Business financial data processing method and device
By processing business and financial data through a mapping rule base, generating standardized financial data, and building a traceability chain, the problems of fragmented business and financial data and low credibility are solved, achieving efficient data processing and in-depth analysis, and supporting compliant business operations.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 太保科技有限公司
- Filing Date
- 2026-01-06
- Publication Date
- 2026-04-10
AI Technical Summary
During the digital transformation of enterprises, the independent operation of business systems and financial systems leads to the fragmentation of business and financial data, low data conversion efficiency, susceptibility to human error, difficulty in meeting compliance requirements, lack of traceability mechanisms, single analytical dimensions, and inability to deeply explore profit value.
By acquiring raw business and financial data, processing the data using a pre-defined mapping rule base, generating standardized financial data, constructing a full-chain traceability chain, automatically generating compliant financial vouchers, and conducting multi-dimensional profit source analysis to generate visual reports.
It improves the efficiency of business and financial data processing, enables two-way traceability of financial and business data, enhances data credibility, and explores the value of financial data from multiple dimensions to provide business decision support for enterprises.
Smart Images
Figure CN121833804A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data processing technology, and in particular to a method and apparatus for processing business data. Background Technology
[0002] In the process of enterprise digital transformation, business systems and financial systems often operate independently, resulting in a serious disconnect between business and financial data.
[0003] In the traditional model, the conversion of business data into financial data mainly relies on manual entry and processing. This is not only inefficient but also prone to data errors due to human mistakes, significantly increasing financial processing costs and risks. Furthermore, existing data processing methods lack standardized mapping rules, making it difficult to strictly adhere to accounting standards and industry norms in the generation of financial vouchers. Moreover, with updates to accounting standards and changes in business operations, the rules lack flexibility in adjustment, failing to meet corporate compliance requirements.
[0004] Furthermore, in traditional business and financial data processing, the data flow chain is unclear and lacks an effective traceability mechanism. When faced with auditing or verification needs, it is difficult to achieve two-way traceability between financial data and original business data, making it difficult to guarantee data credibility. Moreover, existing systems offer only a single dimension of financial data analysis, only performing basic financial accounting functions, and are unable to deeply explore the profit value behind the data, thus failing to provide strong data support for enterprise business decisions.
[0005] In conclusion, improving the efficiency of business and financial data processing and the reliability of the processed business and financial data are problems that urgently need to be solved by those skilled in the art. Summary of the Invention
[0006] In view of this, this application provides a business and financial data processing method and apparatus, which aims to improve the efficiency of business and financial data processing and the reliability of the processed business and financial data.
[0007] Firstly, this application provides a method for processing business and financial data, including:
[0008] Obtain raw business and financial data;
[0009] Based on the corresponding rules in the preset mapping rule base, the original business and financial data are processed to obtain standardized financial data;
[0010] Based on the standardized financial data, compliant financial vouchers are automatically generated, and unique voucher numbers are assigned and associated with business identifiers (IDs).
[0011] Based on the original business and financial data, the transformation process data when processing the original business and financial data, and the correlation of the compliant financial vouchers, a full-chain traceability chain is constructed.
[0012] Based on the standardized financial data and the full-chain traceability chain, a multi-dimensional profit source analysis is performed to generate a visual report.
[0013] Optionally, the step of processing the original business and financial data according to the corresponding rules in the preset mapping rule base to obtain standardized financial data includes:
[0014] The original business data is preprocessed to obtain preprocessed original business data.
[0015] The corresponding rules in the mapping rule library are invoked to perform field matching, attribute transformation, journal entry logic operation and compliance verification on the preprocessed business and financial raw data to generate the standardized financial data.
[0016] Optionally, the step of preprocessing the original business data to obtain preprocessed original business data includes:
[0017] Duplicate, missing, and abnormal data are removed from the original business and financial data, and unstructured data is extracted into structure to obtain the preprocessed original business and financial data.
[0018] Optionally, before processing the raw financial data according to the corresponding rules in the preset mapping rule base to obtain standardized financial data, the method further includes:
[0019] Add, modify, or delete the corresponding rules in the mapping rule base to obtain the updated mapping rule base;
[0020] The process of processing the raw financial data according to the corresponding rules in the preset mapping rule base to obtain standardized financial data includes:
[0021] The original business and financial data are processed according to the corresponding rules in the updated mapping rule base to obtain the standardized financial data.
