54 results about "Risk appraisal" patented technology

The invention provides an intelligent supervision system and method for safety production liability insurance, and is applied to the technical field of supervision science and technology. The system comprises an enterprise port, an insurance institution port, a supervision department port and a background port, and integrates four modules: an automatic safety insurance data matching module synchronizes insurance buying information in real time and generates a supervision form; the safety production state monitoring module collects enterprise data to support risk assessment and provide accident prevention service; the accident prevention service evaluation module judges validity through data comparison before and after service and tracks and rectifies the data; and the data statistical analysis module realizes multi-dimensional query, dynamic ranking and visualization. According to the method, data collection, state monitoring, effect evaluation and rectification closed-loop management are realized through multi-port deployment, and a supervision mechanism of enterprise evaluation and supervision reward and punishment linkage is established. According to the invention, through cross-department data intercommunication, the problems of information isolated island and supervision lagging of the traditional responsibility insurance are effectively solved, and the supervision efficiency of the responsibility insurance is remarkably improved.

The invention relates to the field of risk management and control of insurance underwriting business, and discloses an underwriting risk assessment method and system, and the method comprises the steps: collecting insurance data of a target customer, and recognizing risk factors affecting underwriting in the insurance data; the risk factors comprise discrete factors; performing feature conversion on the discrete factors according to a preset factor splitting election or factor splitting expansion method, and encoding the discrete factors into a numerical form; selecting key features suitable for different risk scenes from the risk factors, and inputting the key features into a plurality of trained sub-models to obtain scores of the target customer in different risk scenes and interpretable results corresponding to the scores; the plurality of sub-models comprise a BMI intelligent identification sub-model, a claim settlement history risk control sub-model, a disease risk level classification sub-model and a delayed risk re-mining sub-model; and performing weighted calculation on the scores obtained by the sub-models, and finally obtaining the total risk score of the target customer in the current business.

The invention discloses an underwriting risk assessment report generation method and system, and the method comprises the steps: obtaining the text data, insurance vehicle video streams and external environment data of an insured person in real time, and extracting a physical defect feature set of each vehicle video stream; performing cross-modal fusion on the text features, the physical defect feature set and the initial environmental risk factor score through an attention mechanism layer to generate a fusion feature vector, and decoding the fusion feature vector to obtain a target surface damage quantized value, a target part corrosion area proportion and a target environmental risk factor score; and through a preset target large language model, generating a structural integrity assessment item, a mechanical fault probability prediction item and an environment damage risk trend item one by one in an autoregression mode until all assessment items are generated, and obtaining an underwriting risk assessment report. According to the method, the physical state change of the insurance object can be dynamically captured, so that the timeliness and interpretability of risk assessment are improved.

The invention discloses a risk assessment method and device, equipment and a storage medium. The method comprises the following steps: determining a risk assessment model, a preset advance rule and advance request data; determining a target score of the advance request data according to a risk assessment model and a preset advance rule; and performing risk assessment on the advance request according to the target score, and determining an approval decision. According to the technical scheme of the invention, through the preset risk assessment model and the preset advance rule, the target score of the advance request data is determined, risk assessment is performed on the advance request according to the target score, and an approval decision is made, so that manual intervention is reduced, the real-time performance and accuracy of the risk assessment of the advance request are improved, and the security of fund advance is ensured. The satisfaction degree and the business conversion rate of the insurance advance service are enhanced, and a safe, reliable and efficient risk management solution is provided for the commercial insurance advance service.

The invention provides an insurance customer cross-institution credit risk assessment system based on federated learning, and relates to the technical field of credit risk assessment, and the system comprises a data preprocessing module, a federated training module, a privacy protection module, a block chain excitation module, an interpretability enhancement module, a model optimization module and a risk assessment module. Through federal learning, available and invisible collaboration of cross-mechanism data is realized, exclusive risk features of the insurance industry are extracted, training strategies and privacy protection intensity are dynamically adjusted, mechanism contributions are quantified, automatic excitation is performed, compliance interpretable evaluation results are generated, and an insurance service cycle optimization model is adapted. According to the invention, comprehensive improvement of risk assessment accuracy, business scene adaptability, privacy security guarantee and supervision compliance is realized through cooperation of multiple modules, and an efficient, safe and feasible integrated technical scheme is provided for cross-institution credit risk assessment in the insurance industry.

