Insurance underwriting and claim checking system based on artificial intelligence

Abstract

The invention discloses an insurance underwriting and claim checking system based on artificial intelligence, and the system comprises an intelligent insurance underwriting and claim checking system which comprises a data collection and preprocessing module, an intelligent underwriting module, a risk assessment and pricing module, an intelligent claim checking module schematic diagram, a result output and feedback module, and a manual review platform. The data acquisition and preprocessing module comprises a data acquisition sub-module, a data cleaning sub-module, a data format conversion sub-module and a data standardization sub-module. According to the invention, the efficiency and accuracy of underwriting and claim checking can be greatly improved, risks caused by human factors are reduced, and more convenient and personalized service experience is provided for clients.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent insurance systems, and more specifically to an insurance underwriting and claims settlement system based on artificial intelligence. Background Art

[0002] The smart insurance underwriting and claims settlement system is a highly integrated and intelligent solution designed to improve the efficiency and accuracy of insurance business. It makes full use of advanced technologies such as big data, machine learning and natural language processing (NLP) to achieve full process automation and intelligence from data collection to result output.

[0003] Existing insurance underwriting and claims settlement are mostly done manually, which is inefficient and the level of intelligence in handling routine cases is low. Therefore, a new technical solution is needed to solve the problem. Summary of the invention

[0004] The purpose of the present invention is to provide an insurance underwriting and claims settlement system based on artificial intelligence, which solves the problem that the existing insurance underwriting and claims settlement are mostly done manually, which is inefficient and has a low degree of intelligence in the processing of routine cases.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an insurance underwriting and claims settlement system based on artificial intelligence, comprising: an intelligent insurance underwriting and claims settlement system, the intelligent insurance underwriting and claims settlement system comprising a data acquisition and preprocessing module, an intelligent underwriting module, a risk assessment and pricing module, an intelligent claims settlement module schematic diagram, a result output and feedback module and a manual review platform, the data acquisition and preprocessing module comprising a data acquisition submodule, a data cleaning submodule, a data format conversion submodule and a data standardization submodule, the intelligent underwriting module comprising a health information analysis submodule, a financial status analysis submodule and a rule matching submodule, the risk assessment and pricing module comprising a risk assessment submodule, a premium calculation submodule and a personalized solution generation submodule, the intelligent claims settlement module comprising a claim information collection submodule, an image recognition submodule and an authenticity judgment submodule, the result output and feedback module comprising a result display submodule, a feedback collection submodule and a feedback processing submodule, and the manual review platform comprising a case query module, a problem case processing module and an insurance company composite module.

[0006] As a preferred embodiment of the present invention, the data acquisition submodule is responsible for collecting raw data from various sources, the data cleaning submodule is used to eliminate duplicate, erroneous or invalid data, the data format conversion submodule converts data of different formats into a format that can be processed by the system, and the data standardization submodule ensures the uniformity and comparability of data, such as converting measurement values ​​of different units into a unified unit.

[0007] As a preferred embodiment of the present invention, the health information analysis submodule uses NLP technology to analyze the customer's health questionnaire and medical records, the financial status analysis submodule analyzes the customer's financial data such as income, expenditure and assets, and the rule matching submodule automatically matches and scores customer information according to the insurance company's underwriting rules and algorithms.

[0008] As a preferred embodiment of the present invention, the risk assessment submodule accurately predicts the customer's risk based on a machine learning algorithm, the premium calculation submodule calculates the premium according to the risk assessment results and the insurance company's pricing strategy, and the personalized plan generation submodule generates a personalized insurance plan according to the customer's risk characteristics and needs.

[0009] As a preferred implementation mode of the present invention, the claim information collection submodule automatically collects customers' claim applications and related information from various channels, the image recognition submodule identifies and analyzes pictures and documents in the claim information, and the image recognition technology includes deep learning technology, image classification technology, target detection technology and image segmentation technology, which can realize fast and accurate damage identification and damage assessment, improve claims efficiency and reduce the error rate of manual operations, and the authenticity judgment submodule judges the authenticity and rationality of the claim application.

[0010] As a preferred embodiment of the present invention, the result display submodule displays the underwriting and claims settlement results to the user in the form of charts, reports, etc. The feedback collection submodule provides an interface and channel for user feedback to collect user opinions and suggestions. The feedback processing submodule analyzes and processes the collected feedback to optimize system performance and service quality.

[0011] As a preferred implementation mode of the present invention, the case query module includes query conditions, content display and case detail entry.

