Financial data processing method, device and equipment and storage medium thereof

Abstract

The embodiment of the invention belongs to the technical field of supply chain management, is applied to business and financial data processing scenes, and relates to a financial data processing method, device and equipment and a storage medium thereof. Adding a first distinguishing mark to data meeting the target adding requirement in the to-be-checked target data; performing template arrangement on all the to-be-checked target data added with the first distinguishing mark; identifying all data meeting the reimbursement requirements in the to-be-checked target data added with the first distinguishing marks, and performing second distinguishing marks; in combination with a preset bill generation template, respectively carrying out business bill generation on all the to-be-checked target data subjected to the second distinguishing marking; and distributing all the finally generated business bills to the corresponding receiving ends. The financial data processing method provided by the invention is applied to a supply chain system with complicated bill data, so that the business and financial data can be efficiently and comprehensively managed on the business and financial combination level.

Description

Technical Field

[0001] The present application relates to the field of supply chain management technology, and is applied to business and financial data processing scenarios, and in particular to a financial data processing method, apparatus, device, and storage medium thereof. Background Art

[0002] With the promotion of online procurement and the popularization of a series of online suppliers such as e-commerce malls, online business travel, and supplier-built malls, online procurement is increasing, the business types are increasing, and the format of supply and procurement bills is becoming more and more complicated, resulting in difficulties in the processing and management of supply chain business systems.

[0003] At present, as the format of supply and procurement bills becomes more and more complicated, supply chain management service providers need to design different data identification plug-ins for different supply and procurement bills, which increases the workload of supply chain management service providers. Moreover, the complicated supply and procurement bill formats and data identification plug-ins are not conducive to the efficient comprehensive management of supply chain management service providers at the business and financial level, and increase the difficulty of management at the business and financial level. Therefore, there is an urgent need for a financial data processing method to achieve efficient comprehensive management of complex supply chain business data and bill data at the business and financial level. Summary of the invention

[0004] The purpose of the embodiments of the present application is to propose a financial data processing method, device, equipment and storage medium thereof to achieve efficient and comprehensive management of complex supply chain business data and billing data at the business and financial levels.

[0005] In order to solve the above technical problems, the present application embodiment provides a financial data processing method, which adopts the following technical solutions:

[0006] A method for processing financial data comprises the following steps:

[0007] Acquire target data to be checked, wherein the target data includes bill data;

[0008] According to a preset mark adding strategy, a first distinguishing mark is added to the data in the target data to be checked that meets the target adding requirement;

[0009] According to a preset data sorting template, sort all the target data to be checked with the first distinguishing mark added thereto, and obtain template sorting results corresponding to all the first distinguishing mark data respectively;

[0010] According to a preset reimbursement identification strategy, extracting reimbursement determination fields corresponding to all first distinguishing mark data from all templated sorting results, wherein the reimbursement identification strategy is provided by the target financial management terminal;

[0011] Based on the reimbursement determination field, identifying all data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added thereto, and performing a second distinguishing mark;

[0012] Combined with the preset bill generation template, business bills are generated for all the target data to be checked that have been marked with the second distinction mark;

[0013] According to the preset distribution strategy, all business bills generated in the end are distributed to the corresponding receiving ends.

[0014] Furthermore, the step of obtaining the target data to be verified specifically includes:

[0015] According to the SOA integrated service architecture provided by the target verification business system, the target data to be verified is obtained from multiple source data terminals, wherein the SOA integrated service architecture supports SSO single point integration, interface integration, ETL data mart integration and Web service integration;

[0016] The step of obtaining target data to be verified from multiple data sources includes:

[0017] Combined with the Restful API call, the target data to be checked is obtained from multiple data sources in a synchronous manner, and

[0018] Utilize message queues to obtain target data to be verified from multiple data sources in an asynchronous manner.

[0019] Furthermore, the step of adding a first distinguishing mark to the data in the target data to be checked that meets the target adding requirement according to the preset mark adding strategy specifically includes:

[0020] Retrieving the supply and demand business record log from the business monitoring component of the target supply chain system to determine whether the generation of the target data to be checked complies with the preset business logic rules;

[0021] If the generation of the target data to be checked complies with the preset business logic rules, a confirmation mark, i.e., the first distinguishing mark, is added to the target data to be checked;

[0022] If the generation of the target data to be checked does not conform to the preset business logic rules, a prompt indicating that the target data to be checked is generated incorrectly is sent to the target monitoring terminal.

