31 results about "Settlement risk" patented technology

The invention discloses a homomorphic encryption-based cross-industry health insurance data sharing and privacy protection method, and relates to the technical field of health insurance data security, and the method specifically comprises the steps: standardizing medical and insurance industry core data, quantifying key indexes such as a disease clinical risk value and an occupational basic risk coefficient, achieving the format unification of cross-industry data, and achieving the privacy protection of the cross-industry data; further generating ownership, risk and business labels, carrying out encryption processing on data through homomorphic encryption on the risk labels based on three scenes of data sensitivity and business influence grading, business label binding pricing, underwriting and claim settlement prediction, adding an integrity check code to high-risk data, screening ciphertexts based on the labels, and then executing fusion calculation; the comprehensive risk adjustment coefficient ciphertext is generated, the data integrity is verified, the comprehensive risk adjustment coefficient is obtained after collaborative decryption, the comprehensive risk adjustment coefficient is applied to premium pricing, underwriting conclusion generation and claim risk pre-judgment, and the scientificity and accuracy of health insurance pricing and underwriting decision making are improved.

The invention relates to the technical field of cross-border trade settlement, and discloses a cross-border trade settlement risk prevention and control system based on a block chain smart contract, and the system comprises a regional network which serves as a distributed account book infrastructure and is used for storing and sharing the transaction data of all participants; the cross-border trade settlement risk prevention and control system comprises a block chain intelligent contract, a trusted data acquisition and uplink module used for acquiring and verifying off-chain entity trade data and uploading the verified trusted data to a local area network, and the off-chain entity trade data comprises logistics information sensed by Internet of Things equipment. The problem of traditional cross-border trade settlement pain points can be effectively solved, and fraud is prevented and controlled in the whole process by means of dual verification and intelligent contracts; a sharing platform is constructed through the block chain, an information island is broken, the settlement efficiency is greatly improved, and data security and traceability are guaranteed.

The invention relates to a process management and control method and device in insurance services, and aims at different types of insurance services, different large models are adopted to carry out automatic claim settlement analysis, and a claim settlement analysis process is divided into two different large models for processing, so that the claim settlement analysis efficiency and accuracy are improved. The method comprises the following steps: in response to an insurance claim payment application operation in an interaction page, according to an insurance type corresponding to an insurance service, determining a target large model used for carrying out claim settlement analysis on the insurance service in a plurality of pre-trained claim payment large models, and obtaining claim settlement materials related to the insurance service; performing claim settlement risk analysis based on the claim settlement material through the first large model to obtain a risk assessment result, and obtaining a claim payment suggestion of the insurance service based on the claim settlement material and the risk assessment result through the second large model; and pushing the claim settlement material and the claim payment suggestion to related insurance business personnel.

Apparatus, systems and methods improve efficiency in transacting a swap or other futures based financial instrument, by using time-weighted index averages to decrease counterparty settlement risk. In preferred embodiments related to Bitcoin and several other cryptocurrencies, the swaps are based upon a time-weighted index average (Dwa) of multiple instances of difficulty (Dx to Dy) of mining the cryptocurrency over multiple time periods (Px to Py) where both Ds and Ps are available from the decentralized public blockchain. Traders can use these time-weighted index averages in conjunction with the anticipated values of Ds and Ps for the remainder of the duration of the index, to calculate the index value at any given time.

The invention provides an intelligent claim settlement method and device, electronic equipment, a storage medium and a program product. The method comprises the steps of receiving claim settlement request information of a to-be-claimed case; determining a compliance verification result of the claim settlement request information based on a preset rule engine; inputting the claim settlement request information into a pre-trained risk assessment model to obtain an assessment result in response to the fact that the compliance verification result is passed; according to the evaluation result, determining a risk score of the case to be subjected to claim settlement; and according to the risk score, allocating a processing channel of the to-be-claimed case, and determining a processing result of the to-be-claimed case. The claim settlement efficiency can be remarkably improved, the claim settlement risk is reduced, and the user experience is improved.

