Report data processing methods, devices, computer equipment, and storage media

Abstract

This application belongs to the fields of artificial intelligence and fintech, and relates to a method for processing report data, including: acquiring target data of an insurance contract; acquiring multiple preset version numbers corresponding to an insurance measurement model, and determining the parameter values ​​corresponding to each preset version number; calculating and generating measurement result tables for each preset version number based on the target data using the insurance measurement model, and processing the measurement result tables to obtain profit reports for each preset version number; synchronizing each measurement result table and each profit report to a business database for display; and outputting a target measurement result table and a target profit report based on the target version number returned by the user. This application also provides a report data processing device, computer equipment, and storage medium. Furthermore, the target measurement result table of this application can be stored in a blockchain. This application can be applied to report processing scenarios in the financial field, improving the processing efficiency of generating target measurement result tables and target profit reports.

Description

Technical Field

[0001] This application relates to the fields of artificial intelligence development technology and financial technology, and in particular to methods, devices, computer equipment and storage media for processing report data. Background Technology

[0002] IFRS 17, developed by the International Accounting Standards Board (IASB), is a standard for insurance contracts aimed at improving transparency and comparability in the insurance industry. As the core step in IFRS 17's financial statement calculations, the measurement model requires multiple adjustments to its results to output the optimal insurance statements. Due to the high complexity of the model logic, the large number of data items involved, and the heavy computational load, the current method for generating optimal insurance statements employs a cyclical adjustment approach based on backend technology. This involves inputting parameters, running the model, analyzing the results, and adjusting the parameters, repeating this cycle until the analysis results conform to the standard and the corresponding optimal insurance statements are obtained. However, this method of generating optimal insurance statements has serious shortcomings. Its processing chain is long, it cannot assess the degree of adjustment, it is time-consuming, and the interactive process consumes human resources, resulting in low processing efficiency for insurance statement generation. Furthermore, the repeated modifications cannot guarantee data accuracy, which in turn affects the timeliness and cost of IFRS 17 month-end closing. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, computer device, and storage medium for processing report data, in order to solve the technical problems of existing methods for generating insurance reports, which are time-consuming, inefficient, and unable to guarantee data accuracy during repeated modifications.

[0004] To address the aforementioned technical problems, this application provides a method for processing report data, employing the following technical solution:

[0005] If a user-triggered insurance report generation request is received, the basic data of the insurance contract is obtained;

[0006] The basic data of the insurance contract is processed to obtain the corresponding target data;

[0007] Based on the model parameters of the preset insurance measurement model, multiple preset version numbers corresponding to the insurance measurement model are obtained, and parameter values ​​corresponding to each preset version number are determined; wherein, the insurance measurement model is a measurement model based on the Hive framework;

[0008] The target data is calculated and processed based on the insurance measurement model to generate a measurement result table corresponding to each preset version number, and a profit report corresponding to each preset version number is obtained based on the measurement result table.

[0009] The measurement result tables and profit reports are synchronized to the preset business database for display.

[0010] Receive the target version number returned by the user after reviewing all the measurement result tables;

[0011] Based on the measurement result table, output the target measurement result table corresponding to the target version number, and based on the profit report, output the target profit report corresponding to the target version number.

[0012] Furthermore, the step of calculating and processing the target data based on the insurance measurement model to generate a measurement result table corresponding to each of the preset version numbers specifically includes:

[0013] Obtain the measurement indicators of the insurance measurement model; wherein, the number of measurement indicators includes multiple indicators;

[0014] Obtain the first version number; wherein, the first version number is any one of all the preset version numbers;

[0015] Based on the first version number, query the indicator data corresponding to the measurement indicator from the target data;

[0016] Based on the indicator data, a preset task processing script is executed to obtain indicator processing data corresponding to the indicator data; wherein, the task processing script is a processing script based on the temporary table method;

[0017] The processing results are stored in a preset entity table to obtain a measurement result table corresponding to the first version number.

[0018] Furthermore, after the step of storing the processing results in a preset entity table to obtain a measurement result table corresponding to the first version number, the method further includes:

[0019] Obtain temporary data and temporary data tables generated during the execution of the task processing script;

[0020] The temporary data and the temporary data table are deleted.

[0021] Furthermore, the step of determining the parameter values ​​corresponding to each of the preset version numbers specifically includes:

[0022] Obtain the historical version number that matches the second version number; wherein the second version number is any one of all the preset version numbers;

[0023] Obtain the historical reference parameters for the historical version number;

[0024] Generate a specified parameter value corresponding to the second version number based on the historical reference parameters.

[0025] Furthermore, the step of obtaining the basic data of the insurance contract specifically includes:

[0026] Obtain initial business data for insurance contracts from a pre-set big data mart;

[0027] Retrieves a specified data type;

[0028] Based on the specified data type, the initial business data is filtered to obtain specified data corresponding to the specified data type;

[0029] The specified data is used as the base data.

[0030] Furthermore, after the steps of outputting the target measurement result table corresponding to the target version number based on the measurement result table, and outputting the target profit report corresponding to the target version number based on the profit report, the method further includes:

[0031] Obtain the preset certificate template;

[0032] Based on the certificate template, the target measurement result table and the target profit report are processed to obtain the corresponding certificate data.

[0033] Store the certificate data.

