24 results about "Risk type" patented technology

The invention provides an intelligent contract risk identification method and device based on a big language model, and the method comprises the steps: constructing a legal knowledge graph and a risk case library, carrying out the structural processing of a contract text, carrying out the preliminary risk assessment through combining with a big language model, and carrying out the deep reasoning and case verification through combining with the knowledge graph. And generating a final report containing the risk type, the confidence coefficient, the reasoning chain and the modification suggestion, and continuously optimizing the model through user feedback data, so that efficient, accurate, explainable and adaptive optimization of contract risk identification is realized.

The invention discloses an intelligent acquisition risk identification system based on deep learning, and the system comprises a time sequence sample construction module which is used for building a time sequence sample sequence; the hierarchical attention structural feature coding module is used for carrying out structural feature coding on the sequential sample sequence by utilizing a hierarchical attention network; the time sequence feature extraction module is used for inputting the structural feature vector into an ETSform model to perform time sequence feature extraction; the hierarchical time sequence collaborative attention adaptive fusion module is used for performing bidirectional attention interaction and dynamically generating a hierarchical weight and a time sequence weight through a meta-learning controller; the improved CatBoost risk identification module is used for outputting a risk score and a risk type label; and the system fusion module is used for summarizing and merging the risk scores and the risk type labels. The method and the device are suitable for merchant transaction risk identification in an acquiring business scene.

This application provides a credit risk analysis method applicable to the fields of big data and artificial intelligence. The method includes: responding to a credit risk analysis request for a target enterprise, acquiring multi-dimensional credit data of the target enterprise, and extracting a set of credit risk features for each dimension based on the credit data. These multiple dimensions include financial, cash flow, and financing dimensions. The method also involves inputting the set of credit risk features for each dimension into a corresponding sub-model to obtain analysis results for that dimension. These results include the initial credit risk level of the target enterprise under different performance periods and risk types in each dimension. Finally, the analysis results are input into a fusion model to obtain the final credit risk level of the target enterprise under different performance periods and risk types across multiple dimensions. This application also provides a credit risk analysis device, equipment, storage medium, and program product.

The invention discloses a real-time all-weather risk control system based on high-frequency data and news public opinions, and the system comprises a quantitative intelligent transaction module, a risk income calculation module, a multi-asset risk control module, and an intelligent evaluation module. The quantitative intelligent transaction module comprises a strategy combination module, a strategy matching fund module, an automatic transaction module and a strategy compliance real-time review sub-module, the sub-module obtains financial supervision compliance requirements in real time, carries out compliance verification on financial product combination and fund putting schemes, blocks execution of uncompliance rules, and feeds back the uncompliance rules; the risk income calculation module comprises a core data collection module and a data traceability evidence storage sub-module, the sub-module marks a source identifier, collection time and personnel information for core data to form non-tampering traceability chain associated storage, and the multi-asset risk control module comprises a risk control module and a risk slow release scheme automatic generation sub-module. The sub-module receives the risk signal and analyzes the risk type and range.

The embodiment of the invention provides an enterprise data processing method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring multi-modal data of a target enterprise; performing feature extraction on the multi-modal data to obtain different multi-modal features; performing feature fusion on different multi-modal features to obtain fused features; identifying feature attributes of the multi-modal features, wherein the feature attributes comprise data integrity, timestamps and risk types; determining a risk assessment type according to the risk assessment task demand of the target enterprise; determining a target processing strategy according to the feature attribute and the risk assessment type; and performing risk assessment processing on the fusion feature according to the target processing strategy through a risk assessment model, and generating a risk assessment result of the corresponding target enterprise. According to the embodiment of the invention, the comprehensiveness and accuracy of enterprise risk assessment can be improved, the resource allocation weight of the risk assessment model is dynamically adjusted according to the target processing strategy, and efficient and accurate enterprise risk assessment can be realized in a financial scene.

The invention discloses an SQL statement intelligent auditing and risk early warning method for financial services, and relates to the technical field of financial service intelligent auditing, and the method comprises the following steps: 1, defining a financial SQL core risk type and a quantitative auditing dimension; 2, a full-dimensional sensing module is constructed, multi-source data related to the SQL to be audited are collected, and the multi-source data at least comprise SQL statement data, database operation environment data, financial service rule data, supervision compliance data and historical SQL execution log data. According to the method, financial SQL auditing scene elements are mapped into four types of element individuals of SQL, risk, compliance and business, association strength among the individuals is quantified in combination with a connection weight algorithm, a virtual social network is constructed, four types of core risks of multi-risk-dimension collaborative judgment, sensitive data coverage, compliance authorization, business logic and performance overload are realized, and the risk level of the financial SQL auditing scene is improved. And the one-sidedness of a traditional static rule is avoided.

