A contract compliance dynamic management and control system and method based on data linkage

Abstract

The present application relates to the technical field of enterprise information management and risk control, and particularly relates to a contract compliance dynamic management and control system and method based on data linkage. The contract compliance dynamic management and control system based on data linkage comprises: a data fusion module, which is used for automatically connecting and integrating internal business data sources and external compliance data sources of an enterprise to form fused data; a compliance monitoring module, which is used for performing real-time dynamic compliance verification on a contract execution process based on the fused data; a supplier verification module, which is used for performing multi-dimensional compliance cross-verification on a supplier at a key node of contract execution based on the fused data; and an early warning and tracing module, which is used for generating a graded risk early warning and performing full-link tracing on a risk event according to verification outputs of the compliance monitoring module and the supplier verification module. By establishing an automatic data connection and processing channel, deep fusion and real-time synchronization of internal and external compliance data are achieved.

Description

Technical Field

[0001] This invention relates to the field of enterprise information management and risk control technology, and in particular to a dynamic contract compliance management system and method based on data linkage. Background Technology

[0002] In business operations, compliant contract execution is a crucial aspect of mitigating legal and operational risks. Traditional contract compliance management models primarily rely on manual review and static checks, which are insufficient to meet the demands for real-time and precise risk control over dynamic business processes. Existing technological solutions have significant limitations in areas such as data integration, process monitoring, and judgment dimensions. Specifically, existing compliance control solutions typically employ the following models: At the data level, internal business systems (such as ERP) and external authoritative data sources (such as credit information platforms) are disconnected. Updates to key external compliance information rely on manual entry and synchronization, resulting in poor data timeliness and incompleteness, creating "data silos." At the process monitoring level, a combination of preset approval nodes and periodic post-event reviews is often used, failing to provide real-time monitoring of dynamic business flows such as fund payments and performance progress during contract execution. This leads to severe delays in risk detection, often missing the optimal intervention window. At the supplier management level, the verification dimensions are singular, usually only checking the internal blacklist or manually reviewing the qualification documents at the time of admission. There is a lack of multi-dimensional and dynamic cross-verification of the supplier's external credit, the continued validity of the qualification, and the historical performance. As a result, some suppliers with external dishonesty or qualification defects have not been effectively identified.

[0003] In summary, existing technologies suffer from inefficient compliance management and passive risk control in enterprise contract execution due to a lack of internal and external data linkage, insufficient real-time monitoring, and one-sided verification dimensions. Therefore, there is an urgent need for a technological solution that can automatically integrate internal and external data, achieve dynamic monitoring throughout the entire process, and perform multi-dimensional intelligent analysis to improve the initiative, accuracy, and real-time nature of contract compliance management. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the problems in the existing technology, such as the lack of internal and external data linkage, insufficient real-time monitoring, and one-sided verification dimensions, which lead to low efficiency in compliance management and passive risk prevention and control of enterprise contract execution.

[0005] To address the aforementioned technical problems, this invention provides a data-driven dynamic contract compliance management system, comprising: The data fusion module is used to automatically connect to and integrate internal business data sources and external compliant data sources to form fused data. The compliance monitoring module, connected to the data fusion module, is used to perform real-time dynamic compliance verification of the contract execution process based on the fused data. The supplier verification module is connected to the data fusion module and is used to perform multi-dimensional cross-compliance verification of suppliers at key nodes of contract execution based on the fused data. The early warning and tracing module is connected to the compliance monitoring module and the supplier verification module. It is used to generate graded risk warnings based on the verification outputs of the compliance monitoring module and the supplier verification module, and to trace the risk events through the entire chain.

[0006] Preferably, the data fusion module includes: The data interface unit is used to connect internal business data sources and external compliance data sources to obtain internal business data and external compliance data. A data processing unit, connected to the data interface unit, is used to clean, align, and correlate the internal business data and the external compliance data to generate standardized fused data. A data update unit, connected to the data processing unit, is used to update the fused data according to a preset strategy in order to maintain the timeliness of the fused data.

