A method, device, computer equipment and storage medium for calculating financial data

Abstract

The embodiment of the present invention discloses a method, device, computer equipment and storage medium for calculating financial data. The method includes processing basic account data to obtain a calculation basic data table set; obtaining a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters; selecting a corresponding target algorithm model according to the product information in the calculation intermediate data table set, and calculating net interest income and expenditure based on the calculation intermediate data table set through the target algorithm model. The embodiment of the present invention calculates net interest income and expenditure data with the most fine-grained basic account data, which is convenient for summarizing and aggregating data of various dimensions, meeting the requirements of completeness and accuracy; through parameterization, the coupling between each internal virtual function module and the calculation algorithm is reduced, and the flexibility and rationality of the net interest income and expenditure calculation method are improved, solving the problem that the current net interest calculation method cannot meet the requirements of the annual plan budget preparation of the bank.

Description

Technical Field

[0001] The embodiments of the present invention relate to data processing technology, and in particular to a method, device, computer equipment and storage medium for calculating financial data. Background Art

[0002] The annual budget plan (also known as the comprehensive business plan) of large and medium-sized commercial banks is a carrier for commercial banks to make overall planning for operations, implement development strategies, and achieve comprehensive unification, coordination and balance of business plan management and resource allocation. For a long time, net interest income has been a very important source of profit for commercial banks. Net interest income is the ratio of net interest income and expenditure to the average balance of total interest-earning assets. Therefore, the estimation of net interest income and expenditure is the main component of the annual budget plan. Its accuracy will directly affect the judgment of bank benefits and the formulation of relevant policies.

[0003] Due to the massive amount of data and the complexity of the scenarios, current budget management software is more based on a combination of manual and system methods and uses coarse-grained estimates for calculations. This approach will affect the accuracy of net interest income and expenditure calculations of my country's large commercial banks under large amounts of data, and therefore cannot meet the needs of banks in preparing annual budget plans. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, computer equipment and storage medium for calculating financial data, which can improve the accuracy of calculation and meet the needs of bank annual plan budget preparation.

[0005] In a first aspect, an embodiment of the present invention provides a method for calculating financial data, including:

[0006] Process the basic account data to obtain the basic data table set for calculation;

[0007] Obtaining a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters;

[0008] A corresponding target algorithm model is selected according to the product information in the calculation intermediate data table set, and the net interest income and expenditure is calculated based on the calculation intermediate data table set by the target algorithm model.

[0009] In a second aspect, an embodiment of the present invention further provides a device for calculating financial data, the device comprising:

[0010] The data processing module is used to process the basic account data to obtain the basic data table set for calculation;

[0011] A data table set generation module, used to obtain a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters;

[0012] The data calculation module is used to select a corresponding target algorithm model according to the product information in the calculation intermediate data table set, and calculate the net interest income and expenditure based on the calculation intermediate data table set through the target algorithm model.

[0013] In a third aspect, an embodiment of the present invention further provides a computer device, the computer device comprising:

[0014] one or more processors;

[0015] a memory for storing one or more programs,

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for calculating financial data as described in any embodiment of the present invention.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for calculating financial data as described in any embodiment of the present invention.

[0018] The embodiment of the present invention provides a method, device, computer equipment and storage medium for calculating financial data, which obtains a calculation basic data table set by processing basic account data, obtains a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters, selects a corresponding target algorithm model according to the product information in the calculation intermediate data table set, and calculates net interest income and expenditure based on the calculation intermediate data table set through the target algorithm model. The embodiment of the present invention calculates net interest income and expenditure data with the most fine-grained basic account data, which is convenient for summarizing and aggregating data of various dimensions, meeting the requirements of completeness and accuracy; based on the calculation of net interest income and expenditure data with basic account data, combined with parameterization, the coupling between each internal virtual function module and the calculation algorithm is reduced, the flexibility and rationality of the net interest income and expenditure calculation method are improved, and the problem that the current net interest calculation method cannot meet the requirements of bank annual plan budget preparation is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flowchart of a method for calculating financial data provided by an embodiment of the present invention;

[0020] Figure 2 A backup framework diagram of account details data in a financial data calculation method provided by an embodiment of the present invention;

[0021] Figure 3 A schematic diagram of the structure of an algorithm configuration table provided in an embodiment of the present invention;

[0022] Figure 4A flowchart of another method for calculating financial data provided by an embodiment of the present invention;

[0023] Figure 5 A flowchart of data processing provided by an embodiment of the present invention;

[0024] Figure 6 A flow chart of calculating net interest income and expenditure provided by an embodiment of the present invention;

[0025] Figure 7 A structural block diagram of a financial data calculation device provided by an embodiment of the present invention;

[0026] Figure 8 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0028] To facilitate understanding, the terms that may appear in the embodiments of the present invention are first explained.

[0029] Net interest income and expenditure refers to the difference between the interest income of a bank or other financial institution's assets and the interest expenses of its liabilities. Net interest income and expenditure reflects the results of a bank's operation of assets or liabilities in the short term (generally within one year).

[0030] It should be noted that for a large or medium-sized commercial bank, it is not easy to calculate net interest income and expenditure. This is because banks have a wide variety of products, including deposits, loans, credit cards, bonds, money markets, reserves, and other interest-bearing assets and non-interest-bearing assets. In terms of subdivision, deposits can be divided into current and fixed deposits according to the deposit term, local currency and foreign currency according to the currency, units and individuals according to the deposit subject, and large amounts, notices, agreements, transfers, fixed and current deposits, etc. according to the deposit type. The calculation methods for interest on different products are also different. Not only should we consider installment interest calculation and segment interest calculation, but also interest rate adjustment and spread adjustment. In terms of comprehensiveness of calculation, we should not only measure stock data, but also incremental data. In terms of the granularity of the calculation data, we should consider whether to use detailed data or packaged data for calculation. In terms of calculation time, we should consider the length of the calculation interval, whether it is fixed or rolling, etc.

[0031] Net Interest Margin refers to the ratio of net interest income to the average balance of total interest-earning assets. The higher the net interest margin, the stronger the bank's profitability.

