Method, device and equipment for automated checking of reserves and storage medium

Abstract

This invention discloses an automated reserve verification method, apparatus, device, and storage medium. The method includes: acquiring a reserve verification request; extracting a target insurance type from the reserve verification request; determining corresponding data requirements based on the target insurance type; and matching a preset first calculation strategy and a second calculation strategy based on the target insurance type; acquiring user historical data from several different databases based on the data requirements; preprocessing the user historical data to obtain first target data; performing calculations based on the first calculation strategy and the first target data to obtain a first reserve calculation result; performing calculations based on the second calculation strategy and the first target data to obtain a second reserve calculation result; and performing a consistency check between the first reserve calculation result and the second reserve calculation result to obtain a verification result. This invention enables automated reserve verification.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and in particular to an automated method, apparatus, equipment, and storage medium for checking reserves. Background Technology

[0002] Insurance reserves refer to a certain amount of funds set aside by an insurer from premium income or surplus, corresponding to its insurance liabilities, to ensure the fulfillment of its insurance compensation or payment obligations, in accordance with relevant government laws or specific business needs. To ensure the normal operation of insurance companies and protect the interests of policyholders, most countries stipulate in insurance legislation that insurance companies should set aside insurance reserves to ensure that they have solvency commensurate with the scale of their insurance business. Currently, under the IFRS 17 standard, the calculation of reserves requires two sets of calculation methods: one manual and one automated. This process requires actuaries to spend a significant amount of time and effort on relevant reserve measurements, and the results need to be manually verified to ensure consistency. The reserve calculation process is complex, involves numerous procedures, many upstream and downstream systems, and a large amount of data, making manual calculation highly prone to errors. Currently, there is no automated method for reserve calculation and verification under the IFRS 17 standard in the insurance industry; the automation of the entire reserve process is currently lacking.

[0003] Therefore, there is an urgent need in this field for an automated reserve verification solution to address the technical problems existing in the background technology. Summary of the Invention

[0004] This invention provides an automated method, apparatus, equipment, and storage medium for checking reserves, which can realize the automated checking of reserves.

[0005] To solve the above-mentioned technical problems, one technical solution adopted by the present invention is: to provide an automated verification method for reserves, comprising:

[0006] Obtain a reserve verification request, extract the target insurance type from the reserve verification request, determine the corresponding data requirements based on the target insurance type, and match a preset first calculation strategy and a second calculation strategy based on the target insurance type.

[0007] Based on the data requirements, obtain user historical data from several different databases, preprocess the user historical data, and obtain the first target data;

[0008] The first reserve calculation result is obtained by calculating based on the first calculation strategy and the first target data; the second reserve calculation result is obtained by calculating based on the second calculation strategy and the first target data.

[0009] A consistency check is performed based on the first reserve calculation result and the second reserve calculation result to obtain the check result.

[0010] In one embodiment, the step of acquiring user historical data from several different databases according to the data requirements, and preprocessing the user historical data to obtain the first target data includes:

[0011] Based on the data requirements, obtain historical user data from several different databases;

[0012] The user's historical data is filtered to obtain second target data, which includes data items of the same type in different databases;

[0013] The consistency of data items of the same type from different databases in the second target data is compared, and the second target data is processed according to the comparison results to obtain the first target data.

[0014] In one embodiment, filtering the user's historical data to obtain the second target data includes:

[0015] Remove blank data items from the user's historical data;

[0016] The second target data is obtained by extracting data items that meet preset conditions from the user's historical data.

[0017] In one embodiment, the step of performing a consistency comparison on data items of the same type from different databases in the second target data, and processing the second target data based on the comparison results to obtain the first target data includes:

[0018] The process involves performing a consistency comparison on data items of the same type from different databases within the second target data to obtain the comparison result.

[0019] Based on the comparison results, determine whether the data items of the same type in different databases in the second target data are consistent;

[0020] If so, the corresponding data item in the second target data shall be used as the data in the first target data;

[0021] If not, then the corresponding data items in the second target data are adjusted for consistency to obtain the first target data.

[0022] In one embodiment, the consistency check based on the first reserve calculation result and the second reserve calculation result, to obtain the check result, includes:

[0023] A consistency check is performed based on the calculation results of the first reserve and the second reserve.

