage value exceeds the financial field cross-chain risk mapping threshold table M c If the upper limit of the mark is reached, the cross-chain delay risk signal S x .

[0021] The working method of the closed-loop management system integrating data elements and blockchain includes the following steps:

[0022] S1: Intercept time periods according to instructions, construct time nodes and mark them, classify and filter high-risk data, form compliant data sets after preprocessing, and archive and store them;

[0023] S2: Compare rules and records to generate a confirmation signal, upload the results to the blockchain, and trigger manual review and warning for batch unauthorized use;

[0024] S3: Generates signals such as compliance and cross-border operation anomalies, and generates cross-chain delay risk signals by comparing cross-chain scenarios;

[0025] S4: The level is determined based on the number of risk signals, with a single group being low, two groups being medium, and three or more groups being high. After integrating the signals, they are shared through the alliance chain, triggering a cross-institutional joint defense mechanism.

[0026] S5: The distributed compliance control module matches policies according to risk levels, conducts low-risk prompt reviews, verifies medium-risk limits, freezes high-risk accounts, etc., and executes and feedbacks closed loops through smart contracts.

[0027] The beneficial effects of the present invention are:

[0028] 1. This invention achieves full-process compliance and risk control. Multi-source data is collected, pre-processed, and intelligently verified for ownership, complying with multiple regulations. The ownership confirmation module automatically verifies based on smart contracts, improving efficiency and reducing disputes. The risk joint prevention module combines multiple data and historical databases to analyze risks, achieving a second-level response to abnormal transaction risks, significantly improving the prevention and control capabilities of financial institutions.

[0029] 2. This invention solves the problem of heterogeneous chain collaboration and protects the rights and interests of authorized users. Through cross-chain protocols and risk mapping tables, it solves the value island problem caused by differences between chains and adapts to different chain security protocols. At the same time, it desensitizes sensitive data, dynamically adjusts permissions and blocks unauthorized access, thereby protecting the information sovereignty of authorized users and reducing the risk of data leakage.

[0030] 3. This invention realizes the integration of regulatory technology and improves efficiency. The distributed compliance control module is based on a pre-storage solution and is executed through smart contracts to improve the efficiency of compliance report submission and reduce labor costs. It can dynamically update rules to adapt to regulatory changes, realize visual management and traceability of data throughout its life cycle, meet regulatory requirements, and promote the development of the financial market. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 It is a schematic diagram of the overall operation method of the present invention;

[0033] Figure 2 This is a flow chart of the system of the present invention. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] Example 1: Please refer to Figure 1 - Figure 2 As shown, this embodiment is a closed-loop management system that integrates data elements and blockchain, including a financial data blockchain management platform. The financial data blockchain management platform is communicatively connected to a multi-source financial data acquisition module for collecting and deploying regulatory areas, marking the original data according to time nodes and classifying and filtering them to generate a financial data set F with timestamps and risk tags. t The data is sent to the data element rights confirmation analysis module and the blockchain risk joint defense module; the multi-source financial data collection module performs the following processing based on the original data collected in the deployment supervision area:

[0036] According to the financial data blockchain management platform, the deployment supervision area intercepts the time period for key data processing instructions, extends it to the intercepted time period based on the historical collection time frequency, and constructs a new extended time node to give a timestamp to the collected original data;

[0037] The deployed regulatory areas include the financial data area connected to the internal database, the external information source connection port, and the third-party information aggregation port, building precise targets for raw data collection and building tag files according to target types, such as multiple sets of data storage tag files for retail transaction files, corporate business files, and cross-border payment files.

[0038] The multi-source financial data acquisition module performs risk screening on marked files based on historical records as follows:

[0039] Retrieve pre-stored high-risk reference templates and marked files from the financial data blockchain management platform for similar comparison processing:

[0040] If the cross-border payment file is greater than the pre-stored cross-border risk threshold, the cross-border payment file data will be marked as high-risk cross-border risk. tag / a , the distributed compliance control module receives high-risk cross-border risk tag / a Afterwards, a regulatory alert log is generated and synchronized to an externally connected currency transaction monitoring center, along with a hash value of the unauthorized cross-border use of data. This is available for real-time access by regulatory authorities, and the risk identification of the data is broadcast to other financial institutions through the alliance chain, prompting them to prohibit receiving or processing related cross-border transactions, thus forming a cross-institutional collaborative prevention and control system.