[0034] Furthermore, after the steps of outputting the target measurement result table corresponding to the target version number based on the measurement result table, and outputting the target profit report corresponding to the target version number based on the profit report, the method further includes:

[0035] Obtain the first intermediate processing data corresponding to the target measurement result table;

[0036] Obtain the second intermediate processing data corresponding to the target profit report;

[0037] The first intermediate processing data and the second intermediate processing data are pushed to the preset verification workbench.

[0038] To address the aforementioned technical problems, this application also provides a report data processing device, which employs the following technical solution:

[0039] The first acquisition module is used to acquire the basic data of the insurance contract if it receives an insurance report generation request triggered by the user.

[0040] The processing module is used to process the basic data of the insurance contract to obtain the corresponding target data;

[0041] The determination module is used to obtain multiple preset version numbers corresponding to the insurance measurement model based on the model parameters of the preset insurance measurement model, and determine the parameter values ​​corresponding to each preset version number; wherein, the insurance measurement model is a measurement model based on the Hive framework;

[0042] The generation module is used to calculate and process the target data based on the insurance measurement model, generate a measurement result table corresponding to each of the preset version numbers, and process the measurement result table to obtain a profit report corresponding to each of the preset version numbers respectively.

[0043] The display module is used to synchronize the measurement result tables and profit reports to a preset business database for display.

[0044] The receiving module is used to receive the target version number returned by the user after reviewing all the measurement result tables;

[0045] The output module is used to output a target measurement result table corresponding to the target version number based on the measurement result table, and to output a target profit report corresponding to the target version number based on the profit report.

[0046] To address the aforementioned technical problems, this application also provides a computer device that employs the following technical solution:

[0047] If a user-triggered insurance report generation request is received, the basic data of the insurance contract is obtained;

[0048] The basic data of the insurance contract is processed to obtain the corresponding target data;

[0049] Based on the model parameters of the preset insurance measurement model, multiple preset version numbers corresponding to the insurance measurement model are obtained, and parameter values ​​corresponding to each preset version number are determined; wherein, the insurance measurement model is a measurement model based on the Hive framework;

[0050] The target data is calculated and processed based on the insurance measurement model to generate a measurement result table corresponding to each preset version number, and a profit report corresponding to each preset version number is obtained based on the measurement result table.

[0051] The measurement result tables and profit reports are synchronized to the preset business database for display.

[0052] Receive the target version number returned by the user after reviewing all the measurement result tables;

[0053] Based on the measurement result table, output the target measurement result table corresponding to the target version number, and based on the profit report, output the target profit report corresponding to the target version number.

[0054] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, employing the technical solution described below:

[0055] If a user-triggered insurance report generation request is received, the basic data of the insurance contract is obtained;

[0056] The basic data of the insurance contract is processed to obtain the corresponding target data;

[0057] Based on the model parameters of the preset insurance measurement model, multiple preset version numbers corresponding to the insurance measurement model are obtained, and parameter values ​​corresponding to each preset version number are determined; wherein, the insurance measurement model is a measurement model based on the Hive framework;

[0058] The target data is calculated and processed based on the insurance measurement model to generate a measurement result table corresponding to each preset version number, and a profit report corresponding to each preset version number is obtained based on the measurement result table.

[0059] The measurement result tables and profit reports are synchronized to the preset business database for display.

[0060] Receive the target version number returned by the user after reviewing all the measurement result tables;

[0061] Based on the measurement result table, output the target measurement result table corresponding to the target version number, and based on the profit report, output the target profit report corresponding to the target version number.

[0062] Compared with the prior art, the embodiments of this application have the following main advantages:

[0063] In this embodiment, if an insurance report generation request triggered by a user is received, the basic data of the insurance contract is obtained, and the basic data of the insurance contract is processed to obtain the corresponding target data; then, based on the model parameters of a preset insurance measurement model, multiple preset version numbers corresponding to the insurance measurement model are obtained, and the parameter values ​​corresponding to each preset version number are determined; then, based on the insurance measurement model, the target data is calculated and processed to generate a measurement result table corresponding to each preset version number, and a profit report corresponding to each preset version number is obtained based on the measurement result table; subsequently, each measurement result table and each profit report are synchronized to a preset business database for display; further, the target version number returned by the user after viewing all the measurement result tables is received; finally, a target measurement result table corresponding to the target version number is output based on the measurement result table, and a target profit report corresponding to the target version number is output based on the profit report. After processing the target data of the insurance contract, this application obtains multiple preset version numbers corresponding to the insurance measurement model through model parameters based on the insurance measurement model, and determines the parameter values ​​corresponding to each preset version number. Then, based on the insurance measurement model, it calculates and processes the target data to generate a measurement result table corresponding to each preset version number, and processes the measurement result table to generate a profit report corresponding to each preset version number. Subsequently, the measurement result tables and profit reports are synchronized to a preset business database for display. This allows users to filter all generated measurement result tables and decide on the optimal target measurement result table and target profit report. Compared with existing schemes for generating the optimal insurance report, which require multiple analyses, calculations, and parameter modifications, this application effectively reduces the number of manual interventions, reduces processing time, improves the processing efficiency of generating target measurement result tables and target profit reports, and effectively avoids distortion caused by repeated modifications and data processing, ensuring the data accuracy of the target measurement result tables and target profit reports. Attached Figure Description

[0064] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 This is an exemplary system architecture diagram to which this application can be applied;

[0066] Figure 2 A flowchart of an embodiment of the report data processing method according to this application;

[0067] Figure 3 This is a schematic diagram of the structure of an embodiment of the report data processing apparatus according to this application;

[0068] Figure 4 This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0069] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0070] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0071] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0072] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. Network 104 serves as the medium for providing communication links between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0073] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

[0074] Terminal devices 101, 102, and 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 players (Moving Picture Experts Group Audio Layer IV), laptops, and desktop computers, etc.