[0022] Secondly, this application provides a business data processing apparatus, comprising:
[0023] The acquisition module is used to acquire raw business and financial data;
[0024] The processing module is used to process the original financial data according to the corresponding rules in the preset mapping rule library to obtain standardized financial data.
[0025] The generation module is used to automatically generate compliant financial vouchers based on the standardized financial data, assign a unique voucher number, and associate it with a business identifier ID;
[0026] The module is used to construct a full-chain traceability chain based on the original business and financial data, the transformation process data when processing the original business and financial data, and the correlation of the compliant financial vouchers.
[0027] The analysis module is used to perform multi-dimensional profit source analysis based on the standardized financial data and the full-chain traceability chain, and generate a visual report.
[0028] Optionally, the processing module includes:
[0029] The preprocessing submodule is used to preprocess the original business data to obtain preprocessed original business data.
[0030] The processing submodule is used to call the corresponding rules in the mapping rule library to perform field matching, attribute transformation, journal entry logic operation and compliance verification on the preprocessed business and financial raw data to generate the standardized financial data.
[0031] Optionally, the preprocessing submodule is specifically used for:
[0032] Duplicate, missing, and abnormal data are removed from the original business and financial data, and unstructured data is extracted into structure to obtain the preprocessed original business and financial data.
[0033] Optionally, the device further includes:
[0034] The update module is used to add, modify, or delete corresponding rules in the mapping rule base to obtain the updated mapping rule base.
[0035] The processing module is specifically used for:
[0036] The original business and financial data are processed according to the corresponding rules in the updated mapping rule base to obtain the standardized financial data.
[0037] Thirdly, embodiments of this application provide a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the business data processing method as described in any of the embodiments of the first aspect of this application.
[0038] Fourthly, embodiments of this application provide a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform the business data processing method described in any of the embodiments of the first aspect of this application.
[0039] This application provides a method for processing business and financial data. When executing the method, raw business and financial data is first acquired. Then, according to the corresponding rules in a preset mapping rule base, the raw business and financial data is processed to obtain standardized financial data. Next, compliant financial vouchers are automatically generated based on the standardized financial data, assigned unique voucher numbers, and associated with business identifier IDs. Then, based on the raw business and financial data, the transformation process data during the processing of the raw business and financial data, and the association relationship of the compliant financial vouchers, a full-chain traceability chain is constructed. Finally, multi-dimensional profit source analysis is performed based on the standardized financial data and the full-chain traceability chain, generating a visual report. In this way, by automatically converting raw business and financial data into standardized financial data and generating compliant vouchers through mapping rules, the efficiency of business and financial data processing can be improved. By establishing a complete traceability mechanism, two-way traceability of financial data and business data can be achieved, meeting audit and verification needs, improving data credibility, and finally, multi-dimensional mining of the value of financial data provides data support for enterprises to identify profit growth points, optimize resource allocation, and formulate business decisions. Attached Figure Description
[0040] To more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings used in the description of the embodiment or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0041] Figure 1 A flowchart illustrating a business data processing method provided in this application embodiment;
[0042] Figure 2 This is a schematic diagram of the structure of a business data processing device provided in an embodiment of this application;
[0043] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation
[0044] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. This application provides a business data processing method and apparatus, relating to the field of data processing technology. The above are merely examples and do not limit the application field of the method and apparatus provided in this application.
[0045] In the process of enterprise digital transformation, business systems and financial systems often operate independently, resulting in a serious disconnect between business and financial data.
[0046] In the traditional model, the conversion of business data into financial data mainly relies on manual entry and processing. This is not only inefficient but also prone to data errors due to human mistakes, significantly increasing financial processing costs and risks. Furthermore, existing data processing methods lack standardized mapping rules, making it difficult to strictly adhere to accounting standards and industry norms in the generation of financial vouchers. Moreover, with updates to accounting standards and changes in business operations, the rules lack flexibility in adjustment, failing to meet corporate compliance requirements.
[0047] Furthermore, in traditional business and financial data processing, the data flow chain is unclear and lacks an effective traceability mechanism. When faced with auditing or verification needs, it is difficult to achieve two-way traceability between financial data and original business data, making it difficult to guarantee data credibility. Moreover, existing systems offer only a single dimension of financial data analysis, only performing basic financial accounting functions, and are unable to deeply explore the profit value behind the data, thus failing to provide strong data support for enterprise business decisions.