[0024] If the calculation results of the first reserve and the second reserve are consistent, then the verification result is determined to be correct;

[0025] If the calculation results of the first reserve and the second reserve are inconsistent, the verification result is determined to be incorrect.

[0026] In one embodiment, after determining that the verification result is correct if the first reserve calculation result and the second reserve calculation result are consistent, the method further includes:

[0027] Actuarial reserve data are obtained based on the first reserve result and the second reserve result;

[0028] The actuarial reserve data is input into a preset calculation model to obtain insurance financial statements.

[0029] In one embodiment, after determining that the check result is incorrect if the first reserve calculation result and the second reserve calculation result are inconsistent, the method further includes:

[0030] The calculation results of the first reserve and the second reserve are reviewed and an early warning is issued.

[0031] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is: to provide an automated reserve inspection device, comprising:

[0032] The matching module is used to obtain reserve verification requests, extract target insurance types from the reserve verification requests, determine corresponding data requirements based on the target insurance types, and match preset first and second calculation strategies based on the target insurance types.

[0033] The preprocessing module is used to obtain user historical data from several different databases according to the data requirements, and to preprocess the user historical data to obtain the first target data.

[0034] The calculation module is used to calculate the first reserve calculation result based on the first calculation strategy and the first target data, and to calculate the second reserve calculation result based on the second calculation strategy and the first target data.

[0035] The verification module is used to perform a consistency check based on the first reserve calculation result and the second reserve calculation result to obtain the verification result.

[0036] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is to provide a computer device, the computer device including a memory and a processor connected to the memory, the memory storing a computer program that can run on the processor, and the processor executing the computer program to implement the reserve automated verification method as described above.

[0037] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is to provide a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, it implements the reserve automated verification method as described above.

[0038] The beneficial effects of this invention are as follows: By obtaining a reserve verification request, the target insurance type is extracted from the request, and the corresponding data requirements are determined based on the target insurance type. The corresponding data is then retrieved according to these requirements, significantly reducing the amount of data processing. Furthermore, a preset first calculation strategy and a second calculation strategy are matched based on the target insurance type, achieving automatic matching of the two different calculation strategies through automated scheduling without manual intervention. Next, user historical data from several different databases is obtained based on the data requirements, and the user historical data is preprocessed to obtain the first target data. A first reserve calculation result is obtained based on the first calculation strategy and the first target data. A second reserve calculation result is obtained based on the second calculation strategy and the first target data. The first target data is directly input into the system, and two reserve calculation results are obtained using the pre-matched two calculation strategies without manual intervention. A consistency check is performed on the first and second reserve calculation results to obtain the check result. The automated reserve verification method of the present invention does not require human intervention in the entire calculation and verification process, thereby automating the reserve verification, reducing human intervention, shortening the overall calculation time, and reducing the occurrence of human error. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the automated reserve verification method according to the first embodiment of the present invention.

[0040] Figure 2 yes Figure 1 A flowchart illustrating an embodiment of step S102;

[0041] Figure 3 yes Figure 1 A flowchart illustrating another embodiment of step S102;

[0042] Figure 4 yes Figure 1 A flowchart illustrating another embodiment of step S102;

[0043] Figure 5 This is a flowchart illustrating the automated reserve verification method according to the second embodiment of the present invention.

[0044] Figure 6 This is a flowchart illustrating the automated reserve verification method according to the third embodiment of the present invention.

[0045] Figure 7 This is a schematic diagram of the structure of the automated reserve inspection device according to an embodiment of the present invention;

[0046] Figure 8 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention;

[0047] Figure 9 This is a schematic diagram of the structure of a computer storage medium according to an embodiment of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0049] The terms "first," "second," and "third" used in this invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this invention are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0050] 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 the invention. 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.

[0051] Figure 1 This is a flowchart illustrating the automated reserve verification method according to the first embodiment of the present invention. It should be noted that if substantially the same result is obtained, the method of the present invention is not necessarily identical. Figure 1 The illustrated process sequence is limited. For example... Figure 1 As shown, the method includes the following steps:

[0052] Step S101: Obtain the reserve verification request, extract the target insurance type from the reserve verification request, determine the corresponding data requirements according to the target insurance type, and match the preset first calculation strategy and second calculation strategy according to the target insurance type.