[0075] Server 105 can be a server that provides various services, such as a backend server that supports the pages displayed on terminal devices 101, 102, and 103.

[0076] It should be noted that the report data processing method provided in the embodiments of this application is generally executed by a server / terminal device, and correspondingly, the report data processing device is generally located in the server / terminal device.

[0077] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0078] Continue to refer to Figure 2 This document illustrates a flowchart of an embodiment of the report data processing method according to this application. The order of steps in the flowchart can be changed, and some steps can be omitted, depending on different requirements. The report data processing method provided in this application can be applied to any scenario requiring report generation, and thus can be applied to products in these scenarios, such as report generation in the financial and insurance fields. The report data processing method includes the following steps:

[0079] Step S201: If an insurance report generation request triggered by a user is received, obtain the basic data of the insurance contract.

[0080] In this embodiment, the report data processing method runs on an electronic device (e.g., Figure 1The server / terminal device shown can obtain basic insurance contract data via wired or wireless connection. It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra-wideband) connections, and other currently known or future-developed wireless connection methods. In the business scenario of generating insurance reports in the financial insurance sector, the aforementioned user is an insurance salesperson on a monthly settlement basis, and the basic insurance contract data may include premiums, fees, claims, and other data. The specific implementation process for obtaining the basic insurance contract data will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated upon here.

[0081] Step S202: Process the basic data of the insurance contract to obtain the corresponding target data.

[0082] In this embodiment, the basic data of the insurance contract can be processed into the metering interface table of the application layer using the IFRS17 standard to obtain the corresponding target data, without the need to synchronize it to the business database for processing.

[0083] Step S203: Based on the model parameters of the preset insurance measurement model, obtain multiple preset version numbers corresponding to the insurance measurement model, and determine the parameter values ​​corresponding to each preset version number; wherein, the insurance measurement model is a measurement model based on the Hive framework.

[0084] In this embodiment, in actual insurance calculation application scenarios, the insurance measurement model may include measurement models based on the Common Basic Model (BBA) and the Permitted Premium Approach (PAA), used to comprehensively measure liabilities, income, claims, expenses, and interest of direct and reinsurance. According to IFRS 17, different measurement models (BBA, VFA, or PAA) should be used depending on the characteristics of different insurance businesses, and changes in the liability amount due to changes in the discount rate should be either directly recorded in OCI or in current profit or loss. Hive is a data warehouse tool based on Hadoop and is also a distributed computing framework. The core function of Hive is to translate SQL statements into MapReduce programs, mapping structured data to a database table and providing HQL (Hive SQL) query functionality. Since the number of model parameters in the insurance measurement model is fixed, multiple possible version numbers corresponding to the insurance measurement model can be calculated based on the number of model parameters; these are the aforementioned preset version numbers. Alternatively, based on the recorded data generated during the historical testing and use of the actual insurance measurement model, users can be assisted in generating multiple preset version numbers corresponding to the insurance measurement model, and producing parameter values ​​corresponding to each preset version number. Furthermore, the specific implementation process for determining the parameter values ​​corresponding to each preset version number will be described in further detail in subsequent specific embodiments of this application, and will not be elaborated upon here. In addition, the input operation data layer can be implemented using Hadoop Sqoop technology, and through data governance processes such as deduplication and fallback, the preset version numbers are labeled with the corresponding parameter values ​​and processed into the measurement interface table of the application layer. This step can be performed as a month-end preprocessing step without any prior dependencies.

[0085] Step S204: Calculate and process the target data based on the insurance measurement model to generate a measurement result table corresponding to each preset version number, and process the measurement result table to obtain a profit report corresponding to each preset version number.

[0086] In this embodiment, the specific implementation process of calculating and processing the target data based on the insurance measurement model to generate measurement result tables corresponding to each preset version number, and processing the measurement result tables to obtain profit reports corresponding to each preset version number, will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated on here. Specifically, the parameter value of the preset version number can be used as a partitioning field to distinguish the measurement result table and profit report corresponding to each preset version number. Furthermore, if the insurance measurement model includes a general model based on the Common Basic Model (BBA) and a measurement model based on the Premium Allocation Method (PAA), then BBA measurement result tables and PAA measurement result tables corresponding to each version number will be generated respectively.

[0087] Step S205: Synchronize each of the measurement result tables and each of the profit reports to the preset business database for display.

[0088] In this embodiment, the obtained measurement result tables and profit reports can be synchronized to the result analysis interface of the pre-built business database through Hadoop Sqoop technology for report display.

[0089] Step S206: Receive the target version number returned by the user after reviewing all the measurement result tables.