[0007] Preferably, the compliance monitoring module includes: The data acquisition unit is used to collect business flow data in the contract execution process in real time; The rules engine unit, connected to the data acquisition unit, stores preset compliance rules and is used to match the business flow data with the compliance rules in real time. The verification execution unit is used to perform preset interception or alarm operations and generate verification logs when the business flow data triggers the compliance rules.

[0008] Preferably, the supplier verification module includes: The indicator construction unit is used to build a supplier compliance verification indicator system that includes multiple dimensions. The scoring calculation unit is used to calculate the supplier's compliance score based on the fused data and in accordance with the supplier compliance verification indicator system. The verification triggering unit is used to trigger the calculation and verification of compliance scores for designated suppliers at preset nodes in contract execution.

[0009] Preferably, the early warning and source tracing module includes: The risk assessment unit is used to calculate the risk level of a risk event based on the verification log or the supplier's compliance score. The early warning push unit is used to push risk warning information to different roles according to the risk level; The traceability record unit is used to record the data source, rule identifier, processing process and results related to risk events, forming a traceable log chain.

[0010] This invention also provides a method for dynamic management and control of contract compliance based on data linkage, including: By linking and integrating internal business data with external compliance data, a unified data stream can be formed. Based on the fused data, real-time dynamic compliance monitoring of the contract execution process is performed to obtain compliance monitoring data; Based on the fused data, multi-dimensional compliance cross-verification of suppliers is performed at preset nodes in contract execution to obtain verification data; Based on the compliance monitoring data and the verification data, graded risk warnings and full-chain traceability are carried out.

[0011] Preferably, the process of linking and integrating internal business data with external compliance data to form integrated data includes: Through preset data interfaces, internal business data is obtained from internal business data sources of the enterprise, and external compliance data is obtained from external compliance data sources. The internal business data and the external compliance data are cleaned, entity aligned, and associated with each other to generate standardized fused data. The fused data is updated according to a scheduled task or event triggering mechanism.

[0012] Preferably, the real-time dynamic compliance monitoring of the contract execution process based on the fused data, to obtain compliance monitoring data, includes: Real-time collection of business flow data during contract execution; The business flow data is matched with preset compliance rules in real time. When the business flow data triggers the compliance rule, the corresponding risk handling operation is executed, and a verification log containing the triggering rule is generated.

[0013] Preferably, based on the fused data, the supplier undergoes multi-dimensional compliance cross-verification at preset nodes in contract execution to obtain verification data, including: Construct a supplier compliance verification indicator system that includes multiple predefined dimensions; At a predetermined point in contract execution, the compliance score of the target supplier is calculated based on the fused data and in accordance with the supplier compliance verification indicator system. The compliance score is compared with a preset threshold to determine the compliance status of the target supplier.

[0014] Preferably, the step of performing graded risk warning and full-chain traceability based on the compliance monitoring data and the verification data includes: Based on the verification logs or the compliance scores, assess the risk value of risk events and classify the risk levels; Based on the risk level, the risk warning information will be pushed to the corresponding processing role; Record the complete processing chain information related to the risk event to form a queryable traceability record.

[0015] The technical solution of the present invention has the following advantages over the prior art: This invention discloses a data-driven dynamic contract compliance management system and method. By establishing automated data connection and processing channels, it overcomes the problems of information lag and lack of evidence caused by traditional "data silos," providing a complete, accurate, and timely data foundation for compliance judgments and significantly reducing the risk of misjudgment due to incomplete information. Through streaming data processing and rule engine technology, the timing of risk identification and intervention is shifted from post-event review to during or even before the event, enabling the immediate detection and blocking of violations such as unauthorized payments and overdue performance, fundamentally changing the passive situation of traditional static, post-event management. By constructing a comprehensive verification indicator system and introducing external multi-source data, supplier compliance management is upgraded from a single, static internal list verification to a dynamic cross-verification covering multiple dimensions such as credit, qualifications, and performance records, significantly improving the accuracy and coverage of non-compliant supplier identification. By establishing a risk quantification assessment model, intelligent risk level classification and targeted push are achieved, improving the pertinence and efficiency of early warnings. Meanwhile, by recording the full-chain data fingerprint and processing logs of risk events, the time for tracing the source can be significantly shortened from the traditional manual step-by-step investigation, and the root cause of the problem can be quickly located. Attached Figure Description

