Intelligent recommendation method, system and device for digital supervision risk monitoring strategy and medium

Abstract

The present application relates to a kind of digital supervision risk monitoring strategy intelligent recommendation method, system, equipment and medium, the method includes constructing multi-source heterogeneous risk knowledge base, and the real-time risk alarm generated by business system is acquired;According to real-time risk alarm, determine risk subject, and the context data of risk subject is obtained from business system, in combination with multi-source heterogeneous risk knowledge base, real-time risk alarm and context data are understood and associated mining with semantics, generate dynamic risk portrait;According to dynamic risk portrait, generate structured risk disposal strategy, and structured risk disposal strategy includes disposal suggestion, operation process guide, system basis reference and similar case reference;The confirmation result of structured risk disposal strategy is acquired, and according to confirmation result, determine the structured risk disposal strategy after confirmation, and then generate work order instruction.The present application has the effect of improving disposal efficiency.

Description

Technical Field

[0001] This invention belongs to the technical field of enterprise supply chain risk management, and in particular relates to a method, system, device and medium for intelligent recommendation of digital supervision and risk monitoring strategies. Background Technology

[0002] Currently, in the field of enterprise supply chain risk management, especially in key business areas such as power materials, business processes involve multiple links such as planning, bidding, contracts, warehousing, quality supervision, and supplier relationship management. Risk events are usually associated with information such as business entities, contract performance, system requirements, and historical handling records. Risk supervision work has high requirements for alarm identification, timeliness of handling, and accuracy of handling basis.

[0003] Existing risk monitoring methods mainly rely on preset rules and fixed monitoring nodes. They identify risks such as contract signing delays, excessive inventory backlogs, and abnormal supply performance by periodically scanning the database and comparing preset conditions. After an alarm is triggered, risk supervisors rely on their personal experience to review system documents, understand the alarm context, and formulate handling opinions. This results in a long risk handling process, low standardization of handling suggestions, and difficulty in reusing historical handling experience in similar risk scenarios. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, device, and medium for intelligent recommendation of risk monitoring strategies for digital supervision, so as to solve the technical problem that existing risk monitoring strategy recommendation methods rely on fixed rules and human experience, resulting in delayed response.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides an intelligent recommendation method for digital supervision and risk monitoring strategies, the method comprising: Build a multi-source heterogeneous risk knowledge base and obtain real-time risk alerts generated by business systems; The risk subject is determined based on the real-time risk alarm, and the context data of the risk subject is obtained from the business system. The real-time risk alarm and the context data are combined with the multi-source heterogeneous risk knowledge base to perform semantic understanding and association mining to generate a dynamic risk profile. A structured risk management strategy is generated based on the dynamic risk profile. Obtain the confirmation result of the structured risk handling strategy, determine the confirmed structured risk handling strategy based on the confirmation result, and then generate a work order instruction.

[0006] By adopting the above technical solutions, and by constructing a multi-source heterogeneous risk knowledge base and acquiring real-time risk alerts, regulations, historical cases, real-time alerts, and external knowledge can be unified as the basis for risk analysis, thereby improving the data completeness of risk monitoring strategy recommendations. By identifying the risk subject based on real-time risk alerts and acquiring contextual data, alert events can be associated with the business background of the risk subject, thereby avoiding judgments based solely on isolated alerts. By generating dynamic risk profiles by combining the multi-source heterogeneous risk knowledge base, risk content, subject performance, institutional basis, and similar cases can be comprehensively represented, thereby improving the accuracy of risk identification and strategy generation. By generating structured risk handling strategies and work order instructions based on dynamic risk profiles, risk handling suggestions can be transformed into executable business instructions, thereby improving the efficiency of risk handling response.

[0007] In one example, the present invention can be further configured as follows: the construction of a multi-source heterogeneous risk knowledge base includes: Acquire rules, regulations, operating manuals, and compliance requirements related to risk management and create a rules and regulations database; Obtain historical risk event records, handling processes, final results, and post-event analysis reports to form a historical case database; Acquire real-time risk alerts from business systems, as well as relevant laws and regulations, inspection and patrol issues data, and industry standards, to form real-time risk alert information and external knowledge; The rules and regulations database, the historical case database, the real-time risk warning information, and the external knowledge are linked and organized to obtain the multi-source heterogeneous risk knowledge base.

[0008] By adopting the above technical solutions, and by acquiring and associating regulations, historical risk events, real-time risk alerts, and external knowledge, a multi-source heterogeneous risk knowledge base covering institutional basis, historical experience, real-time risks, and external norms can be formed, thereby providing more complete knowledge support for subsequent risk profile construction and disposal strategy generation.

[0009] In one example, the present invention can be further configured as follows: the association and organization of the rules and regulations database, the historical case database, the real-time risk warning information, and the external knowledge to obtain the multi-source heterogeneous risk knowledge base includes: Extract the content of the institutional basis from the aforementioned rules and regulations database and the aforementioned external knowledge, and extract historical risk events, handling processes and final results from the historical case database; The alarm type, risk subject, and severity level in the real-time risk alarm information are correlated with the historical risk events to obtain the corresponding correlation results; The system's basis, historical risk events, handling processes, and final results are categorized according to their respective risk types. Based on the aggregated institutional basis, historical risk events, handling process, final result, and corresponding association result, the multi-source heterogeneous risk knowledge base is obtained.

