Financial file generation method and device, equipment and storage medium

Abstract

The invention discloses a financial file generation method and device, equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: in a predetermined business scene, determining a corresponding financial product and a configuration parameter of a preset data generation model, determining initial financial data by using the financial product and a preset data generation model configured based on the configuration parameters, and recording the initial financial data to a plurality of preset data storage tables; determining an initial financial file having a preset association relationship with the business scene in the channel end file, and determining a target data storage table in a plurality of preset data storage tables based on the initial financial file; and determining a corresponding relationship between the initial financial file and the target data storage table, and determining target financial data in the plurality of data storage tables based on the corresponding relationship and the initial financial data, so as to determine a target financial file based on the target financial data and the initial financial file. Therefore, the method can enable the loan system to generate the financial file.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a financial document generation method, device, equipment and storage medium. Background Art

[0002] Under the current demand for financial business expansion, in order to expand the loan balance and introduce online channel access methods, it is necessary to receive financial documents input from other channels for accounting. However, many problems are exposed in this process.

[0003] The key to the loan system lies in the generation of repayment plans, interest and fee calculations, and repayment allocation, but the core content of different channels is different, such as the impact of early repayment on the repayment plan and the different concepts of grace period. This directly leads to differences in the data models of each channel, and in the docking process, data incompatibility and calculation result deviations are prone to occur, which seriously hinders the smooth advancement of the business.

[0004] Therefore, how the loan system generates financial documents that match the information on the channel side is a technical problem that needs to be solved urgently. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a financial document generation method, device, equipment and storage medium, so that the loan system can generate financial documents that match the channel end information. The specific scheme is as follows:

[0006] In a first aspect, the present application provides a financial document generation method, which is applied to a loan system, comprising:

[0007] Under a predetermined business scenario, determine the configuration parameters of a corresponding financial product and a preset data generation model, determine initial financial data using the financial product and the preset data generation model configured based on the configuration parameters, and record the initial financial data into a number of preset data storage tables;

[0008] Determine an initial financial file having a preset association relationship with the business scenario in the channel-side file, and determine a target data storage table in the plurality of preset data storage tables based on the initial financial file; wherein the initial financial file contains no financial data;

[0009] A correspondence between the initial financial file and the target data storage table is determined, and target financial data in the plurality of data storage tables is determined based on the correspondence and the initial financial data, so as to determine a target financial file based on the target financial data and the initial financial file.

[0010] Optionally, determining the configuration parameters of the corresponding financial product and the preset data generation model under the predetermined business scenario includes:

[0011] Determine the business scenario based on the channel information and the local system scenario to complete the scenario determination operation;

[0012] Configuration parameters of a corresponding preset data generation model are determined based on the business scenario, and corresponding financial products are determined based on the business scenario.

[0013] Optionally, determining a target data storage table among the plurality of preset data storage tables based on the initial financial document includes:

[0014] Analyze the storage structure, table item information, and data association relationship of the plurality of preset data storage tables to obtain a first analysis result;

[0015] Analyzing identification information, field attributes, and relationships between fields of the initial financial document to obtain a second analysis result;

[0016] Determine a mapping relationship between an initial financial file and a preset data storage table based on the first analysis result and the second analysis result;

[0017] The target data storage table is determined in the plurality of preset data storage tables by utilizing the mapping relationship.

[0018] Optionally, the determining the correspondence between the initial financial file and the target data storage table includes:

[0019] A correspondence between the initial financial document and the initial financial data is determined based on the first analysis result and the second analysis result.

[0020] Optionally, determining the target financial data in the plurality of data storage tables based on the corresponding relationship and the initial financial data includes:

[0021] If there is a corresponding relationship satisfying the preset relationship mismatch condition among the corresponding relationships, determining the corresponding relationship satisfying the preset relationship mismatch condition as the target corresponding relationship;

[0022] Based on the first analysis result and the second analysis result, modify the financial data in the target data storage table that has the target corresponding relationship to obtain modified financial data;

[0023] The target financial data in the plurality of data storage tables is determined using the modified financial data and the initial financial data.

