Intelligent claim settlement report generation method and system

Abstract

The invention relates to the technical field of big data processing, in particular to an intelligent claim report generation method and system, and the method comprises the following steps: 1) big data processing: integrating multi-source heterogeneous data from different single-core systems, and aligning records in different data sets by using key fields; and 2) claim settlement report generation: according to personalized conditions of the user, different analysis reports are generated based on the template. According to the invention, the efficiency and quality of claim report generation can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of big data processing, and in particular to an intelligent claims report generation method and system. Background Art

[0002] Claims data analysis reports are an important part of insurance companies’ risk control and business optimization. Through in-depth analysis of claims data, we can reveal claims trends, characteristics and problems, thereby improving claims efficiency and reducing claims costs. This is not only beneficial to their own operations, but also effectively improves user experience.

[0003] The traditional claim report generation process usually involves a lot of manual operations, from data collection and organization to report writing and review. The whole process is inefficient and easily affected by personal subjective factors. Although the existing technology has solved the problem of manual report preparation, due to its single data source and limited data processing capacity, the traditional claim report generation process is difficult to provide comprehensive and in-depth data analysis when facing complex cases. In addition, the intervention of manual operations increases the possibility of errors and the processing efficiency is low, which cannot meet the needs of modern insurance companies for rapid response and high-quality services; moreover, the existing technical solutions mainly analyze a single system data source, and the analysis results lack multi-dimensional and diverse data sources, which may lead to deviations in the establishment of models and algorithms, thereby affecting the accuracy of predictions and decisions. Therefore, it is particularly important to develop a method and device that can automatically process large amounts of data, integrate multi-source information, and generate accurate claim reports. Summary of the invention

[0004] The present invention provides an intelligent claim report generation method and system, which can solve the efficiency and quality problems existing in the traditional claim report generation process.

[0005] According to an intelligent claim report generation method of the present invention, the method comprises the following steps:

[0006] Step 1) Big data processing: Integrate multi-source heterogeneous data from different core systems and align records in different data sets using key fields;

[0007] 1.1) Heterogeneous data integration: Integrate heterogeneous data on policies, policyholders, and claims from related internal systems, and record the data sources;

[0008] 1.2) Data extraction and cleaning: Extract the required data from various data sources, perform data cleaning, remove invalid, duplicate or incomplete records, unify the data format, and handle missing values;

[0009] 1.3) Data conversion and standardization: converting data from different data sources into a unified format and standard for subsequent processing and analysis;

[0010] 1.4) Data alignment and fusion: By identifying a set of common key fields as a bridge to connect different data sets, records in different data sources are aligned, and information from different data sources is fused together to form a complete data view;

[0011] 1.5) Data Verification: Verify the integrated data to ensure the quality and integrity of the data. Store the data that meets the requirements in the data warehouse to facilitate subsequent data analysis and report generation. Repair and reuse or discard the data that does not meet the requirements.

[0012] 1.6) Construct thematic data models: extract elements related to contracts, claims, and customers from the database, summarize or merge the data through aggregation functions, and transform the original data into three highly summarized thematic data models with practical business significance for further data analysis and decision support;

[0013] Step 2) Claim report generation: Generate different analysis reports based on templates according to the user's personalized conditions;

[0014] 2.1) Report template design: Design the template of the claim analysis report as needed and reserve the variables that need to be filled in;

[0015] 2.2) Custom conditions: The system front end allows users to customize the content and format of the report, and decomposes it into query variables through custom function matching, obtains the specificity of contract, claim, and customer factors to generate different query conditions, and completes underwriting and claim related data analysis and data preparation;

[0016] 2.3) Template reading and content replacement: Read the claim report template to obtain all elements of the docx document, traverse paragraphs, tables, and pictures, complete content replacement, and form a preliminary claim report;

[0017] 2.4) Report review and output: The preliminary report is submitted to the auditor for content review and adjustment, and then the final claim report is output.

[0018] Preferably, in step 1.1), the internal related systems include a short-term insurance system, an eight-version system and a universal system.

[0019] Preferably, in step 1.3), data conversion and standardization include unit conversion, date format unification and categorical variable encoding operations.