[0010] By adopting the above technical solution, extracting the content of the regulatory basis from the regulatory database and external knowledge, and associating real-time risk alarm information with historical risk events, it is possible to establish the relationship between current alarms and regulatory basis, historical cases and handling results, thereby improving the ability of the multi-source heterogeneous risk knowledge base to support the retrieval of similar risks and the reuse of handling experience.

[0011] In one example, the present invention can be further configured as follows: determining the risk subject based on the real-time risk alarm, obtaining the context data of the risk subject from the business system, and performing semantic understanding and association mining on the real-time risk alarm and the context data in conjunction with the multi-source heterogeneous risk knowledge base to generate a dynamic risk profile, including: Analyze the real-time risk alarm to determine the risk subject, alarm type, occurrence time, and severity level corresponding to the real-time risk alarm; The context data is obtained by the risk subject from the business system based on historical performance records, past evaluations, and contract terms. By combining the multi-source heterogeneous risk knowledge base, semantic understanding and association mining are performed on the real-time risk alarm and the context data to obtain associated risk information; The dynamic risk profile is generated based on the associated risk information.

[0012] By adopting the above technical solutions, the basic attributes of the current risk event can be clearly identified by analyzing real-time risk alarms to determine the risk subject, alarm type, occurrence time, and severity level, thus providing an accurate target for subsequent context acquisition. By obtaining historical performance records, past evaluations, and contract terms based on the risk subject, the business background of the current risk event can be supplemented, thereby improving the pertinence of risk assessment. By performing semantic understanding and correlation mining on real-time risk alarms and contextual data, related risk information can be obtained, thereby improving the completeness of the risk profile. By generating a dynamic risk profile based on related risk information, a comprehensive description of the current risk event can be formed, thus providing a basis for generating structured risk management strategies.

[0013] In one example, the present invention can be further configured as follows: combining the multi-source heterogeneous risk knowledge base, performing semantic understanding and association mining on the real-time risk alarm and the context data to obtain associated risk information, including: Perform semantic understanding on the real-time risk alarm to determine the risk content of the current risk; Based on the risk subject and the context data, retrieve historical cases, supplier production capacity information and regulatory clauses associated with the current risk from the multi-source heterogeneous risk knowledge base; The associated risk information is obtained by correlating the risk content, historical cases, supplier production capacity, and rules and regulations.

[0014] By adopting the above technical solutions, the semantic understanding of real-time risk alarms can be used to determine the current risk content, clarifying the specific risk meaning reflected by the alarm and reducing the misunderstanding of alarm text. By retrieving historical cases, supplier production capacity, and regulatory clauses based on the risk subject and contextual data, the current risk can be associated with historical experience, subject capabilities, and institutional basis, thereby improving the interpretability and reference value of associated risk information. By correspondingly associating risk content, historical cases, supplier production capacity, and regulatory clauses, associated risk information that characterizes the current risk background and the basis for handling can be formed, thereby improving the accuracy of dynamic risk profile construction.

[0015] In one example, the present invention can be further configured as follows: the generation of a structured risk management strategy based on the dynamic risk profile includes: Based on the risk content and historical performance of the risk subject in the dynamic risk profile, the proposed solutions are generated. Based on the aforementioned handling opinions and suggestions, determine the corresponding execution steps and generate the aforementioned operation process guide; Based on the rules and regulations associated with the dynamic risk profile, generate the reference to the legal basis of the system; Based on the historical cases associated with the dynamic risk profile, the similar case reference is generated; The structured risk management strategy is obtained by combining the proposed solutions, the operational guidelines, the institutional basis, and the similar case references.

[0016] By adopting the above technical solutions, and generating disposal recommendations based on the risk content and historical performance of the risk subjects in the dynamic risk profile, the disposal recommendations can be matched with the current risk status and the historical performance of the subjects, thereby improving the pertinence of the disposal recommendations. By generating operational process guidelines based on the disposal recommendations, the disposal recommendations can be transformed into actionable steps, thereby reducing the operational costs of risk supervisors. By generating institutional basis citations based on rules and regulations, institutional support can be provided for the disposal strategies, thereby improving the traceability of the disposal strategies. By generating similar case references based on historical cases, and combining them with the disposal recommendations, operational process guidelines, and institutional basis citations to form a structured risk disposal strategy, the risk disposal strategy can simultaneously possess recommendation content, execution path, institutional basis, and case references, thereby improving the standardization of risk disposal decisions.

[0017] In one example, the present invention can be further configured as follows: obtaining the confirmation result of the structured risk handling strategy, determining the confirmed structured risk handling strategy based on the confirmation result, and then generating a work order instruction, including: The structured risk management strategy is submitted to the risk supervisor, and the supervisor's confirmation of the structured risk management strategy is obtained. Based on the confirmation result, the structured risk management strategy is confirmed to obtain the confirmed structured risk management strategy. Extract suggestions and operational guidelines for handling the risks from the confirmed structured risk management strategy; Based on the proposed solutions and the operational guidelines, the work order instruction is generated.