[0048] The inventors, through research, proposed the technical solution of this application. First, raw business and financial data is acquired. Then, according to corresponding rules in a pre-set mapping rule base, the raw business and financial data is processed to obtain standardized financial data. Next, compliant financial vouchers are automatically generated based on the standardized financial data, assigned unique voucher numbers, and associated with business identifiers. Then, based on the raw business and financial data, the transformation process data during the processing of the raw data, and the relationship between the compliant financial vouchers, a full-chain traceability chain is constructed. Finally, multi-dimensional profit source analysis is performed based on the standardized financial data and the full-chain traceability chain, generating a visual report. In this way, by automatically converting raw business and financial data into standardized financial data and generating compliant vouchers through mapping rules, the efficiency of business and financial data processing can be improved. By establishing a complete traceability mechanism, two-way traceability of financial data and business data can be achieved, meeting audit and verification needs, improving data credibility, and finally, multi-dimensional mining of the value of financial data provides data support for enterprises to identify profit growth points, optimize resource allocation, and formulate business decisions.
[0049] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all of them. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present application. It should be noted that, for ease of description, only the parts related to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of the present application can be combined with each other.
[0050] See Figure 1 , Figure 1A flowchart of a business data processing method provided in this application embodiment includes:
[0051] S101: Obtain raw business and financial data.
[0052] First, collect raw business and financial data from multiple business systems. This raw data includes, but is not limited to, transaction data, asset data, cost data, and revenue data, and the data formats cover structured data, semi-structured data, and unstructured data.
[0053] S102: Process the original business and financial data according to the corresponding rules in the preset mapping rule base to obtain standardized financial data.
[0054] The mapping rule library stores standardized accounting standard mapping rules, which include the correspondence between business data fields and financial accounts, measurement attribute conversion rules, accounting entry generation logic, and compliance verification rules. It supports custom configuration and dynamic updates of rules according to enterprise type, industry characteristics, and accounting standard version.
[0055] The system invokes rules from the mapping rule base to clean, match fields, transform attributes, and perform journal entry logic operations on the raw business and financial data, converting the business data into standardized financial data that conforms to accounting standards. The specific methods are as follows:
[0056] Data cleaning: Remove duplicate, missing, and abnormal data from the original business and financial data, and extract structured data from unstructured data;
[0057] Field matching: Based on the field correspondence in the mapping rule base, accurately match business data fields with financial account fields;
[0058] Attribute conversion: According to the measurement attribute conversion rules, the quantity, amount, unit price and other information in the business data are converted into numerical forms that meet the accounting measurement requirements;
[0059] Logical operations: Based on the accounting entry generation logic, automatically calculate the debit and credit amounts, determine the entry direction, and generate preliminary accounting entries;
[0060] Compliance verification: The preliminary accounting entries are verified for accuracy and compliance using compliance verification rules. If the verification fails, an error message is returned and the problematic data is marked.
[0061] When data mismatch, rule application anomalies, or validation failures occur during the logical transformation process, anomaly alarms are automatically triggered. The system supports anomaly data marking, manual intervention, and writing back the processing results. Anomaly handling records are included in the traceability chain.
[0062] Before implementing the method described in S102, automatic updates can be performed by connecting to the official accounting standards update interface to synchronize the latest standards requirements in real time; manual updates allow administrators to add, modify, and delete mapping rules through a visual interface, and updated rules must go through an approval process before they take effect.
[0063] S103: Automatically generate compliant financial vouchers based on standardized financial data, assign unique voucher numbers, and associate them with business identifier IDs.
[0064] Based on the standardized financial data after logical transformation, it automatically generates compliant financial vouchers that include voucher number, accounting subject, loan amount, summary, and business association number, and supports custom voucher format and multi-dimensional export.
[0065] S104: Construct a full-chain traceability chain based on the original business and financial data, the transformation process data when processing the original business and financial data, and the correlation of compliant financial vouchers.
[0066] Establish a full-chain traceability relationship for business and financial data, recording the association mapping of original business data, mapping rule application records, transformation process data, and financial vouchers. This supports tracing back to original business data through financial vouchers, or querying corresponding financial processing results forward from business data. Specifically, a unique business identifier ID is assigned to each piece of original business and financial data. A transformation process ID is generated during the logical transformation process, and the business identifier ID and transformation process ID are bound when financial vouchers are generated, forming a three-dimensional traceability chain of "business data - transformation process - financial voucher." It supports querying the traceability path through multiple dimensions such as voucher number, business identifier ID, time range, and business type, displaying data flow nodes, rule application details, and operator information.