The invention provides an insurance combination searching method, an insurance combination searching system and a computer program product, which can quickly search an insurance combination matched with a specific insurance applicant from different types of alternative insurance products, and the insurance combination is a plurality of insurance products with variable quantity. And according to the conflict rule, selecting insurance categories from the multi-level categories of the insurance, and dividing all the alternative insurance products into product populations according to the insurance categories. Inputting the insurance applicant feature vector and a group of product feature vectors of insurance products from different product populations into a pre-trained insurance combination quantitative evaluation network, outputting a quantitative evaluation vector representing a plurality of insurance business indexes, and performing comparative calculation on the quantitative evaluation vector and a preset target weight vector, and when a search ending condition is met, ending the search and outputting the group of insurance products as a recommended insurance combination, otherwise, updating the insurance combination and inputting the insurance combination into the insurance combination quantitative evaluation network again. The insurance business indexes comprise a conversion rate, a profit rate, an insurance renewal rate and a claim settlement risk.

The application provides a multi-currency intelligent settlement method and system for cross-border chemical trade, and belongs to the field of trade data processing. The method comprises the following steps: obtaining the characteristics of chemical products and the characteristics of multiple currencies and settlement constraints of multiple currencies during cross-border chemical trade; calculating a settlement sensitivity coefficient according to the settlement constraints; generating a first settlement scheme, analyzing the first settlement time of the first settlement scheme, performing delay analysis and variation prediction, obtaining a first delay amount and a first predicted variation amount; processing and calculating the first delay amount and the first predicted variation amount to obtain a first settlement risk degree, and iteratively optimizing the settlement scheme to obtain an optimal settlement scheme and perform settlement. The settlement sensitivity coefficient quantifies the settlement difficulty, and the settlement scheme is iteratively optimized by combining delay analysis and exchange rate variation prediction, so that the settlement cycle is shortened, the exchange rate fluctuation risk is reduced, and the multi-currency settlement efficiency and transaction stability of cross-border chemical trade are improved.

The present application relates to the technical field of insurance claim settlement, and discloses a property insurance claim settlement risk management method and system based on multi-source spatio-temporal precipitation data, which comprises the following steps: obtaining a precipitation data set of a target region in a target period; determining a precipitation time series stability index based on the continuity change characteristics of the precipitation data set in the time series dimension, and constructing a regional difference dispersion degree based on the distribution discrete characteristics of the precipitation data set in the spatial dimension; obtaining a risk spatial correlation degree according to the historical claim case region and the current precipitation grid, in combination with the intensity evolution mode of the precipitation data set; generating a claim settlement threshold dynamic correction coefficient by fusing the precipitation time series stability index, the regional difference dispersion degree and the risk spatial correlation degree; and dynamically adjusting a preset claim settlement trigger threshold based on the claim settlement threshold dynamic correction coefficient to form a claim settlement risk control management strategy, which significantly optimizes the survey resource allocation efficiency and the disaster prevention and loss reduction action efficiency of the insurance company under the premise of improving the claim settlement risk identification accuracy.

A computerized platform is disclosed for offering event-based outcome contracts, including sports event contracts, while dynamically enforcing jurisdictional eligibility, integrity-scored settlement, and adaptive risk controls. The platform computes an eligibility vector per user and product class using geo-location signals with anti-spoof checks, identity and account attributes, and versioned jurisdiction rules that can incorporate time-varying legalization indicators and exclusion geofences. The system automatically enables, disables, or sunsets classes of contracts in a jurisdiction when predicates change, and records eligibility decisions with ruleset identifiers in an append-only audit log. Event outcomes are determined via multi-source data ingestion with anomaly detection and integrity scoring, including a provisional outcome, challenge window, dispute workflow, and final cash settlement. A risk engine enforces position and exposure limits, throttles, and kill-switch triggers, and a surveillance module flags manipulation patterns. A regulator export interface supports post-trade reconstruction.