[0032] The annual budget plan (also known as the comprehensive business plan) of large and medium-sized commercial banks is a carrier for commercial banks to make overall planning for operations, implement development strategies, and achieve comprehensive unification, coordination and balance of business plan management and resource allocation. For a long time, net interest income has been a very important source of profit for commercial banks. Net interest income is the ratio of net interest income and expenditure to the average balance of total interest-earning assets. Therefore, the estimation of net interest income and expenditure is the main component of the annual budget plan. Its accuracy is directly related to the judgment of bank benefits and the formulation of relevant policies.

[0033] Although there are many budget management software products on the market, there are almost no mature products that can support the net interest income and expenditure calculation under large data volumes of my country's large commercial banks. Due to the massive amount of data and the complexity of the scenarios, net interest income and expenditure calculation is mostly done by combining manual and system, using coarse-grained estimates.

[0034] Figure 1 This is a flowchart of a method for calculating financial data provided by an embodiment of the present invention. This embodiment is applicable to the case of calculating net interest income and expenditure data in financial data. The method can be executed by a financial data calculation device, which can be implemented by software and / or hardware and configured in a computer device. Figure 1 As shown, the method includes:

[0035] Step 110: Process the basic account data to obtain a calculation basic data table set.

[0036] It should be noted that the financial data may be data related to the operation of a bank or other financial institution. In an embodiment of the present invention, the financial data may be net interest income and expenditure data (or simply referred to as net interest income and expenditure).

[0037] Basic account data may be account-related data in a bank or other financial institution. For example, basic account data may be account detail data required for net interest calculation. Specifically, basic account data may include account detail data such as deposits, loans, credit card overdrafts, bonds, overdue non-accruals, money markets, and other interest-bearing and non-interest-bearing asset and liability data. These account detail data originate from various customer-related transaction systems of banks or other financial institutions. For example, customer-related transaction systems of banks include deposit systems, loan systems, credit card systems, bond systems, and financial market systems. In an embodiment of the present invention, the above-mentioned account detail data is backed up to a data warehouse according to a set period. In the data warehouse, the storage and calculation of massive and most fine-grained basic account data are realized in a distributed database manner.

[0038] When executing financial data measurement methods, these account detail data can be obtained directly from the data warehouse. Figure 2 A backup framework diagram of account details data in a financial data calculation method provided by an embodiment of the present invention. Figure 2 The scenario shows that the account detail data generated by the bank's customer-related transaction systems 210 are backed up to the data warehouse 220. If the processor 230 needs to perform a net interest income and expenditure calculation operation, the account detail data required for the net interest income and expenditure calculation can be directly obtained from the data warehouse 220.

[0039] Optionally, before processing the basic account data to obtain the basic data table set for calculation, it also includes: obtaining pre-configured static parameters, and obtaining the basic account data required for calculation from the data warehouse according to the static parameters. Among them, the static parameters include institutional information, indicator definition, account, product information, currency, verification rules, various coding information and various comparison relationships. Specifically, the static parameters are read, and the corresponding basic account data is read from the data warehouse based on the parameters required for net interest income and expenditure calculation, such as institutional information, indicator definition, account, product information, currency, etc., included in the static parameters.

[0040] It should be noted that static parameters can be data configured in advance for net interest calculation. For example, a configuration file of static parameters can be written in advance, and when needed, the configuration file can be loaded to obtain static parameters. Static parameters are generally maintained manually by the user on the interface.

[0041] In the embodiment of the present invention, the calculation basic data table set is a set of account data tables required for calculating net interest income and expenditure after processing, that is, the calculation basic data table set is determined by the processed account data.

[0042] Exemplarily, after obtaining the basic account data, the obtained basic account data can be processed in the following manner to obtain the processed account data. The data table recording the processed account data constitutes a basic data table set for calculation. The processing of the basic account data includes: correction processing, total score verification processing, packaging processing, and incremental data splitting processing. Specifically, the basic account data is corrected, the total score verification processing, packaging processing, and incremental data splitting processing are performed to obtain the processed account data, and the basic data table set for calculation is constituted by the processed account data.

[0043] Step 120: Obtain a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters.

[0044] Among them, the calculation parameters are parameters involved in the calculation of net interest income and expenditure. For example, the calculation parameters include static parameters, dynamic parameters and calculation operation parameters.

[0045] Dynamic parameters refer to parameters that are continuously updated at fixed times or triggered by specific events, such as interest rates, exchange rates, prices, and information on mergers and reorganizations of institutions. The source of these parameters is generally actively pushed by external data warehouse systems.

[0046] The measurement operation parameters are parameters manually input by business personnel. The measurement operation parameters mainly include the measurement start and end time, the simulation generation parameters for incremental data, and the measurement factors, etc. The measurement operation parameters determine the accuracy and efficiency of the measurement. Among them, the measurement start and end time determine the start and end time of the measurement, the simulation generation parameters for incremental data reflect the coarseness of the granularity of the incremental data simulation generation, and the measurement factors reflect the optimism of the growth rate forecast. The measurement operation parameters depend on the judgment and requirements of the testers. The coarseness of the granularity of the incremental data simulation generation, the optimism of the growth rate forecast in different measurement factors, and the growth requirements for different institutions will lead to different results for each measurement.

[0047] Exemplarily, the calculation parameters are obtained, the source data required for a single calculation in the calculation basic data table set is determined according to the calculation parameters, and the calculation intermediate data table set is generated according to the source data.

[0048] Step 130: Select a corresponding target algorithm model according to the product information in the calculation intermediate data table set, and calculate the net interest income and expenditure based on the calculation intermediate data table set through the target algorithm model.

[0049] Among them, the product information in the measurement intermediate data table set is the information related to the product in the account information of the measurement intermediate data table set. For example, the product information may include product type information, etc. The account data is the account detail data obtained after the basic account data is processed. Since the basic account data is the account detail data that matches the static parameters in the data warehouse, and the static parameters include product information, the basic account data contains data related to the product information. The account data obtained after processing the basic account data also contains data related to the product information.