[0067] S105: Conduct multi-dimensional profit source analysis based on standardized financial data and the entire traceability chain, and generate a visual report.
[0068] Based on standardized financial data and traceable related data, a profit source analysis model is constructed to realize analytical functions such as revenue composition analysis, cost allocation analysis, profit contribution analysis, business line profitability ranking, and customer / product profit source mining, and output visualized analysis reports.
[0069] In the embodiments provided in this application, raw business and financial data are first acquired. Then, according to the corresponding rules in the preset mapping rule base, the raw business and financial data are processed to obtain standardized financial data. Next, compliant financial vouchers are automatically generated based on the standardized financial data, assigned unique voucher numbers, and associated with business identifier IDs. Then, based on the raw business and financial data, the transformation process data during the processing of the raw business and financial data, and the association relationship of the compliant financial vouchers, a full-chain traceability chain is constructed. Finally, multi-dimensional profit source analysis is performed based on the standardized financial data and the full-chain traceability chain, generating a visual report. In this way, by automatically converting raw business and financial data into standardized financial data and generating compliant vouchers through mapping rules, the efficiency of business and financial data processing can be improved. By establishing a complete traceability mechanism, two-way traceability of financial data and business data can be achieved, meeting audit and verification needs, improving data credibility, and finally, multi-dimensional mining of the value of financial data provides data support for enterprises to identify profit growth points, optimize resource allocation, and formulate business decisions.
[0070] The above are some specific implementations of the business data processing method provided in the embodiments of this application. Based on this, this application also provides a corresponding apparatus. The apparatus provided in the embodiments of this application will be described below from the perspective of functional modularization.
[0071] See Figure 2 , Figure 2 This is a schematic diagram of the structure of a business data processing device 200 provided in an embodiment of this application. The business data processing device 200 includes:
[0072] Module 210 is used to acquire raw business and financial data;
[0073] The processing module 220 is used to process the original financial data according to the corresponding rules in the preset mapping rule library to obtain standardized financial data.
[0074] The generation module 230 is used to automatically generate compliant financial vouchers based on the standardized financial data, assign a unique voucher number, and associate it with a business identifier ID;
[0075] The construction module 240 is used to construct a full-chain traceability chain based on the original business and financial data, the transformation process data when processing the original business and financial data, and the correlation of the compliant financial vouchers.
[0076] Analysis module 250 is used to perform multi-dimensional profit source analysis based on the standardized financial data and the full-chain traceability chain, and generate a visual report.
[0077] Optionally, the processing module 220 includes:
[0078] The preprocessing submodule is used to preprocess the original business data to obtain preprocessed original business data.
[0079] The processing submodule is used to call the corresponding rules in the mapping rule library to perform field matching, attribute transformation, journal entry logic operation and compliance verification on the preprocessed business and financial raw data to generate the standardized financial data.
[0080] Optionally, the preprocessing submodule is specifically used for:
[0081] Duplicate, missing, and abnormal data are removed from the original business and financial data, and unstructured data is extracted into structure to obtain the preprocessed original business and financial data.
[0082] Optionally, the device 200 further includes:
[0083] The update module is used to add, modify, or delete corresponding rules in the mapping rule base to obtain the updated mapping rule base.
[0084] The processing module 220 is specifically used for:
[0085] The original business and financial data are processed according to the corresponding rules in the updated mapping rule base to obtain the standardized financial data.
[0086] This application also provides corresponding devices and computer storage media for implementing the solutions provided in this application.
[0087] like Figure 3 As shown, computer device 01 is represented in the form of a general-purpose computing device. The components of computer device 01 may include, but are not limited to: one or more processors or processor units 03, system memory 08, and bus 04 connecting different system components (including system memory 08 and processor unit 03).
[0088] Bus 04 represents one or more of several bus architectures, including memory buses or memory controllers, peripheral buses, graphics acceleration ports, processors, or local buses using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.
[0089] Computer device 01 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computer device 01, including volatile and non-volatile media, removable and non-removable media.
[0090] System memory 08 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 09 and / or cache memory 10. Computer device 01 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 11 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 3 Not shown; usually referred to as a "hard drive"). Although Figure 3 As not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 04 via one or more data media interfaces. System memory 08 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.
[0091] A program / utility 12 having a set (at least one) of program modules 13 may be stored, for example, in system memory 08. Such program modules 13 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 13 typically perform the functions and / or methods described in the embodiments of the present invention.