The invention provides an insurance risk assessment and health management scheme generation system for sub-health crowds, which is applied to the technical field of health management, an acquisition module is responsible for collecting actual data of a user in the process of executing a health management scheme, and a modeling module quantifies the physiological response degree of an individual to the scheme and outputs a physiological response value. And the evaluation module evaluates the overall effect of the health management scheme currently executed by the user by using the physiological response value output by the modeling module. And the adjustment module modifies the health management scheme of the user according to the quantitative evaluation result obtained by the evaluation module. Through a cycle process of acquisition, modeling, evaluation and adjustment, the system can continuously monitor individual response and dynamically optimize the scheme, so that the actual improvement effect of the scheme on individual health is improved, and a data basis is provided for more accurate insurance risk evaluation.

The Decentralized Global Banking System (DGBS) introduces a borderless, AI-enhanced, blockchain-powered financial infrastructure that eliminates reliance on traditional banks, credit bureaus, and centralized institutions. It enables global individuals and entities to access financial services autonomously, ensuring universal financial inclusion, efficiency, and security through decentralized credit scoring, AI-driven risk assessment, P2P lending, decentralized automated teller machines, and smart contract-driven financial solutions.

The invention discloses a dynamic risk assessment method and system before network security insurance protection based on a PIPDR2 model, and the method comprises the steps: building and determining the PIPDR2 model, and enabling the PIPDR2 model to comprise a PIPDR2 risk assessment factor layer and a risk assessment index layer; a security policy factor module, a risk identification factor module, a security defense factor module, a security detection factor module, a security response factor module and a security recovery factor module are configured in the PIPDR2 risk assessment factor layer; in the risk evaluation index layer, corresponding risk evaluation indexes are configured for each evaluation factor module in the PIPDR2 risk evaluation factor layer based on network security level protection evaluation data; on the basis, an analytic hierarchy process (AHP) is adopted to carry out risk quantitative evaluation. According to the scheme, risk quantification, accurate premium pricing and continuous optimization are realized by integrating the equal insurance evaluation data and the AHP, and the collaborative efficiency of insurance products and safety protection is improved.

The invention discloses a multi-mortgage guarantee clearing ability assessment and risk disposal method and device, electronic equipment and a storage medium, and relates to the field of financial risk assessment. According to the technical scheme, the method comprises the following steps of: evaluating the clearing capability, obtaining a mortgage guarantee object type, and determining a mortgage guarantee object clearing capability value; performing settlement risk assessment, and obtaining a comprehensive settlement capability coefficient of the assessment object after loan default; carrying out clearing risk early warning, and carrying out risk prompting to a lending institution according to the comprehensive clearing capability coefficient of the evaluation object; and carrying out clearing risk disposal, calculating an amount of adding or replacing the mortgage guarantee according to the comprehensive clearing capability coefficient of the evaluation object and a preset lowest comprehensive clearing capability coefficient, and displaying a mortgage guarantee supplementing scheme to a lending institution. The problem of low stock loan risk assessment and disposal efficiency in the prior art is solved.

The invention discloses a building fire risk and secondary disaster accident risk assessment method, and relates to the technical field of fire insurance risk assessment, and the method comprises the steps: building an interdisciplinary assessment team, and dividing the risk levels; linkage between the assessment subject capability and the insurance business is broken through; and carrying out risk monitoring on the building. According to the invention, systematic identification and quantification of building fire and secondary disaster risks thereof are realized; the accurate pricing capacity, the active damage prevention capacity and the dynamic risk control level of the insurance industry in the field of fire risks are improved, meanwhile, an insurance buyer is stimulated to continuously improve the fire safety condition, and formation of a good management ecology with risk sensibility, insurance premium accompanying and prevention and control preposition is promoted.

