71 results about "Risk profiling" patented technology

The invention discloses a risk analysis method and device for a financial system, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence or other related fields, and the method comprises the steps: obtaining multi-source financial data which at least comprises structured data and unstructured text data; performing semantic analysis on the multi-source financial data to obtain an analysis result containing semantic information; extracting risk entities, association relationships among the risk entities, risk events and attribute information of the risk events from the analysis result; constructing a financial risk knowledge graph based on the risk entities, the association relationships, the risk events and the attribute information; and performing association analysis based on the financial risk knowledge graph to obtain a risk analysis result, and executing risk early warning based on the risk analysis result. Through the method and the device, the technical problem of low risk analysis accuracy of the financial transaction system in related technologies is solved.

The invention discloses an enterprise financial risk determination method and a related device, and relates to the technical field of artificial intelligence. Six dimensions of mobility, credit, market, operation, industry macroscopic and public opinion reputation are respectively processed through six special and precise agents including a mobility risk analysis agent, a credit risk analysis agent, a market risk analysis agent, an operation risk agent, an industry macroscopic risk analysis agent and a public opinion and reputation risk analysis agent; and full-quadrant scanning of enterprise financial risks is realized. The cross validation coordinator and the dynamic cooperation engine form a double-wheel drive, and the cross validation coordinator can obtain a cooperation agent identifier set, a cooperation task type and cooperation configuration information; the dynamic collaboration engine dispatches multi-agent parallel collaboration in real time based on the collaboration agent identifier set, the collaboration task type and the collaboration configuration information, information islands are eliminated, and misjudgment and missing report are remarkably reduced. Therefore, accurate enterprise financial risks can be obtained.

The invention provides an anti-fraud method and system based on multi-modal perception and cross-time feature modeling. The method comprises the following steps: receiving a multi-modal financial transaction graph sent by an edge computing node; inputting the multi-modal financial transaction graph into a risk control model for risk analysis to obtain a node risk score of each node, an edge risk score of each edge and a gang risk score of each sub-graph; the risk control model is a multi-scale ST-Transform-GCN framework, and the risk control model is a multi-scale ST-Transform-GCN framework; processing the node risk score, the edge risk score and the gang risk score through a gating fusion mechanism to obtain a comprehensive risk score; based on the node risk score, the edge risk score and the gang risk score, extracting a suspicious transaction sub-graph from the multi-modal financial transaction graph; and inputting the comprehensive risk score and the suspicious transaction sub-graph into a preset reinforcement learning decision maker to obtain an anti-fraud strategy, and executing the anti-fraud strategy to achieve the purpose of accurately identifying the complex collaborative fraud behavior.

The invention discloses a risk assessment method and device for a financial service, electronic equipment and a storage medium, and relates to the technical field of big data and artificial intelligence or other related fields, and the method comprises the steps: carrying out the information collection of a target service main body from N heterogeneous data sources after receiving a financial service application submitted by the target service main body, n is a positive integer; performing multi-modal feature extraction processing on the business main body information to obtain business main body features; the business main body features are input to a risk assessment model, a risk assessment result is output, the risk assessment model comprises a feature fusion layer and a risk quantification layer, the risk assessment model is used for cooperatively calculating assessment scores of M risk dimensions through the feature fusion layer and the risk quantification layer, and M is a positive integer; and triggering a risk early warning signal based on the risk assessment result. Through the method and the device, the technical problem of low efficiency of risk analysis of business data of different data sources and different structures in related technologies is solved.

The invention discloses a financial risk early warning method, and relates to the technical field of financial management, and a risk early warning system adopted by the method comprises a financial data acquisition module, an analysis sensitivity adjustment module and an auxiliary risk identification module. The financial data acquisition module is used for performing data acquisition on financial data change of a fund circulation path and distributed fund flow time points, and the analysis sensitivity adjustment module is used for adjusting the financial analysis frequency of the risk analysis unit according to the acquired data. The auxiliary risk identification module is used for detecting the head end of a financial risk signal by adopting a manual processing method when the risk analysis unit fails to accurately identify the front point of the risk signal; and the financial data acquisition module comprises a fund access recording module, a financial data change acquisition module, a distributed detection unit, a financial structure mapping module and a financial risk analysis unit. The system has the characteristic of automatic risk response.