[0018] By adopting the above technical solutions, and submitting structured risk management strategies to risk supervisors for confirmation, manual confirmation can be introduced before strategy execution, thereby improving the reliability of strategy application. By obtaining confirmed structured risk management strategies based on the confirmation results, the confirmed or adjusted strategies can be used as the basis for execution, thus preventing unconfirmed strategies from directly entering the management process. By extracting management opinions and operational process guidelines from the confirmed structured risk management strategies, core content that can be converted into executable tasks can be obtained, thereby improving the accuracy of work order generation. By generating work order instructions based on management opinions and operational process guidelines, the management strategies can be transformed into executable task instructions for the business system, thereby improving the efficiency of risk management execution.

[0019] In a second aspect, the present invention provides an intelligent recommendation system for digital supervision and risk monitoring strategies, the system comprising: The knowledge module is used to build a multi-source heterogeneous risk knowledge base and obtain real-time risk alerts generated by business systems. The profiling module is used to determine the risk subject based on the real-time risk alarm, obtain the context data of the risk subject from the business system, and perform semantic understanding and association mining on the real-time risk alarm and the context data in combination with the multi-source heterogeneous risk knowledge base to generate a dynamic risk profile. The strategy module is used to generate structured risk management strategies based on the dynamic risk profile. The instruction module is used to obtain the confirmation result of the structured risk handling strategy, determine the confirmed structured risk handling strategy based on the confirmation result, and then generate a work order instruction.

[0020] By adopting the above technical solutions, and by constructing a multi-source heterogeneous risk knowledge base and acquiring real-time risk alerts, regulations, historical cases, real-time alerts, and external knowledge can be unified as the basis for risk analysis, thereby improving the data completeness of risk monitoring strategy recommendations. By identifying the risk subject based on real-time risk alerts and acquiring contextual data, alert events can be associated with the business background of the risk subject, thereby avoiding judgments based solely on isolated alerts. By generating dynamic risk profiles by combining the multi-source heterogeneous risk knowledge base, risk content, subject performance, institutional basis, and similar cases can be comprehensively represented, thereby improving the accuracy of risk identification and strategy generation. By generating structured risk handling strategies and work order instructions based on dynamic risk profiles, risk handling suggestions can be transformed into executable business instructions, thereby improving the efficiency of risk handling response.

[0021] In a third aspect, the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the intelligent recommendation method for digital supervision and risk monitoring strategies.

[0022] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the intelligent recommendation method for a digital intelligent supervision risk monitoring strategy. Attached Figure Description

[0023] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart of an intelligent recommendation method for digital supervision and risk monitoring strategies in an embodiment of the present invention; Figure 2 This is a structural block diagram of the intelligent recommendation system for digital supervision and risk monitoring strategies in an embodiment of the present invention; Figure 3This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0024] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0025] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0026] Example 1 like Figure 1 As shown, this invention discloses an intelligent recommendation method for digital supervision and risk monitoring strategies, which specifically includes the following steps: S10: Build a multi-source heterogeneous risk knowledge base and obtain real-time risk alerts generated by business systems.

[0027] Specifically, information related to risk management, including institutional information, historical handling information, real-time alarm information, and external regulatory information, is incorporated into a unified data organization framework. Information from different sources, formats, and business processes is also organized to serve as the knowledge base for subsequent risk understanding and strategy generation. At the same time, real-time risk alarms are received from business systems corresponding to business processes such as planning, bidding, contracts, warehousing, quality supervision, supplier relationship management, and waste disposal. These real-time risk alarms can then be integrated with the established multi-source heterogeneous risk knowledge base into subsequent processing flows.

[0028] S20: Identify the risk subject based on real-time risk alerts, obtain the contextual data of the risk subject from the business system, and combine the real-time risk alerts and contextual data with a multi-source heterogeneous risk knowledge base to perform semantic understanding and correlation mining to generate a dynamic risk profile.

[0029] Specifically, upon receiving a real-time risk alarm, it is not treated as an isolated event. Instead, the corresponding risk subject is first determined based on the business object reflected in the real-time risk alarm. Then, contextual data related to the current risk is supplemented from the business system around the risk subject. The real-time risk alarm, contextual data, and multi-source heterogeneous risk knowledge base are used together as the basis for understanding. The meaning, business background, historical correlation, and institutional correlation of the current risk are analyzed to form a dynamic risk profile that can characterize the current risk status.

[0030] S30: Generate structured risk management strategies based on dynamic risk profiles.

[0031] Specifically, after obtaining a dynamic risk profile, a structured risk management strategy is generated based on the risk content, risk subject status, related institutional basis, and similar historical situations reflected in the dynamic risk profile. This structured risk management strategy can simultaneously express how the current risk should be handled, how the handling action should be executed, what institutional basis the handling recommendation is, and how similar risks in the past were handled, thereby providing complete strategy content for subsequent confirmation and work order instruction generation.