[0012] As a preferred implementation mode of the present invention, the problem case processing module includes a problem case query page, a problem case task management page and an insurance company problem case page.

[0013] As a preferred embodiment of the present invention, the insurance composite module includes query conditions, batch approval, review operation entry and display area.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] The intelligent insurance underwriting and claims settlement system of the present invention includes a data acquisition and preprocessing module, an intelligent underwriting module, a risk assessment and pricing module, a schematic diagram of an intelligent claims settlement module, a result output and feedback module, and a manual review platform, wherein the data acquisition and preprocessing module includes a data acquisition submodule, a data cleaning submodule, a data format conversion submodule, and a data standardization submodule, sets the cycle and channel of data acquisition, ensures the real-time and integrity of the data, performs preliminary screening and classification of the data, facilitates subsequent analysis and processing, uses preset cleaning rules and algorithms to automatically process noise and outliers in the data, and performs standardized processing on the cleaned data to provide support for subsequent intelligent analysis. Provide high-quality data foundation. The intelligent underwriting module includes health information analysis submodule, financial status analysis submodule and rule matching submodule. After the customer submits the underwriting application, the system automatically retrieves the customer's health information and financial data from the database, uses NLP technology to understand the semantics of health information and extract key information, conducts quantitative analysis of the customer's financial status, evaluates its payment ability, and gives preliminary underwriting recommendations and risk level classification based on the rule matching results. The risk assessment and pricing module includes risk assessment submodule, premium calculation submodule and personalized solution generation submodule. The output results of the intelligent underwriting module are received as input data for risk assessment. The machine learning model predicts and classifies the customer's risks, automatically calculates the premium based on the risk assessment results and pricing rules, and generates insurance plans that meet the customer's risk characteristics and budget in combination with the customer's personalized needs. The intelligent claims settlement module includes a claims information collection submodule, an image recognition submodule, and an authenticity judgment submodule. After the customer submits a claim application, the system automatically collects relevant claims information, uses image recognition technology to extract and identify key information in the claims information, and combines NLP technology to analyze and understand the text description of the claim application. According to the preset rules and algorithms, the authenticity and rationality of the claim application are judged, and the result output and feedback module It includes a result display submodule, a feedback collection submodule and a feedback processing submodule. It organizes and optimizes the output results of the intelligent underwriting and intelligent claims settlement modules, and displays them to users in an intuitive and easy-to-understand manner. It provides an entry for user feedback, allowing users to appeal or supplement the underwriting and claims settlement results, summarizes and analyzes the collected user feedback, finds out the problems and improvement directions of the system, and makes corresponding adjustments and optimizations to the system based on the feedback results to improve service quality and customer satisfaction. The insurance underwriting and claims settlement system can greatly improve the efficiency and accuracy of underwriting and claims settlement, reduce the risks brought by human factors, and provide customers with a more convenient and personalized service experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of the intelligent insurance underwriting and claims settlement system of the present invention;

[0017] Figure 2This is a schematic diagram of the data acquisition and preprocessing module of the present invention;

[0018] Figure 3 This is a schematic diagram of the intelligent underwriting module of the present invention;

[0019] Figure 4 This is a schematic diagram of the risk assessment and pricing module of the present invention;

[0020] Figure 5 This is a schematic diagram of the intelligent claims settlement module of the present invention;

[0021] Figure 6 It is a schematic diagram of the result output and feedback module of the present invention;