The invention discloses a power system insurance and supply risk assessment method considering an extreme weather typical meteorological year, and the method comprises the steps: 1, obtaining historical meteorological data of a target region, generating a typical meteorological year through employing a Sandia method, and improving the typical meteorological year through employing a quantile increment mapping method, and obtaining the extreme weather typical meteorological year; 2, performing scene division on historical meteorological data in a typical meteorological year of extreme weather by adopting a K-means clustering algorithm, using an obtained clustering result to train a denoising variation auto-encoder model, generating a typical weather scene set and calculating the probability of a typical meteorological scene; 3, by taking the minimum load shedding capacity and the minimum wind and light abandoning capacity of the power system as targets, constructing a supply guarantee operation model of the power system; and 4, calculating an insurance supply risk assessment index of the power system. According to the method, supply insurance risk assessment is carried out on the typical meteorological year of the extreme weather, and supply insurance weak links of the novel power system with high new energy permeability under the extreme weather are described by calculating supply insurance risk indexes under the typical scene of the extreme weather.

The invention provides a privacy protection insurance data fusion method, which is realized by depending on three modules of data preprocessing, data fusion and analysis application and cloud servers SA, SB and SC, and comprises the following steps: a data owner uploads original data to the SA; the SA performs de-identification and standardization on the data to obtain a unified feature vector; the SA encrypts the vector by using the public key of the SC and transmits the vector to the SB; executing PFTD fusion by the SB and the SC based on a FairTD algorithm, and iteratively generating fusion data in a ciphertext domain; the SC decrypts the fused data and returns the fused data to the SA; the SA uses the fusion data to train a model, and a user calls the model to obtain an analysis result. According to the method, sensitive information can be preliminarily shielded, the privacy disclosure risk is reduced, fairness and high quality of fusion data are guaranteed, analysis accuracy is improved, and the method is suitable for insurance buying, risk assessment, anti-fraud and other businesses.

The invention belongs to the technical field of life insurance management, and discloses an intelligent group life insurance management system based on group dynamic portraits, which comprises the following modules: a multi-dimensional data fusion module, a group health risk dynamic modeling module, a self-adaptive group pricing and automatic underwriting engine and a claim settlement anti-fraud collaborative network. Enterprise HR data, financial data, employee health data and industry macroscopic data are integrated through a multi-dimensional data fusion module to construct a group dynamic portrait, and comprehensive and dynamic data support is provided for risk assessment, so that group health risk dynamic modeling based on the portrait can accurately capture health risk changes of an insured group; according to the method, a rate adjustment model is established in combination with dynamic factors such as employee flow rate and enterprise financial stability, high matching of insurance premium and group real risks can be realized, more competitive prices are provided for low-risk enterprises to improve the customer retention rate, and accurate fee adding can be performed on high-risk enterprises to effectively cover risk openness.

The invention relates to the field of financial science and technology, and discloses an insurance data processing method, device and equipment and a storage medium, which can be applied to the field of financial science and technology, and comprises the following steps: determining a target geographic area needing insurance data processing, and carrying out hexagonal rasterization processing on the target geographic area, obtaining a hexagonal grid of the target geographic area, wherein the hexagonal grid comprises a plurality of hexagonal grid units; associating historical huge disaster insurance policies in the target geographic area to the corresponding hexagonal grid units; for each hexagonal grid unit, determining a drawing style of the hexagonal grid unit according to the insurance information of the historical disaster insurance policy associated with the hexagonal grid unit; and according to the drawing styles of the hexagonal grid units, the hexagonal grids are superimposed and drawn on the regional map of the target geographic region. The problems of insufficient refined assessment and poor visualization effect during huge disaster underwriting risk assessment in the prior art are solved.

The application discloses a kind of underwriting risk assessment report generation method and system, comprising: the text data of the insured person, insurance vehicle video stream and external environment data are acquired in real time, and the physical defect feature set of each vehicle video stream is extracted;Text features, the physical defect feature set and initial environmental risk factor score are fused through attention mechanism layer across modalities, generate fusion feature vector, and the target surface damage quantitative value, target component rust area proportion and target environmental risk factor score obtained by decoding the fusion feature vector;Through the target large language model of pre-setting, in autoregressive manner item by item generate structure integrity evaluation item, mechanical failure probability prediction item and environmental damage risk trend item, until all evaluation items are generated, obtain the underwriting risk assessment report.The present application can dynamically capture the physical state change of insurance object, and then improve the timeliness and explainability of risk assessment.