[0032] S40: Obtain the confirmation result of the structured risk handling strategy, determine the confirmed structured risk handling strategy based on the confirmation result, and then generate a work order instruction.

[0033] Specifically, the generated structured risk management strategies are entered into the confirmation stage, enabling risk supervisors to confirm and process the structured risk management strategies. Based on the confirmation results, the final structured risk management strategies to be implemented are determined. Then, the content of the confirmed structured risk management strategies that can be converted into actionable actions is organized into work order instructions, so that the work order instructions can be identified and executed by the corresponding business processes.

[0034] In one embodiment, step S10, namely constructing a multi-source heterogeneous risk knowledge base, includes: S11: Obtain rules, regulations, operating manuals and compliance requirements related to risk management and establish a rules and regulations database.

[0035] Specifically, institutional materials are obtained from unstructured documents such as internal risk management-related policy documents, operation manuals, and compliance requirements. These materials are then organized, categorized by subject, and marked with their applicable business scope. This allows rules, regulations, operational requirements, and compliance constraints to be grouped according to risk management scenarios, forming a regulatory library that can be retrieved and referenced later.

[0036] S12: Obtain historical risk event records, handling processes, final results, and post-event analysis reports to form a historical case library.

[0037] Specifically, historical risk event records are collected, and the handling process, final results, and post-event analysis reports corresponding to each historical risk event are obtained simultaneously. The background, involved parties, handling actions, handling results, and lessons learned from historical risk events are archived, so that historical handling experience is no longer scattered in personnel experience or fragmented documents, but forms a historical case library that can support reference for similar risks.

[0038] S13: Obtain real-time risk alerts from business systems, as well as relevant laws and regulations, inspection and patrol issue data, and industry standards to form real-time risk alert information and external knowledge.

[0039] Specifically, real-time risk alerts are obtained from business systems such as planning, bidding, contracts, warehousing, quality supervision, supplier relationship management, and waste disposal. These real-time risk alerts include structured data such as alert type, occurrence time, involved parties, and severity level. At the same time, relevant laws and regulations, internal and external inspection and supervision problem data, and industry standards are also obtained. The real-time risk alerts are then compiled into real-time risk alert information, and the laws and regulations, inspection and supervision problem data, and industry standards are compiled into external knowledge.

[0040] S14: Link and organize the rules and regulations database, historical case database, real-time risk warning information and external knowledge to obtain a multi-source heterogeneous risk knowledge base.

[0041] Specifically, the system content in the rules and regulations database, the historical risk events and handling experience in the historical case database, the alarm elements in the real-time risk alarm information, and the regulatory requirements and industry standards in external knowledge are uniformly organized, and corresponding relationships are established according to the related dimensions such as risk type, risk subject, business process and handling result, so that information from different sources can be jointly retrieved and called around the same risk scenario, resulting in a multi-source heterogeneous risk knowledge base.

[0042] In one embodiment, in step S14, the regulatory database, historical case database, real-time risk warning information, and external knowledge are correlated and organized to obtain a multi-source heterogeneous risk knowledge base, including: S141: Extract the content of the institutional basis from the rules and regulations database and external knowledge, and extract historical risk events, handling processes and final results from the historical case database.

[0043] Specifically, the system extracts content from institutional documents, operation manuals, and compliance requirements in the rules and regulations database, identifies the institutional basis content that can be used as the basis for risk disposal, extracts the basis content related to risk control from external knowledge such as laws and regulations, inspection and supervision problem data, and industry standards, and extracts historical risk events, disposal processes, and final results from the historical case database, so that the institutional basis and historical disposal experience can be linked into data content.

[0044] S142: Correlate the alarm type, risk subject, and severity level in the real-time risk alarm information with historical risk events to obtain the corresponding correlation results.

[0045] Specifically, the alarm type, risk subject, and severity level in the real-time risk alarm information are identified, and the identified alarm type, risk subject, and severity level are matched with historical risk events in the historical case database. This enables the current real-time risk alarm to find historical risk events with the same or similar risk type, similar risk subject characteristics, or similar severity level, and obtains the corresponding association results used to characterize the correspondence between real-time risk alarms and historical risk events.

[0046] S143: Collect the content of the system, historical risk events, handling process and final result according to the corresponding risk type.

[0047] Specifically, the content of the institutional basis, historical risk events, handling process and final result are classified and collected based on the risk type. This allows for the simultaneous identification of relevant institutional basis, historical occurrence, implemented handling actions and final handling effect under the same risk type. As a result, when facing similar risks in the future, the institutional basis and historical experience can be called upon in the same collection result.

[0048] S144: Based on the collected institutional basis content, historical risk events, handling process, final result and corresponding related results, a multi-source heterogeneous risk knowledge base is obtained.

[0049] Specifically, the collected institutional basis, historical risk events, handling process, final result and corresponding related results are integrated to form a knowledge unit under each risk type, which is composed of institutional basis, historical cases, handling process, handling result and real-time alarm correspondence. Multiple knowledge units are then incorporated into the risk knowledge organizational structure to obtain a multi-source heterogeneous risk knowledge base.