[0090] In this embodiment, users can compare all the measurement result tables displayed in the business database according to actual insurance business needs, comparing the differences between different versions and the requirements of analysis criteria to select the target version number corresponding to the optimal report. This eliminates the need for offline calculations and parameter modifications, making the operation more convenient. The intuitive display of differences between multiple versions provides monthly settlement agents with more comprehensive decision-making reference data. Based on the measurement optimization scheme proposed in this application, the implementation efficiency and accuracy of IFRS 17 can be effectively improved, thereby helping insurance companies reduce costs and enhance competitiveness. Furthermore, after the user's decision is implemented through page interaction, the returned template version number will be scheduled through the Spark web interface to schedule a Hadoop Sqoop task, achieving real-time synchronization to the big data application layer.

[0091] Step S207: Output a target measurement result table corresponding to the target version number based on the measurement result table, and output a target profit report corresponding to the target version number based on the profit report.

[0092] In this embodiment, all measurement result tables can be filtered by target version number to output a target measurement result table corresponding to the target version number, and all profit reports can be filtered by target version number to output a target profit report corresponding to the target version number. By allowing users to filter all generated measurement result tables and determine the optimal insurance report, compared to the old method which required multiple analyses, calculations, and parameter modifications, this approach effectively reduces manual intervention, protects data accuracy, and prevents distortion from repeated data modifications and calculations.

[0093] If this application receives an insurance report generation request triggered by a user, it obtains the basic data of the insurance contract and processes the basic data of the insurance contract to obtain the corresponding target data; then, based on the model parameters of a preset insurance measurement model, it obtains multiple preset version numbers corresponding to the insurance measurement model and determines the parameter values ​​corresponding to each preset version number; subsequently, it calculates and processes the target data based on the insurance measurement model to generate a measurement result table corresponding to each preset version number, and processes the measurement result table to obtain a profit report corresponding to each preset version number; subsequently, it synchronizes each measurement result table and each profit report to a preset business database for display; further, it receives the target version number returned by the user after viewing all the measurement result tables; finally, it outputs a target measurement result table corresponding to the target version number based on the measurement result table, and outputs a target profit report corresponding to the target version number based on the profit report. After processing the target data of the insurance contract, this application obtains multiple preset version numbers corresponding to the insurance measurement model through model parameters based on the insurance measurement model, and determines the parameter values ​​corresponding to each preset version number. Then, based on the insurance measurement model, it calculates and processes the target data to generate a measurement result table corresponding to each preset version number, and processes the measurement result table to generate a profit report corresponding to each preset version number. Subsequently, the measurement result tables and profit reports are synchronized to a preset business database for display. This allows users to filter all generated measurement result tables and decide on the optimal target measurement result table and target profit report. Compared with existing schemes for generating the optimal insurance report, which require multiple analyses, calculations, and parameter modifications, this application effectively reduces the number of manual interventions, reduces processing time, improves the processing efficiency of generating target measurement result tables and target profit reports, and effectively avoids distortion caused by repeated modifications and data processing, ensuring the data accuracy of the target measurement result tables and target profit reports.

[0094] In some alternative implementations, step S204 includes the following steps:

[0095] Obtain the measurement indicators of the insurance measurement model;

[0096] In this embodiment, the number of measurement indicators includes multiple ones. In actual insurance calculation application scenarios, the insurance measurement model may include measurement models based on the Common Basic Model (BBA) and the Premium Allocation Method (PAA), used to comprehensively measure liabilities, income, claims, expenses, interest, etc. of direct insurance and reinsurance. For example, the insurance measurement model is a BBA-based measurement model, and the corresponding measurement indicator may be POL_INC (insurance contract income), and the measurement indicator corresponding to this insurance contract income is calculated from 17 basic numbers.

[0097] Get the first version number.

[0098] In this embodiment, the first version number is any one of all the preset version numbers.

[0099] Based on the first version number, the indicator data corresponding to the measurement indicator is retrieved from the target data.

[0100] In this embodiment, after processing the basic data of the insurance contract to obtain the corresponding target data, the target data will be further stored in the metering interface table of the application layer. Subsequently, Hive SQL can be used in the application layer to query the metering interface table to retrieve the indicator data corresponding to the first version number and the metering indicator.

[0101] Based on the indicator data, a preset task processing script is executed to obtain indicator processing data corresponding to the indicator data; wherein, the task processing script is a processing script based on the temporary table method.

[0102] In this embodiment, the existing insurance contract measurement processing method uses Java variable assignment calculation to implement the processing. This embodiment uses a measurement model based on the Hive framework to implement the processing. Since it requires 11 layers of dependent processing, the SQL process based on subqueries is prone to memory overflow and other problems. Therefore, this application adopts a temporary table method to bypass the overflow situation, thereby ensuring the stable execution of the data processing process. The specific method is as follows: Enable Spark 3.0 engine calculation; set the parameter spark.sql.legacy.hive.tmpTable = true; create a temporary table tmp1 to retain the first layer of basic data processing results and retain all intermediate processing fields; create a temporary table tmp2 to reference tmp1 to process the second layer of intermediate data results and retain all intermediate processing fields; and so on, until a temporary table tmp10 is created to reference tmp9 to process the tenth layer of results and retain the result fields; then insert the tmp10 results into the entity table of the application layer to store the indicator processing data corresponding to the indicator data, thereby obtaining the measurement result table corresponding to the first version number.

[0103] The processing results are stored in a preset entity table to obtain a measurement result table corresponding to the first version number.