[0053] In step S101, the reserve verification request can be triggered by the user in real time or by the system backend at regular intervals. This reserve verification request actually includes the target insurance type. In practical applications, reserve calculation includes reserve calculation for various types of insurance, such as universal life and participating insurance. Different insurance types have different compensation amounts and rules, and therefore different reserve calculation strategies. International Financial Reporting Standard 17 (IFRS 17) is the latest international financial reporting standard. In this version, reserve calculation is particularly complex. This embodiment of the invention mainly uses IFRS 17 as an example for illustration.

[0054] In this step, the calculation and verification of reserves involve a large amount of data and calculation formulas. The data requirements for calculating reserves for various insurance types can be pre-organized according to IFRS 17 standards. In subsequent steps, the corresponding data can be obtained based on the data requirements of the target insurance type. Furthermore, reserve calculation strategies for various insurance types can be compiled according to IFRS 17 standards, and a first and second preset mapping relationship can be pre-established between various insurance types and their corresponding reserve calculation strategies. When the reserve verification request is received, the first and second calculation strategies corresponding to the target insurance type can be directly found from the first and second preset mapping relationship tables. More specifically, the first calculation strategy consists of several pre-established task modules, each including: earned premiums before maturity, verification of expected claims before maturity, discounted cash flow before maturity, outstanding claims, and loss ratio prediction modules. The first calculation strategy for each insurance type is pre-set in the first preset mapping relationship table. When the reserve verification request is received, the corresponding first calculation strategy is searched in the first preset mapping table according to the target insurance type. Each task module is automatically scheduled according to the first calculation strategy to meet the reserve calculation process. The second calculation strategy is based on the Excel file provided by the business personnel. By using Excel nesting technology to embed the Excel file with complex formulas into the Java program, a second preset mapping table is established according to each insurance type to obtain the second calculation strategy for the reserves of each insurance type.

[0055] Step S102: Obtain user historical data from several different databases according to the data requirements, preprocess the user historical data to obtain the first target data.

[0056] In step S102, user historical data is obtained from different databases according to the data requirements. These databases include, but are not limited to, numerous business systems, financial systems, actuarial systems, and reinsurance systems. This step involves data scraping between databases of various systems. Therefore, the user historical data needs to be processed first, such as removing missing or empty data items and extracting traceable, non-orphaned data rows to ensure the scraped data is valid. Furthermore, since different databases are involved, it is essential to ensure consistency of identical data items such as amounts and quantities across these databases. Therefore, a consistency comparison of the user historical data is required to ensure the consistency of the upstream and downstream data chains.

[0057] Specifically, please see Figure 2 Step S102 includes the following steps:

[0058] Step S201: Obtain user historical data from several different databases according to the data requirements.

[0059] In step S201, corresponding user historical data is retrieved from different databases according to the data requirements. Retrieving data based on these requirements can significantly reduce the amount of data processing.

[0060] Step S202: Filter the user's historical data to obtain second target data, which includes data items of the same type in different databases.

[0061] In step S202, the first step is to filter the acquired user data to obtain the second target data. Specifically, different databases may contain data items of the same type. For example, both System 1 and System 2 include the data item "user historical premium." Although this data item exists in different system databases, the data item itself is the same, so the corresponding data should also be identical. Furthermore, since there may be instances where certain data items in the user historical data are missing or empty in different databases, it is necessary to filter the user historical data. For further details, please refer to... Figure 3 Step S202 includes:

[0062] Step S301: Remove blank data items from the user's historical data.

[0063] In step S301, blank data items in the user's historical data are first removed. It is understood that the reasons for blankness include missing data, empty data items, etc.

[0064] Step S302: Extract data items that meet preset conditions from the user's historical data to obtain the second target data.

[0065] In step S302, traceable and non-isolated data items are extracted from the filtered user historical data to obtain the second target data.

[0066] Step S203: Perform a consistency comparison on data items of the same type from different databases in the second target data, and process the second target data according to the comparison results to obtain the first target data.