[0050] In one embodiment, in step S20, the risk subject is determined based on the real-time risk alarm, and the contextual data of the risk subject is obtained from the business system. A multi-source heterogeneous risk knowledge base is used to perform semantic understanding and association mining on the real-time risk alarm and contextual data to generate a dynamic risk profile, including: S21: Analyze real-time risk alarms to determine the risk subject, alarm type, occurrence time, and severity level corresponding to the real-time risk alarm.

[0051] Specifically, the real-time risk alarms generated by the business system are parsed by field and text analysis to identify the corresponding risk subject, alarm type, occurrence time and severity level in the real-time risk alarm. The risk subject is used to indicate the supplier or other business object involved in the current risk, the alarm type is used to characterize the current abnormal business category, the occurrence time is used to characterize the time and location when the risk is triggered, and the severity level is used to characterize the priority of handling the current risk.

[0052] S22: Contextual data is obtained by retrieving historical performance records, past evaluations, and contract terms from the business system by the risk entity.

[0053] Specifically, for the identified risk entity, historical performance records, past evaluations, and contract terms related to that risk entity are obtained from the corresponding business system. The historical performance records reflect the risk entity's performance in past contracts or business transactions, the past evaluations reflect the risk entity's overall performance in historical business transactions, and the contract terms reflect the rights and obligations involved in the current risk and the basis for handling breaches. This information is then linked with real-time risk alerts to obtain contextual data.

[0054] S23: By combining a multi-source heterogeneous risk knowledge base, semantic understanding and correlation mining are performed on real-time risk alerts and contextual data to obtain related risk information.

[0055] Specifically, real-time risk alerts and contextual data are used together as input for the current risk event. By combining institutional basis, historical cases, real-time alert information and external knowledge from a multi-source heterogeneous risk knowledge base, the semantic relationship between alert text, business context and knowledge base content is analyzed. The correlation between the current risk and historical cases, supplier production capacity and rules and regulations is then extracted to obtain related risk information.

[0056] S24: Generate dynamic risk profiles based on associated risk information.

[0057] Specifically, the relevant risk information is comprehensively organized so that the dynamic risk profile can reflect what the current risk is, how the risk subject has performed in historical business, which compliance clauses the current risk may trigger, and whether there are similar risk cases. The risk content, the risk subject's historical performance, the relevant institutional basis, and similar historical situations are all incorporated into the same risk profile expression to generate a dynamic risk profile.

[0058] In one embodiment, in step S23, the real-time risk alarm and contextual data are semantically understood and correlated by combining a multi-source heterogeneous risk knowledge base to obtain associated risk information, including: S231: Perform semantic understanding on real-time risk alerts to determine the risk content of the current risk.

[0059] Specifically, semantic understanding is performed on the alarm description, alarm type and involved subjects in real-time risk alarms to identify the business anomaly meaning expressed by the current risk, such as abnormal risk of untimely supply, abnormal risk of contract performance or abnormal risk of inventory backlog, and the identified abnormal meaning is used as the risk content of the current risk, so that subsequent retrieval and strategy generation can be carried out around accurate risk semantics.

[0060] S232: Based on the risk subject and contextual data, retrieve historical cases, supplier production capacity information, and regulatory clauses related to the current risk from a multi-source heterogeneous risk knowledge base.

[0061] Specifically, based on the historical performance records, past evaluations, and contract terms in the risk subject and contextual data, historical cases, supplier production capacity information, and rules and regulations that are relevant to the current risk are retrieved from a multi-source heterogeneous risk knowledge base. Among them, historical cases are used to provide experience in handling similar risks, supplier production capacity information is used to help determine the risk subject's ability to fulfill its current business obligations, and rules and regulations are used to provide the institutional basis required for handling the current risk.

[0062] S233: Correspond to the risk content, historical cases, supplier production capacity and rules and regulations to obtain related risk information.

[0063] Specifically, the current risk content is correlated with retrieved historical cases, supplier production capacity, and regulatory clauses, so that the risk content can be matched with similar historical risks, the risk subject's capability status, and applicable regulatory basis. These correspondences are then compiled into associated risk information, which serves as the basis for generating dynamic risk profiles.

[0064] In one embodiment, step S30, namely generating a structured risk management strategy based on the dynamic risk profile, includes: S31: Generate disposal opinions and suggestions based on the risk content in the dynamic risk profile and the historical performance of the risk subject.

[0065] Specifically, the risk content and historical performance of the risk subject are extracted from the dynamic risk profile. Combined with the risk subject's historical performance, past evaluations, and the business background corresponding to the current risk, handling opinions and suggestions are generated for risk supervisors. For example, when there is an abnormal risk of untimely material supply from the supplier, the system generates handling opinions and suggestions to send an early warning to the supplier and suggest that the supply performance department intervene in a timely manner and urge the supplier to deliver the goods on time.

[0066] S32: Determine the corresponding execution steps based on the handling opinions and suggestions, and generate operation process guidelines.