[0023] Furthermore, before executing the step of arranging all the target data to be checked with the first distinguishing mark added thereto according to the preset data arranging template to obtain the templated arranging results corresponding to all the first distinguishing mark data respectively, the method further includes:

[0024] According to all the supply and demand relationships involved in the target supply chain system, corresponding data sorting templates are created respectively, where different supply and demand relationships correspond to different data sorting templates;

[0025] Obtaining data sorting templates corresponding to all supply and demand relationships respectively as the preset data sorting template;

[0026] Deploy the preset data sorting template into a preset text content extraction model;

[0027] The preset text content extraction model is automatically trained using pre-constructed training samples to obtain a text content extraction model that has completed automatic extraction training, wherein the training samples include target data to be verified that are simulated and generated based on all the supply and demand relationships.

[0028] Furthermore, the step of arranging all the target data to be checked with the first distinguishing mark added thereto according to the preset data arranging template to obtain the templated arranging results corresponding to all the first distinguishing mark data respectively comprises:

[0029] Inputting all the target data to be checked with the first distinguishing mark added thereto into the text content extraction model trained by the automatic extraction;

[0030] By using the text content recognition component in the text content extraction model, the data sorting templates corresponding to all the target data to be checked to which the first distinguishing mark is added are respectively identified;

[0031] Extracting text content from all the target data to be checked to which the first distinguishing mark is added by the text content extraction component in the text content extraction model, and filling the text content extraction result into the corresponding data sorting template;

[0032] The templated sorting results corresponding to all the first distinguishing mark data output by the text content extraction model are obtained.

[0033] Further, the preset reimbursement identification strategy includes a first identification strategy, a second identification strategy, a third identification strategy and a fourth identification strategy, and the reimbursement determination field includes a first determination field, a second determination field, a third determination field and a fourth determination field. Before executing the step of extracting the reimbursement determination fields corresponding to all the first distinguishing mark data from all the templated sorting results according to the preset reimbursement identification strategy, the method further includes:

[0034] Generate an automated determination model according to the first identification strategy, the second identification strategy, the third identification strategy and the fourth identification strategy, wherein the first identification strategy specifies a first determination field, and is used to identify whether the corresponding first distinguishing mark data conforms to the proposed business budget range according to the first determination field, the second identification strategy specifies a second determination field, and is used to identify whether the corresponding first distinguishing mark data conforms to the proposed fee usage standard according to the second determination field, the third identification strategy specifies a third determination field, and is used to identify whether the corresponding first distinguishing mark data conforms to the statutory business scope according to the third determination field, and the fourth identification strategy specifies a fourth determination field, and is used to identify whether the corresponding first distinguishing mark data conforms to the statutory reimbursement business type according to the fourth determination field;

[0035] The step of extracting the reimbursement determination fields corresponding to all the first distinguishing mark data from all the templated sorting results according to the preset reimbursement identification strategy specifically includes:

[0036] According to the first recognition strategy, first determination fields of all first distinguishing mark data are respectively extracted from all templated sorting results;

[0037] According to the second recognition strategy, second determination fields of all first distinguishing mark data are respectively extracted from all templated sorting results;

[0038] According to the third recognition strategy, extracting the third determination fields of all first distinguishing mark data from all templated sorting results respectively;

[0039] According to the fourth recognition strategy, the fourth determination fields of all first distinguishing mark data are respectively extracted from all templated sorting results.

[0040] Furthermore, the step of identifying all data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added thereto based on the reimbursement determination field and performing the second distinguishing mark specifically includes:

[0041] inputting the reimbursement decision fields into the automated decision model;

[0042] Identify whether the target data to be checked, to which the first distinguishing mark is currently added, meets the proposed business budget range according to the first identification strategy and the first determination field in the reimbursement determination field;

[0043] Identify whether the target data to be checked, to which the first distinguishing mark is currently added, meets the proposed expense usage standard according to the second identification strategy and the second determination field in the reimbursement determination field;

[0044] Identify whether the target data to be checked, to which the first distinguishing mark is currently added, complies with the legal business scope according to the third identification strategy and the third determination field in the reimbursement determination field;

[0045] Identify whether the target data to be checked, to which the first distinguishing mark is currently added, complies with the statutory reimbursement business type according to the fourth identification strategy and the fourth determination field in the reimbursement determination field;

[0046] If the target data to be checked that is currently added with the first distinguishing mark meets the proposed business budget scope, the proposed expense usage standards, the statutory business scope and the statutory reimbursement business type, a second distinguishing mark will be added to it. Otherwise, a prompt message that reimbursement will not be made will be sent to the target data source.