The invention relates to the technical field of financing risk analysis, in particular to a financing risk report dynamic graph generation method based on multi-source invoice data. Obtaining input invoice data and output invoice data, and extracting a first commercial feature and a second commercial feature; using the financing event as a time anchor point, aiming at each financing event, applying an operation risk analysis model to process the first commercial feature and the second commercial feature, and generating a pre-financing risk set and a post-financing risk set including risk types; performing first-order differentiation analysis on the pre-financing risk set and the post-financing risk set, and identifying risk state parameters; for multiple financing events, executing second-order differentiation analysis, and identifying a cross-cycle change trend of the risk mode of the target enterprise; and based on the first-order and second-order differentiation analysis, generating a multi-layer time sequence knowledge graph, and forming a financing risk dynamic graph. According to the invention, dynamic analysis of financing risks is realized through multi-source invoice data identification.

The invention discloses a financial document review method, a related device and a system, and relates to the technical field of data processing, after a to-be-reviewed multi-modal financial document is processed into structured financial data, related domain knowledge and risk analysis specification information of the structured financial data are retrieved from a dynamic knowledge graph, and the structured financial data are reviewed according to the related domain knowledge and risk analysis specification information. And generating a risk analysis instruction command based on the structured financial data, the related domain knowledge and the risk analysis specification information, and inputting the risk analysis instruction command into the generative pre-training model to obtain a risk analysis result. The process does not need manual participation in auditing, the auditing efficiency is greatly improved, the indication information of risk analysis is generated according to the latest related domain knowledge retrieved from the dynamic knowledge graph and the risk analysis specification information, and a more accurate risk analysis result of the structured financial data can be obtained in real time.

The invention belongs to the field of big data, and relates to an agent-based report generation method and device, equipment and a medium, and the method comprises the steps: receiving an analysis demand of a user, and generating a structured demand description through semantic analysis; matching a target analysis process template from the analysis process template set according to the demand description; generating a risk analysis step document based on the demand description and the target analysis process template; sending the risk analysis step document to the user to obtain confirmation information of the user; based on the confirmation information, distributing a data processing task corresponding to the risk analysis step document to a corresponding tool agent through a routing agent so as to execute the data processing task; and receiving a processing result of the data processing task returned by each tool agent, and generating a structured analysis report based on a plurality of processing results. The method can be applied to the business field of financial insurance and the like, and can realize full-process intelligent cooperation of insurance risk section analysis and improve the analysis efficiency and quality.

The invention discloses a supply chain artificial intelligence financial risk decision-making system, and belongs to the technical field of data processing. A learning data customization module and a learning data label module are arranged, so that a user can customize a risk analysis task, personalized data learning can be realized, and the user experience is improved. And meanwhile, the intelligent library module, the data learning module and the model operation module are arranged, so that the data relationship specified by the user can be accurately learned, the user is assisted to make a financial risk decision, and the processing efficiency of the user can be effectively improved.

This invention relates to the field of privacy computing and discloses a collaborative analysis method for potential financial risks based on fuzzy privacy set intersection. The method first protects the privacy of deposit and loan data from various financial institutions through Paillier homomorphic encryption. Then, it utilizes a fuzzy privacy set intersection algorithm based on Unintentional Key-Value Storage (OKVS) and the discrete logarithm problem to achieve fuzzy matching of user identities across multiple institutions. While ensuring the privacy of user feature data, it identifies records of the same user that meet a predetermined distance threshold. Finally, it aggregates the encrypted deposit and loan data of the matched records and compares them with the threshold. A trusted third party decrypts the data and completes the judgment of potential financial risks, thus realizing financial privacy and security risk analysis under cross-institutional data collaboration.