[0024] Optionally, determining the target financial data in the plurality of data storage tables based on the corresponding relationship and the initial financial data includes:

[0025] If there is a corresponding relationship among the corresponding relationships that satisfies the preset relationship matching condition, the corresponding relationship that satisfies the preset relationship matching condition is determined as the target corresponding relationship;

[0026] The target financial data in the plurality of data storage tables are determined based on the target correspondence relationship and the initial financial data.

[0027] Optionally, the determining of the target financial document based on the target financial data and the initial financial document includes:

[0028] Extracting the target financial data from the plurality of preset data storage tables based on preset data query rules to complete a data extraction operation;

[0029] The target financial data is recorded into the initial financial file based on a preset data filling rule to obtain a target financial file.

[0030] In a second aspect, the present application provides a financial document generation device, which is applied to a loan system, comprising:

[0031] A data generation module, used to determine the configuration parameters of the corresponding financial product and the preset data generation model under a predetermined business scenario, and determine initial financial data using the financial product and the preset data generation model configured based on the configuration parameters, and record the initial financial data into a plurality of preset data storage tables;

[0032] A storage table determination module is used to determine an initial financial file having a preset association relationship with the business scenario in the channel-side file, and determine a target data storage table in the plurality of preset data storage tables based on the initial financial file; wherein the initial financial file does not contain financial data;

[0033] The file generation module is used to determine the correspondence between the initial financial file and the target data storage table, and determine the target financial data in the plurality of data storage tables based on the correspondence and the initial financial data, so as to determine the target financial file based on the target financial data and the initial financial file.

[0034] In a third aspect, the present application provides an electronic device, including:

[0035] Memory, used to store computer programs;

[0036] A processor is used to execute the computer program to implement the aforementioned financial document generation method.

[0037] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the aforementioned financial document generation method is implemented.

[0038] In the present application, the loan system determines the configuration parameters of the corresponding financial product and the preset data generation model under a predetermined business scenario, and determines the initial financial data using the financial product and the preset data generation model configured based on the configuration parameters, and records the initial financial data to a number of preset data storage tables; determines an initial financial file that has a preset association relationship with the business scenario in the channel-side file, and determines a target data storage table in the number of preset data storage tables based on the initial financial file; wherein, there is no financial data in the initial financial file; determines the correspondence between the initial financial file and the target data storage table, and determines the target financial data in the number of data storage tables based on the correspondence and the initial financial data, so as to determine the target financial file based on the target financial data and the initial financial file. As can be seen from the above, the loan system determines the configuration parameters of the corresponding financial products and preset data generation model under the predefined business scenario, uses the two to generate initial financial data, and records them in several preset data storage tables; finds the initial financial files related to the business scenario from the channel-side files, and determines the target data storage table in several preset data storage tables based on this; clarifies the correspondence between the initial financial files and the target data storage table, and determines the target financial data based on this and the initial financial data, and then generates the target financial file. In this way, this application can enable the loan system to generate financial files that match the channel-side information and improve the user experience to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0040] Figure 1 A flow chart of a method for generating financial documents disclosed in this application;

[0041] Figure 2 A schematic diagram of a financial data generation process disclosed in this application;

[0042] Figure 3 A schematic diagram of a data benchmarking process disclosed in this application;

[0043] Figure 4 A schematic diagram of a data filling process disclosed in this application;

[0044] Figure 5A flowchart of a specific financial document generation method disclosed in this application;

[0045] Figure 6 This is a schematic diagram of the structure of a financial document generating device disclosed in this application;

[0046] Figure 7 This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] At present, the key to the loan system lies in the generation of repayment plans, interest and fee calculations, and repayment allocation, but the core content of different channels is different, such as the impact of early repayment on the repayment plan and the different concepts of grace periods. This directly leads to differences in the data models of each channel, and in the docking process, data incompatibility and deviations in accounting results are prone to occur, which seriously hinders the smooth progress of the business. To this end, this application provides a financial document generation method, device, equipment, and storage medium, so that the loan system can generate financial documents that match the channel-side information.