[0047] In order to solve the above technical problems, the embodiment of the present application also provides a financial data processing device, which adopts the following technical solution:

[0048] A financial data processing device, comprising:

[0049] A target data acquisition module, used to acquire target data to be checked, wherein the target data includes bill data;

[0050] A first distinguishing mark adding module, used for adding a first distinguishing mark to the data that meets the target adding requirement in the target data to be checked according to a preset mark adding strategy;

[0051] A templated sorting module, used to sort all the target data to be checked with the first distinguishing mark added thereto according to a preset data sorting template, and obtain the templated sorting results corresponding to all the first distinguishing mark data respectively;

[0052] A reimbursement determination field extraction module, used to extract the reimbursement determination fields corresponding to all the first distinguishing mark data from all the templated sorting results according to a preset reimbursement identification strategy, wherein the reimbursement identification strategy is provided by the target financial management terminal;

[0053] A second distinguishing mark module is used to identify all data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added thereto based on the reimbursement determination field, and perform a second distinguishing mark;

[0054] A business bill generation module, used to generate business bills for all target data to be checked that have been marked with the second distinguishing mark, in combination with a preset bill generation template;

[0055] The business bill distribution module is used to distribute all the business bills finally generated to the corresponding receiving ends according to the preset distribution strategy.

[0056] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0057] A computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the above-mentioned financial data processing method when executing the computer-readable instructions.

[0058] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0059] A computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the financial data processing method as described above.

[0060] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0061] The financial data processing method described in the embodiment of the present application is to obtain the target data to be checked; add a first distinguishing mark to the data in the target data to be checked that meets the target adding requirements; template-organize all the target data to be checked with the first distinguishing mark added; identify all the data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added, and perform a second distinguishing mark; combine the preset bill generation template to generate business bills for all the target data to be checked that have been marked with the second distinguishing mark; distribute all the business bills finally generated to the corresponding receiving end. The financial data processing method described in the present application is applied to the supply chain business system with complex billing data and many subsystems involved, so that the management service department can conduct efficient and comprehensive management of complex supply chain business data and billing data at the business and financial level. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0063] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0064] Figure 2 is a flow chart of an embodiment of a financial data processing method according to the present application;

[0065] Figure 3 yes Figure 2 A flowchart of a specific embodiment of step 202 is shown;

[0066] Figure 4 It is a flowchart of a specific embodiment of the automated processing training before template sorting in the financial data processing method described in the present application;

[0067] Figure 5 yes Figure 2 A flowchart of a specific embodiment of step 203 is shown;

[0068] Figure 6 yes Figure 2 A flowchart of a specific embodiment of step 206 is shown;

[0069] Figure 7 is a schematic diagram of the structure of an embodiment of a financial data processing device according to the present application;

[0070] Figure 8 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0071] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0072] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0073] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0074] like Figure 1As shown, the system architecture 100 may include a terminal device 101, a network 102 and a server 103. The terminal device 101 may be a laptop 1011, a tablet computer 1012 or a mobile phone 1013. The network 102 is used to provide a medium for a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables.

[0075] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0076] The terminal device 101 can be any electronic device with a display screen and supporting web browsing. In addition to a laptop computer 1011, a tablet computer 1012 or a mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV), a laptop computer, a desktop computer, etc.

[0077] The server 103 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal device 101 .

[0078] It should be noted that the financial data processing method provided in the embodiment of the present application is generally executed by a server, and accordingly, the financial data processing device is generally arranged in the server.

[0079] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0080] Continue to refer Figure 2 , shows a flow chart of an embodiment of a financial data processing method according to the present application. The financial data processing method comprises the following steps:

[0081] Step 201, obtaining target data to be checked, wherein the target data includes billing data.