[0067] In step S203, since different databases may contain data items of the same type, even if a data item exists in different databases, the data item itself is the same, so the corresponding data should also be identical. Therefore, a consistency comparison needs to be performed on data items of the same type across different databases. For details, please refer to [further details]. Figure 4Step S203 includes:

[0068] Step S401: Based on the comparison results, determine whether the data items of the same type in different databases in the second target data are consistent.

[0069] Step S402: If yes, then the corresponding data item in the second target data is used as the data in the first target data.

[0070] Step S403: If not, then perform consistency adjustment on the corresponding data items in the second target data to obtain the first target data.

[0071] In steps S401-S403, consistency is ensured by comparing data items of the same type across different databases. If data items of the same type are consistent, no further processing is required. If data items of the same type are inconsistent, processing is necessary to determine their consistency. Specifically, consistency adjustments can be made to the data item based on preset conditions to ensure consistency. For example, using a specific database as a standard, data items in other databases can be forced to be adjusted to match this database. More specifically, to improve data processing efficiency, in one optional embodiment, an artificial intelligence algorithm is used to collect data scenarios where data items of the same type are inconsistent, and a decision tree is used to train the model. Historical data scenarios where data items of the same type are inconsistent are archived and organized, and corresponding solutions are provided to obtain training samples. The training samples are used to train the model, and this process is repeated until all scenarios are included in the model, enabling the model to autonomously judge and automatically process problematic data, ensuring eventual data consistency.

[0072] Step S103: Calculate the first reserve calculation result according to the first calculation strategy and the first target data, and calculate the second reserve calculation result according to the second calculation strategy and the first target data.

[0073] In step S103, the first target data is input into the scheduled first calculation strategy and second calculation strategy to obtain the corresponding first reserve calculation result and second reserve calculation result, respectively. It should be noted that although the calculation processes of the first calculation strategy and the second calculation strategy are different, theoretically, the two strategies only use different calculation methods, and the calculation results should be the same. That is to say, the first reserve calculation result and the second reserve calculation result are equal under normal circumstances.

[0074] Step S104: Perform a consistency check based on the first reserve calculation result and the second reserve calculation result to obtain the check result.

[0075] In step S104, a consistency check is performed on the first reserve calculation result obtained using the first calculation strategy and the second reserve calculation result obtained using the second calculation strategy. Specifically, please refer to... Figure 5 In an optional embodiment, step S104 includes the following steps:

[0076] Step S501: Perform a consistency check based on the first reserve calculation result and the second reserve calculation result.

[0077] Step S502: If the calculation result of the first reserve is consistent with the calculation result of the second reserve, then the verification result is determined to be correct.

[0078] Step S503: If the calculation result of the first reserve and the calculation result of the second reserve are inconsistent, the verification result is determined to be incorrect.

[0079] The automated reserve verification method of this invention obtains a reserve verification request, extracts the target insurance type from the request, determines the corresponding data requirements based on the target insurance type, and retrieves the corresponding data, greatly reducing the amount of data processing. It then matches a preset first calculation strategy and a second calculation strategy based on the target insurance type, achieving automatic matching of the two different calculation strategies through automated scheduling without manual operation. Next, it obtains user historical data from several different databases based on the data requirements, preprocesses the user historical data to obtain first target data, calculates a first reserve calculation result based on the first calculation strategy and the first target data, and calculates a second reserve calculation result based on the second calculation strategy and the first target data. The first target data is directly input into the system, and the two pre-matched calculation strategies yield two reserve calculation results without manual intervention. Finally, a consistency check is performed on the first and second reserve calculation results to obtain the verification result. The automated reserve verification method of the present invention does not require human intervention in the entire calculation and verification process, thereby automating the reserve verification, reducing human intervention, shortening the overall calculation time, and reducing the occurrence of human error.

[0080] Figure 6 This is a flowchart illustrating an automated reserve verification method according to another embodiment of the present invention. It should be noted that if substantially the same result is obtained, the method of the present invention does not necessarily require further clarification. Figure 6 The illustrated process sequence is limited. Based on the above embodiments, such as... Figure 6 As shown, after step 502, the method further includes:

[0081] Step S601: Obtain actuarial reserve data based on the first reserve result and the second reserve result.