[0049] See also Figure 1 , Figure 2 , Figure 3 as well as Figure 4 As shown, the embodiment of the present invention discloses a financial document generation method, which is applied to a loan system, comprising:

[0050] Step S11: Under a predetermined business scenario, determine the configuration parameters of the corresponding financial product and the preset data generation model, and use the financial product and the preset data generation model configured based on the configuration parameters to determine initial financial data, and record the initial financial data into several preset data storage tables.

[0051] In this embodiment, the channel-side information covers many aspects such as the business characteristics of the channel-side, data format requirements, and specific business rules. For example, different channels may have different regulations on repayment plans. Some channels may allow early repayment without changing the original repayment plan, while some channels will adjust the repayment plan according to the time and amount of early repayment. The local system scenario involves the business scope, data model, and historical business data of its own system. Therefore, it is necessary to determine the business scenario based on the channel-side information and the local system scenario to complete the scenario determination operation. That is, through in-depth analysis and integration of the channel-side information and the local system scenario, it is possible to accurately determine the corresponding business scenarios. For example, if the channel side is mainly aimed at short-term micro-loan business, and the overdue repayment processing is relatively strict, and the local system has certain historical data on short-term loan business, then by combining this information, it is possible to determine the business scenario focusing on the overdue processing of short-term micro-loans.

[0052] Furthermore, in this embodiment, after determining the business scenario, the configuration parameters of the corresponding preset data generation model are determined based on the business scenario. Specifically, the preset data generation model can generate financial data that meets specific business needs according to different configuration parameters, and the determination of the configuration parameters needs to be closely combined with the characteristics of the business scenario. For example, in a scenario involving loan interest calculation, the configuration parameters may include interest rate adjustment rules, interest calculation period, grace period settings, etc. Taking the interest rate and penalty interest rate after the principal expires as an example, according to the requirements of the business scenario, the interest rate after the principal expires may be set to 0, and the penalty interest rate may be set to 3 times the original value. Such a setting can make the generated data more in line with the actual business situation.

[0053] At the same time, the corresponding financial products are determined based on the business scenario. The selection of financial products depends on the business type and customer needs involved in the business scenario. In other words, it is necessary to select financial products that match the business scenario from the financial product system. For example, in the housing loan business scenario, the corresponding housing loan product will be selected, and the existing coding and entry models of the product will be used. These models are verified and optimized, and can provide a certain framework for subsequent data generation.

[0054] Step S12: determining an initial financial file having a preset association relationship with the business scenario in the channel-side file, and determining a target data storage table among the plurality of preset data storage tables based on the initial financial file; wherein the initial financial file contains no financial data.

[0055] In this embodiment, first, the storage structure, table item information and data association relationship of the several preset data storage tables are analyzed to obtain a first analysis result. Specifically, the analysis of the storage structure can understand how the data is organized in the table, such as whether it is stored by row or by column, and how the association relationship between different tables is established. At the same time, the table item information is analyzed in detail to clarify the specific meaning represented by each table item, such as whether a table item represents the loan amount or the repayment date. In addition, the data association relationship is analyzed to understand the transmission and dependency of data between different tables, such as how the data in the repayment plan table is related to the data in the interest calculation table. Through detailed analysis of these aspects, the first analysis result can be obtained.

[0056] At the same time, the identification information, field attributes, and relationships between fields of the initial financial document are analyzed to obtain a second analysis result. Specifically, identification information can help identify key information such as the type of file, the business scope to which it belongs, and the version. For example, the naming rules of files, specific identifiers in the file header, etc. all fall into the category of identification information. Next, analyze the field attributes, including the data type of the field, the length limit of the field, and the value range of the field. In addition, sort out the relationships between the fields to clarify how different fields interact and relate to each other, such as whether the value of a certain field will affect the calculation or value of other fields. Through this series of analysis, the second analysis result can be obtained.

[0057] After obtaining the first analysis result and the second analysis result, the mapping relationship between the initial financial file and the preset data storage table is determined based on the first analysis result and the second analysis result, that is, the specific location in the preset data storage table where the initial financial file should correspond is found out through the first analysis result and the second analysis result.