[0082] Specifically, the bill data includes bill ID, bill dimension, amount payable, tax rate, amount excluding tax, invoice type, and other fields. Among them, the bill dimension refers to the specific dimension of the business and financial affiliation of the bill, generally including the original order number, sub-order number, business type code, purchasing department code, purchasing company code, cost control department code and accounting entity code. Other fields refer to other reference information for user confirmation in addition to the bill dimension, such as: product name, product category and consignee address, etc. The financial data processing method described in this application is applied to a supply chain business system with complex billing data and involving many subsystems, so as to facilitate the management or service department to carry out efficient and comprehensive management of complex supply chain business data and billing data.

[0083] Step 202: according to a preset mark adding strategy, a first distinguishing mark is added to the data in the target data to be checked that meets the target adding requirement.

[0084] In this embodiment, a first distinguishing mark is added to the data in the target data to be checked that meets the target adding requirements. It should be understood that all the target data to be checked acquired in step 201, that is, each piece of the target data to be checked is unmarked data. In step 202, the target adding requirements specify for which data the first distinguishing mark is added, and the preset mark adding strategy specifies the marking format of the first distinguishing mark.

[0085] Specifically, for example, the target adding requirement is to perform a first distinguishing mark on the correct data of business execution or supply business records in the supply chain business.

[0086] By adding the first distinguishing mark, the data to be processed can be identified for the convenience of subsequent processing steps. For data that has not been marked with the first distinguishing mark, it may be data that has not yet been checked by the business process, or it may be data that has been checked by the business process but the business process may be questionable. For these two types of data, subsequent processing will not be performed yet.

[0087] Step 203: sorting all the target data to be checked with the first distinguishing mark added thereto according to a preset data sorting template, and obtaining template sorting results corresponding to all the first distinguishing mark data respectively.

[0088] Specifically, all the target data to be checked with the first distinguishing mark added refer to all the data that have been checked at the business level and passed the check. For such data, a preset data sorting template is used for template sorting to facilitate data management and subsequent calls.

[0089] In this embodiment, the preset data sorting template can be set as a specific data sorting template according to the actual supply chain business system.

[0090] Step 204: extracting the reimbursement determination fields corresponding to all first distinguishing mark data from all templated sorting results according to a preset reimbursement identification strategy, wherein the reimbursement identification strategy is provided by the target financial management terminal.

[0091] Specifically, since the financial management end is most clear about what kind of billing data can be reimbursed, according to the reimbursement identification strategy provided by the target financial management end, the reimbursement judgment fields corresponding to all the first distinguishing mark data are extracted from all the templated sorting results to achieve subsequent rapid identification and judgment of the reimbursable billing data.

[0092] In this embodiment, the preset reimbursement identification strategy is provided by the target financial management end; the reimbursement determination field is also set by the target financial management end, specifically, the reimbursement determination field, for example: business name, business type, reimbursement expenses, name and type of purchased goods, etc.

[0093] Step 205: Based on the reimbursement determination field, all data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added thereto are identified, and a second distinguishing mark is performed.

[0094] Specifically, the business billing data that has been checked and verified at the business level and organized in a template is identified and marked for reimbursement compliance through the reimbursement judgment field. For the target data to be checked that meets the reimbursement requirements, that is, the billing data, a second distinguishing mark is performed; for the target data to be checked that does not meet the reimbursement requirements, cache management can be performed first for subsequent statistical analysis, or a prompt message can be sent to the target data source end that it does not meet the reimbursement requirements and will not be reimbursed.

[0095] This embodiment realizes the combination of business-level and financial-level financial data processing, and can quickly identify bill data generated by supply chain business that meets financial reimbursement requirements. It is convenient for subsequent business management to quickly screen out reimbursable bill data, and it is also convenient for the financial management end to perform reimbursement management between business and finance.

[0096] In this embodiment, the first distinguishing mark and the second distinguishing mark, for example, have different mark formats, use different mark characters, etc.

[0097] Step 206, combining with the preset bill generation template, business bills are generated for all the target data to be checked that have been marked with the second distinguishing mark.

[0098] In this embodiment, the preset bill generation template can be a bill generation template in a unified format provided by the service support party in the supply chain business system. In order to facilitate the unified processing of bills for different supply sub-businesses, the bill generation template provided by the tax authority can be preferably used to generate business bills, which is convenient for subsequent bill accounting and management.