[0067] Specifically, the suggestions and recommendations for handling the situation are converted into operational steps that can be performed by risk supervisors. Operational process guidelines are generated based on the business entry points and handling modules in the business system. For example, risk supervisors are guided to log in to the supply chain management system, enter the digital supervision module, select the anomaly handling function, and generate early warning information according to the corresponding template, so that the suggestions and recommendations for handling the situation can be implemented in specific business processes.

[0068] S33: Generate the legal basis references based on the rules and regulations associated with the dynamic risk profile.

[0069] Specifically, the institutional basis for current handling opinions and suggestions is extracted from the rules and regulations associated with the dynamic risk profile, and the original text of the rules and regulations or the content of the clauses related to the current risk is cited as the institutional basis, so that risk supervisors can judge the rationality and compliance of handling opinions and suggestions based on the institutional basis.

[0070] S34: Generate similar case references based on historical cases associated with dynamic risk profiles.

[0071] Specifically, risk cases that are highly similar to the current risk are selected from historical cases associated with the dynamic risk profile, and the risk background, handling process and handling results of similar risk cases are extracted to generate similar case references, so that risk supervisors can judge the handling direction and intensity of the current risk by combining the historical handling results.

[0072] S35: Combine the opinions and suggestions on handling the situation, the operational process guidelines, the reference to the institutional basis, and the reference to similar cases to obtain a structured risk handling strategy.

[0073] Specifically, the suggestions for handling the situation, operational guidelines, references to relevant regulations, and similar cases are combined in a structured output format. This allows the suggestions, implementation steps, regulatory basis, and case references corresponding to the same risk event to be presented in a centralized manner. These serve as the basis for risk supervisors to confirm the information and generate subsequent work orders, resulting in a structured risk handling strategy.

[0074] In one embodiment, step S40 involves obtaining the confirmation result of the structured risk handling strategy, determining the confirmed structured risk handling strategy based on the confirmation result, and then generating a work order instruction, including: S41: Submit the structured risk management strategy to the risk supervisor and obtain their confirmation of the structured risk management strategy.

[0075] Specifically, the structured risk management strategy is submitted to the risk supervisor for review, allowing the supervisor to review the management opinions and suggestions, operational procedures, institutional references, and similar case studies. The supervisor can then confirm, modify, or reject the structured risk management strategy based on the current business situation, and obtain the supervisor's confirmation of the structured risk management strategy.

[0076] S42: Based on the confirmation results, the structured risk management strategy is confirmed to obtain the confirmed structured risk management strategy.

[0077] Specifically, the structured risk management strategy is processed based on the confirmation result. When the confirmation result indicates direct confirmation, the original structured risk management strategy is used as the confirmed structured risk management strategy. When the confirmation result indicates confirmation after modification, the strategy content adjusted by the risk supervisor is used as the confirmed structured risk management strategy. When the confirmation result indicates rejection, the work order instruction generation stage is not entered, thus obtaining a confirmed structured risk management strategy that can be executed.

[0078] S43: Extract suggestions and operational guidelines for handling structured risks from the confirmed structured risk management strategy.

[0079] Specifically, the confirmed structured risk management strategy is analyzed to extract management suggestions that can be converted into actionable tasks and operational guidelines that guide the operation. The correspondence between the management suggestions and the operational guidelines is retained so that the work order instructions generated subsequently can simultaneously reflect the management actions that need to be performed and the business process for performing those actions.

[0080] S44: Generate work order instructions based on the handling opinions and suggestions and the operation process guidelines.

[0081] Specifically, the suggestions for handling the situation are converted into task content in the work order instructions, the operation process guidelines are converted into execution requirements in the work order instructions, and the recipients of the work order instructions are determined in conjunction with the business links corresponding to the real-time risk alarms, so that the generated work order instructions can be received by the corresponding business systems and used for risk handling execution.

[0082] Example 2 like Figure 2 As shown, based on the same inventive concept as the above embodiments, the present invention also provides a digital intelligent supervision risk monitoring strategy intelligent recommendation system, including: The knowledge module is used to build a multi-source heterogeneous risk knowledge base and obtain real-time risk alerts generated by business systems. The profiling module is used to identify the risk subject based on real-time risk alerts, obtain the contextual data of the risk subject from the business system, and combine the real-time risk alerts and contextual data with a multi-source heterogeneous risk knowledge base to perform semantic understanding and correlation mining to generate dynamic risk profiles. The strategy module is used to generate structured risk management strategies based on dynamic risk profiles; The instruction module is used to obtain the confirmation results of the structured risk handling strategy, determine the confirmed structured risk handling strategy based on the confirmation results, and then generate work order instructions.

[0083] Optional, the knowledge modules include: The regulations submodule is used to acquire rules, regulations, operation manuals and compliance requirements related to risk management and control, forming a rules and regulations library; The case study submodule is used to obtain historical risk event records, handling processes, final results, and post-event analysis reports to form a historical case study library. The External Knowledge submodule is used to acquire real-time risk alerts from business systems, as well as relevant laws and regulations, inspection and patrol issue data, and industry standards, to form real-time risk alert information and external knowledge. The organization submodule is used to associate and organize the rules and regulations database, historical case database, real-time risk warning information and external knowledge to obtain a multi-source heterogeneous risk knowledge base.