A method for analyzing investment opportunities includes receiving an identifier of a security of interest. The method further includes identifying an address associated with the security of interest based on public filings by an issuer of the security of interest. The method also includes retrieving public ratings of, and additional public information regarding, the security of interest by using the identifier and the identified address of the security of interest, the method also includes calculating an expected return for the security of interest based on the public ratings and the additional public information. The method also includes generating a proprietary score of the security of interest based on the public ratings, the additional public information, and the expected return.

The invention relates to the technical field of data analysis systems, and particularly discloses a financial risk data analysis system supporting dynamic modeling. Comprising a multi-source heterogeneous financial data acquisition and fusion module, a risk factor dynamic modeling and weight optimization module, a risk conduction relation modeling and influence prediction module, a risk prediction and dynamic evaluation module, a risk coping strategy generation and optimization module and a closed-loop learning and model updating module. According to the method, on the basis of efficient fusion tamping risk analysis of multi-source heterogeneous financial data, risk factor evolution characteristics under market changes are accurately captured by means of dynamic modeling, and the risk prediction capability is depicted and strengthened through a refined conduction path; the timeliness of coping with suggestions and the long-term adaptability of the system are guaranteed by relying on strategy dynamic optimization and a closed-loop learning mechanism, the usability and the risk management and control initiative are improved by matching with a perfect visual interaction and abnormity early warning function, and accurate identification, real-time monitoring and efficient coping of financial risks are comprehensively realized.

The invention discloses an insurance agent data processing method, device and equipment and a medium, which are applied to an insurance service platform, comprise a management agent, an analysis agent and an adjustment agent, and send customer information, historical insurance data and inherent risk data to the analysis agent based on the management agent, the historical claim settlement data is sent to an adjustment agent, an analysis agent is used to carry out risk analysis on a client to obtain a target analysis result, an initial insurance policy is generated according to the target analysis result and is sent to the adjustment agent, the adjustment agent is used to adjust the initial insurance policy to obtain an adjusted insurance policy, and a management agent is used to carry out risk analysis on the client to obtain the adjusted insurance policy. And checking the adjusted insurance policy to obtain a checking result, and if a preset condition is not met, executing the step of using the analysis agent until the preset condition is met to obtain a target insurance policy. The method can be applied to the field of financial science and technology, and the insurance policy generation reliability is improved while the insurance policy generation efficiency is improved.

The invention discloses an economics analysis and risk evaluation method and system based on an enhanced retrieval agent, and belongs to the technical field of crossing of artificial intelligence and sociology. According to the method, a knowledge graph is constructed by integrating sociology and financial data, a thinking chain template is trained, and cross-layer calculation and evaluation are realized by using a layer-by-layer conduction model. The core of the method lies in establishing evaluation indexes and methods from a sociology calculation model to social financial data fluctuation, and the problem that an effective evaluation system is lacked in the prior art is solved. The method can more accurately reveal the influence of social factors on financial data, improves the reliability and practicability of the model, and is mainly applied to financial risk analysis and decision support.

The invention discloses a business risk analysis method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence or other related fields, and the method comprises the steps: obtaining target multi-source data related to a target financial business from N financial data sources, N being a positive integer; the target multi-source data is input into a preset target model, a data analysis result in a natural language form is output, and the preset target model is a large model adjusted in advance according to the financial field direction and is used for analyzing risk data relevance of the target multi-source data and expressing the risk data relevance in the natural language form; and filling a preset report template with the data analysis result in the natural language form to obtain a business risk analysis report of the target financial business. Through the method and the device, the technical problem of low accuracy of a business risk report caused by insufficient data integration analysis in related technologies is solved.