[0022] Figure 7 Schematic diagram of the manual review platform of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] See also Figure 1-7The present invention provides a technical solution: an insurance underwriting and claims settlement system based on artificial intelligence, comprising: an intelligent insurance underwriting and claims settlement system, the intelligent insurance underwriting and claims settlement system comprising a data acquisition and preprocessing module, an intelligent underwriting module, a risk assessment and pricing module, an intelligent claims settlement module schematic diagram, a result output and feedback module and a manual review platform, the data acquisition and preprocessing module comprising a data acquisition submodule, a data cleaning submodule, a data format conversion submodule and a data standardization submodule, the intelligent underwriting module comprising a health information analysis submodule, a financial status analysis submodule and a rule matching submodule, the risk assessment and pricing module comprising a risk assessment submodule, a premium calculation submodule and a personalized solution generation submodule, the intelligent claims settlement module It includes a claims information collection submodule, an image recognition submodule and an authenticity judgment submodule. The result output and feedback module includes a result display submodule, a feedback collection submodule and a feedback processing submodule. The manual review platform includes a case query module, a problem case processing module and an insurance company composite module. The intelligent insurance underwriting and claims settlement system includes a data collection and preprocessing module, an intelligent underwriting module, a risk assessment and pricing module, a schematic diagram of an intelligent claims settlement module, a result output and feedback module and a manual review platform. The data collection and preprocessing module includes a data collection submodule, a data cleaning submodule, a data format conversion submodule and a data standardization submodule. The cycle and channel of data collection are set to ensure the real-time and integrity of the data and to perform preliminary screening of the data. The intelligent underwriting module includes a health information analysis submodule, a financial status analysis submodule and a rule matching submodule. After the customer submits the underwriting application, the system automatically retrieves the customer's health information and financial data from the database, uses NLP technology to understand the semantics of health information and extract key information, conducts quantitative analysis of the customer's financial status, evaluates its ability to pay, and gives preliminary underwriting recommendations and risk level classification based on the rule matching results. The risk assessment and pricing module includes a risk assessment submodule, a premium calculation submodule and an individual The personalized solution generation submodule receives the output results of the intelligent underwriting module as the input data for risk assessment, uses the machine learning model to predict and classify the customer's risks, automatically calculates the premium based on the risk assessment results and pricing rules, and generates an insurance solution that meets the customer's risk characteristics and budget in combination with the customer's personalized needs. The intelligent claims settlement module includes a claims information collection submodule, an image recognition submodule, and an authenticity judgment submodule. After the customer submits a claim application, the system automatically collects relevant claims information, uses image recognition technology to extract and identify key information in the claims information, and combines NLP technology to analyze and understand the text description of the claims application. According to the preset rules and algorithms, the authenticity and rationality of the claims application are judged.The result output and feedback module includes a result display submodule, a feedback collection submodule, and a feedback processing submodule. It organizes and optimizes the output results of the intelligent underwriting and intelligent claims settlement modules, displays them to users in an intuitive and easy-to-understand manner, provides an entry for user feedback, allows users to appeal or supplement information on underwriting and claims settlement results, summarizes and analyzes the collected user feedback, finds out the problems and improvement directions of the system, and adjusts and optimizes the system accordingly based on the feedback results to improve service quality and customer satisfaction. The insurance underwriting and claims settlement system can greatly improve the efficiency and accuracy of underwriting and claims settlement, reduce the risks caused by human factors, and provide customers with a more convenient and personalized service experience.

[0025] Further improvements, such as Figure 2 As shown: the data acquisition submodule is responsible for collecting raw data from various sources;

[0026] The data cleaning submodule is used to eliminate duplicate, erroneous or invalid data, and the data format conversion submodule converts data of different formats into a format that can be processed by the system;

[0027] The data standardization submodule ensures the uniformity and comparability of data, for example, converting measurements in different units into a uniform unit.

[0028] Further improvements, such as Figure 3 As shown: the health information analysis submodule uses NLP technology to analyze the customer's health questionnaire and medical records;

[0029] The financial status analysis submodule analyzes the financial data of the customer, such as income, expenditure and assets;

[0030] The rule matching submodule automatically matches and scores customer information according to the insurance company's underwriting rules and algorithms.

[0031] Further improvements, such as Figure 4 As shown: the risk assessment submodule accurately predicts the customer's risk based on a machine learning algorithm;

[0032] The premium calculation submodule calculates the premium based on the risk assessment results and the insurance company's pricing strategy;

[0033] The personalized solution generation submodule generates personalized insurance solutions according to the risk characteristics and needs of customers, wherein the personalized solutions include user portrait and demand analysis, customized claims strategy, flexible cost calculation and estimation, intelligent service recommendation and customizable service process. User portrait and demand analysis will build user portraits according to the user's personal information, historical claims records, vehicle type and usage, etc. The system can analyze the user's specific needs and risk points, so as to generate a claims solution that is more in line with the user's actual situation. Customized claims strategy formulates customized claims strategy for different users, different accident types and different degrees of damage. Flexible cost calculation and estimation can perform flexible repair cost calculation and estimation according to the specific damage of the vehicle and market price fluctuations. Intelligent service recommendation is based on the user's historical behavior and preferences, and intelligently recommends suitable insurance products and services. Customizable service process allows users to customize the claims service process according to their own needs.