The application provides a smart contract risk identification method and device based on a large language model, which constructs a legal knowledge graph and a risk case library, performs structured processing on a contract text, performs preliminary risk evaluation by using a joint large language model, performs deep reasoning and case verification in combination with the knowledge graph, generates a final report containing a risk type, a confidence, a reasoning chain and a modification suggestion, and continuously optimizes the model through user feedback data, so that efficient, accurate, interpretable and self-adaptive optimization of contract risk identification are realized.

An electronic apparatus is configured to track risk factors of a real-world event. The apparatus has utility to business-to-business sale transactions such that it reduces the likelihood of lost sales opportunities. The apparatus display's a risk visualization area subdivided into distinct segments, each representing a unique type of risk associated with the real-world event. Each segment indicates a risk level based on inputted or received data relating to the event. The electronic apparatus utilizes an Expert System to improve the accuracy of the inputted data. The apparatus is communicable with a server such that: multiple users may access the same data and receive real-time updates on the event and any associated changes in risk; and the apparatus can communicate with third-party nodes, either to retrieve information or for data analysis, which may be carried out via artificial intelligence (AI). The risk-management is effected using the P6™ / methodology.

The invention discloses an enterprise-level application operation and maintenance risk management and control method and device, a program and a storage medium. The method comprises the following steps: acquiring a plurality of risk characteristics of a target risk event; determining the risk type of the target risk event; determining a risk coping strategy for the target risk event according to the risk field and a preset risk coping strategy set; under the condition that the risk field is the known risk, obtaining operation environment data of the operation and maintenance carrier; determining a target diagnosis script according to the operation environment data, the risk coping strategy and a preset diagnosis script library; determining a target solution for the target risk event based on the target diagnosis script and a preset solution set; sending the target solution to the front end, and in response to a received confirmation instruction sent by the front end, generating a risk disposal script according to the target solution; and controlling the operation and maintenance carrier to operate the risk disposal script, and outputting a risk disposal result. According to the method, the risk blind area in enterprise-level application operation and maintenance can be reduced.

The invention discloses an account risk assessment method and device, electronic equipment and a computer program product, and relates to the financial field, the method comprises the following steps: obtaining first feature data and second feature data associated with a to-be-assessed account, the first feature data being used for indicating historical transaction behaviors of the account, and the second feature data being used for indicating the historical transaction behaviors of the account; the second feature data is used for indicating the account attribute of the account; inputting the first feature data into a first evaluation model to obtain third feature data output by the first evaluation model, the third feature data being used for indicating a time sequence dependency relationship of the first feature data; and inputting the second feature data and the third feature data into a second evaluation model to obtain a risk evaluation result of the account output by the second evaluation model, the risk evaluation result being used for indicating the risk type of the account. The account risk assessment method and device solve the technical problem that the accuracy of account risk assessment is low in the prior art.

The invention discloses a transaction risk assessment method and device, a program product and electronic equipment, and relates to the technical field of federal learning, and the method comprises the steps: collecting the transaction information of a financial transaction initiated by a user after the authorization information of the user is received; transmitting the transaction information of the financial transaction to a local target model of the target website; performing feature extraction on the transaction information of the financial transaction through a local target model to obtain L transaction features; determining a risk score of the financial transaction based on the L transaction features; and when the risk score is greater than or equal to a preset score, generating a risk report corresponding to the financial transaction, the risk report at least comprising the risk score, the risk type and the risk transaction link of the financial transaction. The technical problem that in the prior art, due to poisoning attack in the modeling process of a federated model, the accuracy of transaction risk detection through a local model obtained through training based on the federated learning technology is low is solved.

The invention provides an account risk early warning method and device for a financial management system. The method comprises the following steps: acquiring real-time transaction data of a financial account; the value of at least one account path index in the real-time transaction data forms a path feature vector; obtaining a user portrait corresponding to the financial account, and calculating a personal risk score according to the deviation between the path feature vector and the user portrait; when the individual risk score is greater than or equal to a second threshold value, determining a pre-stored risk cluster to which the path feature vector belongs, and calculating a correlation degree between the path feature vector and the pre-stored risk cluster to obtain a group risk score; and performing weighted calculation on the individual risk score and the group risk score to obtain a risk early warning score, and generating alarm information under the condition that the risk early warning score is greater than or equal to a third threshold value. The method solves the problem that in the prior art, account risk early warning rules are rigid, and the risk early warning accuracy is low due to the fact that newly-added risk types are difficult to deal with.