[0016] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings, wherein: Figure 1 This is a structural diagram of a contract compliance dynamic management and control system based on data linkage provided by the present invention; Figure 2 This is a flowchart of a dynamic contract compliance management method based on data linkage provided by the present invention; Figure 3 It is a flowchart of the automated linkage and integration of internal and external data; Figure 4 This is a flowchart of the supplier's multi-dimensional compliance cross-verification process; Figure 5 This is the overall system architecture diagram; Figure 6 This is the flowchart of the core module. Detailed Implementation

[0017] The core of this invention is to provide a dynamic contract compliance management system based on data linkage, which achieves deep integration and real-time synchronization of internal and external compliance data by establishing an automated data docking and processing channel.

[0018] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please refer to Figure 1. Figure 1 The logical relationship diagram of a data-linked dynamic contract compliance management system provided by this invention is shown below; the specific operation steps are as follows: The data fusion module is used to automatically connect to and integrate internal business data sources and external compliant data sources to form merged data. The data fusion module includes: The data interface unit is used to connect internal business data sources and external compliance data sources to obtain internal business data and external compliance data. A data processing unit, connected to the data interface unit, is used to clean, align, and correlate the internal business data and the external compliance data to generate standardized fused data. A data update unit, connected to the data processing unit, is used to update the fused data according to a preset strategy in order to maintain the timeliness of the fused data.

[0020] Specifically, a multi-source data interface system is constructed: internally, it connects to the contract management system, ERP system, internal supplier blacklist database, and approval system to obtain data such as contract terms, payment records, approval permissions, and internal credit default markers; externally, it connects to the National Enterprise Credit Information Publicity System API to capture supplier external credit scores, credit default records, qualification validity periods, and industry compliance standard updates in real time. Data cleaning and fusion processing: Entity alignment algorithms are used to remove duplicate data and clean data with inconsistent formats; data association mapping is established through knowledge graphs; Dynamic data update mechanism: Set up timed external data retrieval and triggered updates to ensure timely synchronization of internal and external data.

[0021] It solves the problem of poor internal and external data linkage, reducing the data update lag from more than 72 hours under existing technology to less than or equal to 5 minutes, and improving the data dimension coverage from less than 60% to 100%; it eliminates data silos, with the accuracy of internal and external data linkage greater than or equal to 98%, and the missing basis rate for compliance judgment reduced to 1%, avoiding the risk of misjudgment due to incomplete data.

[0022] A compliance monitoring module, connected to the data fusion module, is used to perform real-time dynamic compliance verification of the contract execution process based on the fused data; wherein, the compliance monitoring module includes: The data acquisition unit is used to collect business flow data in the contract execution process in real time; The rules engine unit, connected to the data acquisition unit, stores preset compliance rules and is used to match the business flow data with the compliance rules in real time. The verification execution unit is used to perform preset interception or alarm operations and generate verification logs when the business flow data triggers the compliance rules.

[0023] Specifically, the real-time data acquisition layer: based on a stream processing framework (such as Apache Flink), it accesses real-time data from the entire contract execution process—performance progress data, financial data, and acceptance data; Compliance rules engine: Visually configure multi-dimensional compliance rules, and the rule triggering logic supports "real-time data matching and verification"; Real-time verification and interception: When real-time data meets the rule triggering conditions, the system automatically pauses the business process and generates a real-time verification log, recording the triggering rule, data source, and interception time.

[0024] It solves the problem of lagging compliance monitoring, with a risk identification response time of less than 1 second, representing an improvement of 1.296 × 10⁻⁶ days compared to existing technologies (lagging by 15-30 days). 5 This achieves a multiple; it enables risk prevention, with over 80% of potential compliance risks being intercepted before business execution, thus preventing risks from actually occurring.