[0099] Step 207: Distribute all the business tickets finally generated to the corresponding receiving ends according to the preset distribution strategy.

[0100] Specifically, a business note is generated for the billing data corresponding to a complete supply and demand transaction process. At least the business note should be sent to the corresponding receiving ends of the two parties to the bill transaction, such as the business management end and the financial management end. Of course, it should also be sent to the service support end that provides supply chain business services, so that the supply chain business service provider can supervise and verify the transaction data.

[0101] In this embodiment, by acquiring the target data to be checked; adding a first distinguishing mark to the data in the target data to be checked that meets the target adding requirements; template-organizing all the target data to be checked with the first distinguishing mark added; identifying all the data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added, and performing a second distinguishing mark; combining with the preset bill generation template, respectively generating business bills for all the target data to be checked with the second distinguishing mark; distributing all the business bills finally generated to the corresponding receiving end. The financial data processing method described in this application is applied to the supply chain business system with complex billing data and many subsystems involved, so that the management service department can perform efficient and comprehensive management of complex supply chain business data and billing data at the business and financial level.

[0102] In this embodiment, the step of obtaining the target data to be checked specifically includes: obtaining the target data to be checked from multiple source data terminals according to the SOA integrated service architecture provided by the target checking business system, wherein the SOA integrated service architecture supports SSO single point integration, interface integration, ETL data mart integration and Web service integration.

[0103] Specifically, the target verification business system can be a verification subsystem in the supply chain business system. The verification subsystem supports obtaining the target data to be verified from multiple data sources, and the verification subsystem has a SOA (Service-Oriented Architecture) integrated service architecture, which can support SSO (Single Sign On) single point integration, interface integration, ETL (Extract-Transform-Load) data mart integration and Web service integration, so as to obtain the target data to be verified from different integration modules in the future.

[0104] Specifically, the obtaining of the target data to be verified from the multi-source data terminals includes: combining a Restful API call to obtain the target data to be verified from the multi-source data terminals in a synchronous acquisition manner, and using a message queue to obtain the target data to be verified from the multi-source data terminals in an asynchronous acquisition manner.

[0105] In this embodiment, the acquisition of the target data to be verified supports not only synchronous acquisition but also asynchronous acquisition. The multi-source data end includes multiple different commodity supply ends in the target supply chain business system, and also includes multiple commodity purchasing ends that use the target supply chain business system as the purchasing system.

[0106] Continue to refer Figure 3 , Figure 3 yes Figure 2 The flowchart of a specific embodiment of step 202 shown includes the following steps:

[0107] Step 301, retrieve the supply and demand business record log from the business monitoring component of the target supply chain system to determine whether the generation of the target data to be checked complies with the preset business logic rules;

[0108] Specifically, the business process can be automatically checked based on the supply and demand business record log, and the supply and demand business record log can be retrieved from the business monitoring component of the target supply chain system to determine whether the generation of the target data to be verified complies with the preset business logic rules. The supply and demand business record log is generally recorded and provided by the business monitoring component in the target supply chain business system.

[0109] Step 302: If the generation of the target data to be checked complies with the preset business logic rule, a confirmation mark, that is, the first distinguishing mark, is added to the target data to be checked;

[0110] Step 303: If the generation of the target data to be checked does not conform to the preset business logic rules, a prompt indicating that the target data to be checked is generated incorrectly is sent to the target monitoring terminal.

[0111] Specifically, for example: before the bill data is obtained and not organized into a template, the bill data generation or recording is reviewed to see if it is correct based on the supply and demand order purchases involved in the generation of the bill data. If it is correct, add a confirmation, otherwise, send a supply and demand bill data generation error prompt, that is, the supply and demand business record log is retrieved from the business monitoring component of the target supply chain system, so as to achieve a business-level verification check on the target data to be checked before generating business bills and financial bills. For data that has passed the inspection, a first distinguishing mark is made to facilitate subsequent processing, while for data that has not passed the inspection or has not been inspected, no first distinguishing mark is made to facilitate identification of the processing unit during subsequent processing.