[0020] Preferably, in step 1.4), the key fields include policy number, policyholder information, premium, insurance type and claim amount.

[0021] Preferably, in step 1.5), data sampling inspection, statistical analysis and anomaly detection methods are used for verification.

[0022] Preferably, in step 1.6), the aggregation functions include SUM and AVG.

[0023] Preferably, in step 2.1), the template includes a cover page, charts, tables and text descriptions.

[0024] The present invention provides an intelligent claim report generation system which adopts the above-mentioned intelligent claim report generation method.

[0025] The beneficial effects of the present invention are as follows:

[0026] 1) Data integration capability: By integrating information from different data sources, such as insurance policy information, claim records, etc., the present invention can provide a comprehensive perspective to analyze claim cases, ensure the richness and completeness of the report content, and provide a solid data foundation for claim decision-making.

[0027] 2) Efficient data processing: The present invention can quickly process large amounts of data without human intervention, greatly shortening the time it takes to generate claims reports. This not only improves work efficiency, but also enables insurance companies to respond to customer needs more quickly, improving customer satisfaction.

[0028] 3) Accuracy and consistency: By reducing manual operations, the automated system reduces the error rate caused by human factors. At the same time, the standardized process of the present invention ensures that the format and content of each claim report are consistent, improving the professionalism and credibility of the report.

[0029] 4) Flexibility and scalability: As technology develops and new data sources emerge, the present invention can flexibly adapt to changes, continuously optimize and expand its functions to adapt to market changes and business growth.

[0030] 5) Cost savings: Automation reduces reliance on human resources, thereby reducing long-term operating costs. In addition, due to fewer errors, additional costs and legal risks caused by errors may also be reduced.

[0031] In summary, the present invention will greatly improve the operational efficiency of insurance companies, enhance the accuracy and depth of data processing, while reducing costs and improving customer service experience. This will enable insurance companies to maintain their leading position in the highly competitive market and better meet the needs of the modern insurance industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flowchart of big data processing in the embodiment;

[0033] Figure 2 A flow chart for generating a claim report in an embodiment. DETAILED DESCRIPTION

[0034] In order to further understand the content of the present invention, the present invention is described in detail in conjunction with the accompanying drawings and embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0035] Example

[0036] like Figure 1 and Figure 2 As shown, this embodiment provides an intelligent claim report generation method, which includes the following steps:

[0037] Step 1) Big data processing: Integrate multi-source heterogeneous data from different core systems and align records in different data sets using key fields.

[0038] 1.1) Heterogeneous data integration: Integrate heterogeneous data on policies, policyholders, and claims from related internal systems, and record the data sources. Related internal systems include short-term insurance system, version 8 system, and universal system.

[0039] 1.2) Data extraction and cleaning: Extract the required data from various data sources, perform data cleaning, remove invalid, duplicate or incomplete records, unify the data format, and handle missing values.

[0040] 1.3) Data conversion and standardization: Convert data from different data sources into a unified format and standard to facilitate subsequent processing and analysis; data conversion and standardization include unit conversion, date format unification and categorical variable coding operations.

[0041] 1.4) Data alignment and fusion: By identifying a set of common key fields as a bridge to connect different data sets, records in different data sources are aligned and information from different data sources is integrated to form a complete data view; key fields include policy number, policyholder information, premium, insurance type and claim amount.

[0042] 1.5) Data Verification: Use data sampling inspection, statistical analysis and anomaly detection methods to verify the integrated data to ensure the quality and integrity of the data. Store the data that meets the requirements in the data warehouse to facilitate subsequent data analysis and report generation. Repair and reuse or discard the data that does not meet the requirements.

[0043] 1.6) Construct thematic data models: Extract elements related to contracts, claims, and customers from the database, summarize or merge the data through aggregation functions, and transform the original data into three highly summarized thematic data models with practical business significance for further data analysis and decision support; aggregation functions include SUM and AVG.

[0044] Step 2) Claim report generation: Generate different analysis reports based on templates according to the user's personalized conditions.

[0045] 2.1) Report template design: Design a template for the claims analysis report as needed, and reserve variables that need to be filled in; the template includes a cover page, charts, tables, and text descriptions.