[0104] In this embodiment, the aforementioned preset entity table can refer to the entity table of the application layer. In actual application, the report data processing method based on this application can reduce the process of repeatedly modifying parameters and running models, thereby improving timeliness. For example, the average running time of a single version of the monthly settlement measurement model backend for an insurance company is 0.5 hours / month, with an average of 2.5 parameter modifications / month. The actual measured running time for multiple versions of big data is 0.85 hours / month, improving timeliness by 6.65 hours / month. Reduced data synchronization: Compared with existing processes, the report data processing method of this application postpones the process of importing big data into the business database until the highly summarized results of multiple version running data are obtained, reducing the amount of data in the synchronization task and saving synchronization time and business database table space. For example, an insurance company's monthly settlement data consists of 21 items, each with 20,000 to 8 million records. The data imported into the business database will amount to as much as 100 million records, with a synchronization wait time exceeding 0.5 hours. The multi-version results only have two multi-version result tables, namely PAA and BBA, with each result table containing only dozens to hundreds of records. The synchronization efficiency will also be improved, the space occupied in the business database will be greatly reduced, and the separation of basic data and application data will be achieved.

[0105] This application obtains the measurement indicators of the insurance measurement model; then obtains a first version number; subsequently, based on the first version number, it queries the target data to retrieve the indicator data corresponding to the measurement indicators; next, it executes a preset task processing script based on the indicator data to obtain the indicator processing data corresponding to the indicator data; finally, it stores the processing results in a preset entity table to obtain a measurement result table corresponding to the first version number. This application, by using a task processing script based on a temporary table method and the insurance measurement model to process the target data, can quickly and accurately generate measurement result tables corresponding to each preset version number, effectively improving the generation efficiency of the measurement result table.

[0106] In some optional implementations of this embodiment, after the step of storing the processing result in a preset entity table to obtain a measurement result table corresponding to the first version number, the above-mentioned electronic device may further perform the following steps:

[0107] Obtain the temporary data and temporary data table generated during the execution of the task processing script.

[0108] In this embodiment, during the execution of the task processing script, corresponding temporary data and temporary data tables will also be generated.

[0109] The temporary data and the temporary data table are deleted.

[0110] In this embodiment, by deleting the temporary data and the temporary data table, other data besides the temporary data and the temporary data table are removed, thereby freeing up corresponding space.

[0111] This application obtains temporary data and temporary data tables generated during the execution of the task processing script; subsequently, it deletes the temporary data and temporary data tables. By deleting the temporary data and temporary data tables generated during the execution of the task processing script, this application can effectively free up available space in electronic devices, thereby helping to ensure the normal operation of electronic devices.

[0112] In some optional implementations, the step S203 of determining the parameter values ​​corresponding to each of the preset version numbers includes the following steps:

[0113] Retrieve the historical version number that matches the second version number;

[0114] In this embodiment, the second version number is any one of all the preset version numbers.

[0115] Obtain the historical reference parameters for the historical version number.

[0116] In this embodiment, the historical reference parameters of the historical version number can be found by obtaining the historical reference data of the pre-stored historical version number.

[0117] Generate a specified parameter value corresponding to the second version number based on the historical reference parameters.

[0118] In this embodiment, the generation method for the second version number can be to directly use the historical reference parameters as the specified parameter value corresponding to the second version number, or to display the historical reference parameters to the user and then use the reference parameters entered by the user after consulting the historical reference parameters as the specified parameter value corresponding to the second version number.

[0119] This application obtains a historical version number that matches the second version number; then obtains historical reference parameters for the historical version number; and subsequently generates a specified parameter value corresponding to the second version number based on the historical reference parameters. By obtaining a historical version number that matches the second version number and its historical reference parameters, this application can generate a specified parameter value corresponding to the second version number quickly, improving the generation efficiency and intelligence of parameter values ​​corresponding to preset version numbers.

[0120] In some alternative implementations, obtaining the basic data of the insurance contract in step S201 includes the following steps:

[0121] Obtain initial business data for insurance contracts from a pre-set big data mart.

[0122] In this embodiment, the aforementioned big data mart is a pre-built data mart that stores business data containing insurance contracts.

[0123] Retrieves the specified data type.

[0124] In this embodiment, the specified data type may specifically include premiums, fees, compensation, etc.

[0125] Based on the specified data type, the initial business data is filtered to obtain specified data corresponding to the specified data type.

[0126] In this embodiment, the specified data may refer to the data corresponding to the basic data required for the processing of measurement indicators in the initial business data, such as premiums, expenses, claims, etc.

[0127] The specified data is used as the base data.

[0128] This application obtains initial business data of insurance contracts from a pre-set big data mart; then obtains a pre-set specified data type; subsequently, it filters the initial business data based on the specified data type to obtain specified data corresponding to the specified data type; and finally, it uses the specified data as the base data. By using a specified data type to filter the initial business data of insurance contracts obtained from the big data mart, this application can quickly extract the required base data of insurance contracts from the big data mart, ensuring the accuracy of the obtained base data.

[0129] In some optional implementations of this embodiment, after step S207, the electronic device may further perform the following steps:

[0130] Obtain the preset certificate template.

[0131] In this embodiment, the certificate template is a template constructed according to the actual financial certificate requirements for financial certificate creation of each data item in the measurement result table and profit statement.

[0132] Based on the certificate template, the target measurement result table and the target profit report are processed to obtain the corresponding certificate data.