[0041] If the public business file is greater than the pre-stored transfer upper limit, the public business file data will be marked as high risk. tag / b , the distributed compliance control module receives the high risk tag / b After that, the blockchain traceability contract pre-stored in the financial data blockchain management platform is activated to track the flow of funds and the operating IP, generate an abnormal operation trajectory report, and push it to the compliance department and economic investigation agency to assist in the investigation;

[0042] If the retail transaction file is greater than the pre-stored credit threshold, the retail transaction file data is marked as high risk credit risk. tag / c , the distributed compliance control module receives high-risk credit risk tag / c Afterwards, the risky data will be migrated to a dedicated secure storage node, which is only accessible to regulators and authorized investigators. Through cross-chain protocols, the data will be forcibly inserted into the "SAFE Compliance Verification" node. The isolation can only be lifted after verification, ensuring that the risks are fully controllable.

[0043] Construct the classified financial dataset F t It is stored in the financial data blockchain management platform and transmitted to the data element rights confirmation analysis module and the blockchain risk joint defense module through an encrypted channel, providing structured data support for subsequent compliance reviews and risk assessments.

[0044] The multi-source financial data acquisition module performs risk screening on marked files based on historical records as follows:

[0045] For the financial dataset F t Copy and generate the retrieved folder-sub-page, perform compliance pre-processing on the data in the retrieved folder-sub-page, remove the un-masked customer biometric data, convert the sensitive fields in the personal information into anonymous identification characters through a hash algorithm or masking method, and generate a compliant data set F t / anon ;

[0046] Retrieve the pre-stored compliance verification code from the financial data blockchain management platform and locate it in the compliance data set F t / anon Multi-type data is supplemented with collection source identification and compliance verification code to form a compliance data set F t / anon Build multi-level protection, and archive pre-processed data into three-dimensional indexes based on time, business, and risk level.

[0047] Example 2: This example is a closed-loop management system that integrates data elements and blockchain. The data element rights confirmation analysis module: receives the financial data set F t Conduct ownership verification, combining financial regulatory rules with historical ownership records r , generate a compliance dataset F t / anon , compliance authorization signal S a or overriding warning signal S u And send it to the blockchain risk joint defense module; the data element right confirmation analysis module analyzes the compliance data set F t / anon The analysis process is as follows:

[0048] Receive the compliance dataset F t / anon Then, the data usage simulation scenarios are restored one by one based on the multiple data types in the collection, and the pre-stored authorizer agreement threshold, financial institution data sharing agreement threshold and compliance data set F are retrieved from the financial data blockchain management platform. t / anon Analyze multiple types of data one by one:

[0049] If a single retail transaction file is marked as high-risk cross-border risk tag / a , and only the “domestic use” style mark is marked in the authorization agreement threshold range, then an unauthorized warning signal S is generated. u , with the unauthorized type "cross-border use without authorization" style mark, the distributed compliance control module receives the unauthorized warning signal S u , and generates an unauthorized warning signal S u The compliance dataset F t / anon Marked as high risk cross-border risk tag / a, based on the regulatory plan rules pre-stored within the financial data blockchain management platform, generate a prohibition instruction on cross-border transmission. At the same time, use the smart contract signed between the financial data blockchain management platform and the original data acquisition source to trigger a deletion instruction, delete or lock the cross-border transmission path records in the blockchain, and generate a regulatory alert log for back-end retrieval and query and as a basis for historical data judgment;

[0050] If there is a protocol permission query / verification mark in the multi-type data, and the purpose of use is within the query range and verification range, a compliance authorization signal S is generated. a , construct the ownership confirmation mark and compliance dataset F based on the multiple analysis results t / anon Bind to the chain to form an unalterable record of ownership H r The module automatically triggers an early warning work order and pushes it to the compliance department for manual review.