[0050] The algorithm model is determined based on the calculation rules for measuring net interest income and expenditure and is used to calculate net interest income and expenditure. The calculation rules of various products can be sorted out in advance and summarized into centralized typical models, and then a public basic algorithm function library (including multiple basic algorithm functions) can be formed through programming, and then the basic algorithm function of the net interest of each product can be configured in the algorithm configuration table. Figure 3 A schematic diagram of the structure of an algorithm configuration table provided in an embodiment of the present invention. Figure 3As shown, the algorithm configuration table stores the correspondence between product types and calculation algorithms, and the algorithms configured in the algorithm configuration table include the general calculation algorithm for deposits and loans, the agreed deposit calculation algorithm, the fixed-term and flexible calculation algorithm, the untransferred deposit calculation algorithm, the loan repayment method calculation algorithm, the credit card overdraft calculation algorithm, the non-accrued payment collection and recovery calculation algorithm, the loan overdue calculation algorithm and the general bond calculation algorithm, etc.

[0051] Among them, the corresponding relationship between product type and measurement algorithm includes:

[0052] 1. Deposit and loan products correspond to the general deposit and loan calculation algorithm. Most deposit and loan products use this algorithm to calculate interest.

[0053] 2. The unit agreement deposit product corresponds to the agreement deposit calculation algorithm, that is, the agreement deposit calculation algorithm is mainly used for the interest calculation of the unit agreement deposit product.

[0054] 3. The fixed-term and flexible deposit products correspond to the fixed-term and flexible calculation algorithm, that is, the fixed-term and flexible calculation algorithm is mainly used for the interest calculation of fixed-term and flexible deposit products.

[0055] 4. The regular deposit products that are not automatically transferred correspond to the non-transferred deposit calculation algorithm, that is, the non-transferred deposit calculation algorithm is mainly used for the interest calculation of regular deposit products that are not automatically transferred by units or individuals.

[0056] 5. The loan product corresponds to the loan repayment method calculation algorithm, that is, the loan repayment method calculation algorithm is mainly used for the interest calculation of personal housing loans, consumer loans and other products.

[0057] 6. The credit card product corresponds to the credit card overdraft calculation algorithm, that is, the credit card speculation calculation algorithm is mainly used for the overdraft interest calculation of credit card products.

[0058] 7. Loan products also correspond to loan overdue calculation algorithms, that is, the loan overdue calculation algorithm is mainly used to calculate overdue interest on loan products.

[0059] 8. The non-accrual loan collection and recovery product corresponds to the non-accrual loan collection and recovery calculation algorithm, that is, the non-accrual loan collection and recovery calculation algorithm is mainly used for the calculation of non-accrual loan collection and recovery interest.

[0060] 9. Bond products correspond to the general bond calculation algorithm, that is, the general bond calculation algorithm is mainly used for interest calculation of bond products.

[0061] Exemplarily, the account data in the intermediate data table set are traversed, and the product type corresponding to each account data is determined according to the product type information included in the account data; the algorithm configuration table is queried based on the product type to obtain the target algorithm model corresponding to the product type, wherein the algorithm configuration table stores the product type and the algorithm model in association; the account data in the intermediate data table set is passed into the target algorithm model, and the net interest income and expenditure calculation result is determined by the target algorithm model. For example, the account data corresponding to the intermediate data table set is traversed to obtain the product type to which the account detail data to be calculated belongs. Due to the correspondence between the product type and the calculation algorithm stored in the algorithm configuration table, the target algorithm model corresponding to the product can be obtained by querying the algorithm configuration table. Furthermore, the interest income of assets and the interest expenditure of liabilities can be calculated based on the account detail data according to the calculation algorithms corresponding to different products, and the net interest income and expenditure can be calculated by calculating the difference between the interest income and the interest expenditure of liabilities.

[0062] In the case of large amounts of data, the basic algorithm functions in the public basic algorithm function library will be frequently called, and the algorithm execution efficiency is usually improved through parallel computing combined with database table partitioning, indexing and other technologies. Specifically, the net interest income and expenditure calculation can be performed based on the cluster architecture, that is, the net interest income and expenditure calculation task is assigned to the available servers in the server cluster, so that each server can execute the net interest income and expenditure calculation task in parallel. The net interest income and expenditure calculation process may include: calculating the interest income of assets and the interest expenditure of liabilities based on the account details data in the intermediate data table set according to the calculation algorithm corresponding to different products, and calculating the net interest income and expenditure by calculating the difference between the interest income and the interest expenditure of liabilities. Optionally, when storing account data, the data acquisition efficiency is improved through the partitioning and indexing technology of the database table, and then, when the basic algorithm function is frequently called, the calculation operation can be performed simply and efficiently.

[0063] The technical solution of this embodiment is to obtain a basic data table set for calculation by processing the basic account data, obtain a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters, select the corresponding target algorithm model according to the product information in the calculation intermediate data table set, and calculate the net interest income and expenditure based on the calculation intermediate data table set through the target algorithm model. The embodiment of the present invention calculates the net interest income and expenditure data with the most fine-grained basic account data, which is convenient for summarizing and aggregating data of various dimensions to meet the requirements of completeness and accuracy; on the basis of calculating the net interest income and expenditure data with the basic account data, combined with the parameterized method, the coupling between each internal virtual function module and the calculation algorithm is reduced, the flexibility and rationality of the net interest income and expenditure calculation method are improved, and the problem that the current net interest calculation method cannot meet the needs of the bank's annual plan budget preparation is solved.

[0064] Figure 4 A flowchart of another method for calculating financial data provided by an embodiment of the present invention. Based on the above technical solution, this embodiment further defines the correction processing, total score verification processing, packaging processing and incremental data splitting processing of the basic account data. The correction processing, total score verification processing, packaging processing and incremental data splitting processing of the basic account data include: traversing the account data basic table set to obtain the basic account data of each account; correcting the abnormal account data with attribute errors in the basic account data to obtain the account data intermediate table set; based on the data day account data of the general ledger, the total score verification of the stock balance of the corresponding account product in the account data intermediate table set is carried out, and the account data intermediate table set is adjusted according to the total score verification result; the intermediate account data corresponding to the adjusted account data intermediate table set is packaged to obtain the calculated stock data table set; according to the calculated stock data table set, the calculated incremental data table set is simulated and generated, and the calculated stock data table set and the calculated incremental data table set are used as the calculated basic data table set.