[0084] Optionally, the organization submodule includes: The extraction unit is used to extract the content of the legal basis for the system from the rules and regulations database and external knowledge, and to extract historical risk events, handling processes and final results from the historical case database. The association unit is used to associate the alarm type, risk subject, and severity level in real-time risk alarm information with historical risk events to obtain the corresponding association results; The aggregation unit is used to aggregate the content of the institutional basis, historical risk events, handling process and final result according to the corresponding risk type; The database unit is used to obtain a multi-source heterogeneous risk knowledge base based on the collected institutional basis content, historical risk events, handling process, final result and corresponding related results.

[0085] Optionally, the portrait module includes: The parsing submodule is used to parse real-time risk alarms and determine the risk subject, alarm type, occurrence time and severity level of the real-time risk alarm. The context submodule is used to obtain context data by retrieving historical performance records, past evaluations, and contract terms from the business system based on the risk subject. The mining submodule is used to combine a multi-source heterogeneous risk knowledge base to perform semantic understanding and association mining on real-time risk alarms and contextual data to obtain associated risk information. The profiling submodule is used to generate dynamic risk profiles based on associated risk information.

[0086] Optionally, the mining submodule includes: Semantic units are used to perform semantic understanding of real-time risk alerts and determine the risk content of the current risk. The retrieval unit is used to retrieve historical cases, supplier production capacity information, and regulatory clauses related to the current risk from a multi-source heterogeneous risk knowledge base based on the risk subject and contextual data. The risk control unit is used to correlate risk content, historical cases, supplier production capacity, and rules and regulations to obtain associated risk information.

[0087] Optionally, the strategy module includes: The Opinion Submodule is used to generate disposal opinions and suggestions based on the risk content in the dynamic risk profile and the historical performance of the risk subject; The process submodule is used to determine the corresponding execution steps based on the handling opinions and suggestions, and generate operation process guidelines; Based on the submodule, it is used to generate references to the rules and regulations associated with the dynamic risk profile; The case reference module is used to generate similar case references based on historical cases associated with dynamic risk profiles; The combination submodule is used to combine disposal opinions and suggestions, operational process guidelines, institutional references, and similar case references to obtain a structured risk disposal strategy.

[0088] Optionally, the instruction module includes: The submission submodule is used to submit the structured risk management strategy to the risk supervisor and obtain the risk supervisor's confirmation of the structured risk management strategy; The confirmation submodule is used to confirm the structured risk management strategy based on the confirmation results, and obtain the confirmed structured risk management strategy. The extraction submodule is used to extract handling opinions and suggestions and operational process guidelines from the confirmed structured risk handling strategies; The instruction submodule is used to generate work order instructions based on handling opinions and suggestions and operation process guidelines.

[0089] Example 3 like Figure 3 As shown, the present invention also provides an electronic device 100 for implementing an intelligent recommendation method for digital supervision and risk monitoring strategies; The electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on at least one processor 102, and at least one communication bus 104.

[0090] The memory 101 can be used to store computer programs 103. The processor 102 implements the steps of the intelligent recommendation method for digital supervision risk monitoring strategy in Embodiment 1 by running or executing the computer programs stored in the memory 101 and calling the data stored in the memory 101.

[0091] The memory 101 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0092] At least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 102 may be a microprocessor or any conventional processor. Processor 102 is the control center of electronic device 100, connecting various parts of electronic device 100 via various interfaces and lines.

[0093] The memory 101 in the electronic device 100 stores multiple instructions to implement an intelligent recommendation method for a digital supervision risk monitoring strategy, and the processor 102 can execute multiple instructions to achieve the following: Build a multi-source heterogeneous risk knowledge base and obtain real-time risk alerts generated by business systems; Based on real-time risk alerts, the risk subject is identified, and contextual data of the risk subject is obtained from the business system. Combined with a multi-source heterogeneous risk knowledge base, semantic understanding and correlation mining are performed on the real-time risk alerts and contextual data to generate a dynamic risk profile. Structured risk management strategies are generated based on dynamic risk profiles; Obtain confirmation results of structured risk management strategies, determine the confirmed structured risk management strategies based on the confirmation results, and then generate work order instructions.

[0094] Example 4 If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or system capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, and read-only memory (ROM).

[0095] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0097] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction set implemented in a process. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0098] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0099] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for intelligent recommendation of digital supervision and risk monitoring strategies, characterized in that, The method includes: Build a multi-source heterogeneous risk knowledge base and obtain real-time risk alerts generated by business systems; The risk subject is determined based on the real-time risk alarm, and the context data of the risk subject is obtained from the business system. The real-time risk alarm and the context data are combined with the multi-source heterogeneous risk knowledge base to perform semantic understanding and association mining to generate a dynamic risk profile. Based on the dynamic risk profile, a structured risk management strategy is generated, which includes suggestions for management, operational procedures, references to relevant regulations, and similar case studies. Obtain the confirmation result of the structured risk handling strategy, determine the confirmed structured risk handling strategy based on the confirmation result, and then generate a work order instruction.