[0133] In this embodiment, each data point is read according to its order in the target measurement result table, and then a certificate is created based on the obtained certificate template to obtain the certificate data corresponding to the target measurement result table. Similarly, each data point is read according to its order in the target profit report, and then a certificate is created based on the obtained certificate template to obtain the certificate data corresponding to the target profit report.

[0134] Store the certificate data.

[0135] In this embodiment, no specific limitation is made on the storage method of the certificate data. For example, blockchain storage, database storage, cloud storage, etc. can be used.

[0136] This application obtains a preset certificate template; then, based on the certificate template, it performs certificate production processing on the target measurement result table and the target profit report to obtain corresponding certificate production data; subsequently, it stores the certificate production data. After outputting a target measurement result table corresponding to the target version number based on the measurement result table, and a target profit report corresponding to the target version number based on the profit report, this application intelligently performs certificate production processing on the target measurement result table and the target profit report based on the use of the certificate production template to automatically generate certificate production data. This eliminates the need for extensive manual manipulation of the insurance data in the target measurement result table and the target profit report; it allows direct certificate production processing of each insurance data item in the target measurement result table and the target profit report based on the certificate production template, and enables batch certificate production of data in the data table, effectively improving certificate production efficiency.

[0137] In some optional implementations of this embodiment, after step S207, the electronic device may further perform the following steps:

[0138] Obtain the first intermediate processing data corresponding to the target measurement result table.

[0139] In this embodiment, during the execution of the task processing script, first intermediate processing data corresponding to the target measurement result table will also be generated.

[0140] Obtain the second intermediate processing data corresponding to the target profit report.

[0141] In this embodiment, during the execution of the task processing script, second intermediate processing data corresponding to the target profit report will also be generated.

[0142] The first intermediate processing data and the second intermediate processing data are pushed to the preset verification workbench.

[0143] In this embodiment, by pushing the first intermediate processing data and the second intermediate processing data to a preset verification workbench, the function of conveniently providing insurance operation and maintenance personnel with the intermediate processing data verification function of the target measurement result table and the target profit report can be realized.

[0144] This application acquires first intermediate processing data corresponding to the target measurement result table; then acquires second intermediate processing data corresponding to the target profit report; and subsequently pushes the first and second intermediate processing data to a preset verification workbench. This application automatically and intelligently pushes the acquired first intermediate processing data corresponding to the target measurement result table and the second intermediate processing data corresponding to the target profit report to a preset verification workbench, thereby providing insurance operations and maintenance personnel with a convenient function for verifying the intermediate processing data of the target measurement result table and the target profit report. This allows insurance operations and maintenance personnel to quickly complete the data verification process for intermediate processing, improving data verification efficiency and enhancing the work efficiency and experience of insurance operations and maintenance personnel.

[0145] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0146] It should be emphasized that, in order to further ensure the privacy and security of the aforementioned target measurement results table, the aforementioned target measurement results table can also be stored in a blockchain node.

[0147] The blockchain referred to in this application is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying blockchain platform, a platform product service layer, and an application service layer.

[0148] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0149] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0150] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware with computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0151] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0152] Further reference Figure 3 As a response to the above Figure 2 The implementation of the method shown in this application provides an embodiment of a report data processing device, which is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0153] like Figure 3 As shown, the report data processing device 300 described in this embodiment includes: a first acquisition module 301, a processing module 302, a determination module 303, a generation module 304, a display module 305, a receiving module 306, and an output module 307. Wherein:

[0154] The first acquisition module 301 is used to acquire basic data of the insurance contract if it receives an insurance report generation request triggered by the user.

[0155] Processing module 302 is used to process the basic data of the insurance contract to obtain the corresponding target data;

[0156] The determination module 303 is used to obtain multiple preset version numbers corresponding to the insurance measurement model based on the model parameters of the preset insurance measurement model, and determine the parameter values ​​corresponding to each preset version number; wherein, the insurance measurement model is a measurement model based on the Hive framework;

[0157] The generation module 304 is used to calculate and process the target data based on the insurance measurement model, generate a measurement result table corresponding to each of the preset version numbers, and process the measurement result table to obtain a profit report corresponding to each of the preset version numbers respectively.

[0158] The display module 305 is used to synchronize each of the measurement result tables and each of the profit reports to a preset business database for display.

[0159] The receiving module 306 is used to receive the target version number returned by the user after consulting all the measurement result tables;

[0160] The output module 307 is used to output a target measurement result table corresponding to the target version number based on the measurement result table, and to output a target profit report corresponding to the target version number based on the profit report.

[0161] In this embodiment, the operations performed by the above-mentioned modules or units correspond one-to-one with the steps of the report data processing method of the aforementioned implementation method, and will not be repeated here.

[0162] In some optional implementations of this embodiment, the generation module 304 includes:

[0163] The first acquisition submodule is used to acquire the measurement indicators of the insurance measurement model; wherein, the number of measurement indicators includes multiple;

[0164] The second acquisition submodule is used to acquire a first version number; wherein, the first version number is any one of all the preset version numbers;

[0165] The query submodule retrieves the indicator data corresponding to the measurement indicator from the target data based on the first version number.

[0166] The execution submodule executes a preset task processing script based on the indicator data to obtain indicator processing data corresponding to the indicator data; wherein, the task processing script is a processing script based on a temporary table method;

[0167] The first generation submodule stores the processing results into a preset entity table to obtain a measurement result table corresponding to the first version number.