[0051] Blockchain risk joint defense module: Based on financial data set F t , compliance authorization signal S a / Override warning signal S u and historical risk event database H f , analyze cross-institutional circulation risks and generate risk warning signals S w And send it to the distributed compliance control module; the blockchain risk joint defense module processes the compliance data set F t / anon The further analysis process is as follows:

[0052] Receive the compliance dataset F t / anon , compliance authorization signal S a and over-authority warning signal S u Then, the pre-stored historical risk event database H is retrieved from the financial data blockchain management platform. f Conduct joint risk analysis:

[0053] Analyze the historical risk event database H f The ratio of compliance and unauthorized values ​​in the above table generates the upper limit of the compliance risk index. If the unauthorized warning signal S u > compliance risk index upper limit, then generate compliance risk warning S w1 ;

[0054] Analyze the historical risk event database H f Medium-to-high risk swap tag / b The average number of IP address distributions is used to generate the cross-border risk threshold:

[0055] If the compliance dataset F t / anon Medium-to-high risk swap tag / b If the number of IP address distributions is greater than the cross-border risk threshold, a cross-border operation abnormality signal S is generated. w2When batch unauthorized data is detected, the distributed compliance control module receives the compliance authorization signal S a After that, we will detect suspicious cross-border operation abnormal signals S that meet the characteristics of high-frequency transfer + cross-region IP. w2 To conduct supervision, the relevant pre-stored suspicious plan rule threshold matching is retrieved from the financial data blockchain management platform. If the match is successful, a large transaction report CTR is generated and fed back to the financial data blockchain management platform, generating a large suspicious transaction abnormality alert. At the same time, the relevant data generated by the large suspicious transaction abnormality alert is marked and copied - a copy is marked with an abnormal identifier, and an abnormal storage log is generated for quick reference through subsequent abnormal alerts and used as historical record reference data. The control rules can be dynamically updated through the alliance chain consensus mechanism to ensure that the system continues to meet the latest regulatory requirements;

[0056] Analyze the historical risk event database H f Medium to high risk credit risk tag / c Matching blacklist database, if high risk credit risk tag / c If it is in the blacklist database, a potential abnormal trustless association S is generated. w3 .

[0057] The risk signal level of low, medium and high is retrieved from the financial data blockchain management platform. If the compliance data set F t / anon Analyze and generate a single set of risk signals, such as potential abnormal trust association S w3 , it is judged as low risk. After receiving the low-risk signal, the distributed compliance control module automatically sends a risk warning to the business department and recommends manual review of the customer's credit qualifications;

[0058] If there are two groups generated at the same time, such as the potential abnormal trust association S w3 and cross-border operation abnormal signal S w2 , they are respectively judged as medium risk. After receiving the medium risk signal, the distributed compliance control module triggers the transaction limit mechanism. For example, the daily transfer limit is reduced from 5 million yuan to 1 million yuan, and the authorized user is required to perform a secondary identity verification.

[0059] If there are three groups generated simultaneously, such as the potential abnormal trust association S w3 , Abnormal signal of cross-border operation S w2 and compliance risk warningS w1, they are respectively judged as high risk. After receiving the high-risk signal, the distributed compliance control module triggers the cross-institutional joint defense mechanism signal, immediately freezes the risky account, terminates the cross-chain transaction process, and reports the suspicious transaction report STR to the externally connected currency transaction monitoring center, shares the risk characteristics with all financial institutions in the alliance chain in real time, and broadcasts the risk account identification through the alliance chain to prevent it from opening an account in other institutions. The control plan follows the "least privilege principle", for example, only restricting the risky transaction types, without affecting other normal business of authorized users, to ensure a balance between compliance and authorized user experience.

[0060] Retrieve the risk agreement of the financial data area connection internal database, external information source connection port, and third-party information aggregation port from the financial data blockchain management platform, and build a cross-chain risk mapping threshold table M in the financial field in combination with the internal risk determination plan c :

[0061] When the high risk of internal database crosses borders tag / a When there is duplication or transfer of shared information between data and external information source connection port, call the compliant data set F t / anon Generate relevant compliance dataset F t / anon Compare the original data to generate a comparison duplication percentage value, and compare it with the cross-chain risk mapping threshold table M in the financial field c Perform a reference comparison. If the comparison duplication percentage value exceeds the financial field cross-chain risk mapping threshold table M c If the upper limit of the mark is reached, the cross-chain delay risk signal S x , the distributed compliance control module receives the cross-chain delay risk signal S x After that, cross-chain delay risk signal S x It is bound to the cross-institutional data flow path and the compliance check nodes are forcibly inserted through smart contracts. For example, a "SAFE compliance verification" style node is added to the cross-border payment process. The flow can only continue after verification.