The invention relates to the technical field of artificial intelligence, can be applied to business system platforms such as financial science and technology, and discloses an insurance processing method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining real sample data of an insured product, and based on the real sample data, generating virtual sample data corresponding to the real sample data through a generative adversarial network; fusing the real sample data with the virtual sample data, and performing claim risk assessment on the mixed insurance sample to obtain historical claim risk data; performing fine adjustment on the large language model by utilizing historical claim risk data to generate a claim risk assessment model; obtaining product data of the target insured product, and generating a claim risk assessment result of the target insured product; comparing and analyzing the claim risk assessment result with the insurance policy content of the target insured product, and generating a claim judgment report of the target insured product; in the face of an insurance processing scene, the claim settlement judgment report of the target insured product can be efficiently and accurately generated.

The invention relates to an insurance product recommendation method and system based on a dynamic claim settlement customer portrait. The method comprises the following steps: acquiring insurance company business data and third-party mechanism interface data of a target customer in real time; performing feature extraction to obtain a customer portrait of the target customer; performing comprehensive claim settlement risk assessment on the customer portrait from the family relationship dimension, the insurance claim settlement behavior dimension, the insurance purchase behavior dimension and the customer third-party data dimension by using a preset four-dimensional customer risk scoring model to obtain a claim settlement risk assessment result; and recommending an adaptive insurance product to the target customer according to the claim risk assessment result. The insurance company business data and the third-party mechanism interface data are integrated to obtain the customer portrait, the condition of data islands is avoided, the preset four-dimensional customer risk scoring model is utilized to perform claim risk assessment on the customer portrait from four dimensions, the potential claim risk of the customer is covered more strictly, and the customer experience is improved. And the insurance product recommendation is more accurate.

The invention relates to the technical field of group insurance risk early warning, in particular to a group insurance risk grading early warning method and system based on big data, and the method comprises the following steps: obtaining group members corresponding to a group insurance and risk features for risk assessment, and building an association relationship between the group members and the risk features, the association relationship comprises a feature disk, a member disk and a plurality of docking chains; acquiring risk features corresponding to each group member in the insurance group to obtain a current risk feature set; monitoring a member change event of the insured group; when a member change event occurs in the insured group, updating a current risk feature set of the group based on the association relationship; inputting the updated current risk feature set into a risk assessment model, and generating an updated risk level and early warning information of the insured group; and according to the updated risk level, a corresponding risk early warning response action is triggered, so that the accuracy and timeliness of an evaluation result can be improved.

The invention discloses an insurance risk decrement evaluation method based on a large language model, and relates to the technical field of insurance risk management, and the method comprises the steps: carrying out the interactive cooperative reasoning through a large language model and an insurance risk domain knowledge graph, obtaining a key association assertion, and integrating the results of multiple rounds of reasoning to generate a deep risk conduction chain draft; performing causal inference correction on the key association assertion in the deep risk conduction chain draft, and performing anti-fact intervention and reasoning through a large language model to generate a final version risk assessment report; and according to the final version risk assessment report, proposing an underwriting strategy optimization suggestion for the insurance party, proposing improvement measures and management optimization suggestions for the insurance party, and generating an insurance risk decrement assessment scheme. According to the method, the causal relationship and the statistical association are accurately distinguished through large language model anti-fact intervention analysis, false association links are effectively removed, a real causal path is enhanced, a risk assessment result is more accurate and reliable, and differentiated pricing and risk reduction decisions are supported.

This invention discloses an intelligent auto insurance assessment method and system based on data analysis, specifically relating to the field of auto insurance assessment technology. It involves time-series alignment and noise reduction of continuous driving behavior data streams and road environment data streams collected from in-vehicle and mobile terminals. This process identifies risk events during driving, such as distraction, changes in following distance, and braking response. State transition detection is performed based on the chronological order of these events to delineate risk accumulation zones. A risk chain graph is constructed by calculating the time-delay correlation strength of adjacent risk events within the risk accumulation zone. The continuous contraction of risk margins in the chain path is identified, resulting in a chain risk index. Finally, the insurance risk level and premium rate coefficient are determined based on the chain risk index, ultimately achieving intelligent and precise auto insurance risk assessment and premium pricing, improving the accuracy and rationality of auto insurance assessment.