The invention relates to a bank cash business-oriented public opinion risk insight system and method, and the system comprises an edge end which comprises a data collection module and an edge processing module, and a cloud end which comprises a cloud end analysis module; the data acquisition module acquires cash business data and local public opinion information in real time; the edge processing module performs feature extraction on the cash business data and the local public opinion information to obtain risk features; inputting the risk features into a preset multi-modal risk marking model for risk assessment to obtain a preliminary risk result; and the cloud analysis module analyzes according to the preliminary risk result to obtain a global risk report, and queries based on a preset dynamic knowledge graph to obtain a risk response strategy corresponding to the global risk report. According to the method, feature extraction and preliminary risk assessment are firstly carried out by utilizing the computing power of the edge end, and then global risk analysis is carried out and a risk response strategy is formulated through the cloud end, so that the computing pressure and processing time of the cloud end are reduced, the response speed of risk identification is improved, and public opinion risk prevention is facilitated.

This invention discloses a method and apparatus for generating transaction feature maps, relating to the field of financial risk analysis and identification technology. One specific implementation of the method includes: determining multiple early warning indicators corresponding to a financial transaction; merging the parsed text corresponding to each early warning indicator to generate a summary text; extracting multiple feature words of the financial transaction from the summary text; determining the correlation between each feature word and the financial transaction; and generating a feature map corresponding to the financial transaction based on each feature word and its corresponding correlation. This implementation displays transaction features in a visual feature map format, making the feature map more intuitive and specific, which is beneficial for relevant personnel to make correct analysis and decisions regarding financial transactions.

The invention discloses a risk control decision generation method and device, electronic equipment and a storage medium, and belongs to the technical field of financial risk control. The method comprises the following steps: acquiring multi-source data of an insurance applicant; the multi-source data comprises insurance applicant information and insurance applicant claim settlement related information; based on the multi-source data, performing semantic analysis and recognition through a pre-trained first large model to obtain a structured event fragment, and based on the structured event fragment and the multi-source data, performing entity recognition and relation attribute extraction through the pre-trained first large model to obtain a triple; based on the multi-source data, performing emotion analysis through a pre-trained first large model to obtain emotion risk label information; generating a risk control association knowledge graph based on the structured event fragment, the triple and the emotional risk tag information; and performing risk analysis based on the risk control association knowledge graph to obtain target risk information, and generating a risk control decision based on the target risk information.

The embodiment of the invention provides a risk assessment method and device based on financial data, electronic equipment and a medium, belongs to the technical field of artificial intelligence, and is suitable for the field of financial science and technology. The method comprises the steps of obtaining first financial data of a target object in an analysis period based on a calculation data mapping relation and an initial financial material type; calculating the first financial data to obtain initial analysis data; selecting a reference sub-time period for the analysis time period according to the industry type; performing risk analysis according to the industry type, the initial financial material type and the reference sub-period to obtain a reference financial material type; selecting second financial data of the target object in the reference sub-period based on the calculation data mapping relation and the reference financial material type; calculating the second financial data to obtain candidate analysis data; and performing risk assessment on the target object according to the initial analysis data and the candidate analysis data to obtain a risk level of the target object. According to the embodiment of the invention, the accuracy of risk assessment based on financial data can be improved.

This invention discloses a privacy-preserving analysis terminal and method for financial transaction records based on an edge computing gateway. Addressing the lack of logical error correction and data leakage privacy risks in existing financial bill recognition systems, this invention leverages a general heterogeneous computing architecture to construct an integrated NPU and TEE, and performs hardware-software collaborative processing logic through a high-speed collaborative channel. The method includes: the NPU performing OCR to extract text; the TEE replacing sensitive entities with encryption masks and mapping the text to SMT constraint expressions for logical verification; if a verification conflict occurs, a logical penalty term is calculated, triggering an NPU interrupt via the collaborative channel to call the operator dynamic update interface. While preventing redundant calculation of visual context features, the penalty term is injected as a bias into the decoding layer, dynamically adjusting the decoding weights and reconstructing the recognition result; finally, the desensitized data, based on homomorphic encryption to maintain the topology structure, is transmitted to the cloud for risk analysis and then restored locally. This invention achieves a closed loop between perception and deterministic logic, significantly improving feature extraction accuracy while ensuring privacy data remains within the data domain.