[0065] like Figure 4 As shown, the method includes:

[0066] Step 410: Obtain pre-configured static parameters.

[0067] Exemplarily, when a net interest calculation event is detected to be triggered, pre-configured static parameters are obtained. The condition for triggering the net interest calculation event may be triggered by a manual operation. For example, a business person enters the calculation parameters on the interface and starts the net interest income and expenditure calculation function module to trigger the net interest calculation event. In response to the net interest calculation event, a configuration file corresponding to the static parameters is loaded and read to obtain the static parameters.

[0068] Alternatively, the net interest calculation event is triggered periodically. If the periodic triggering method is adopted, after the net interest calculation event is triggered, the business personnel will be prompted to enter the calculation parameters. In response to the net interest calculation event, the configuration file corresponding to the static parameters is loaded and read to obtain the static parameters.

[0069] Step 420: Obtain basic account data required for calculation from the data warehouse according to the static parameters.

[0070] Step 430: traverse the account data basic table set to obtain basic account data of each account.

[0071] Exemplarily, the account data basic table set is traversed to obtain the basic account data of each account recorded in the account data basic table.

[0072] Step 440: Correct the abnormal account data with incorrect attributes in the basic account data to obtain an intermediate table set of account data.

[0073] Specifically, the non-zero balance data in the basic account data is obtained; the attributes of each non-zero balance data are checked based on the exception judgment rule to determine the target basic account data including the wrong attributes; the target basic account data is corrected according to the correction strategy to obtain the account data intermediate table set. For example, the non-zero balance data in the basic account data is obtained, and the interest rate, balance, repricing, repayment method and other attributes in the non-zero balance data are checked to see whether there are errors. The erroneous non-zero balance data is corrected according to the correction strategy. The account data intermediate table is generated based on the non-zero balance data with correct attributes and the corrected non-zero balance data, and the set of the account data intermediate tables is used as the account data intermediate table set. The account data intermediate table set includes all the corrected non-zero balance data and the non-zero balance data with correct attributes.

[0074] Among them, the anomaly determination rule is a rule for determining whether the attribute of the account detail data is wrong. The anomaly determination rule can be formulated by sorting out all the anomalies in the data. The correction strategy is a rule for correcting the abnormal data. The corresponding correction strategy can be formulated based on all the anomalies of the sorted data.

[0075] The wrong attributes of account details data are caused by various reasons in history. Bank data is usually massive data, and there are more or less attribute errors in the data of each bank. This requires finding and correcting the data with wrong attributes before calculation and processing. For example, find the RMB agreement deposit details in the agreement deposit account details that are not equal to the PBOC benchmark interest rate corresponding to the data date, and correct the interest rate to the PBOC agreement deposit benchmark interest rate corresponding to the data date.

[0076] Since the basic account data may include data with zero balance and data with non-zero balance, the data with zero balance will not affect the net interest income and expenditure calculation results, so it does not need to be processed. For data with non-zero balance, there may be errors in the attributes such as interest rate, balance, term, repricing, repayment method, etc. Before calculation, it is necessary to find out the data with attribute errors and correct them to ensure the accuracy and completeness of the data before packaging.

[0077] Step 450: Perform a total-by-part verification on the stock balances of the corresponding account products in the intermediate table set of account data based on the daily account data of the general ledger, and adjust the intermediate table set of account data according to the total-by-part verification result.

[0078] Among them, the data day account data of the general ledger is the balance of each account data in the general ledger of each product of the bank on the data day. The data day can be understood as each natural day. The stock balance of the account products in the account data intermediate table can be understood as the stock balance of the detailed products of each account in the account data intermediate table. The total and sub-verification is the operation of using the actual balance of the product account of the general ledger to verify the detailed account balance of the corresponding account.

[0079] Specifically, the product inventory balance of each account is calculated based on the account data intermediate table set, and the product inventory balance and the actual balance of the corresponding product account on the data date of the general ledger are matched; if there is a balance difference, virtual account data is added in the account data intermediate table set according to the difference between the actual balance and the product inventory balance.

[0080] Exemplarily, the stock balance of each product account is calculated by summarizing the account details data in the intermediate table of account data. The actual balance of the corresponding product account on the general ledger data date is obtained, and the balance difference between the stock balance and the actual balance of the same product account is calculated. Determine whether the balance difference is zero. If the balance difference is zero, it is determined that the stock balance of each product account is equal to the actual balance of the corresponding product account on the general ledger data date, and the total score verification passes. If the balance difference is not zero, it is determined that there is a balance difference between the stock balance of each product account and the actual balance of the corresponding product account on the general ledger data date, and the actual balance of the corresponding account on the general ledger data date needs to be installed to balance the stock balance of each product account in the account details. Generally, the balance data is balanced by setting a virtual account in the account details. For example, the stock balance of product account A is 800,000, and the actual balance of the corresponding product account on the general ledger data date is 1 million, and there is a balance difference of 200,000. You can add a virtual account to the account details in the account data intermediate table set. The product account to which the virtual account belongs is product account A. The balance of the virtual account is 200,000, and the total score verification is completed.

[0081] Step 460: Packaging the intermediate account data corresponding to the adjusted account data intermediate table set to obtain a measurement inventory data table set.

[0082] Among them, the intermediate account data is the account detail data included in the intermediate table set of account data after the total score verification. Packaging the intermediate account data is an operation to package the data with high consistency of account attributes to ensure the timeliness of the execution of the measurement method.

[0083] For example, before performing the calculation, the stock data included in the adjusted account data intermediate table set is packaged. Packaging is mainly applicable to businesses with large data volumes and high consistency of account attributes, such as demand deposits, time deposits, personal loans, and discounts.