[0082] In step S601, actuarial reserve data is obtained based on the first reserve result and the second reserve result. Since the first reserve result and the second reserve result are consistent, either calculation result can be used as the actuarial reserve data.

[0083] Step S602: Input the actuarial reserve data into the preset calculation model to obtain the insurance financial statement.

[0084] In step S602, the preset calculation model is a pre-selected calculation model. The calculation action corresponding to the preset calculation model is determined according to the target insurance type to obtain the insurance financial statement.

[0085] The automated reserve verification method of the second embodiment of the present invention, based on the first embodiment, realizes the automated generation of insurance financial statements, which can obtain insurance financial statements without manual intervention, greatly reducing labor costs.

[0086] Based on the above embodiments, after step 503, the method further includes:

[0087] Step S603: Review the calculation results of the first reserve and the second reserve, and issue an early warning.

[0088] Figure 7 This is a schematic diagram of the structure of the automated reserve inspection device 70 according to an embodiment of the present invention. Figure 7 As shown, the device 70 includes a matching module 71, a preprocessing module 72, a calculation module 73, and a verification module 74.

[0089] The matching module 71 is used to obtain the reserve verification request, extract the target insurance type from the reserve verification request, determine the corresponding data requirements according to the target insurance type, and match the preset first calculation strategy and second calculation strategy according to the target insurance type.

[0090] The preprocessing module 72 is used to obtain user historical data from several different databases according to the data requirements, and preprocess the user historical data to obtain the first target data;

[0091] The calculation module 73 is used to perform calculations based on the first calculation strategy and the first target data to obtain a first reserve calculation result, and to perform calculations based on the second calculation strategy and the first target data to obtain a second reserve calculation result.

[0092] The verification module 74 is used to perform a consistency check based on the first reserve calculation result and the second reserve calculation result to obtain the verification result.

[0093] The automated reserve verification device 70 is an apparatus for the automated reserve verification method, capable of implementing all steps of the automated reserve verification method. For functional limitations of each module of the automated reserve verification device 70, please refer to the description of the automated reserve verification method; it will not be repeated here.

[0094] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Figure 8 As shown, the computer device 80 includes a processor 81 and a memory 82 coupled to the processor 81.

[0095] The memory 82 stores a computer program that can run on the processor 81 and is used to implement the automated reserve verification method described in any of the above embodiments.

[0096] The processor 81 is used to execute the computer program stored in the memory 82 to implement an automated reserve verification method.

[0097] The processor 81 can also be referred to as a CPU (Central Processing Unit). The processor 81 may be an integrated circuit chip with signal processing capabilities. The processor 81 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0098] See Figure 9 , Figure 9This is a schematic diagram of the structure of a computer storage medium according to an embodiment of the present invention. The computer storage medium of this embodiment stores a computer program 91 capable of implementing all the above methods. This computer program 91 can be stored in the computer storage medium in the form of a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned computer storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, or terminal devices such as computers, servers, mobile phones, and tablets.

[0099] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0100] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0101] The above are merely embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. An automated method for checking reserves, characterized in that, include: Obtain a reserve verification request, extract the target insurance type from the reserve verification request, determine the corresponding data requirements based on the target insurance type, and match a preset first calculation strategy and a second calculation strategy based on the target insurance type. The first calculation strategy consists of several pre-established task modules, and the second calculation strategy is a calculation strategy based on an Excel spreadsheet. According to the data requirements, user historical data from several different databases is obtained, and the user historical data is preprocessed to obtain first target data, including: obtaining user historical data from several different databases according to the data requirements; filtering the user historical data to obtain second target data, the second target data including data items of the same type in different databases; performing a consistency comparison on the data items of the same type in different databases in the second target data, and processing the second target data according to the comparison result to obtain the first target data; The step of performing a consistency comparison of data items of the same type from different databases in the second target data, and processing the second target data according to the comparison result to obtain the first target data includes: performing a consistency comparison of data items of the same type from different databases in the second target data to obtain the comparison result; determining whether the data items of the same type from different databases in the second target data are consistent according to the comparison result; if so, using the corresponding data item in the second target data as the data in the first target data; if not, performing consistency adjustment on the corresponding data item in the second target data to obtain the first target data. The consistency adjustment of the corresponding data items in the second target data includes: using artificial intelligence algorithms to collect inconsistent data scenarios of the same type of data items, and using decision trees to train the model; using training samples to train the model so that the model can autonomously judge and automatically process problematic data, ensuring the final consistency of the data; The first reserve calculation result is obtained by calculating based on the first calculation strategy and the first target data; the second reserve calculation result is obtained by calculating based on the second calculation strategy and the first target data. A consistency check is performed on the first reserve calculation result and the second reserve calculation result to obtain the check result. If the first reserve calculation result and the second reserve calculation result are consistent, the check result is determined to be correct. Then, actuarial reserve data is obtained based on the first reserve calculation result and the second reserve calculation result. The actuarial reserve data is input into a preset calculation model to obtain insurance financial statements.