[0046] 2.2) Custom conditions: The system front end allows users to customize the content and format of the report, and decompose it into query variables through custom function matching, obtain the specificity of contracts, claims, and customer factors to generate different query conditions, and complete underwriting and claims related data analysis and data preparation.

[0047] 2.3) Template reading and content replacement: Read the claim report template to obtain all elements of the docx document, traverse paragraphs, tables, and pictures, complete content replacement, and form a preliminary claim report.

[0048] 2.4) Report review and output: The preliminary report is submitted to the auditor for content review and adjustment, and then the final claim report is output.

[0049] This embodiment provides an intelligent claim report generation system, which adopts the above-mentioned intelligent claim report generation method.

[0050] This embodiment will greatly improve the operational efficiency of insurance companies, enhance the accuracy and depth of data processing, while reducing costs and improving customer service experience. This will enable insurance companies to maintain their leading position in the highly competitive market and better meet the needs of the modern insurance industry.

[0051] The present invention and its embodiments are described schematically above, and the description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if a person skilled in the art is inspired by it and designs a structural method and an embodiment similar to the technical solution without creativity without departing from the purpose of the invention, they shall all fall within the protection scope of the present invention.

Claims

1. An intelligent claim report generation method, characterized by: The following steps are involved: Step 1) Big data processing: Integrate multi-source heterogeneous data from different core systems and align records in different data sets using key fields; 1.1) Heterogeneous data integration: Integrate heterogeneous data on policies, policyholders, and claims from related internal systems, and record the data sources; 1.2) Data extraction and cleaning: Extract the required data from various data sources, perform data cleaning, remove invalid, duplicate or incomplete records, unify the data format, and handle missing values; 1.3) Data conversion and standardization: converting data from different data sources into a unified format and standard for subsequent processing and analysis; 1.4) Data alignment and fusion: By identifying a set of common key fields as a bridge to connect different data sets, records in different data sources are aligned, and information from different data sources is fused together to form a complete data view; 1.5) Data Verification: Verify the integrated data to ensure the quality and integrity of the data. Store the data that meets the requirements in the data warehouse to facilitate subsequent data analysis and report generation. Repair and reuse or discard the data that does not meet the requirements. 1.6) Construct thematic data models: extract elements related to contracts, claims, and customers from the database, summarize or merge the data through aggregation functions, and transform the original data into three highly summarized thematic data models with practical business significance for further data analysis and decision support; Step 2) Claim report generation: Generate different analysis reports based on templates according to the user's personalized conditions; 2.1) Report template design: Design the template of the claim analysis report as needed and reserve the variables that need to be filled in; 2.2) Custom conditions: The system front end allows users to customize the content and format of the report, and decomposes it into query variables through custom function matching, obtains the specificity of contract, claim, and customer factors to generate different query conditions, and completes underwriting and claim related data analysis and data preparation; 2.3) Template reading and content replacement: Read the claim report template to obtain all elements of the docx document, traverse paragraphs, tables, and pictures, complete content replacement, and form a preliminary claim report; 2.4) Report review and output: The preliminary report is submitted to the auditor for content review and adjustment, and then the final claim report is output.

2. The intelligent claim report generation method according to claim 1, characterized in that: In step 1.1), the internal related systems include the short-term insurance system, the eighth version system and the universal system.

3. The intelligent claim report generation method according to claim 2 is characterized by: In step 1.3), data conversion and standardization include unit conversion, date format unification and categorical variable encoding operations.

4. The intelligent claim report generation method according to claim 3 is characterized by: In step 1.4), the key fields include policy number, policyholder information, premium, insurance type, and claim amount.

5. The intelligent claim report generation method according to claim 4 is characterized by: In step 1.5), data sampling inspection, statistical analysis and anomaly detection methods are used for verification.

6. The intelligent claim report generation method according to claim 5, characterized in that: In step 1.6), the aggregation functions include SUM and AVG.

7. The intelligent claim report generation method according to claim 6, characterized in that: In step 2.1), the template includes a cover page, charts, tables, and text descriptions.

8. An intelligent claim report generation system, characterized by: It adopts an intelligent claims report generation method as described in any one of claims 1-7.

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