[0084] It should be noted that the embodiment of the present invention can divide the packaging mode into a fast mode and a normal mode according to the time urgency. The difference between the fast mode and the normal mode is whether the institutional dimension is ignored. It is understandable that the packaging mode can also be divided into other modes based on other actual situations, and is not limited to the two modes listed above.

[0085] Specifically, obtain the product type information of the intermediate account data corresponding to each adjusted account data intermediate table set; classify the intermediate account data according to the product type information, and compress the intermediate account data belonging to the same category into a data packet; generate a table set of estimated stock data according to the data packet. Assuming that the net interest is calculated at the head office and the first-level branches, and the fast mode is selected, the head office and the first-level branches will only run the calculation according to the major product categories, ignoring the institutional dimension. The advantage of this design is that it meets the requirements for calculating net interest income and expenditure in time emergencies.

[0086] Optionally, if the institutional dimension is considered, data packaging may include the following steps: obtaining the institutional information and product type information of the intermediate account data corresponding to each adjusted account data intermediate table set; classifying the intermediate account data according to the institutional information; classifying the intermediate account data belonging to the same institution according to the product type information of the next-level unit of the institution; compressing the intermediate account data of the same institution and the same product type into a data packet, and generating a set of inventory data tables based on the data packet. For example, assuming that net interest is calculated at the head office and the first-level branches, and the normal mode is selected, before the head office runs the net interest income and expenditure calculation, the system packages the data according to the major product categories of the first-level branches; before the first-level branches run the net interest income and expenditure calculation, the system packages the data according to the major product categories of the second-level branches under the branch. This embodiment takes the institutional dimension into consideration in data packaging, which can meet the packaging requirements of finer dimensions and is suitable for non-time-critical situations.

[0087] Step 470: simulate and generate a set of measured incremental data tables based on the set of measured stock data tables, and use the set of measured stock data tables and the set of measured incremental data tables as the basic data tables for calculation.

[0088] Specifically, each stock data corresponding to the measured stock data table set is split to generate incremental data; a measured incremental data table set is generated according to the incremental data, and the measured incremental data table set and the measured stock data table set are used as a measured basic data table set.

[0089] Furthermore, each piece of stock data corresponding to the measured stock data table set is split to generate incremental data, including: obtaining business structure information of each piece of stock data corresponding to the measured stock data table set; and simulating and generating corresponding incremental data based on the business structure information according to preset incremental rules.

[0090] Net interest income and expenditure requires not only the calculation of stock data but also incremental data. Incremental data is data for a future time period and needs to be predicted, that is, to formulate incremental rules for data in advance, and simulate a new data record based on the incremental rules according to the structural information of stock business data (for example, balance, term, repricing and currency, etc.), and then assign interest rate attributes to the data record to form complete incremental data for net interest income and expenditure calculation.

[0091] An embodiment of simulating deposit increments includes: extracting the business structure of stock data as the basis for splitting incremental data. Assume that the institution is subdivided into the first-level branch, the product is subdivided into the major product dimension, and the contract term is divided according to the standard term of the benchmark interest rate of deposits and loans. Based on the stock data and its business structure, the stock data is decomposed downward layer by layer according to the dimensions of institution, product, term, etc. based on the incremental rules, and the incremental measurement basic data is simulated and generated. For example, the current personal deposit is 1 million, and the measurement factor is a 3-month growth of 5%. It is predicted that the personal deposit will reach 1.05 million on a certain day in 3 months. It has increased by 50,000. According to the business structure of branches, sub-branches, personal current, personal fixed, public current, public fixed, two-year fixed or five-year fixed, the simulation generation parameters of the incremental data are comprehensively determined, and the 1.05 million personal deposit data are split according to the stock data, the measurement factor and the simulation generation parameters to obtain the incremental data.

[0092] Figure 5 A flow chart of data processing provided by an embodiment of the present invention. Figure 5 As shown, the data of external account data 1 to external account data n are obtained as basic data, and the account data basic table set is obtained according to the basic data. The data in the account data basic table set is checked and corrected to obtain the account data intermediate table set. The data in the account data intermediate table set is aggregated and calculated to obtain the stock balances of various detailed products. The external account data is obtained, and the above stock balances are verified with the actual balances of the corresponding product accounts on the general ledger data date. The account data intermediate table set is adjusted according to the verification results, and the adjusted data in the account data intermediate table set is packaged to obtain the measured stock data table set. The incremental generation rules are obtained, and the incremental data of the measured stock data table set is split according to the incremental generation rules to obtain the measured incremental data table set. The measured stock data table set and the measured incremental data table set constitute the measured basic data table set. It should be noted that the key point of the above process lies in the granularity of the measured data and the accuracy of the data information. The finer the granularity, the more accurate the data information, and the more accurate the measurement result. Under normal circumstances, the account data with the most detailed granularity is taken for measurement.

[0093] Step 480: Obtain a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters.

[0094] Step 490: Select a corresponding target algorithm model according to the product information in the calculation intermediate data table set, and calculate the net interest income and expenditure based on the calculation intermediate data table set through the target algorithm model.

[0095] Figure 6 The flowchart of a net interest income and expenditure calculation provided by the embodiment of the present invention. The entire net interest income and expenditure calculation process is quite complicated and cumbersome. The entire design needs to meet the requirements of completeness, flexibility, massive data, parallel computing, etc. The overall process mechanism designed by the embodiment of the present invention is as follows Figure 6 As shown. In terms of measurement precision, the most detailed account detail granularity is used as the calculation basis, which can facilitate the aggregation of various dimensions and meet the needs of completeness; in terms of flexibility, a large number of parameterized definitions and configuration methods are adopted to reduce repeated development and reduce the coupling between internal modules and algorithms; in big data processing, a distributed database for data warehouse applications is adopted to support distributed data storage and parallel computing, meeting the timeliness requirements for processing massive data.