The invention provides a business finance and taxation direct connection-based data, electricity and ticket aggregation analysis processing method, which comprises the following steps of: S101, configuring a security authentication gateway, respectively acquiring business data, financial data and tax data of a target enterprise from a business management system, a financial management system and a tax platform through the security authentication gateway, and collecting the business data, the financial data and the tax data into original business finance and taxation data; s102, storing the original industry finance and taxation data into a data lake, constructing a cross-domain unified data model, and performing association mapping on the digital and electronic invoice of the target enterprise and the original industry finance and taxation data through the cross-domain unified data model; and S103, monitoring the key operation of the digital and electronic invoice initiated by the target enterprise through the intelligent agent, analyzing the potential risk of the digital and electronic invoice based on the cross-domain unified data model in combination with a rule engine and AI analysis, and generating and outputting a risk analysis report. According to the method, a rule engine, an artificial intelligence technology and direct connection industry finance and tax data are combined to carry out aggregation analysis on potential risks of digital-to-electricity invoices, and the risks can be identified and blocked in time.

The invention relates to the technical field of machine learning, can be applied to business system platforms of medical health, financial science and technology and the like, and discloses a risk data feature value analysis method, device and equipment and a medium, and the method comprises the steps: obtaining multi-dimensional data of a preset risk type, carrying out the basic feature extraction of the multi-dimensional data, and obtaining data basic features; performing basic risk analysis on the data basic features to obtain initial risk feature values; obtaining a residual feature value according to a preset residual, and combining the initial risk feature value with the residual feature value to generate a risk feature value; extracting key features of the multi-dimensional data by adopting a preset residual analysis model, and performing interval score assignment on the key features to obtain feature interval scores; and constructing an initial risk analysis model according to the feature interval scores and the key features. By integrating the residual error correction logic into the initial risk analysis model, the initial risk analysis model is optimized in a targeted manner to eliminate the deviation of the initial model, and finally the risk scoring accuracy is improved.

The invention relates to the technical field of computer data processing and project management, and discloses an industrial-grade business and financial fusion method and system based on project management and a storage medium, and the method comprises the following steps: S1, obtaining multi-source heterogeneous data in a project, and mapping the data into business and financial entities; s2, abstracting the state of the business and financial entity into a system state vector, and establishing a state transition matrix for defining a time evolution rule of the system state vector; s3, performing prediction or risk analysis on future financial indexes of the project based on evolution of the system state vector driven by the state transition matrix; and S4, according to the prediction or risk analysis result, generating a decision scheme for intervening the project execution, the real-time business operation of the project and the financial state change are deeply fused, and through establishing the dynamic state space evolution model, the prospective and quantitative prediction of future financial indexes of the project is realized.

The invention relates to the technical field of data analysis, in particular to a risk analysis method and system based on financial institution data. A risk analysis system based on financial institution data comprises a transaction account screening module and a transaction record screening module. According to the method, the financial institution data is mapped into the transaction thermodynamic diagram in the preset period, and attention enhancement is performed in combination with the transaction adjacency matrix, so that account information associated with risks can be quickly positioned in a diagram recognition mode, and first screening of large-scale transaction data is realized; furthermore, for the screened risk transaction pairs, transaction feature distribution values and joint distribution values are extracted to construct transaction feature distribution vectors, the transaction feature distribution vectors are input into a transaction risk analysis model for secondary screening, and high-risk transaction records are output, so that through the double-layer screening mechanism, the transaction data volume needing manual auditing can be effectively reduced, and the transaction efficiency is improved. The workload of transaction risk analysis is significantly reduced, and the efficiency of risk identification is improved.