The present application relates to the technical field of construction monitoring, and discloses a method and system for dynamic monitoring of construction quality of oblique jet grouting piles in heavy haul railway transition section for settlement control, which comprises: real-time collection of construction parameters including real-time drilling speed, real-time grouting pressure and real-time grout flow rate and settlement records including real-time settlement and vibration interference values of subgrade surface and slope toe during the construction stage of oblique jet grouting piles; calculation of pile forming quality indicators based on the construction parameters and calculation of layered subgrade settlement rates based on the settlement records; construction of a three-dimensional correlation model with the construction parameters as the input layer, the pile forming quality indicators as the intermediate layer and the layered subgrade settlement rates as the output layer; when a settlement risk is determined to occur, reverse matching of the settlement risk traceability results is carried out based on the correlation model according to the same period parameters, construction parameter adjustment suggestions are determined, and a construction quality detection report is generated; and effective settlement control of the construction process of oblique jet grouting piles in heavy haul railway transition section is realized.

Embodiments of the present invention provide novel methods and systems to instantly settle transactions, remove middlemen, reduce and remove settlement risk, and dramatically reduce time and costs in the operations of a financial exchange across asset categories.

Apparatus, systems and methods improve efficiency in transacting a swap or other futures based financial instrument, by using time-weighted index averages to decrease counterparty settlement risk. In preferred embodiments related to Bitcoin and several other cryptocurrencies, the swaps are based upon a time-weighted index average (Dwa) of multiple instances of difficulty (Dx to Dy) of mining the cryptocurrency over multiple time periods (Px to Py) where both Ds and Ps are available from the decentralized public blockchain. Traders can use these time-weighted index averages in conjunction with the anticipated values of Ds and Ps for the remainder of the duration of the index, to calculate the index value at any given time.

The invention provides a service provider settlement management system and method and an intelligent terminal. The method comprises the following steps: collecting biological characteristics and an initial physiological state of a user, performing wavelet transform on the biological characteristics to extract a frequency domain component, and performing Kalman filtering on the initial physiological state to obtain a target physiological state. And carrying out space-time alignment on the two through a dynamic time warping algorithm to generate a target multi-dimensional identity feature vector. Inputting the vector into a deep belief network for classification to obtain a biological feature classification result; and calculating a risk assessment parameter by using a preset risk assessment model, and calculating a target biological feature matching degree score at the same time. And associating and integrating the risk assessment parameter and the matching degree score, generating a settlement risk assessment file, and executing biological feature authentication of payment authorization according to the settlement risk assessment file. And finally, according to the authentication result and the evaluation file, service provider settlement operation is completed. According to the invention, the security, accuracy and efficiency of payment authorization and service provider settlement are improved.

The invention discloses an insurance customer demand matching and business recommendation method and device based on a knowledge graph, and the method comprises the steps: carrying out the targeted preprocessing of structured data and unstructured data in an insurance business scene, and extracting standardized entity, relation and attribute data; s2, converting the standardized data extracted in the step S1 into an RDF / RDFS format of a unified semantic framework to obtain a multi-source independent initial knowledge graph; through an entity alignment method combining semantic standardization and semantic matching, redundancy and noise of a multi-source initial knowledge graph are eliminated, and a global customer knowledge network is formed through fusion; based on the fused global customer knowledge network, customer portraits are perfected through rule reasoning, and potential association relationships among entities are identified; and realizing accurate matching and personalized recommendation of customer demands and insurance businesses through risk level evaluation, hidden demand mining and claim settlement risk check in combination with the improved customer portrait and the inference result.