[0096] like Figure 6As shown in the figure, the static parameter set is pre-configured in the system for performing the net interest income and expenditure calculation, and the static parameters in the static parameter set rarely change. If the static parameters need to be adjusted, the user can operate manually on the interface. Obtain the account detail data that matches the static parameters in the data from external account data 1 to external account data n as the basic data, and obtain the account data basic table set based on the basic data. Check and correct the data in the account data basic table set to obtain the account data intermediate table set. Summarize and calculate the data in the account data intermediate table set to obtain the stock balance of various detailed products. Obtain external account data, and perform a total and partial verification on the above stock balance and the actual balance of the corresponding product account on the general ledger data date. Adjust the account data intermediate table set according to the verification result, and package the adjusted data in the account data intermediate table set to obtain the calculated stock data table set. Obtain the incremental generation rule, and perform incremental data splitting processing on the calculated stock data table set according to the incremental generation rule to obtain the calculated incremental data table set. The calculated stock data table set and the calculated incremental data table set constitute the calculated basic data table set. Obtain external dynamic parameters, and use the obtained dynamic parameters to update the dynamic parameter set. Obtain manually input parameters as measurement operation parameters, and obtain the measurement parameter set based on the measurement operation parameters. Generate single measurement source data based on the measurement basic data table set, static parameter set, dynamic parameter set and measurement parameter set, and obtain the measurement intermediate data table set based on the single measurement source data. When calculating net interest income and expenditure, find the corresponding algorithm in the algorithm configuration table according to the product type of the measurement source data corresponding to the measurement intermediate data table set, and then pass the corresponding parameters to the algorithm to complete the measurement. Obtain the measurement result table set based on the measurement results. Generate the report result table set based on the data related to the report in the measurement result table set. Determine the log information that meets the preset conditions in the measurement process as the measurement tracking table data. Among them, the preset conditions are the conditions manually configured according to the measurement tracking requirements. Obtain the measurement tracking table set based on the measurement tracking table data. When a report viewing request from a front-end user is detected, obtain the report data from the report result table set and display it to the front-end user. If a request to view the calculation process is detected, the calculation tracking table data is obtained from the calculation tracking table set and displayed to the front-end user.

[0097] The net interest income and expenditure calculation process mechanism provided by the embodiment of the present invention can meet the needs of net interest income and expenditure calculation of many products of large and medium-sized commercial banks or financial institutions. The process mechanism designs and defines all important steps from initial data to results, and describes the key points of each step. Based on this, large and medium-sized banks and financial institutions can develop their own net interest income and expenditure calculation function modules, and can also develop general calculation products. The process mechanism takes into account the complexity of products and data of large and medium-sized banks or financial institutions, and also designs flexible configuration functions in each link, and retains extensibility, with strong adaptability. The process mechanism does not rely on specific technical implementation. In the actual implementation process, the appropriate technical platform and development tools can be freely selected according to their own situation, and the intermediate steps or calculation methods can be tailored according to the complexity of their own business and data, and it has strong versatility. The process mechanism does not rely on specific accounting standards, currencies, languages, etc., nor does it rely on specific front-end transaction system categories and quantities, and has good independence. This process mechanism has been implemented and deployed in the systems of large domestic banks. Technically, JAVA, Perl, SQL, GP database, Oracle database, data warehouse, etc. are used. Its correctness and usability have been verified, and it has a good demonstration effect.

[0098] The technical solution of this embodiment is to obtain a basic data table set for calculation by correcting the basic account data, checking the total and the total, packaging and splitting the incremental data, generating a single calculation source data based on the basic data table, the static parameter set, the dynamic parameter set and the calculation parameter set defined and configured, obtaining a calculation intermediate data table set based on the single calculation source data, and performing calculation based on the different product data in the calculation intermediate data table set by matching the corresponding algorithm from the algorithm configuration table to obtain the net interest income and expenditure calculation result. The embodiment of the present invention achieves maximum flexibility in a parameterized manner, realizes the storage and calculation of massive and fine-grained basic data with a distributed database, and realizes the separation of access and calculation in a sub-library and sub-platform manner, which effectively realizes the net interest income and expenditure calculation under massive data of large and medium-sized commercial banks as a whole, and meets the needs of the annual planning and budget preparation of the whole bank.

[0099] Figure 7 This is a structural block diagram of a financial data calculation device provided by an embodiment of the present invention. The device can execute the financial data calculation method described in any embodiment of the present invention, and solve the problem that the accuracy of the current net interest calculation method cannot meet the requirements of the bank's annual budget planning by executing the above calculation method. The device can be implemented by software and / or hardware and configured in a computer device. Figure 7 As shown, the device comprises:

[0100] The data processing module 710 is used to process the basic account data to obtain a calculation basic data table set;

[0101] A data table set generation module 720, configured to obtain a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters;

[0102] The data calculation module 730 is used to select a corresponding target algorithm model according to the product information in the calculation intermediate data table set, and calculate the net interest income and expenditure based on the calculation intermediate data table set through the target algorithm model.

[0103] The embodiment of the present invention provides a financial data calculation device, which calculates net interest income and expenditure data with the most fine-grained basic account data, facilitates the aggregation of data in various dimensions, and meets the requirements of completeness and accuracy; on the basis of calculating the net interest income and expenditure data with the basic account data, combined with a parameterized method, reduces the coupling between each internal virtual function module and the calculation algorithm, improves the flexibility and rationality of the net interest income and expenditure calculation method, and solves the problem that the current net interest calculation method cannot meet the needs of the bank's annual plan budget preparation.

[0104] Optionally, the device further comprises:

[0105] The basic account data acquisition module is used to obtain pre-configured static parameters before processing the basic account data to obtain the basic data table set for calculation, wherein the static parameters include institution information, indicator definition, subject, product information, currency, verification rules, coding information and comparison relationship;

[0106] The basic account data required for the calculation is obtained from the data warehouse according to the static parameters.

[0107] Optionally, the data processing module 710 is specifically used for:

[0108] The basic account data is corrected, the total score is verified, the data is packaged and the incremental data is split to obtain the processed account data, which is then used to form the basic data table set for calculation.