[0062] Distributed compliance control module: automatically matches and triggers preset stored financial regulatory policies based on the received risk signals, generates compliance control plans, executes them through smart contracts and feeds them back to the financial data blockchain management platform. It should be noted that smart contracts are one of the key technologies for blockchain technology integration, and together with encryption technology and distributed networks, they constitute the blockchain's technical system, which is used to realize automated business processes and rule execution. Through pre-set logical codes, it automatically verifies and executes the rules in the circulation of data elements, such as automated processing in scenarios such as data ownership verification, authority management, and risk prevention and control.

[0063] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

[0064] In the description of this specification, the descriptions with reference to the terms "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. Related accessories include couplings, screws, gears, gaskets and other commonly used mechanical connection components in this field, but are not limited to these. They are replaced and adapted according to actual use.

[0065] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A closed-loop management system integrating data elements and blockchain, characterized by: The financial data blockchain management platform is connected to a multi-source financial data collection module for collecting and deploying regulatory areas, marking the original data according to the time node and classifying and filtering it to generate a financial data set F with a timestamp and risk label. t And send it to the data element rights confirmation analysis module and the blockchain risk joint defense module; Data element ownership analysis module: for the received financial data set F t Conduct ownership verification, combining financial regulatory rules with historical ownership records r , generate a compliance dataset F t / anon , compliance authorization signal S a or overriding warning signal S u And send it to the blockchain risk joint defense module; Blockchain risk joint defense module: Based on financial data set F t , compliance authorization signal S a / Override warning signal S u and historical risk event database H f , analyze cross-institutional circulation risks and generate risk warning signals S w And send it to the distributed compliance control module; Distributed compliance control module: Automatically matches and triggers preset stored financial regulatory policies based on received risk signals, generates compliance control plans, executes them through smart contracts and feeds them back to the financial data blockchain management platform.

2. The closed-loop management system integrating data elements and blockchain according to claim 1 is characterized in that: The multi-source financial data collection module performs the following processing based on the raw data collected in the deployment supervision area: According to the financial data blockchain management platform, the deployment supervision area intercepts the time period for key data processing instructions, extends it to the intercepted time period according to the historical collection time frequency, and constructs a new extended time node to give a timestamp mark to the collected original data. The deployment supervision area includes the financial data area connecting to the internal database, the external information source connection port, and the third-party information aggregation port, constructing the precise target of original data collection, and the target type to construct a tag file, such as retail transaction files, corporate business files, cross-border payment files and multiple groups of data storage tag files.

3. The closed-loop management system for integrating data elements and blockchain according to claim 2 is characterized in that: The multi-source financial data acquisition module performs risk screening on marked files based on historical records as follows: Retrieve the pre-stored high-risk reference template from the financial data blockchain management platform and compare it with the marked files. If the cross-border payment file is greater than the pre-stored cross-border risk threshold, the cross-border payment file data will be marked as high-risk cross-border risk. tag / a If the corporate business file is greater than the pre-stored transfer upper limit, the corporate business file data will be marked as high risk. tag / b If the retail transaction file is greater than the pre-stored credit threshold, the retail transaction file data is marked as high risk credit risk. tag / c , and construct the classified financial dataset F t Stored on the financial data blockchain management platform.

4. The closed-loop management system for integrating data elements and blockchain according to claim 3 is characterized in that: The multi-source financial data acquisition module performs risk screening on marked files based on historical records as follows: For the financial dataset F t Copy and generate the retrieved folder-sub-page, perform compliance pre-processing on the data in the retrieved folder-sub-page, remove the un-masked customer biometric data, convert the sensitive fields in the personal information into anonymous identification characters through a hash algorithm or masking method, and generate a compliant data set f t / anon , retrieve the pre-stored compliance verification code from the financial data blockchain management platform and add it to the compliance data set F t / anon The multiple types of data are supplemented with collection source identification and compliance verification code to form a compliance data set F t / anon Build multi-level protection, and archive pre-processed data into three-dimensional indexes based on time, business, and risk level.