[0025] A supplier verification module, connected to the data fusion module, is used to perform multi-dimensional compliance cross-verification of suppliers at key points in contract execution based on the fused data; wherein, the supplier verification module includes: The indicator construction unit is used to build a supplier compliance verification indicator system that includes multiple dimensions. The scoring calculation unit is used to calculate the supplier's compliance score based on the fused data and in accordance with the supplier compliance verification indicator system. The verification triggering unit is used to trigger the calculation and verification of compliance scores for designated suppliers at preset nodes in contract execution.

[0026] Specifically, a "5-dimensional verification indicator system" is constructed, including internal blacklist, external credit rating, qualification validity, historical performance compliance record, and regulatory compliance status. Cross-validation algorithm: A weighted scoring model is used to calculate the supplier's compliance score. A threshold is set, and if the score is lower than the threshold, the supplier is judged to be non-compliant. Dynamic verification trigger: Verification is automatically triggered at key nodes in contract execution. If the supplier's compliance status changes, the score is updated in real time and an alert is triggered.

[0027] It solves the problem of lagging compliance monitoring: the risk identification response time is less than or equal to 1 second, which is 1.296×10 times faster than existing technologies (lagging by 15-30 days). 5 It achieves multiple times the risk prevention: over 80% of potential compliance risks are intercepted before business execution, preventing risks from actually occurring.

[0028] The early warning and source tracing module, connected to the compliance monitoring module and the supplier verification module, is used to generate tiered risk warnings based on the verification outputs of the compliance monitoring module and the supplier verification module, and to perform full-chain source tracing of risk events. The early warning and source tracing module includes: The risk assessment unit is used to calculate the risk level of a risk event based on the verification log or the supplier's compliance score. The early warning push unit is used to push risk warning information to different roles according to the risk level; The traceability record unit is used to record the data source, rule identifier, processing process and results related to risk events, forming a traceable log chain.

[0029] Specifically, the risk level calculation model calculates the risk value based on "risk impact level × probability of occurrence × data credibility" and divides it into three levels of early warning: high, medium and low. Intelligent early warning push: High-risk warnings are pushed to compliance specialists and business managers in real time, triggering emergency handling procedures; medium-risk warnings are pushed to business managers for verification within a specified period; low-risk warnings are only notified by the system. End-to-end traceability mechanism: adopts "log chain + data fingerprint" to record risk events - including the internal and external data sources that trigger the risk, the verification rule ID, the person in charge, and the processing result, and supports one-click backtracking of the entire risk judgment process.

[0030] It solves the problem of low accuracy in early warning: the false alarm rate has been reduced from greater than or equal to 30% under existing technology to less than or equal to 5%, and the missed alarm rate has been reduced from greater than or equal to 20% to less than or equal to 1%; it also solves the problem of weak traceability: the risk traceability time has been shortened from greater than or equal to 4 hours under existing technology to less than or equal to 10 seconds, and the responsible link can be quickly located.

[0031] This embodiment provides a data-driven dynamic contract compliance management system and method. By establishing automated data connection and processing channels, it overcomes the information lag and lack of evidence caused by traditional "data silos," providing a complete, accurate, and timely data foundation for compliance judgments and significantly reducing the risk of misjudgment due to incomplete information. Through streaming data processing and rule engine technology, the timing of risk identification and intervention is shifted from post-event review to during or even before the event, enabling the immediate detection and blocking of violations such as unauthorized payments and overdue performance, fundamentally changing the passive situation of traditional static, post-event management. By constructing a comprehensive verification indicator system and introducing external multi-source data, supplier compliance management is upgraded from a single, static internal list check to a dynamic cross-verification covering multiple dimensions such as credit, qualifications, and performance records, significantly improving the accuracy and coverage of non-compliant supplier identification. By establishing a risk quantification assessment model, intelligent risk level classification and targeted push are achieved, improving the pertinence and efficiency of early warnings. Meanwhile, by recording the full-chain data fingerprint and processing logs of risk events, the time for tracing the source can be significantly shortened from the traditional manual step-by-step investigation, and the root cause of the problem can be quickly located.