[0109] Optionally, the data processing module 710 includes:

[0110] The table set traversal submodule is used to traverse the account data basic table set to obtain the basic account data of each account;

[0111] A data correction submodule, used to correct abnormal account data with incorrect attributes in the basic account data to obtain an intermediate table set of account data;

[0112] A total score verification submodule, used to perform a total score verification on the stock balance of the corresponding subject products in the account data intermediate table set based on the data day subject data of the general ledger, and adjust the account data intermediate table set according to the total score verification result;

[0113] The data packaging submodule is used to package the intermediate account data corresponding to the adjusted account data intermediate table set to obtain the measurement stock data table set;

[0114] The incremental data generation submodule is used to simulate and generate a measurement incremental data table set based on the measurement stock data table set, and use the measurement stock data table set and the measurement incremental data table set as the measurement basic data table set.

[0115] Optionally, the data correction submodule is specifically used for:

[0116] Obtaining non-zero balance data in the basic account data;

[0117] Checking the attributes of each of the non-zero balance data based on anomaly determination rules to determine target basic account data including error attributes;

[0118] The target basic account data is modified according to the modification strategy to obtain an intermediate table set of account data.

[0119] Optionally, the total score check submodule is specifically used for:

[0120] Calculate the product inventory balance of each account based on the account data intermediate table set, and match the product inventory balance with the actual balance of the corresponding product account on the data date of the general ledger;

[0121] If there is a balance difference, virtual account data is added to the account data intermediate table set according to the difference between the actual balance and the product inventory balance.

[0122] Optionally, the data packaging submodule is specifically used for:

[0123] Obtain product type information of the intermediate account data corresponding to each adjusted account data intermediate table set;

[0124] Classifying the intermediate account data according to the product type information of the next level unit of the institution, and compressing the intermediate account data belonging to the same category into one data packet;

[0125] A set of inventory measurement data tables is generated based on the data packet.

[0126] Optionally, the data packaging submodule is further specifically used for:

[0127] Obtain the institution information and product type information of the intermediate account data corresponding to each adjusted account data intermediate table set;

[0128] classifying the intermediate account data according to the institution information;

[0129] Classifying the intermediate account data belonging to the same institution according to the product type information of the next level unit of the institution;

[0130] The intermediate account data of the same institution and the same product type are compressed into a data package, and a set of inventory measurement data tables are generated based on the data package.

[0131] Optionally, the incremental data generation submodule is specifically used for:

[0132] Splitting each stock data corresponding to the measured stock data table set to generate incremental data;

[0133] A calculation incremental data table set is generated according to the incremental data, and the calculation incremental data table set and the calculation stock data table set are used as a calculation basic data table set.

[0134] Optionally, the incremental data generation submodule is further specifically used for:

[0135] Obtaining business structure information of each piece of stock data corresponding to the measured stock data table set;

[0136] The corresponding incremental data is simulated and generated based on the business structure information according to preset incremental rules.

[0137] Optionally, the data table set generating module 720 is specifically used for:

[0138] Acquiring measurement parameters, wherein the measurement parameters include static parameters, dynamic parameters and measurement operation parameters;

[0139] The source data required for a single calculation in the calculation basic data table set is determined according to the calculation parameters, and the calculation intermediate data table set is generated according to the source data.

[0140] Optionally, the data calculation module 730 is specifically used for:

[0141] Traversing the account data in the calculation intermediate data table set, and determining the product type corresponding to each account data according to the product type information included in the account data;

[0142] Based on the product type, an algorithm configuration table is queried to obtain a target algorithm model corresponding to the product type, wherein the algorithm configuration table stores product types and algorithm models in an associated manner;

[0143] The account data in the calculation intermediate data table set is transferred into the target algorithm model, and the net interest income and expenditure calculation result is determined by the target algorithm model.

[0144] The financial data calculation device provided in the embodiment of the present invention can execute the financial data calculation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0145] Figure 8 The following is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. For example, the computer device may be each server in a server cluster. Figure 8 As shown, the computer device includes a processor 80, a memory 81, an input device 82 and an output device 83; the number of processors 80 in the computer device can be one or more. Figure 8 A processor 80 is taken as an example; the processor 80, memory 81, input device 82 and output device 83 in the computer device can be connected by a bus or other means. Figure 8 The example of connecting through bus is taken in the following.

[0146] The memory 81, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the financial data calculation method in the embodiment of the present invention (for example, the data processing module 710, the data table set generation module 720 and the data calculation module 730). The processor 80 executes various functional applications and data processing of the computer device by running the software programs, instructions and modules stored in the memory 81, that is, realizes the above-mentioned financial data calculation method.

[0147] The memory 81 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 81 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 81 may further include a memory remotely arranged relative to the processor 80, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0148] The input device 82 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the computer device. The output device 83 may include display devices such as a display screen.

[0149] An embodiment of the present invention further provides a storage medium comprising computer executable instructions, wherein the computer executable instructions are used to execute a method for calculating financial data when executed by a computer processor, the method comprising:

[0150] Process the basic account data to obtain the basic data table set for calculation;

[0151] Obtaining a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters;

[0152] A corresponding target algorithm model is selected according to the product information in the calculation intermediate data table set, and the net interest income and expenditure is calculated based on the calculation intermediate data table set by the target algorithm model.

[0153] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present invention is not limited to the method operations described above, and can also execute related operations in the financial data calculation method provided in any embodiment of the present invention.