The present invention is an insurance deductible coverage system. The system includes a mobile application and website interface that enable users to browse, select, and manage deductible costs, coverage, and insurance plans. A server with interconnected databases stores user profiles, insurance provider information, and claim records, while an API module provides real-time access to insurance data from approved providers. The system incorporates a risk assessment engine to analyze user data and claims history, enabling optimized bundling of premiums and deductible coverage tailored to user needs. Upon selection, the system generates a digital policy and processes deductible coverage payments. The system offers users a cost-effective, streamlined way to manage deductible expenses and insurance coverage.

The invention relates to the technical field of data processing and risk assessment, and provides an insurance risk assessment method, a training method, a training device, equipment and a storage medium, and the method comprises the steps: obtaining health state data of a user, the health state data comprising multiple types of archive data; extracting features corresponding to the health state data based on a preset feature extraction network; based on a preset portrait construction model, fusing features corresponding to the health state data to obtain a health portrait of the user; and based on a preset risk assessment model, according to the health portrait of the user, assessing the risk that the user purchases the life insurance to obtain an assessment result. According to the method, the specific health state of the user is combined, so that the accuracy of insurance risk assessment is improved. By taking a medical scene as an example, physiological indexes of a user and health status data such as medical images and blood test reports in a medical institution can be obtained, and different types of health status data are fused, so that the comprehensiveness of risk assessment is improved.

This invention relates to the field of financial customer data management technology, and in particular to a financial customer data management method and system based on big data assessment. This invention combines the financial customer's main attribute data and historical financial transaction data to analyze the potential for triggering claims for the financial customer's goods; it combines the cargo transportation data and transportation route data of the financial customer's associated goods to analyze the risk of abnormal cargo status in the current transportation task; based on the analysis results of the financial customer's potential for triggering claims for the financial customer's goods, and the analysis results of the risk of abnormal cargo status in the current transportation task, it assesses the claim risk of the financial customer's current transportation task; based on the assessment results of the claim risk of the financial customer's current transportation task, it provides a cargo claim warning; thereby improving the accuracy of risk pricing and claims review, effectively reducing potential cargo damage losses and claim costs, and enhancing customer service experience and risk management efficiency.

The invention discloses a pet insurance file management system based on feature recognition, and relates to the technical field of pet insurance management, and the system comprises a pet collection module which is used for collecting the basic feature information of a pet, and obtaining a preliminary insurance scheme according to the comparison of the basic feature information; the risk assessment module is used for assessing the preliminary insurance scheme according to the collected basic feature information, and if the assessment is passed, the preliminary insurance scheme is determined as an insurance scheme; a standby scheme generation module; a claim settlement module; specific conditions of pets and insurance schemes are closely combined, through risk assessment and personalized services, customer satisfaction is improved, customer loss is reduced, risk control is provided for insurance companies, and the problems of information asymmetry and unreasonable customer expectation possibly existing in a traditional insurance recommendation process can be effectively solved.

The invention relates to the technical field of intelligent financing, in particular to a general financial service platform and method based on big data, artificial intelligence and RPA, and the platform comprises a message push system, a data receiving and collection module, a data storage module, a pre-loan admission credit approval module, and a post-loan management module. The message pushing system is used for issuing credit product information and carrying out customer drainage and data interaction; the data receiving and collecting module is used for receiving a credit request of a customer, automatically inputting information of the customer and establishing a customer label; the data storage module is used for storing data information; the before-loan admission credit granting approval module is used for verifying credit materials provided by the customer, judging whether the customer meets a credit admission condition or not, and then performing risk assessment and limit calculation to complete customer credit granting approval; and the post-loan management module is used for performing post-loan management, and performing customer operation data tracking, customer interest settlement and repayment pre-reminding.