[0032] like Figure 2 As shown, Figure 2 The present invention provides a data-driven dynamic management method for contract compliance, as detailed below: Step S201: Integrate and merge internal business data with external compliance data to form integrated data; Step S202: Based on the fused data, perform real-time dynamic compliance monitoring of the contract execution process to obtain compliance monitoring data; Step S203: Based on the fused data, perform multi-dimensional compliance cross-verification of the supplier at preset nodes of contract execution to obtain verification data; Step S204: Based on the compliance monitoring data and the verification data, perform graded risk warning and full-chain traceability.

[0033] Based on the above embodiments, this embodiment will provide a detailed description of step S201: In one embodiment, such as Figure 3 As shown, internal business data is obtained from internal business data sources and external compliance data is obtained from external compliance data sources through preset data interfaces; The internal business data and the external compliance data are cleaned, entity aligned, and associated with each other to generate standardized fused data. The fused data is updated according to a scheduled task or event triggering mechanism.

[0034] Based on the above embodiments, this embodiment will provide a detailed description of step S202: In one embodiment, business flow data in the contract execution process is collected in real time; The business flow data is matched with preset compliance rules in real time. When the business flow data triggers the compliance rule, the corresponding risk handling operation is executed, and a verification log containing the triggering rule is generated.

[0035] Based on the above embodiments, this embodiment will provide a detailed description of step S203: In one embodiment, such as Figure 4 As shown, a supplier compliance verification indicator system with multiple predefined dimensions is constructed; At a predetermined point in contract execution, the compliance score of the target supplier is calculated based on the fused data and in accordance with the supplier compliance verification indicator system. The compliance score is compared with a preset threshold to determine the compliance status of the target supplier.

[0036] Based on the above embodiments, this embodiment will provide a detailed description of step S204: In one embodiment, the risk value of a risk event is assessed and the risk level is classified based on the verification log or the compliance score; Based on the risk level, the risk warning information will be pushed to the corresponding processing role; Record the complete processing chain information related to the risk event to form a queryable traceability record.

[0037] This embodiment provides a data-driven dynamic management method for contract compliance. By establishing an automated data connection and processing channel, it overcomes the problems of information lag and lack of evidence caused by traditional "data silos," providing a complete, accurate, and timely data foundation for compliance judgments and significantly reducing the risk of misjudgment due to incomplete information. Through streaming data processing and rule engine technology, the timing of risk identification and intervention is shifted from post-event review to during or even before the event, enabling the immediate detection and blocking of violations such as unauthorized payments and overdue performance, fundamentally changing the passive situation of traditional static, post-event management. By constructing a comprehensive verification indicator system and introducing external multi-source data, supplier compliance management is upgraded from a single, static internal list verification to a dynamic cross-verification covering multiple dimensions such as credit, qualifications, and performance records, significantly improving the accuracy and coverage of non-compliant supplier identification. By establishing a risk quantification assessment model, intelligent risk level classification and targeted push are achieved, improving the pertinence and efficiency of early warnings. Meanwhile, by recording the full-chain data fingerprint and processing logs of risk events, the time for tracing the source can be significantly shortened from the traditional manual step-by-step investigation, and the root cause of the problem can be quickly located.

[0038] Based on the above embodiments, this embodiment provides a detailed description of a data-driven dynamic management and control system for contract compliance, such as... Figure 5 As shown, the details are as follows: The data layer, serving as the system's data foundation, has the core function of automating the collection and fusion of internal and external data. Specifically, the data layer includes: Internal data source access unit: such as Figure 6 As shown, it can connect with the enterprise's contract management system, enterprise resource planning system, financial system and supplier management database through a preset enterprise service bus or API interface, and automatically obtain contract texts, approval process records, payment application and execution data, internal supplier directory and blacklist information.

[0039] External data source access unit: By calling the application programming interfaces of external public service platforms, such as the National Enterprise Credit Information Publicity System, industry regulatory databases, and data interfaces of third-party commercial credit reporting agencies, it automatically obtains the target supplier's business registration information, credit rating, administrative penalty records, qualification certificate status, and industry compliance standard changes.