2. The intelligent recommendation method for digital supervision and risk monitoring strategies according to claim 1, characterized in that, The construction of the multi-source heterogeneous risk knowledge base includes: Acquire rules, regulations, operating manuals, and compliance requirements related to risk management and create a rules and regulations database; Obtain historical risk event records, handling processes, final results, and post-event analysis reports to form a historical case database; Acquire real-time risk alerts from business systems, as well as relevant laws and regulations, inspection and patrol issues data, and industry standards, to form real-time risk alert information and external knowledge; The rules and regulations database, the historical case database, the real-time risk warning information, and the external knowledge are linked and organized to obtain the multi-source heterogeneous risk knowledge base.

3. The intelligent recommendation method for digital supervision and risk monitoring strategies according to claim 2, characterized in that, The process of associating and organizing the rules and regulations database, the historical case database, the real-time risk warning information, and the external knowledge to obtain the multi-source heterogeneous risk knowledge base includes: Extract the content of the institutional basis from the aforementioned rules and regulations database and the aforementioned external knowledge, and extract historical risk events, handling processes and final results from the historical case database; The alarm type, risk subject, and severity level in the real-time risk alarm information are correlated with the historical risk events to obtain the corresponding correlation results; The system's basis, historical risk events, handling processes, and final results are categorized according to their respective risk types. Based on the aggregated institutional basis, historical risk events, handling process, final result, and corresponding association result, the multi-source heterogeneous risk knowledge base is obtained.

4. The intelligent recommendation method for digital supervision and risk monitoring strategies according to claim 1, characterized in that, The step of determining the risk subject based on the real-time risk alarm, obtaining the context data of the risk subject from the business system, and performing semantic understanding and association mining on the real-time risk alarm and the context data in conjunction with the multi-source heterogeneous risk knowledge base to generate a dynamic risk profile includes: Analyze the real-time risk alarm to determine the risk subject, alarm type, occurrence time, and severity level corresponding to the real-time risk alarm; The context data is obtained by the risk subject from the business system based on historical performance records, past evaluations, and contract terms. By combining the multi-source heterogeneous risk knowledge base, semantic understanding and association mining are performed on the real-time risk alarm and the context data to obtain associated risk information; The dynamic risk profile is generated based on the associated risk information.

5. The intelligent recommendation method for digital supervision and risk monitoring strategies according to claim 4, characterized in that, The method combines the multi-source heterogeneous risk knowledge base to perform semantic understanding and association mining on the real-time risk alerts and the context data to obtain associated risk information, including: Perform semantic understanding on the real-time risk alarm to determine the risk content of the current risk; Based on the risk subject and the context data, retrieve historical cases, supplier production capacity information and regulatory clauses associated with the current risk from the multi-source heterogeneous risk knowledge base; The associated risk information is obtained by correlating the risk content, historical cases, supplier production capacity, and rules and regulations.

6. The intelligent recommendation method for digital supervision and risk monitoring strategies according to claim 1, characterized in that, The generation of structured risk management strategies based on the dynamic risk profile includes: Based on the risk content and historical performance of the risk subject in the dynamic risk profile, the proposed solutions are generated. Based on the aforementioned handling opinions and suggestions, determine the corresponding execution steps and generate the aforementioned operation process guide; Based on the rules and regulations associated with the dynamic risk profile, generate the reference to the legal basis of the system; Based on the historical cases associated with the dynamic risk profile, the similar case reference is generated; The structured risk management strategy is obtained by combining the proposed solutions, the operational guidelines, the institutional basis, and the similar case references.

7. The intelligent recommendation method for digital supervision and risk monitoring strategies according to claim 1, characterized in that, The process of obtaining the confirmation result of the structured risk handling strategy, determining the confirmed structured risk handling strategy based on the confirmation result, and then generating a work order instruction includes: The structured risk management strategy is submitted to the risk supervisor, and the supervisor's confirmation of the structured risk management strategy is obtained. Based on the confirmation result, the structured risk management strategy is confirmed to obtain the confirmed structured risk management strategy. Extract handling suggestions and operational guidelines from the confirmed structured risk management strategy; Based on the proposed solutions and the operational guidelines, the work order instruction is generated.

8. A digital intelligent supervision and risk monitoring strategy intelligent recommendation system, characterized in that, The system includes: The knowledge module is used to build a multi-source heterogeneous risk knowledge base and obtain real-time risk alerts generated by business systems. The profiling module is used to determine the risk subject based on the real-time risk alarm, obtain the context data of the risk subject from the business system, and perform semantic understanding and association mining on the real-time risk alarm and the context data in combination with the multi-source heterogeneous risk knowledge base to generate a dynamic risk profile. The strategy module is used to generate structured risk management strategies based on the dynamic risk profile. The instruction module is used to obtain the confirmation result of the structured risk handling strategy, determine the confirmed structured risk handling strategy based on the confirmation result, and then generate a work order instruction.

9. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement the intelligent recommendation method for digital supervision risk monitoring strategy as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which, when executed by a processor, implements the intelligent recommendation method for digital supervision and risk monitoring strategies as described in any one of claims 1 to 7.

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