[0112] Continue to refer Figure 4 In some optional implementations, before step 203, a step of performing automated processing training before template sorting is also included. Figure 4 It is a flowchart of a specific embodiment of the automated processing training before template sorting in the financial data processing method described in the present application, comprising the following steps:

[0113] Step 401, creating corresponding data sorting templates according to all supply and demand relationships involved in the target supply chain system, wherein different supply and demand relationships correspond to different data sorting templates;

[0114] Specifically, the corresponding data sorting templates are created according to all supply and demand relationships involved in the target supply chain system. For example, different data sorting templates are created according to different supply and demand businesses, different supply and demand companies, different supply and demand departments, and different supply and demand types.

[0115] Step 402, obtaining data sorting templates corresponding to all supply and demand relationships as the preset data sorting template;

[0116] Step 403, deploying the preset data sorting template into a preset text content extraction model;

[0117] Step 404, using the pre-constructed training samples to perform automatic extraction training on the preset text content extraction model to obtain a text content extraction model that has completed automatic extraction training, wherein the training samples include the target data to be verified that are simulated and generated based on all the supply and demand relationships.

[0118] By combining the data sorting template and the simulated target data to be checked, a text content extraction model for automatic extraction is trained, so that the model processing method can be used later to automatically extract the text content of the actual target data to be checked, that is, all the target data to be checked with the first distinguishing mark added, and automatically perform template sorting, thereby improving the efficiency of template sorting and being more automated and intelligent.

[0119] Continue to refer Figure 5 , Figure 5 yes Figure 2 The flowchart of a specific embodiment of step 203 shown includes the following steps:

[0120] Step 501, inputting all the target data to be checked with the first distinguishing mark added thereto into the text content extraction model that has been trained by the automatic extraction;

[0121] Step 502, identifying the data sorting templates corresponding to all the target data to be checked with the first distinguishing mark added thereto through the text content recognition component in the text content extraction model;

[0122] Specifically, the text content recognition component in the text content extraction model may be a text content recognition component based on OCR optical recognition technology.

[0123] First, according to the text content recognition component in the text content extraction model, all specific data contents contained in all the target data to be checked with the first distinguishing mark added are identified. Then, according to the sortable data contents corresponding to different data sorting templates, the data sorting templates corresponding to all the target data to be checked with the first distinguishing mark added are screened out.

[0124] It is also possible to identify the supply and demand relationships contained in all the target data to be verified with the first distinguishing mark added according to the text content recognition component in the text content extraction model, and screen out the data sorting templates corresponding to all the target data to be verified with the first distinguishing mark added according to the data sorting templates corresponding to different supply and demand relationships.

[0125] Here, the specific data content of the target data to be checked includes a pre-set identification field for characterizing the association relationship between the data sorting template and the target data to be checked, and the corresponding data sorting template is determined through the identification field.

[0126] Step 503, extracting text content from all the target data to be checked to which the first distinguishing mark is added through the text content extraction component in the text content extraction model, and filling the text content extraction result into the corresponding data sorting template;

[0127] Specifically, the text content extraction component in the text content extraction model can be a text content extraction component based on the Transformer codec structure. Through the text content extraction component, it is possible to accurately extract the text content in the target data to be checked, and directly use the decoder in the Transformer codec structure to fill the extracted text content output into the corresponding data sorting template.

[0128] Step 504: Obtain templated sorting results corresponding to all first distinguishing mark data output by the text content extraction model.

[0129] The model processing method is adopted to automatically extract the text content and automatically organize the templates for the actual target data to be checked, that is, all the target data to be checked with the first distinguishing mark added, which improves the efficiency of the template organization and is more automated and intelligent.

[0130] In this embodiment, the preset reimbursement identification strategy includes a first identification strategy, a second identification strategy, a third identification strategy and a fourth identification strategy, and the reimbursement determination field includes a first determination field, a second determination field, a third determination field and a fourth determination field.

[0131] In this embodiment, before executing the step of extracting the reimbursement judgment fields corresponding to all first distinguishing mark data from all templated sorting results according to the preset reimbursement identification strategy, the method also includes: generating an automated judgment model according to the first identification strategy, the second identification strategy, the third identification strategy and the fourth identification strategy, wherein the first identification strategy stipulates a first judgment field, and is used to identify whether the corresponding first distinguishing mark data complies with the proposed business budget range according to the first judgment field, the second identification strategy stipulates a second judgment field, and is used to identify whether the corresponding first distinguishing mark data complies with the proposed expense usage standard according to the second judgment field, the third identification strategy stipulates a third judgment field, and is used to identify whether the corresponding first distinguishing mark data complies with the statutory business scope according to the third judgment field, and the fourth identification strategy stipulates a fourth judgment field, and is used to identify whether the corresponding first distinguishing mark data complies with the statutory reimbursement business type according to the fourth judgment field.