[0040] The integrated data warehouse receives raw data from internal and external data source access units, and performs preprocessing operations such as data cleaning (e.g., deduplication and format standardization) and entity alignment (e.g., using the unified social credit code as the core identifier to associate different sources of data from the same supplier) to form standardized and interconnected integrated data, providing a unified and complete data view for upper-layer applications.

[0041] The platform layer, serving as the core capability support of the system, encapsulates four core engines based on the fused data provided by the data layer: Data Linkage and Fusion Engine: This engine encapsulates the core processing logic of the data layer, is responsible for scheduling data collection, cleaning, alignment and fusion tasks, and manages the data update strategy that combines "timed polling" and "event triggering" to ensure the timeliness of information in the fused data warehouse.

[0042] Real-time compliance monitoring engine: This engine is built on a stream processing framework and subscribes in real time to the business event stream generated during contract execution (such as "payment application submission" and "performance node completion"). The engine has a pre-configured compliance rule base. When streaming data matches the rule conditions, the engine triggers verification immediately and can automatically intercept risky operations by sending instructions to the business process system, while generating structured risk event logs.

[0043] Supplier Multidimensional Verification Engine: This engine predefines a supplier compliance assessment model that includes multiple dimensions (such as entity qualification, credit status, qualification status, and historical behavior). In scenarios such as contract signing, key performance milestones, or periodic assessments, the engine automatically retrieves relevant information about the supplier from the integrated data warehouse, performs model calculations, and outputs a compliance score and status conclusion.

[0044] Risk Warning and Traceability Engine: This engine receives outputs (risk event logs, supplier compliance status changes) from the real-time compliance monitoring engine and the supplier multi-dimensional verification engine. First, it calculates the risk level based on factors such as the scope of risk impact and probability of occurrence. Second, based on the level, it pushes warning information to pre-defined compliance specialists, business managers, and other roles via message queues or internal communication tools. Finally, it associates and records all data sources, triggering rules, processing procedures, and participating personnel involved in this risk event, forming an immutable traceability chain, which is stored in the traceability log database.

[0045] The application layer, as the output interface of the system capabilities, provides specific business function modules to end users: Compliance Monitoring Dashboard: Provides compliance managers with a visual view that centrally displays information such as real-time captured risk events, system interception statistics, and distribution of high-risk contracts, and supports drill-down analysis of abnormal events.

[0046] Supplier Compliance Verification Portal: Provides an interface for procurement and business personnel to manually or automatically initiate multi-dimensional compliance verifications of specific suppliers at stages such as supplier onboarding and before contract signing, and displays detailed assessment reports and risk warnings.

[0047] Risk Warning Center: Provides personalized warning message inboxes for managers at all levels, displays warning information according to risk level, and includes links to preliminary analysis conclusions and handling suggestions, supporting one-click jump to the handling process.

[0048] End-to-end traceability query platform: When a compliance dispute occurs or an issue review is required, authorized users can quickly retrieve and visualize the complete chain of occurrence, judgment, warning and handling of the event by entering the contract number, supplier name or risk event ID, and accurately locate the problematic link.

[0049] In this embodiment, the data flow runs through a three-layer architecture from bottom to top: the data layer is responsible for aggregating and standardizing raw data; the four engines of the platform layer provide core intelligent processing capabilities based on this data; and the application layer encapsulates these capabilities into business functions tailored to user scenarios. The entire process achieves automated closed-loop management from multi-source heterogeneous data collection to intelligent risk identification and intervention, and finally to result presentation and traceability, significantly improving the initiative, accuracy, and efficiency of enterprise contract execution compliance management.

[0050] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A dynamic contract compliance management system based on data linkage, characterized in that, include: The data fusion module is used to automatically connect to and integrate internal business data sources and external compliant data sources to form fused data. The compliance monitoring module, connected to the data fusion module, is used to perform real-time dynamic compliance verification of the contract execution process based on the fused data. The supplier verification module, connected to the data fusion module, is used to perform multi-dimensional compliance cross-verification of suppliers at key nodes in contract execution based on the fused data. The early warning and tracing module is connected to the compliance monitoring module and the supplier verification module. It is used to generate graded risk warnings based on the verification outputs of the compliance monitoring module and the supplier verification module, and to trace the risk events through the entire chain.