[0058] Furthermore, the mapping relationship is used to determine the target data storage table from among the plurality of preset data storage tables. In addition, it should be noted that the target data storage table is the source of the subsequent data extraction to fill the initial financial document. Through this process, it can be ensured that the generated financial document meets the requirements of the channel end and the actual needs of the business scenario.

[0059] Step S13: determine the correspondence between the initial financial file and the target data storage table, and determine the target financial data in the plurality of data storage tables based on the correspondence and the initial financial data, so as to determine the target financial file based on the target financial data and the initial financial file.

[0060] In this embodiment, the correspondence between the initial financial file and the initial financial data is determined based on the first analysis result and the second analysis result. For example, the "loan principal amount" field in the initial financial file will be searched for a corresponding table item recording the loan principal amount in the preset data storage table, which may involve the integration and association of related data in multiple tables to ensure that the most matching correspondence is found.

[0061] In the process of determining the corresponding relationship, in a specific implementation, if there is a corresponding relationship among the corresponding relationships that satisfies the preset relationship mismatch condition, the corresponding relationship that satisfies the preset relationship mismatch condition is determined as the target corresponding relationship. The preset relationship mismatch condition may include inconsistent data types, data value ranges beyond expectations, and field logical relationships that cannot be directly corresponded. When these mismatches are detected, the corresponding relationship that satisfies the preset relationship mismatch condition is determined as the target corresponding relationship.

[0062] For these target correspondences, the financial data in the target data storage table that has the target correspondences is modified based on the first analysis result and the second analysis result to obtain modified financial data. That is, based on the first analysis result and the second analysis result, the reasons for the mismatch and the inherent connection between the data are analyzed. For example, if the data type required by a field in the initial financial file is an integer, and the corresponding data in the target data storage table is a floating point number, it is necessary to perform type conversion on the data in the target data storage table and convert it to an integer type according to business rules and data accuracy requirements. Alternatively, if the value range of a certain data in the target data storage table does not meet the requirements of the initial financial file, it is necessary to correct the data according to preset adjustment rules. Through these operations, the modified financial data is obtained. After obtaining the modified financial data, the target financial data in the several data storage tables is determined using the modified financial data and the initial financial data.

[0063] In another specific implementation, if there is a corresponding relationship among the corresponding relationships that satisfies the preset relationship matching condition, the corresponding relationship that satisfies the preset relationship matching condition is determined as the target corresponding relationship. These matching corresponding relationships indicate that the structure and data logic of the relevant parts of the initial financial file and the target data storage table are consistent. Further, the target financial data in the plurality of data storage tables is determined based on the target corresponding relationship and the initial financial data.

[0064] After determining the target financial data, the target financial data is extracted from the plurality of preset data storage tables based on the preset data query rules to complete the data extraction operation. The preset data query rules may take into account the structure of the data storage table, data association relationships, and business requirements. For example, for some complex business scenarios, it may be necessary to extract the target financial data by means of a multi-table joint query. During the query process, it is necessary to accurately set the query conditions to ensure that the extracted data is both comprehensive and accurate. For example, when extracting target financial data related to a specific loan, it is necessary to filter out all corresponding data in multiple related data storage tables based on the unique identifier of the loan, including basic loan information, repayment records, interest calculation details, etc.

[0065] After the target financial data is extracted, the target financial data is recorded into the initial financial file based on the preset data filling rules to obtain the target financial file. The preset data filling rules specify in detail how to accurately fill the extracted target financial data into the corresponding position of the initial financial file. This includes the adjustment of the data format, the arrangement of the data sequence, and the verification of data integrity.

[0066] During the entire filling process, it is also necessary to consider possible abnormal situations, such as data volume mismatch, data conflict, etc. In response to these abnormal situations, corresponding processing mechanisms have been formulated to ensure the quality and accuracy of the generated target financial documents. For example, if it is found that the amount of filled data does not match the space reserved in the initial financial document, it is necessary to further check whether there are omissions or errors in the data extraction process and make corrections in a timely manner.