[0154] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0155] It is worth noting that in the embodiment of the above-mentioned financial data calculation device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0156] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for calculating financial data, characterized in that: include: Process the basic account data to obtain the basic data table set for calculation; Obtaining a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters; Selecting a corresponding target algorithm model according to the product information in the intermediate data table set, and calculating net interest income and expenditure based on the intermediate data table set by using the target algorithm model; The basic account data is processed to obtain a basic data table set for calculation, including: The basic account data is corrected, checked for total and total scores, packaged, and split into incremental data to obtain processed account data, and the calculation basic data table set is formed by the processed account data; The correction processing, total score verification processing, packaging processing and incremental data splitting processing of the basic account data include: Traversing the account data basic table set to obtain the basic account data of each account; Correcting abnormal account data with incorrect attributes in the basic account data to obtain an intermediate table set of account data; Based on the daily account data of the general ledger, the total and specific balances of the corresponding account products in the intermediate table set of the account data are verified, and the intermediate table set of the account data is adjusted according to the total and specific verification results; Packaging the intermediate account data corresponding to the adjusted account data intermediate table set to obtain a measurement stock data table set; A calculation increment data table set is generated by simulating the calculation stock data table set, and the calculation stock data table set and the calculation increment data table set are used as the calculation basic data table set.

2. The method according to claim 1, characterized in that: Before processing the basic account data to obtain the basic data table set for calculation, it also includes: Obtain pre-configured static parameters, where the static parameters include institution information, indicator definition, subject, product information, currency, verification rules, coding information and comparison relationship; The basic account data required for the calculation is obtained from the data warehouse according to the static parameters.

3. The method according to claim 1, characterized in that The correction of abnormal account data with incorrect attributes in the basic account data to obtain an intermediate table set of account data includes: Obtaining non-zero balance data in the basic account data; Checking the attributes of each of the non-zero balance data based on anomaly determination rules to determine target basic account data including error attributes; The target basic account data is modified according to the modification strategy to obtain an intermediate table set of account data.

4. The method according to claim 1, characterized in that The method of performing a total-to-score check on the stock balances of the corresponding subject products in the intermediate table set of the account data based on the daily subject data of the general ledger, and adjusting the intermediate table set of the account data according to the total-to-score check result, includes: Calculate the product inventory balance of each account based on the account data intermediate table set, and match the product inventory balance with the actual balance of the corresponding product account on the data date of the general ledger; If there is a balance difference, virtual account data is added to the account data intermediate table set according to the difference between the actual balance and the product inventory balance.

5. The method according to claim 1, characterized in that: The intermediate account data corresponding to the adjusted account data intermediate table set is packaged to obtain the measured stock data table set, including: Obtain product type information of the intermediate account data corresponding to each adjusted account data intermediate table set; Classifying the intermediate account data according to the product type information, and compressing the intermediate account data belonging to the same category into one data packet; A set of inventory measurement data tables is generated based on the data packet.

6. The method according to claim 1, characterized in that The intermediate account data corresponding to the adjusted account data intermediate table set is packaged to obtain the measured stock data table set, including: Obtain the institution information and product type information of the intermediate account data corresponding to each adjusted account data intermediate table set; classifying the intermediate account data according to the institution information; Classifying the intermediate account data belonging to the same institution according to the product type information of the next level unit of the institution; The intermediate account data of the same institution and the same product type are compressed into a data package, and a set of inventory measurement data tables are generated based on the data package.

7. The method according to claim 1, characterized in that The step of simulating and generating a measurement increment data table set according to the measurement stock data table set, and using the measurement stock data table set and the measurement increment data table set as a measurement basic data table set, includes: Splitting each stock data corresponding to the measured stock data table set to generate incremental data; A calculation incremental data table set is generated according to the incremental data, and the calculation incremental data table set and the calculation stock data table set are used as a calculation basic data table set.

8. The method according to claim 7, characterized in that The step of splitting each piece of stock data corresponding to the measured stock data table set to generate incremental data includes: Obtaining business structure information of each piece of stock data corresponding to the measured stock data table set; The corresponding incremental data is simulated and generated based on the business structure information according to preset incremental rules.

9. The method according to claim 1, characterized in that: The step of obtaining a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters includes: Acquiring measurement parameters, wherein the measurement parameters include static parameters, dynamic parameters and measurement operation parameters; The source data required for a single calculation in the calculation basic data table set is determined according to the calculation parameters, and the calculation intermediate data table set is generated according to the source data.

10. The method according to claim 1, characterized in that The selecting a corresponding target algorithm model according to the product information in the intermediate data table set, and calculating net interest income and expenditure based on the intermediate data table set by the target algorithm model, includes: Traversing the account data in the calculation intermediate data table set, and determining the product type corresponding to each account data according to the product type information included in the account data; Based on the product type, an algorithm configuration table is queried to obtain a target algorithm model corresponding to the product type, wherein the algorithm configuration table stores product types and algorithm models in an associated manner; The account data in the calculation intermediate data table set is transferred into the target algorithm model, and the net interest income and expenditure calculation result is determined by the target algorithm model.

11. A financial data calculation device, characterized in that: include: The data processing module is used to process the basic account data to obtain the basic data table set for calculation; A data table set generation module, used to obtain a calculation intermediate data table set according to the calculation basic data table set and the configured calculation parameters; A data calculation module, used to select a corresponding target algorithm model according to the product information in the calculation intermediate data table set, and calculate the net interest income and expenditure based on the calculation intermediate data table set through the target algorithm model; The data processing module is specifically used to perform correction processing, total score verification processing, packaging processing and incremental data splitting processing on the basic account data to obtain processed account data, and the calculation basic data table set is formed by the processed account data; Wherein, the data processing module includes: A table set traversal submodule, used to traverse the account data basic table set to obtain the basic account data of each account; A data correction submodule, used to correct abnormal account data with incorrect attributes in the basic account data to obtain an intermediate table set of account data; A total score verification submodule is used to perform a total score verification on the stock balance of the corresponding subject products in the account data intermediate table set based on the data day subject data of the general ledger, and adjust the account data intermediate table set according to the total score verification result; A data packaging submodule, used for packaging the intermediate account data corresponding to the adjusted account data intermediate table set to obtain a measurement stock data table set; The incremental data generation submodule is used to simulate and generate a measurement incremental data table set based on the measurement stock data table set, and use the measurement stock data table set and the measurement incremental data table set as the measurement basic data table set.

12. A computer device, characterized in that: The computer device comprises: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the financial data calculation method as described in any one of claims 1-10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for calculating financial data as described in any one of claims 1 to 10 is implemented.

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