2. The automated reserve verification method according to claim 1, characterized in that, The filtering of the user's historical data to obtain the second target data includes: Remove blank data items from the user's historical data; The second target data is obtained by extracting data items that meet preset conditions from the user's historical data.

3. The automated reserve verification method according to claim 1, characterized in that, The consistency check based on the first reserve calculation result and the second reserve calculation result includes the following: A consistency check is performed based on the calculation results of the first reserve and the second reserve. If the calculation results of the first reserve and the second reserve are inconsistent, the verification result is determined to be incorrect.

4. The automated reserve verification method according to claim 3, characterized in that, If the calculation results of the first reserve and the second reserve are inconsistent, and the verification result is determined to be incorrect, the method further includes: The calculation results of the first reserve and the second reserve are reviewed and an early warning is issued.

5. An automated reserve verification device, characterized in that, include: The matching module is used to obtain the reserve verification request, extract the target insurance type from the reserve verification request, determine the corresponding data requirements according to the target insurance type, and match the preset first calculation strategy and second calculation strategy according to the target insurance type. The first calculation strategy is a number of pre-established task modules, and the second calculation strategy is a calculation strategy based on Excel draft. A preprocessing module is used to acquire user historical data from several different databases according to the data requirements, and preprocess the user historical data to obtain first target data; including: acquiring user historical data from several different databases according to the data requirements; filtering the user historical data to obtain second target data, the second target data including data items of the same type in different databases; performing a consistency comparison on the data items of the same type in different databases in the second target data, and processing the second target data according to the comparison result to obtain the first target data; the step of performing a consistency comparison on the data items of the same type in different databases in the second target data, and processing the second target data according to the comparison result to obtain the first target data includes: The process involves comparing the consistency of data items of the same type from different databases in the second target data to obtain the comparison result; determining whether the data items of the same type from different databases in the second target data are consistent based on the comparison result; if so, using the corresponding data item in the second target data as the data in the first target data; if not, adjusting the consistency of the corresponding data item in the second target data to obtain the first target data; the adjustment of the consistency of the corresponding data item in the second target data includes: using artificial intelligence algorithms to collect data scenarios where data items of the same type are inconsistent, training the model using decision trees; and training the model using training samples so that the model can autonomously judge and automatically process problematic data, ensuring the final consistency of the data. The calculation module is used to calculate the first reserve calculation result based on the first calculation strategy and the first target data, and to calculate the second reserve calculation result based on the second calculation strategy and the first target data. The verification module is used to perform a consistency check on the first reserve calculation result and the second reserve calculation result to obtain the verification result; A consistency check is performed on the first reserve calculation result and the second reserve calculation result. If the first reserve calculation result and the second reserve calculation result are consistent, the check result is determined to be correct. Then, actuarial reserve data is obtained based on the first reserve calculation result and the second reserve calculation result. The actuarial reserve data is input into a preset calculation model to obtain insurance financial statements.

6. A computer device, the computer device comprising a memory and a processor connected to the memory, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the automated reserve verification method as described in any one of claims 1-4.

7. A computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is executed by the processor, it implements the reserve automation verification method as described in any one of claims 1-4.

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