[0034] Further improvements, such as Figure 5 As shown: the claim information collection submodule automatically collects customers' claim applications and related information from various channels;

[0035] The image recognition submodule recognizes and analyzes pictures and documents in the claim information; image recognition technology includes deep learning technology, image classification technology, target detection technology and image segmentation technology, which can realize fast and accurate damage identification and damage assessment, improve claim efficiency and reduce the error rate of manual operation. Deep learning technology uses deep convolutional neural network to extract and recognize features of images, image classification technology classifies collected images to distinguish different types of damage or accident situations, target detection technology accurately identifies and locates the damaged parts in the image, and image segmentation technology divides the image into different areas or objects. The system can distinguish different parts of the vehicle (such as the front face, side, rear, etc.) and perform independent damage assessment on each area;

[0036] The authenticity judgment submodule judges the authenticity and rationality of the claim application.

[0037] Further improvements, such as Figure 6 As shown: the result display submodule displays the underwriting and claims settlement results to the user in the form of charts, reports, etc.;

[0038] The feedback collection submodule provides an interface and channel for user feedback to collect user opinions and suggestions;

[0039] The feedback processing submodule analyzes and processes the collected feedback to optimize system performance and service quality.

[0040] Further improvements, such as Figure 7As shown: the case query module includes query conditions, content display and case details entry;

[0041] The query conditions allow for multi-dimensional queries, such as application number, case acceptance number, insured person's name, insured person's mobile phone number, current status of the case, and whether there are any problem cases;

[0042] The content displayed includes the insured's report information, claim information, problem case records, return records during the case review process, payee information and case review conclusions.

[0043] Further improvements, such as Figure 7 As shown: the problem case processing module includes a problem case query page, a problem case task management page and an insurance company problem case page;

[0044] The problem case query page is used to query all problem case records, including the initiation and processing time, image content, initiation reason and other information;

[0045] The problem piece task management page is a public pool for problem pieces. All initiated problem pieces will be displayed on this page, allowing users to select and receive them to their personal problem piece task pool.

[0046] The insurance company's problem case page is where problem cases are collected or assigned from the management page and displayed on that page, which is the page where the insurance company handles problem cases. It allows problem cases to be written back and reasons for the write-back to be filled in, and it also allows images to be uploaded for the problem cases.

[0047] Further improvements, such as Figure 7 As shown: the insurance company composite module includes query conditions, batch approval, review operation entry and display area;

[0048] In the case where the insurance company has too many cases to review, the query conditions allow for quick location of the case through fields such as policy number, insured person information, policyholder information, case status, and reporting time;

[0049] The batch approval is when there are too many cases for the insurance company to review. In special scenarios, it is allowed to review and approve some cases in batches. Select the required cases and click the batch approval button. The selected cases will be directly reviewed and approved by the insurance company. The case status will be set to review and approved, and will enter the next link for circulation;

[0050] Click the case number button at the review entry to jump to the review page to view case details and review conclusions. All cases entering the insurance company's review will be displayed in the display area on this page. The review status can be used to distinguish between reviewed and pending cases through the query conditions above. This page defaults to displaying pending cases sorted from early to late according to entry time.

[0051] Working principle: The intelligent insurance underwriting and claims settlement system includes data collection and preprocessing module, intelligent underwriting module, risk assessment and pricing module, intelligent claims settlement module schematic diagram, result output and feedback module and manual review platform. The data collection and preprocessing module includes data collection submodule, data cleaning submodule, data format conversion submodule and data standardization submodule. It sets the cycle and channel of data collection to ensure the real-time and integrity of data, performs preliminary screening and classification of data to facilitate subsequent analysis and processing, uses preset cleaning rules and algorithms to automatically process noise and outliers in the data, and standardizes the cleaned data for subsequent intelligent analysis. Provide high-quality data foundation. The intelligent underwriting module includes health information analysis submodule, financial status analysis submodule and rule matching submodule. After the customer submits the underwriting application, the system automatically retrieves the customer's health information and financial data from the database, uses NLP technology to understand the semantics of health information and extract key information, conducts quantitative analysis of the customer's financial status, evaluates its payment ability, and gives preliminary underwriting suggestions and risk level classification based on the rule matching results. The risk assessment and pricing module includes risk assessment submodule, premium calculation submodule and personalized solution generation submodule. It receives the output results of the intelligent underwriting module as the input data for risk assessment. Use machine learning models to predict and classify customer risks, automatically calculate premiums based on risk assessment results and pricing rules, and generate insurance plans that meet customer risk characteristics and budgets based on their personalized needs. The intelligent claims settlement module includes a claims information collection submodule, an image recognition submodule, and an authenticity judgment submodule. After a customer submits a claim application, the system automatically collects relevant claims information, uses image recognition technology to extract and identify key information in the claims information, and combines NLP technology to analyze and understand the text description of the claims application. According to preset rules and algorithms, the authenticity and rationality of the claims application are judged, and the result output and feedback module is used to generate a real-time report. The module includes a result display submodule, a feedback collection submodule and a feedback processing submodule. It organizes and optimizes the output results of the intelligent underwriting and intelligent claims settlement modules, and displays them to users in an intuitive and easy-to-understand manner. It provides an entry for user feedback, allowing users to appeal or supplement the underwriting and claims settlement results, summarize and analyze the collected user feedback, identify system problems and improvement directions, and make corresponding adjustments and optimizations to the system based on the feedback results to improve service quality and customer satisfaction. The insurance underwriting and claims settlement system can greatly improve the efficiency and accuracy of underwriting and claims settlement, reduce the risks brought by human factors, and provide customers with a more convenient and personalized service experience.