The application provides a multi-modal data-driven intelligent claim settlement risk control system, relates to the technical field of insurance services, and comprises a multi-modal data acquisition module, a multi-modal data fusion and correlation analysis module, a historical claim analysis module and a decision output module; the multi-modal data acquisition module acquires multi-modal data related to a vehicle accident claim settlement event; the multi-modal data fusion and correlation analysis module constructs a multi-modal fusion model and calculates a correlation index; the historical claim analysis module acquires metadata of a claim settlement event and calculates a claim settlement similarity index based on the metadata; the decision output module pre-sets a correlation threshold and a claim settlement similarity threshold, establishes an inspection mechanism, and determines whether to trigger a manual inspection process. The application realizes multi-dimensional evidence consistency verification and space-time context risk perception capability that cannot be achieved by a conventional system, locks high-risk cases through a double-threshold joint decision mechanism, and automatically triggers manual inspection, effectively solving the limitations of traditional risk control systems, such as dependence on a single data source, difficulty in identifying complex fraud patterns, and lack of dynamic adaptability.

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 discloses an international trade cross-border settlement risk control management method, and relates to the technical field of block chains, and the method comprises the following steps: S1, continuously collecting price push records of a target object on a block chain through a price path state maintenance module, each record comprising a price value, a push timestamp and an object identifier, when the positions are opened, price path index mapping is established with the corresponding position identifiers, so that each position has a clear price path fragment on the chain; and S2, executing aggregation operation on the price pushing record through a dislocation risk calculation module according to a preset sliding window rule, integrating price path state maintenance, two-stage income settlement and state compression management of a delay settlement voucher on a chain, and through sliding window price path consensus and voucher storage of suspicious income, carrying out real-time settlement on the price pushing record. And on the premise of no rollback transaction, automatic posterior callback aiming at the misprice arbitrage income of the oracle machine is realized with relatively low chain storage and calculation overhead.

The invention relates to a fund settlement abnormity monitoring method, device and system. The method comprises the following steps: in response to monitoring that the transaction amount of a to-be-monitored transaction is greater than a preset amount or the transaction frequency is greater than a preset frequency, obtaining transaction data of the to-be-monitored transaction and transaction party information of a transaction party associated with the to-be-monitored transaction; generating a first transaction sub-graph of the to-be-monitored transaction based on the transaction amount, the transaction party information and the transaction relationship network; selecting a candidate normal transaction sub-graph matched with the first transaction sub-graph from a preset transaction relationship network by adopting a graph matching algorithm; performing similarity comparison on the first transaction sub-graph and each candidate normal transaction sub-graph in the candidate normal transaction sub-graphs to obtain similarity values corresponding to the candidate normal transaction sub-graphs; selecting a maximum similarity value from the similarity values; and under the condition that the maximum similarity value is smaller than a preset threshold value, determining that the to-be-monitored transaction is an abnormal transaction. According to the scheme, the comprehensiveness of fund settlement risk identification is improved.

The application discloses a kind of electric power bilateral transaction settlement deviation strategy optimization method, system and storage medium, belong to electric power market transaction technical field.The application obtains user historical load data, electricity demand prediction and transaction package parameters in real time through data interface;Based on probability distribution, construct load random fluctuation model, generate multi-scenario simulation load curve using Monte Carlo algorithm;Parallel trial calculation is carried out to candidate package using simulation settlement engine;The optimal transaction package is dynamically screened by multi-objective optimization function, and transaction instruction is generated;In transaction execution, deviation is monitored in real time by closed-loop feedback module, and contract adaptive adjustment is triggered.System includes five modules of data acquisition, random modeling, simulation settlement, strategy optimization and closed-loop feedback, integrates LSTM-GARCH hybrid prediction, GPU accelerated calculation, block chain storage technology.Improves the accuracy and adaptability of deviation strategy, reduces settlement risk, optimizes transaction efficiency, supports stable operation of electric power market.

Apparatus, systems and methods improve efficiency in transacting a swap or other futures based financial instrument, by using time-weighted index averages to decrease counterparty settlement risk. In preferred embodiments related to Bitcoin and several other cryptocurrencies, the swaps are based upon a time-weighted index average (Dwa) of multiple instances of difficulty (Dx to Dy) of mining the cryptocurrency over multiple time periods (Px to Py) where both Ds and Ps are available from the decentralized public blockchain. Traders can use these time-weighted index averages in conjunction with the anticipated values of Ds and Ps for the remainder of the duration of the index, to calculate the index value at any given time. The index can be used to increase or decrease mining of digital assets, or switch allocation of resources between mining different digital assets.