[0092] Computer device 01 can also communicate with one or more external devices 02 (e.g., keyboard, pointing device, display 07, etc.), and with one or more devices that enable a user to interact with the computer device 01, and / or with any device that enables the computer device 01 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed through input / output (I / O) interface 06. Furthermore, computer device 01 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) through network adapter 05. Figure 3 As shown, network adapter 05 communicates with other modules of computer device 01 via bus 04. It should be understood that, although... Figure 3 As not shown in the diagram, it can be used in conjunction with computer device 01 with other hardware and / or software modules, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.
[0093] The processor unit 03 executes various functional applications and data processing by running programs stored in the system memory 08, such as implementing a business data processing method provided in the embodiments of this application.
[0094] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0095] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that all or part of the steps in the methods of the above embodiments can be implemented by means of software plus a general-purpose hardware platform. Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as a read-only memory (ROM) / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network communication device such as a router) to execute the methods described in various embodiments or some parts of the embodiments of this application.
[0096] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.
[0097] The above description is merely an exemplary implementation of this application and is not intended to limit the scope of protection of this application.
Claims
1. A method for processing business and financial data, characterized in that, include: Obtain raw business and financial data; Based on the corresponding rules in the preset mapping rule base, the original business and financial data are processed to obtain standardized financial data; Based on the standardized financial data, compliant financial vouchers are automatically generated, and unique voucher numbers are assigned and associated with business identifiers (IDs). Based on the original business and financial data, the transformation process data when processing the original business and financial data, and the correlation of the compliant financial vouchers, a full-chain traceability chain is constructed. Based on the standardized financial data and the full-chain traceability chain, a multi-dimensional profit source analysis is performed to generate a visual report.
2. The method according to claim 1, characterized in that, The process of processing the raw financial data according to the corresponding rules in the preset mapping rule base to obtain standardized financial data includes: The original business data is preprocessed to obtain preprocessed original business data. The corresponding rules in the mapping rule library are invoked to perform field matching, attribute transformation, journal entry logic operation and compliance verification on the preprocessed business and financial raw data to generate the standardized financial data.
3. The method according to claim 2, characterized in that, The step of preprocessing the original business data to obtain preprocessed original business data includes: Duplicate, missing, and abnormal data are removed from the original business and financial data, and unstructured data is extracted into structure to obtain the preprocessed original business and financial data.
4. The method according to claim 1, characterized in that, Before processing the raw financial data according to the corresponding rules in the preset mapping rule base to obtain standardized financial data, the method further includes: Add, modify, or delete the corresponding rules in the mapping rule base to obtain the updated mapping rule base; The process of processing the raw financial data according to the corresponding rules in the preset mapping rule base to obtain standardized financial data includes: The original business and financial data are processed according to the corresponding rules in the updated mapping rule base to obtain the standardized financial data.
5. A business data processing device, characterized in that, include: The acquisition module is used to acquire raw business and financial data; The processing module is used to process the original financial data according to the corresponding rules in the preset mapping rule library to obtain standardized financial data. The generation module is used to automatically generate compliant financial vouchers based on the standardized financial data, assign a unique voucher number, and associate it with a business identifier ID; The module is used to construct a full-chain traceability chain based on the original business and financial data, the transformation process data when processing the original business and financial data, and the correlation of the compliant financial vouchers. The analysis module is used to perform multi-dimensional profit source analysis based on the standardized financial data and the full-chain traceability chain, and generate a visual report.
6. The apparatus according to claim 5, characterized in that, The processing module includes: The preprocessing submodule is used to preprocess the original business data to obtain preprocessed original business data. The processing submodule is used to call the corresponding rules in the mapping rule library to perform field matching, attribute transformation, journal entry logic operation and compliance verification on the preprocessed business and financial raw data to generate the standardized financial data.
7. The apparatus according to claim 6, characterized in that, The preprocessing submodule is specifically used for: Duplicate, missing, and abnormal data are removed from the original business and financial data, and unstructured data is extracted into structure to obtain the preprocessed original business and financial data.
8. The apparatus according to claim 5, characterized in that, The device further includes: The update module is used to add, modify, or delete corresponding rules in the mapping rule base to obtain the updated mapping rule base. The processing module is specifically used for: The original business and financial data are processed according to the corresponding rules in the updated mapping rule base to obtain the standardized financial data.
9. A computer device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the business data processing method as described in any one of claims 1-4.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the business data processing method as described in any one of claims 1-4.