[0052] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

[0053] Finally, a few points should be explained: First, in the description of this application, it should be noted that, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, and can be mechanical or electrical connections, or internal connectivity between two components, or direct connections. "Up", "down", "left", "right", etc. are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may change.

[0054] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An insurance underwriting and claims settlement system based on artificial intelligence, characterized by: include: An intelligent insurance underwriting and claims settlement system, the intelligent insurance underwriting and claims settlement system comprising a data collection and preprocessing module, an intelligent underwriting module, a risk assessment and pricing module, an intelligent claims settlement module schematic diagram, a result output and feedback module and a manual review platform, the data collection and preprocessing module comprising a data collection submodule, a data cleaning submodule, a data format conversion submodule and a data standardization submodule, the intelligent underwriting module comprising a health information analysis submodule, a financial status analysis submodule and a rule matching submodule, the risk assessment and pricing module comprising a risk assessment submodule, a premium calculation submodule and a personalized solution generation submodule, the intelligent claims settlement module comprising a claim information collection submodule, an image recognition submodule and an authenticity judgment submodule, the result output and feedback module comprising a result display submodule, a feedback collection submodule and a feedback processing submodule, the manual review platform comprising a case query module, a problem case processing module and an insurance company composite module.

2. The insurance underwriting and claims settlement system based on artificial intelligence according to claim 1, characterized in that: The data acquisition submodule is responsible for collecting raw data from various sources, the data cleaning submodule is used to eliminate duplicate, erroneous or invalid data, the data format conversion submodule converts data of different formats into a format that can be processed by the system, and the data standardization submodule ensures the uniformity and comparability of data.

3. The insurance underwriting and claims settlement system based on artificial intelligence according to claim 1, characterized in that: The health information analysis submodule uses NLP technology to analyze the customer's health questionnaire and medical records, the financial status analysis submodule analyzes the customer's financial data such as income, expenditure and assets, and the rule matching submodule automatically matches and scores customer information according to the insurance company's underwriting rules and algorithms.

4. The insurance underwriting and claims settlement system based on artificial intelligence according to claim 1, characterized in that: The risk assessment submodule accurately predicts the customer's risk based on a machine learning algorithm. The premium calculation submodule calculates the premium based on the risk assessment results and the insurance company's pricing strategy. The personalized plan generation submodule generates a personalized insurance plan based on the customer's risk characteristics and needs.

5. The insurance underwriting and claims settlement system based on artificial intelligence according to claim 1, characterized in that: The claim information collection submodule automatically collects customers' claim applications and related information from various channels. The image recognition submodule identifies and analyzes pictures and documents in the claim information. Image recognition technology includes deep learning technology, image classification technology, target detection technology and image segmentation technology, which can achieve fast and accurate damage identification and damage assessment, improve claims efficiency and reduce the error rate of manual operations. The authenticity judgment submodule judges the authenticity and rationality of the claim application.

6. The insurance underwriting and claims settlement system based on artificial intelligence according to claim 1, characterized in that: The result display submodule displays the underwriting and claims settlement results to the user in the form of charts, reports, etc. The feedback collection submodule provides an interface and channel for user feedback to collect user opinions and suggestions. The feedback processing submodule analyzes and processes the collected feedback to optimize system performance and service quality.

7. The artificial intelligence-based insurance underwriting and claims settlement system according to claim 1, characterized in that: The case query module includes query conditions, content display and case detail entry.

8. The insurance underwriting and claims settlement system based on artificial intelligence according to claim 1, characterized in that: The problem case processing module includes a problem case query page, a problem case task management page and an insurance company problem case page.

9. The insurance underwriting and claims settlement system based on artificial intelligence according to claim 1, characterized in that: The insurance company composite module includes query conditions, batch approval, review operation entry and display area.

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