[0067] As can be seen from the above, the loan system determines the configuration parameters of the corresponding financial products and preset data generation model under the predefined business scenario, uses the two to generate initial financial data, and records them in several preset data storage tables; finds the initial financial files related to the business scenario from the channel-side files, and determines the target data storage table in several preset data storage tables based on this; clarifies the correspondence between the initial financial files and the target data storage table, and determines the target financial data based on this and the initial financial data, and then generates the target financial file. In this way, this application can enable the loan system to generate financial files that match the channel-side information and improve the user experience to a certain extent.

[0068] Combine the following Figure 5 The schematic diagram shown specifically illustrates the technical solution of the embodiment of the present application.

[0069] Specifically, it should be noted that the passive accounting file in the figure is the initial financial file, and the Actor is the person who initiates the operation of generating financial files. Based on the business scenario of loan-repayment, the corresponding financial products must be clarified first. In the product system of the loan system, determine the types of financial products related to loan and repayment that are suitable for this scenario, such as specific loan products and corresponding repayment modes. At the same time, fine-tune the configuration parameters of the preset data generation model. In view of the characteristics of the loan link, key parameters such as loan interest rate and loan period are set according to the requirements of the channel end and the business logic in the loan system to ensure that the data generated subsequently meets the actual business needs.

[0070] After completing the above operations, the model is generated using the determined financial products and the configured preset data to execute the loan operation in the loan system. At this point, the system generates detailed loan data, including information such as loan amount, loan time, and loan account, and accurately records these initial financial data in several preset data storage tables. These data storage tables store loan-related information from different dimensions, such as the loan information table records basic loan details, and the fund flow table records the specific flow of loan funds.

[0071] Next, the files sent from the channel end include loan flow files, repayment plan files, interest rate files, user files and other files related to loan. For these files, their identification information, field attributes and the relationship between fields are analyzed in detail. At the same time, the storage structure, table item information and data association relationship of several preset data storage tables are deeply analyzed. Through rigorous comparison, the mapping relationship between the initial financial file and the preset data storage table is determined. For example, the loan time field in the loan flow file is determined to correspond to the loan time table item of the loan information table in the preset data storage table in the loan system through analysis. Based on this mapping relationship, the target data storage table is accurately located in the preset data storage table to prepare for subsequent data extraction.

[0072] Based on the previously determined correspondence, relevant financial data is extracted from the target data storage table. For the loan flow file, key data such as loan amount, loan time, and loan account number are extracted from the corresponding data storage table, and these data are accurately filled into the loan flow file according to the preset data filling rules to generate a loan flow file that meets the requirements of the channel end. Similarly, the generation of related files such as repayment plan files, interest rate files, and user files is completed.

[0073] After completing the simulation generation of loan-related documents, enter the repayment scenario on the billing date. Although there is no completely consistent scenario in the loan system, it is simulated with the help of the active repayment function. Perform active repayment operations on the billing date, and the system generates repayment-related data, such as repayment amount, repayment time, repayment method, etc. At this time, for repayment-related files sent by the channel end, such as repayment flow, repayment plan and other files, determine the correspondence with the preset data storage table in the loan system, extract the target financial data and fill it into the corresponding file. The generated file is connected to the repayment connection code, and the verification of the scenario is successfully completed, ensuring the accuracy and completeness of the entire financial document generation process in complex business scenarios, and effectively meeting the connection requirements with the channel end.

[0074] Accordingly, see Figure 6 As shown, the embodiment of the present application provides a financial document generation device, which is applied to a loan system, including:

[0075] The data generation module 11 is used to determine the configuration parameters of the corresponding financial product and the preset data generation model under the predetermined business scenario, and determine the initial financial data by using the financial product and the preset data generation model configured based on the configuration parameters, and record the initial financial data into a plurality of preset data storage tables;

[0076] A storage table determination module 12 is used to determine an initial financial file having a preset association relationship with the business scenario in the channel-side file, and determine a target data storage table in the plurality of preset data storage tables based on the initial financial file; wherein the initial financial file does not contain financial data;

[0077] The file generation module 13 is used to determine the correspondence between the initial financial file and the target data storage table, and determine the target financial data in the plurality of data storage tables based on the correspondence and the initial financial data, so as to determine the target financial file based on the target financial data and the initial financial file.