[0168] In this embodiment, the operations performed by the above-mentioned modules or units correspond one-to-one with the steps of the report data processing method of the aforementioned implementation method, and will not be repeated here.

[0169] In some optional implementations of this embodiment, the generation module 304 further includes:

[0170] The third acquisition submodule is used to acquire temporary data and temporary data tables generated during the execution of the task processing script;

[0171] The deletion submodule is used to delete the temporary data and the temporary data table.

[0172] In this embodiment, the operations performed by the above modules or units correspond one-to-one with the steps of the report data processing method in the aforementioned implementation method, and will not be repeated here.

[0173] In some optional implementations of this embodiment, the determining module 303 includes:

[0174] The fourth acquisition submodule is used to acquire a historical version number that matches the second version number; wherein the second version number is any one of all the preset version numbers;

[0175] The fifth acquisition submodule is used to acquire the historical reference parameters of the historical version number;

[0176] The second generation submodule is used to generate a specified parameter value corresponding to the second version number based on the historical reference parameters.

[0177] In this embodiment, the operations performed by the above-mentioned modules or units correspond one-to-one with the steps of the report data processing method of the aforementioned implementation method, and will not be repeated here.

[0178] In some optional implementations of this embodiment, the first acquisition module 301 includes:

[0179] The sixth acquisition submodule is used to acquire the initial business data of insurance contracts from a preset big data mart;

[0180] The seventh submodule is used to retrieve a preset specified data type;

[0181] The filtering submodule is used to filter the initial business data based on the specified data type to obtain specified data corresponding to the specified data type.

[0182] The determination submodule is used to use the specified data as the base data.

[0183] In this embodiment, the operations performed by the above-mentioned modules or units correspond one-to-one with the steps of the report data processing method of the aforementioned implementation method, and will not be repeated here.

[0184] In some optional implementations of this embodiment, the report data processing device further includes:

[0185] The second acquisition module is used to acquire the preset certificate template;

[0186] The processing module is used to perform certificate processing on the target measurement result table and the target profit report based on the certificate template to obtain the corresponding certificate data;

[0187] A storage module is used to store the certificate production data.

[0188] In this embodiment, the operations performed by the above-mentioned modules or units correspond one-to-one with the steps of the report data processing method of the aforementioned implementation method, and will not be repeated here.

[0189] In some optional implementations of this embodiment, the report data processing device further includes:

[0190] The third acquisition module is used to acquire the first intermediate processing data corresponding to the target measurement result table;

[0191] The fourth acquisition module is used to acquire the second intermediate processing data corresponding to the target profit report;

[0192] The push module is used to push the first intermediate processing data and the second intermediate processing data to a preset verification workbench.

[0193] In this embodiment, the operations performed by the above-mentioned modules or units correspond one-to-one with the steps of the report data processing method of the aforementioned implementation method, and will not be repeated here.

[0194] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0195] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected via a system bus. It should be noted that only the computer device 4 with components 41-43 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0196] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0197] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 4. Of course, the memory 41 may include both the internal storage unit and its external storage device of the computer device 4. In this embodiment, the memory 41 is typically used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for processing report data. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or will be output.

[0198] In some embodiments, the processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to execute computer-readable instructions stored in the memory 41 or to process data, such as computer-readable instructions for executing the report data processing method.

[0199] The network interface 43 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 4 and other electronic devices.

[0200] Compared with the prior art, the embodiments of this application have the following main advantages:

[0201] In this embodiment, after processing the target data of the insurance contract, multiple preset version numbers corresponding to the insurance measurement model are obtained through model parameters based on the insurance measurement model, and parameter values ​​corresponding to each preset version number are determined. Then, the target data is calculated and processed based on the insurance measurement model to generate measurement result tables corresponding to each preset version number. Based on the measurement result tables, profit reports corresponding to each preset version number are generated. Subsequently, each measurement result table and each profit report are synchronized to a preset business database for display. This allows users to filter all generated measurement result tables and decide on the optimal target measurement result table and target profit report. Compared with existing schemes for generating the optimal insurance report, which require multiple analyses, calculations, and parameter modifications, this method effectively reduces the number of manual interventions, reduces processing time, improves the processing efficiency of generating target measurement result tables and target profit reports, and effectively avoids distortion caused by repeated modifications and data processing, ensuring the data accuracy of the target measurement result tables and target profit reports.

[0202] This application also provides another embodiment, namely, providing a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor to cause the at least one processor to perform the steps of the report data processing method described above.

[0203] Compared with the prior art, the embodiments of this application have the following main advantages:

[0204] In this embodiment, after processing the target data of the insurance contract, multiple preset version numbers corresponding to the insurance measurement model are obtained through model parameters based on the insurance measurement model, and parameter values ​​corresponding to each preset version number are determined. Then, the target data is calculated and processed based on the insurance measurement model to generate measurement result tables corresponding to each preset version number. Based on the measurement result tables, profit reports corresponding to each preset version number are generated. Subsequently, each measurement result table and each profit report are synchronized to a preset business database for display. This allows users to filter all generated measurement result tables and decide on the optimal target measurement result table and target profit report. Compared with existing schemes for generating the optimal insurance report, which require multiple analyses, calculations, and parameter modifications, this method effectively reduces the number of manual interventions, reduces processing time, improves the processing efficiency of generating target measurement result tables and target profit reports, and effectively avoids distortion caused by repeated modifications and data processing, ensuring the data accuracy of the target measurement result tables and target profit reports.