5. The closed-loop management system integrating data elements and blockchain according to claim 1 is characterized in that: The data element rights confirmation analysis module performs the following operations on the compliance data set F t / anon The analysis process is as follows: Receive the compliance dataset F t / anon Then, the data usage simulation scenarios are restored one by one based on the multiple data types in the collection, and the pre-stored authorizer agreement threshold, financial institution data sharing agreement threshold and compliance data set F are retrieved from the financial data blockchain management platform. t / anon Analyze multiple types of data one by one: If a single retail transaction file data is marked as high-risk cross-border risk tag / a , and only the "domestic use" style mark is marked in the authorization agreement threshold range, then an unauthorized warning signal S is generated. u , with an unauthorized "cross-border use without authorization" style mark; if there is a protocol-permitted query / verification mark in the multi-type data, and the purpose of use is within the query scope and verification scope, a compliance authorization signal S is generated. a , construct the ownership confirmation mark and compliance dataset F based on the multiple analysis results t / anon Bind to the chain to form an unalterable record of ownership H r .

6. The closed-loop management system integrating data elements and blockchain according to claim 1 is characterized in that: The blockchain risk joint defense module is used to check the compliance data set F t / anon The further analysis process is as follows: Receive the compliance dataset F t / anon , compliance authorization signal S a and over-authority warning signal S u Then, the pre-stored historical risk event database H is retrieved from the financial data blockchain management platform. f Conduct joint risk analysis and analyze the historical risk event database H f The ratio of compliance and unauthorized values ​​in the above table generates the upper limit of the compliance risk index. If the unauthorized warning signal S u > compliance risk index upper limit, then generate compliance risk warning S w1 ;Analyze the historical risk event database H f Medium-to-high risk swap tag / b The mean number of IP address distributions is used to generate the cross-border risk threshold. If the compliance dataset F t / anon Medium-to-high risk swap tag / b If the number of IP address distributions is greater than the cross-border risk threshold, a cross-border operation abnormality signal S is generated. w2 ;Analyze the historical risk event database H f Medium to high risk credit risk tag / c Matching blacklist database, if high risk credit risk tag / c If it is in the blacklist database, a potential abnormal trustless association S is generated. w3 .

7. The closed-loop management system integrating data elements and blockchain according to claim 6 is characterized in that: Retrieve the risk agreement of the financial data area connection internal database, external information source connection port, and third-party information aggregation port from the financial data blockchain management platform, and build a cross-chain risk mapping threshold table M in the financial field in combination with the internal risk determination plan c , when the high risk of internal database cross-border risk tag / a When there is duplication or transfer of shared information between data and external information source connection port, call the compliant data set F t / anon Generate relevant compliance dataset F t / anon Compare the original data to generate a comparison duplication percentage value, and compare it with the cross-chain risk mapping threshold table M in the financial field c Perform a reference comparison. If the comparison duplication percentage value exceeds the financial field cross-chain risk mapping threshold table M c If the upper limit of the mark is reached, the cross-chain delay risk signal S x .

8. A closed-loop management method for integrating data elements and blockchain, used for a closed-loop management system for integrating data elements and blockchain as described in any one of claims 1 to 7, characterized in that: The following steps are involved: S1: Intercept time periods according to instructions, construct time nodes and mark them, classify and filter high-risk data, form compliant data sets after preprocessing, and archive and store them; S2: Compare rules and records to generate a confirmation signal, upload the results to the blockchain, and trigger manual review and warning for batch unauthorized use; S3: Generates signals such as compliance and cross-border operation anomalies, and generates cross-chain delay risk signals by comparing cross-chain scenarios; S4: The level is determined based on the number of risk signals, with a single group being low, two groups being medium, and three or more groups being high. After integrating the signals, they are shared through the alliance chain, triggering a cross-institutional joint defense mechanism. S5: The distributed compliance control module matches policies according to risk levels, conducts low-risk prompt reviews, verifies medium-risk limits, freezes high-risk accounts, etc., and executes and feedbacks closed loops through smart contracts.

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