[0078] As can be seen from the above, the loan system determines the configuration parameters of the corresponding financial products and preset data generation model under the predefined business scenario, uses the two to generate initial financial data, and records them in several preset data storage tables; finds the initial financial files related to the business scenario from the channel-side files, and determines the target data storage table in several preset data storage tables based on this; clarifies the correspondence between the initial financial files and the target data storage table, and determines the target financial data based on this and the initial financial data, and then generates the target financial file. In this way, this application can enable the loan system to generate financial files that match the channel-side information and improve the user experience to a certain extent.

[0079] In a specific implementation, the data generation module 11 specifically includes:

[0080] A scenario determination unit, used to determine a business scenario based on channel-side information and a local system scenario to complete a scenario determination operation;

[0081] The product determination unit is used to determine the configuration parameters of the corresponding preset data generation model based on the business scenario, and determine the corresponding financial product based on the business scenario.

[0082] In a specific implementation, the storage table determination module 12 specifically includes:

[0083] A first information analysis unit, configured to analyze the storage structure, table item information, and data association relationship of the plurality of preset data storage tables to obtain a first analysis result;

[0084] A second information analysis unit, configured to analyze identification information, field attributes, and relationships between fields of the initial financial document to obtain a second analysis result;

[0085] A first relationship determination unit, configured to determine a mapping relationship between an initial financial file and a preset data storage table based on the first analysis result and the second analysis result;

[0086] The storage table determining unit is used to determine a target data storage table from among the plurality of preset data storage tables by using the mapping relationship.

[0087] In a specific implementation, the file generation module 13 specifically includes:

[0088] A second relationship determining unit is configured to determine a corresponding relationship between the initial financial document and the initial financial data based on the first analysis result and the second analysis result.

[0089] In a specific implementation, the file generation module 13 specifically includes:

[0090] a third relationship determination unit, configured to determine the corresponding relationship satisfying the preset relationship mismatching condition as a target corresponding relationship if there is a corresponding relationship satisfying the preset relationship mismatching condition among the corresponding relationships;

[0091] A data modification unit, configured to modify the financial data in the target data storage table that has the target corresponding relationship based on the first analysis result and the second analysis result to obtain modified financial data;

[0092] The first data determination unit is configured to determine target financial data in the plurality of data storage tables by using the modified financial data and the initial financial data.

[0093] In a specific implementation, the file generation module 13 specifically includes:

[0094] a fourth relationship determination unit, configured to determine the corresponding relationship satisfying the preset relationship matching condition as a target corresponding relationship if there is a corresponding relationship satisfying the preset relationship matching condition among the corresponding relationships;

[0095] The second data determination unit is configured to determine target financial data in the plurality of data storage tables based on the target correspondence relationship and the initial financial data.

[0096] In a specific implementation, the file generation module 13 specifically includes:

[0097] A data extraction unit, configured to extract the target financial data from the plurality of preset data storage tables based on preset data query rules to complete a data extraction operation;

[0098] The file determining unit is used to record the target financial data into the initial financial file based on a preset data filling rule to obtain a target financial file.

[0099] Furthermore, the present application also discloses an electronic device. Figure 7 1 is a structural diagram of an electronic device 20 according to an exemplary embodiment, and the content in the diagram cannot be regarded as any limitation on the scope of use of this application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the financial document generation method disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0100] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0101] In addition, the memory 22 as a carrier for storing resources may be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon may include an operating system 221, a computer program 222, etc., and the storage method may be temporary storage or permanent storage.

[0102] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, and may be Windows Server, Netware, Unix, Linux, etc. In addition to computer programs that can be used to complete the financial document generation method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 may further include computer programs that can be used to complete other specific tasks.

[0103] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the financial document generation method disclosed above is implemented. The specific steps of the method can refer to the corresponding contents disclosed in the above embodiments, and will not be repeated here.