[0205] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0206] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A method for processing report data, characterized in that, Includes the following steps: If a user-triggered insurance report generation request is received, the basic data of the insurance contract is obtained; The basic data of the insurance contract is processed to obtain the corresponding target data; Based on the model parameters of the preset insurance measurement model, multiple preset version numbers corresponding to the insurance measurement model are obtained, and parameter values ​​corresponding to each preset version number are determined; wherein, the insurance measurement model is a measurement model based on the Hive framework; The target data is calculated and processed based on the insurance measurement model to generate a measurement result table corresponding to each preset version number, and a profit report corresponding to each preset version number is obtained based on the measurement result table. The measurement result tables and profit reports are synchronized to the preset business database for display. Receive the target version number returned by the user after reviewing all the measurement result tables; Based on the measurement result table, output the target measurement result table corresponding to the target version number, and based on the profit report, output the target profit report corresponding to the target version number; The step of determining the parameter values ​​corresponding to each of the preset version numbers specifically includes: Obtain the historical version number that matches the second version number; wherein the second version number is any one of all the preset version numbers; Obtain the historical reference parameters for the historical version number; Generate a specified parameter value corresponding to the second version number based on the historical reference parameters; Among them, the insurance measurement models include measurement models based on the Common Basic Model (BBA) and the Premium Allocation Method (PAA), which are used to comprehensively measure liabilities, income, claims, expenses, and interest of direct insurance and reinsurance.

2. The method for processing report data according to claim 1, characterized in that, The step of calculating and processing the target data based on the insurance measurement model to generate a measurement result table corresponding to each preset version number specifically includes: Obtain the measurement indicators of the insurance measurement model; wherein, the number of measurement indicators includes multiple indicators; Obtain the first version number; wherein, the first version number is any one of all the preset version numbers; Based on the first version number, query the indicator data corresponding to the measurement indicator from the target data; Based on the indicator data, a preset task processing script is executed to obtain indicator processing data corresponding to the indicator data; wherein, the task processing script is a processing script based on the temporary table method; The processing results are stored in a preset entity table to obtain a measurement result table corresponding to the first version number.

3. The method for processing report data according to claim 2, characterized in that, After the step of storing the processing result in a preset entity table to obtain a measurement result table corresponding to the first version number, the method further includes: Obtain temporary data and temporary data tables generated during the execution of the task processing script; The temporary data and the temporary data table are deleted.

4. The method for processing report data according to claim 1, characterized in that, The steps for obtaining the basic data of the insurance contract specifically include: Obtain initial business data for insurance contracts from a pre-set big data mart; Retrieves a specified data type; Based on the specified data type, the initial business data is filtered to obtain specified data corresponding to the specified data type; The specified data is used as the base data.

5. The method for processing report data according to claim 1, characterized in that, After the steps of outputting the target measurement result table corresponding to the target version number based on the measurement result table, and outputting the target profit report corresponding to the target version number based on the profit report, the method further includes: Obtain the preset certificate template; Based on the certificate template, the target measurement result table and the target profit report are processed to obtain the corresponding certificate data. Store the certificate data.

6. The method for processing report data according to claim 1, characterized in that, After the steps of outputting the target measurement result table corresponding to the target version number based on the measurement result table, and outputting the target profit report corresponding to the target version number based on the profit report, the method further includes: Obtain the first intermediate processing data corresponding to the target measurement result table; Obtain the second intermediate processing data corresponding to the target profit report; The first intermediate processing data and the second intermediate processing data are pushed to the preset verification workbench.

7. A report data processing device, characterized in that, include: The first acquisition module is used to acquire the basic data of the insurance contract if it receives an insurance report generation request triggered by the user. The processing module is used to process the basic data of the insurance contract to obtain the corresponding target data; The determination module is used to obtain multiple preset version numbers corresponding to the insurance measurement model based on the model parameters of the preset insurance measurement model, and determine the parameter values ​​corresponding to each preset version number; wherein, the insurance measurement model is a measurement model based on the Hive framework; The generation module is used to calculate and process the target data based on the insurance measurement model, generate a measurement result table corresponding to each of the preset version numbers, and process the measurement result table to obtain a profit report corresponding to each of the preset version numbers respectively. The display module is used to synchronize the measurement result tables and profit reports to a preset business database for display. The receiving module is used to receive the target version number returned by the user after reviewing all the measurement result tables; The output module is used to output a target measurement result table corresponding to the target version number based on the measurement result table, and to output a target profit report corresponding to the target version number based on the profit report; The determining module includes: The fourth acquisition submodule is used to acquire a historical version number that matches the second version number; wherein the second version number is any one of all the preset version numbers; The fifth acquisition submodule is used to acquire the historical reference parameters of the historical version number; The second generation submodule is used to generate a specified parameter value corresponding to the second version number based on the historical reference parameters; Among them, the insurance measurement models include measurement models based on the Common Basic Model (BBA) and the Premium Allocation Method (PAA), which are used to comprehensively measure liabilities, income, claims, expenses, and interest of direct insurance and reinsurance.

8. A computer device comprising a memory and a processor, the memory storing computer-readable instructions, wherein the processor, when executing the computer-readable instructions, implements the steps of the method for processing report data as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the report data processing method as described in any one of claims 1 to 6.

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