The invention discloses a customer service intelligent processing method and device, equipment and a storage medium, belongs to the technical field of artificial intelligence, and is applied to optimization processing of financial business services. According to the method, the distributed data processing architecture is constructed, so that each node completes model training locally and uploads gradient parameters, and a global model is generated. And aligning the timestamp information and the updating frequency of each data source through a unified time reference. And standardizing the heterogeneous data into a unified feature vector by using feature mapping and dimension reduction technologies, and generating a customer portrait. Market policy changes and hot event information are collected in real time, and market state classification tags are generated in combination with natural language processing and event influence evaluation. Optimal model configuration adapting to different market states is obtained by dynamically adjusting model parameter weights and reward function evaluation. In a customer claim settlement processing process, customer portraits and market state information are fused, and intelligent decision-making of claim settlement risk grade assessment and personalized product recommendation is realized.

Apparatus, systems and methods improve efficiency in transacting a swap or other futures based financial instrument, by using time-weighted index averages to decrease counterparty settlement risk. In preferred embodiments related to Bitcoin and several other cryptocurrencies, the swaps are based upon a time-weighted index average (Dwa) of multiple instances of difficulty (Dx to Dy) of mining the cryptocurrency over multiple time periods (Px to Py) where both Ds and Ps are available from the decentralized public blockchain. Traders can use these time-weighted index averages in conjunction with the anticipated values of Ds and Ps for the remainder of the duration of the index, to calculate the index value at any given time.

This application provides a method, system, equipment, and medium for foundation settlement detection in engineering testing, relating to the field of engineering safety testing technology. The method includes acquiring multi-source monitoring data collected in the area to be tested and adjacent sensitive structures; fusing the multi-source monitoring data to obtain a target detection dataset; inputting the target detection dataset into a rapid screening model to obtain settlement risk assessment values, forming a risk assessment point set; if the settlement risk assessment value at any point in the risk assessment point set is greater than a first warning threshold, generating a preliminary warning signal, and determining the area of ​​interest based on the spatial distribution of the risk assessment point set; responding to the preliminary warning signal, acquiring a fused dataset for in-depth analysis; performing in-depth analysis of the area of ​​interest based on multiphysics coupled numerical simulation using the fused dataset to obtain a settlement risk level; and generating graded warning information based on the settlement risk level. This application improves the accuracy of detection.

The invention discloses a dynamic data-driven risk control method for health insurance claim settlement, and the method comprises the steps: collecting and preprocessing claim settlement text data, and generating a text corpus; normal claim settlement samples are screened based on compliance labels, potential Dirichlet distribution topic modeling is carried out, and a topic probability feature library is constructed; comparing by a K-nearest neighbor algorithm, and determining K nearest normal claim settlement samples; calculating an anomaly score, comparing the anomaly score with a preset threshold value, and performing anomaly recognition and early warning; dynamic acquisition, data updating and regular parameter adjustment are carried out to form a risk control closed loop. According to the invention, automatic anomaly detection and risk early warning of the whole process of health insurance claim settlement are realized, and the intelligence and precision level of claim settlement risk control is improved.

The application relates to the technical field of artificial intelligence, and discloses an intelligent claim settlement method and device, computer equipment and a storage medium, which comprise the following steps: in response to detecting that a user triggers a self-service insurance claim settlement service on a client, taking a picture of a road surface at a vehicle accident site through the client to obtain a claim settlement photo; performing semantic segmentation on the claim settlement photo to obtain a target road surface texture fingerprint; performing slope calculation according to the claim settlement photo to obtain a target road surface physical inclination; obtaining target location information of the user through the client, and querying a map database based on the target location information to obtain reference road surface information; performing risk identification on the target road surface texture fingerprint and the target road surface physical inclination based on the reference road surface information to obtain claim settlement risk information; and performing insurance claim settlement for the user based on the claim settlement risk information and the claim settlement photo. The application can be applied to the insurance scene of financial technology and medical health, and the self-service insurance claim settlement safety is improved.