[0104] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0105] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0106] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0107] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0108] The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for generating an accounting file, characterized in that: Applied to loan systems, including: Under a predetermined business scenario, determine the configuration parameters of a corresponding financial product and a preset data generation model, determine initial financial data using the financial product and the preset data generation model configured based on the configuration parameters, and record the initial financial data into a number of preset data storage tables; Determine an initial financial file having a preset association relationship with the business scenario in the channel-side file, and determine a target data storage table in the plurality of preset data storage tables based on the initial financial file; wherein the initial financial file contains no financial data; A correspondence between the initial financial file and the target data storage table is determined, and target financial data in the plurality of data storage tables is determined based on the correspondence and the initial financial data, so as to determine a target financial file based on the target financial data and the initial financial file.

2. The financial document generation method according to claim 1, characterized in that: Determining the configuration parameters of the corresponding financial products and the preset data generation model under the predetermined business scenario includes: Determine the business scenario based on the channel information and the local system scenario to complete the scenario determination operation; Configuration parameters of a corresponding preset data generation model are determined based on the business scenario, and corresponding financial products are determined based on the business scenario.

3. The financial document generation method according to claim 1, characterized in that: The step of determining a target data storage table among the plurality of preset data storage tables based on the initial financial document comprises: Analyze the storage structure, table item information, and data association relationship of the plurality of preset data storage tables to obtain a first analysis result; Analyzing identification information, field attributes, and relationships between fields of the initial financial document to obtain a second analysis result; Determine a mapping relationship between an initial financial file and a preset data storage table based on the first analysis result and the second analysis result; The target data storage table is determined in the plurality of preset data storage tables by utilizing the mapping relationship.

4. The financial document generation method according to claim 3, characterized in that: Determining the correspondence between the initial financial file and the target data storage table includes: A correspondence between the initial financial document and the initial financial data is determined based on the first analysis result and the second analysis result.

5. The financial document generation method according to claim 3, characterized in that: The determining the target financial data in the plurality of data storage tables based on the corresponding relationship and the initial financial data includes: If there is a corresponding relationship satisfying the preset relationship mismatch condition among the corresponding relationships, determining the corresponding relationship satisfying the preset relationship mismatch condition as the target corresponding relationship; Based on the first analysis result and the second analysis result, modify the financial data in the target data storage table that has the target corresponding relationship to obtain modified financial data; The target financial data in the plurality of data storage tables is determined using the modified financial data and the initial financial data.

6. The financial document generation method according to claim 3, characterized in that: The determining the target financial data in the plurality of data storage tables based on the corresponding relationship and the initial financial data includes: If there is a corresponding relationship among the corresponding relationships that satisfies the preset relationship matching condition, the corresponding relationship that satisfies the preset relationship matching condition is determined as the target corresponding relationship; The target financial data in the plurality of data storage tables are determined based on the target correspondence relationship and the initial financial data.

7. The method for generating a financial document according to any one of claims 3 to 6, characterized in that: The determining of the target financial document based on the target financial data and the initial financial document comprises: Extracting the target financial data from the plurality of preset data storage tables based on preset data query rules to complete a data extraction operation; The target financial data is recorded into the initial financial file based on a preset data filling rule to obtain a target financial file.

8. A financial document generation device, characterized in that: Applied to loan systems, including: A data generation module, used to determine the configuration parameters of the corresponding financial product and the preset data generation model under a predetermined business scenario, and determine initial financial data using the financial product and the preset data generation model configured based on the configuration parameters, and record the initial financial data into a plurality of preset data storage tables; A storage table determination module is used to determine an initial financial file having a preset association relationship with the business scenario in the channel-side file, and determine a target data storage table in the plurality of preset data storage tables based on the initial financial file; wherein the initial financial file does not contain financial data; The file generation module is used to determine the correspondence between the initial financial file and the target data storage table, and determine the target financial data in the plurality of data storage tables based on the correspondence and the initial financial data, so as to determine the target financial file based on the target financial data and the initial financial file.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the financial document generation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program; wherein, when the computer program is executed by a processor, the financial document generation method according to any one of claims 1 to 7 is implemented.

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