The invention provides a financial transaction accounting risk real-time management and control and monitoring alarm method and system, and relates to the technical field of finance, and the method comprises the steps: when a financial transaction occurs, an accounting risk management and control SDK obtains financial transaction information, inquires a risk accounting management and control rule base, and judges whether the financial transaction needs to be managed and controlled; if management and control are needed, a distributed lock is obtained, and the financial transaction is locked; according to the risk transaction processing rule corresponding to the financial transaction, transaction control is performed on the financial transaction, and the distributed lock is released after the financial transaction is finished; the accounting risk alarm SDK asynchronously extracts messages in the financial transaction process; matching a verification rule in a risk accounting alarm rule base according to the message, and judging whether the transaction has a risk or not; and if the risk exists, respectively registering alarm information according to the risk type, and pushing the alarm information to an alarm module. The risk accounting management and control is carried out through the distributed lock and the risk accounting management and control rule base, the accounting risk is acquired through the transaction message, and the risk alarm is realized.

The invention relates to a platform for realizing accounting intelligent transaction risk management and control, and belongs to the technical field of accounting. The platform comprises a background support class module, an application service class module, an accounting knowledge base, a plurality of MCP servers, an accounting intelligent assistant agent and a client module. According to the invention, aiming at transaction risks which need to be prevented and processed by accountants, the accountants can receive risk early warning information of a monitoring system through a natural language interaction interface based on an mcp protocol by taking a large language model as an intelligent core and through the support of an accounting knowledge base; according to the method, information related to transaction risk prevention in the monitoring system and the accounting system is inquired, the capability of monitoring new risk types is achieved, the transaction risk management efficiency of accountants is improved, and the operation efficiency of the accounting system is improved.

An object of a system according to an embodiment is to analyze risk information of a user and recommend an optimal insurance.SOLUTION: A system includes a reception unit, an analysis unit, and a recommendation unit. The reception unit inputs risk information of a user in a question form. The analysis unit analyzes the risk information input by the receiving unit, and identifies a risk type of the user. The recommendation unit recommends an appropriate insurance based on the risk type specified by the analysis unit.SELECTED DRAWING: Figure 1

The invention discloses a financial risk identification method and device, electronic equipment and a storage medium, and relates to the field of financial science and technology. The method comprises the steps of performing risk monitoring on transaction behavior data to obtain a risk event, a corresponding risk type and target transaction behavior data; according to the target transaction behavior data, extracting a risk sub-graph from a knowledge graph constructed by adopting the transaction behavior data in advance; according to the target transaction behavior data and the risk sub-graph, matching the risk event with a plurality of sub-risk modes included in the risk type to obtain a target sub-risk mode; matching the target transaction behavior data with risk reference information in a knowledge base to obtain target risk reference information; and through a large language model, according to the target transaction behavior data, the target sub-risk mode and the target risk reference information, determining a financial risk identification result of the risk event. According to the technical scheme, the efficiency and accuracy of financial risk identification are improved.

The invention relates to the technical field of financial transactions, in particular to a financial transaction real-time risk identification system and method based on big data, and the method comprises the steps: obtaining transaction process data of a user in response to an evaluation trigger condition, calculating a deviation characterization value in combination with a time deviation degree and a place deviation degree, and determining the risk type of the current transaction; calculating the position concentration degree of the user to determine a backtracking interval for analyzing the historical transaction data, and updating the risk type; clustering a plurality of transaction characteristic values generated by the browsing and purchasing conversion ratio of the user and the order modification frequency ratio to determine a transaction inertia value, and judging the inertia deviation degree of the transaction on that day; acquiring historical data to determine a risk type migration curve of the user; and determining an inertia reference threshold based on the fluctuation characteristic, and determining whether the risk type of the current transaction needs to be corrected based on the inertia deviation degree and the inertia reference threshold. The accuracy of the financial transaction real-time risk identification method based on big data is improved.

The invention belongs to the technical field of electricity market risk identification, and discloses a multi-level spot market risk identification method and a related device, and the method comprises the steps: reading the market data of a multi-level spot market; based on the market data, risk assessment index values of the multi-level spot market are calculated, and the risk assessment index values comprise a market price risk index value, a multi-level market association risk index value and a market power risk index value; calculating a weight coefficient of the risk assessment index value of the multi-level spot market by adopting an improved entropy weight method; and based on the risk assessment index value and the weight coefficient of the multi-level spot market, calculating a market risk comprehensive assessment value, and identifying a risk type and a risk level according to the market risk comprehensive assessment value. An improved entropy weight method is adopted to determine various risk index weights, and the improved entropy weight method can effectively overcome the defects of a traditional entropy weight method and can also enable the entropy weight method to keep the capability of distinguishing entropy value differences.