The invention relates to the technical field of data processing, can be applied to the field of finance, and provides an insurance risk identification method, device, equipment and medium: performing entropy processing on insurance structured data and insurance unstructured data through an entropy model to obtain a time distribution entropy and a channel use entropy; generating a behavior complexity score according to the time distribution entropy and the channel use entropy; weighting all text data in the insured unstructured data to obtain a keyword weighted score and a semantic weighted score; and performing risk identification on the keyword weighted score, the semantic weighted score and the behavior complexity score through a preset scoring model to obtain a risk scoring result corresponding to the target customer. According to the method, the information contribution degree of the structured data and the non-structured data in risk assessment is quantified by calculating the information entropy value. And the structured data and the unstructured data are combined, so that the identification of non-structural factors is increased, and the accuracy of insurance risk identification is improved.

The application provides a kind of safe production liability insurance intelligent supervision system and method, applied to the field of supervision science and technology.The system contains enterprise, insurance agency, regulatory department port and background port, integrates four modules: safety responsibility insurance data automatic matching module real-time synchronizes insurance information and generates supervision form;Safety production state monitoring module collects enterprise data to support risk assessment and provide accident prevention services;Accident prevention service evaluation module determines effectiveness by comparing data before and after service and tracks rectification;Data statistical analysis module realizes multidimensional query, dynamic ranking and visualization.The method realizes data collection, state monitoring, effect evaluation and rectification closed-loop management through multi-port deployment, and establishes a supervision mechanism of enterprise evaluation and supervision reward and punishment linkage.The application effectively solves the problems of traditional safety responsibility insurance information island and supervision lag through cross-department data interconnection, and significantly improves the safety responsibility insurance supervision efficiency.

The embodiments of the present application provide an insurance pricing method, device, electronic device, and medium based on data fusion, which belongs to the field of financial technology. The method includes: in response to a user's pricing instruction, obtaining the basic product information corresponding to the pricing instruction through the pricing system; receiving the identity information sent by the user through the pricing system, and determining the user-related data and the credit platform bound to the pricing system based on the identity information; in response to the user's authorization instruction, obtaining the user's corresponding credit score through the credit platform; determining the comprehensive discount parameters based on the credit score and the user-related data; performing a risk assessment on the basic product information, credit score, and user-related data to obtain a risk assessment result; performing a pricing analysis on the risk assessment result and the comprehensive discount parameters through a pricing model to obtain the target insurance pricing. The embodiments of the present application fully reflect the customer's risk level through multi-dimensional data, thereby realizing dynamic adjustment of the customer's insurance pricing.

The invention provides an insurance auditing method and system and a readable storage medium, in the method, firstly, on the basis of a preset global auditing rule base, a rule subset matched with a target insurance material is determined from the preset global auditing rule base based on the target insurance material, so that irrelevant rule interference is filtered; furthermore, the rule subset is embedded into the preset cue word template to generate the auditing cue word, so that the preset insurance auditing model can be guided to focus on the key auditing dimension, the model output is prevented from deviating from the compliance core, and the identification of the first violation problem point is ensured to fit the actual condition of the material. And finally, material risk assessment is carried out based on the first violation problem point, so that risk analysis is always carried out around a specific violation fact, a material risk analysis report can accurately present a violation essence, a corresponding rule and a risk degree, a basis is provided for subsequent rectification and decision making, and the overall accuracy and reliability of insurance auditing are effectively improved.

The application discloses an insurance customer risk assessment system, which comprises a list module, a collection module and an operation module.The list module is used for displaying a plurality of relevant suitable insurance products in the form of a table to an insurance customer; the collection module is used for collecting information data corresponding to each insurance product, wherein the information data comprises an insurance product validity time limit parameter, an insurance product risk level parameter and an insurance product applicable field parameter, and the collection module is used for statistically collecting all information data sets as R; the operation module is used for operating element data in the set R through a regression function f(x) to obtain a plurality of regression parameters f(x1), f(x2),..., f(x n ); and the evaluation module is used for judging a real risk condition of each insurance product according to specific values of the regression parameters f(x1), f(x2),..., f(x n ).