2. The contract compliance dynamic management and control system based on data linkage according to claim 1, characterized in that, The data fusion module includes: The data interface unit is used to connect internal business data sources and external compliance data sources to obtain internal business data and external compliance data. A data processing unit, connected to the data interface unit, is used to clean, align, and correlate the internal business data and the external compliance data to generate standardized fused data. A data update unit, connected to the data processing unit, is used to update the fused data according to a preset strategy in order to maintain the timeliness of the fused data.

3. The contract compliance dynamic management and control system based on data linkage according to claim 1, characterized in that, The compliance monitoring module includes: The data acquisition unit is used to collect business flow data in the contract execution process in real time; The rules engine unit, connected to the data acquisition unit, stores preset compliance rules and is used to match the business flow data with the compliance rules in real time. The verification execution unit is used to perform preset interception or alarm operations and generate verification logs when the business flow data triggers the compliance rules.

4. The contract compliance dynamic management and control system based on data linkage according to claim 3, characterized in that, The supplier verification module includes: The indicator construction unit is used to build a supplier compliance verification indicator system that includes multiple dimensions. The scoring calculation unit is used to calculate the supplier's compliance score based on the fused data and in accordance with the supplier compliance verification indicator system. The verification triggering unit is used to trigger the calculation and verification of compliance scores for designated suppliers at preset nodes in contract execution.

5. The contract compliance dynamic management and control system based on data linkage according to claim 4, characterized in that, The early warning and source tracing module includes: The risk assessment unit is used to calculate the risk level of a risk event based on the verification log or the supplier's compliance score. The early warning push unit is used to push risk warning information to different roles according to the risk level; The traceability record unit is used to record the data source, rule identifier, processing process and results related to risk events, forming a traceable log chain.

6. A method for dynamic management and control of contract compliance based on data linkage, characterized in that, include: By linking and integrating internal business data with external compliance data, a unified data stream can be formed. Based on the fused data, real-time dynamic compliance monitoring of the contract execution process is performed to obtain compliance monitoring data; Based on the fused data, multi-dimensional compliance cross-verification of suppliers is performed at preset nodes in contract execution to obtain verification data; Based on the compliance monitoring data and the verification data, graded risk warnings and full-chain traceability are carried out.

7. The contract compliance dynamic management method based on data linkage according to claim 6, characterized in that, The process of linking and integrating internal business data with external compliance data to form integrated data includes: Through preset data interfaces, internal business data is obtained from internal business data sources of the enterprise, and external compliance data is obtained from external compliance data sources. The internal business data and the external compliance data are cleaned, entity aligned, and associated with each other to generate standardized fused data. The fused data is updated according to a scheduled task or event triggering mechanism.

8. The contract compliance dynamic management method based on data linkage according to claim 7, characterized in that, The real-time dynamic compliance monitoring of the contract execution process based on the fused data, and the resulting compliance monitoring data, include: Real-time collection of business flow data during contract execution; The business flow data is matched with preset compliance rules in real time. When the business flow data triggers the compliance rule, the corresponding risk handling operation is executed, and a verification log containing the triggering rule is generated.

9. The contract compliance dynamic management method based on data linkage according to claim 8, characterized in that, Based on the fused data, multi-dimensional compliance cross-verification is performed on suppliers at preset nodes in contract execution, and the resulting verification data includes: Construct a supplier compliance verification indicator system that includes multiple predefined dimensions; At a predetermined point in contract execution, the compliance score of the target supplier is calculated based on the fused data and in accordance with the supplier compliance verification indicator system. The compliance score is compared with a preset threshold to determine the compliance status of the target supplier.

10. The contract compliance dynamic management method based on data linkage according to claim 9, characterized in that, The step of conducting tiered risk warnings and full-chain traceability based on the compliance monitoring data and the verification data includes: Based on the verification logs or the compliance scores, assess the risk value of risk events and classify the risk levels; Based on the risk level, the risk warning information will be pushed to the corresponding processing role; Record the complete processing chain information related to the risk event to form a queryable traceability record.

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