The invention discloses a risk prevention and control method based on a large model and electronic equipment, and the method comprises the steps: carrying out the invalid data filtering and compliance verification of multi-source business data related to an initiated financial declaration request, and carrying out the data cleaning, and obtaining standard business data; generating a to-be-assessed risk task according to a service association key matched with the standard service data; performing rule verification on the structured business data in the to-be-assessed risk task according to a risk control rule determined by the business association key, and generating a structured risk clue; determining a first risk clue in the unstructured business data of the to-be-assessed risk task by using the large model, and determining a corresponding composite risk control rule according to the actual risk type to which the first risk clue belongs; extracting a second risk clue corresponding to the actual risk type from the structured risk clues, and analyzing the composite risk control rule, the first risk clue and the second risk clue by means of a large model to obtain a risk rating; and determining a disposal operation corresponding to the to-be-assessed risk task according to the risk rating.

The present application 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, extracting first business features and second business features; taking financing events as time anchor points, for each financing event, applying an operating risk analysis model to process the first business features and the second business features, generating a pre-financing risk set and a post-financing risk set including risk types; performing first-order differential analysis on the pre-financing risk set and the post-financing risk set, identifying risk state parameters; for multiple financing events, performing second-order differential analysis, identifying the cross-cycle change trend of the target enterprise risk mode; based on the first-order and second-order differential analysis, generating a multi-layer time sequence knowledge graph to constitute a financing risk dynamic graph. The present application realizes dynamic analysis of financing risk through multi-source invoice data recognition.

The invention relates to a financial risk assessment method and device, electronic equipment and a storage medium, and relates to the field of new energy storage and financial science and technology cross technologies, and the method comprises the steps: constructing and updating a dynamic risk network based on multi-source risk data of uplink storage; simulating the infection characteristics of different risk types in the updated dynamic risk network by adopting a risk infection simulation model, and calculating the risk index value of each node in the dynamic risk network in real time according to the infection characteristics; the risk index value is continuously monitored through the intelligent contract, and when it is detected that the risk index value exceeds a preset threshold value, risk prevention and control measures are executed, multi-dimensional risk factors in shared economy can be captured, a conduction mechanism of risks through a transaction relation, a guarantee chain and other paths can be identified, the data island problem is broken, and the risk prevention and control measures are taken. Data intercommunication of different participants is achieved, and privacy is not leaked through centralized data collection; meanwhile, the data processing period is shortened, the risk of rapid propagation is found and dealt with in time, and the real-time performance of the system is enhanced.

The invention relates to the technical field of intelligent decision, can be applied to a financial science and technology business system platform, and discloses a risk data list reinsurance proportion optimization method, device, equipment and medium, and the method comprises the steps: obtaining an original risk data list of a preset risk type, carrying out the quantum feature coding of the original risk data list, and obtaining a data quantum state code; performing key risk feature screening on the data quantum state codes to obtain key risk features; constructing a quantum risk assessment model according to the key risk features; calculating a risk score of the original risk data sheet according to the quantum risk assessment model; and according to the risk score and a preset reinsurance risk preference, dynamically allocating a reinsurance proportion to the original risk data list. By calculating the risk score, an objective and comparable numerical basis is provided for reinsurance proportion distribution, and meanwhile, in combination with reinsurance risk preference, dynamic adjustment of the risk data single reinsurance proportion is achieved.

The invention discloses a resource allocation method and device, a program product and a storage medium, and the method comprises the steps: inputting target data into a first model, and obtaining the risk probability of the target data outputted by the first model; determining an initial risk type probability of the target product based on the risk probability and the target data; determining a target risk type probability of the target product based on the initial risk type probability and the target data; determining the risk type of the target product based on the target risk type probability; and allocating resources to events corresponding to the transaction data based on the risk types. Through application of the method and the device, the problem that the resource allocated to the event corresponding to the transaction data of the product is inaccurate due to the fact that the risk type of the product cannot be accurately judged in the related technology is solved, and the effects of accurately identifying the risk type of the product and accurately allocating the resource to the event corresponding to the transaction data of the product are achieved.

The application discloses an agent-based financial risk decision method and device, equipment and a storage medium, relates to the field of artificial intelligence, is applied to a terminal carrying a target risk decision agent, and comprises the following steps: obtaining original multi-source heterogeneous data from each target financial data source and performing a data preprocessing operation to obtain corresponding preprocessed data; performing feature extraction processing on the preprocessed data based on a pre-set feature extraction algorithm to obtain corresponding target data, determining a target risk type and a corresponding risk measurement value based on the target data by using the target risk decision agent, determining target knowledge from a financial knowledge data source based on the target risk type and the risk measurement value corresponding to the target data, and fusing all the target knowledge by using a pre-determined target data fusion algorithm to generate a corresponding target decision strategy. The application improves the analysis capability of financial related data, thereby improving the financial risk assessment capability and decision efficiency.