This invention discloses a knowledge graph-based financial data analysis method, comprising the following steps: collecting and preprocessing multi-source financial data; performing semantic unification and hierarchical element extraction on standardized financial datasets; constructing a set of financial semantic subgraphs based on the hierarchical financial semantic element set; determining target cross-layer connection relationships and constructing a hierarchical financial knowledge graph based on the set of financial semantic subgraphs; comprehensively analyzing cross-layer association paths between different semantic layers based on the hierarchical financial knowledge graph; constructing a filtering sequence and performing continuous coherence analysis to extract hierarchical graph structural features and generate a set of hierarchical graph structural features; determining potential association relationships, association strength, and risk transmission relationships between financial entities, and generating financial data analysis results. This invention employs knowledge graphs and cross-layer semantic analysis methods to achieve multi-source financial data association modeling, possessing the advantages of accurate association identification and comprehensive risk analysis.

The invention relates to the technical field of bank data management, in particular to an asset and liability management method and device, equipment and a medium. The method comprises the steps of receiving a risk analysis request of a service; the risk analysis request comprises a service identifier and service information of the service; the risk analysis comprises exchange rate risk analysis, mobility risk analysis and interest rate risk analysis; determining a product and product information corresponding to the business according to the business information and a preset product information table; determining affirmation information corresponding to the business based on the business information, the product information and a preset affirmation information table; performing risk analysis according to the business information, the affirmation information and a preset liability management information set, and determining a risk level of the business; determining the risk level of the product according to the risk level of the business and the historical risk level of the product; the liability management information set comprises data information corresponding to bank asset liability management.

This application provides a method, apparatus, device, medium, and program product for security detection of application behavior, relating to the financial technology field. It includes: based on the startup status of a banking application installed on a terminal device under test, in a trusted execution environment corresponding to the security chip of the terminal device, real-time collection of sensitive behavior data of the banking application; in the trusted execution environment, risk analysis processing of the sensitive behavior data is performed based on the historical usage data of the banking application corresponding to the terminal device to determine the risk category of the sensitive behavior data; based on the risk category, a security report for the banking application is generated, and a security report generation prompt is displayed; in response to the user's viewing operation of the prompt, abnormal behavior verification is performed on the terminal device and the banking application in the trusted execution environment; if the verification is successful, the security report is de-identified to obtain and display a de-identified security report. The method of this application improves the security of application behavior detection.

The invention is suitable for the technical field of customer risk analysis, and provides a customer risk management analysis method and device and a medium, and the method comprises the following steps: calling historical contract execution information of a customer, and determining a contract execution risk cardinal number based on the historical contract execution information; acquiring financial public data of the customer, and determining a financial stability cardinal number of the customer according to the financial public data; determining a reference change trend and a demand quantity change trend of the customer, comparing the demand quantity change trend with the reference change trend, and determining a demand quantity change risk cardinal number; and public opinion evaluation information related to the customer in the social media is collected to obtain a social public opinion risk cardinal number. According to the method, a comprehensive and systematic risk assessment model is constructed by summarizing the historical contract execution information, the financial public data, the demand quantity change trend and the social media public opinion multi-dimensional data of the customer, the obtained customer comprehensive risk value is more accurate, and the accuracy and timeliness of risk assessment are improved.

The application provides a method for aggregating and analyzing electronic invoices based on direct connection of industry, finance and tax, comprising: S101, configuring a secure authentication gateway, obtaining business data, financial data and tax data of a target enterprise from a business management system, a financial management system and a tax platform through the secure authentication gateway, and collecting the data into original industry, finance and tax data; S102, storing the original industry, finance and tax data into a data lake, constructing a cross-domain unified data model, and associating and mapping the electronic invoices of the target enterprise with the original industry, finance and tax data through the cross-domain unified data model; S103, monitoring key operations of the electronic invoices initiated by the target enterprise through an intelligent agent, analyzing potential risks of the electronic invoices based on the cross-domain unified data model, combining a rule engine and AI analysis, generating a risk analysis report and outputting. The method combines the rule engine and the artificial intelligence technology, aggregates and analyzes the potential risks of the electronic invoices based on the direct connection of the industry, finance and tax data, and can identify and block the risks in time.