The invention provides a power market settlement bill abnormity identification method and system based on an isolated forest, and relates to the technical field of power grids. According to the method, the time sequence alignment is performed on the original settlement data through the dynamic time warping algorithm, the problem of data dislocation caused by inconsistent settlement period and rhythm is solved, and the multi-dimensional features such as the mean value, the variance and the time sequence trend are synchronously extracted by using the sliding window to perform global fusion. The method comprises the following steps of: forming a fusion feature vector capable of representing statistical characteristics and reflecting a time sequence change rule, inputting the fusion feature into an isolated forest model to obtain an abnormal score, and judging in combination with a preset threshold value to realize bill abnormity identification, and in the process, abnormal isolation of the statistical characteristics and auxiliary verification of the time sequence rule are fused, so that the accuracy of bill abnormity identification is improved. The statistical fluctuation and the real abnormity are better distinguished, the problem that the bill abnormity identification of the electricity market is inaccurate is solved, and the automation level and the accuracy of the settlement risk identification of the electricity market are improved.

The invention relates to the technical field of financial data processing, and discloses an online insurance buying and claim settlement integrated processing method and system, and the method comprises the steps: building an initial risk vector for online insurance buying; when claim settlement is initiated, initializing a trust state vector based on the risk vector; in the claim settlement period, dynamically updating the trust vector according to the updating information, and calculating a trust scalar; calculating a pre-payment amount in combination with the trust scalar and the pre-estimated compensation amount, and paying the pre-payment amount to a specified account after the pre-payment amount is confirmed by the insured party; the system comprises a risk vector establishment module, a trust vector initialization module, a trust vector updating module, a trust scalar calculation module, an advance payment amount calculation module and an advance payment processing module. According to the invention, the dynamic trust evaluation model penetrating from the insuring stage to the claim settlement stage is constructed, and the model utilizes the state vector and the state space equation to realize continuous quantitative evaluation of the claim settlement risk and automatic and precise advance payment pricing decision.

The invention relates to the technical field of financial science and technology, can be applied to the agricultural insurance industry, and discloses an insurance claim risk assessment method, device and equipment and a storage medium. The method comprises the following steps: acquiring historical accident data with a time sequence, and determining accident factors according to the historical accident data; taking the accident factor as a dependent variable, taking whether the accident occurs as a result variable, fitting a function relationship between the dependent variable and the result variable, and establishing a first time sequence model according to the function relationship; based on a Granger causality test method, executing Granger causality test according to the first time sequence model and the historical accident data, and executing result test according to a Granger causality test result to obtain a feature relation graph; and performing claim settlement risk assessment according to the characteristic relation graph. According to the method, the application scene barrier of a traditional algorithm model can be broken through, the risk factors are mined from the global perspective, the time sequence is introduced to associate the risk factors, and the evaluation accuracy of the agricultural insurance claim payment condition is improved.

The invention relates to the technical field of insurance claim settlement, and discloses a financial claim settlement risk management method and system based on multi-source space-time rainfall data, and the method comprises the steps: obtaining a rainfall data set of a target region in a target time period; determining a precipitation time sequence stability index on the basis of continuous change characteristics of the precipitation data set on the time sequence dimension, and constructing regional difference dispersity on the basis of distribution discrete characteristics of the precipitation data set on the spatial dimension; according to the historical claim settlement case area and the current precipitation grid, combining an intensity evolution mode of the precipitation data set to obtain a risk space correlation degree; fusing the precipitation time sequence stability index, the regional difference dispersion degree and the risk space correlation degree to generate a dynamic correction coefficient of a claim settlement threshold value; and dynamically adjusting the preset claim settlement trigger threshold based on the claim settlement threshold dynamic correction coefficient to form a claim settlement risk control management strategy, and significantly optimizing the survey resource configuration efficiency and the insurance company disaster prevention and loss reduction action efficiency on the premise of improving the claim settlement risk identification precision.