[0132] By pre-setting the first determination field, the second determination field, the third determination field and the fourth determination field, and respectively setting the first identification strategy, the second identification strategy, the third identification strategy and the fourth identification strategy according to the first determination field, the second determination field, the third determination field and the fourth determination field, it is convenient to subsequently screen out the reimbursable bill data that meets the proposed business budget range, the proposed expense usage standards, the statutory business scope and the statutory reimbursement business type, that is, the reimbursable target data to be processed.

[0133] In this embodiment, the step of extracting the reimbursement judgment fields corresponding to all the first distinguishing mark data from all the templated sorting results according to the preset reimbursement identification strategy specifically includes: according to the first identification strategy, extracting the first judgment fields of all the first distinguishing mark data from all the templated sorting results; according to the second identification strategy, extracting the second judgment fields of all the first distinguishing mark data from all the templated sorting results; according to the third identification strategy, extracting the third judgment fields of all the first distinguishing mark data from all the templated sorting results; according to the fourth identification strategy, extracting the fourth judgment fields of all the first distinguishing mark data from all the templated sorting results.

[0134] In this embodiment, the step of identifying all data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added thereto based on the reimbursement determination field and performing the second distinguishing mark specifically includes: inputting the reimbursement determination field into the automated determination model, specifically, inputting the first determination field, the second determination field, the third determination field and the fourth determination field into the automated determination model; identifying whether the target data to be checked that currently has the first distinguishing mark added thereto meets the proposed business budget range based on the first identification strategy and the first determination field in the reimbursement determination field; identifying whether the target data to be checked that currently has the first distinguishing mark added thereto meets the proposed business budget range based on the second identification strategy and the second determination field in the reimbursement determination field. Check whether the target data complies with the proposed expense usage standards; identify whether the target data to be checked that is currently added with the first distinguishing mark complies with the statutory business scope according to the third identification strategy and the third determination field in the reimbursement determination field; identify whether the target data to be checked that is currently added with the first distinguishing mark complies with the statutory reimbursement business type according to the fourth identification strategy and the fourth determination field in the reimbursement determination field; if the target data to be checked that is currently added with the first distinguishing mark complies with the proposed business budget scope, the proposed expense usage standards, the statutory business scope and the statutory reimbursement business type at the same time, then add a second distinguishing mark to it, otherwise, send a prompt message to the target data source that reimbursement is not granted.

[0135] Through the first determination field, the second determination field, the third determination field and the fourth determination field, as well as the first identification strategy, the second identification strategy, the third identification strategy and the fourth identification strategy, the business bill data that can be reimbursed is screened out, and a second distinguishing mark is performed to facilitate the subsequent generation of relevant business and financial documents for the reimbursable business bill data.

[0136] In this embodiment, the preset bill generation template includes a bill generation template provided by a tax authority.

[0137] Continue to refer Figure 6 , Figure 6 yes Figure 2 The flowchart of a specific embodiment of step 206 shown includes the following steps:

[0138] Step 601, obtaining each piece of target data to be checked that has been marked with a second distinguishing mark;

[0139] Step 602, extracting specific data content from all target data to be checked that have been marked with the second distinguishing mark, and obtaining a data content extraction result;

[0140] Specifically, the specific data content extraction of all target data to be checked that have been marked with the second distinction to obtain the data content extraction result includes: according to the fill-in items in the bill generation template provided by the tax authority, all target data to be checked that have been marked with the second distinction to obtain the fill-in data content extraction result.

[0141] Step 603, mapping the data content extraction result to the bill generation template provided by the tax authority to generate a business bill.

[0142] By adopting the bill generation template provided by the tax authority to generate business bills, we can avoid the problem of each business service provider generating bills separately, which leads to complicated business bill types, and facilitate subsequent bill accounting and management.

[0143] In this embodiment, the receiving end includes a business management end and a financial management end, and also includes a supply chain business service supervision end.

[0144] Specifically, the step of distributing all the finally generated business bills to the corresponding receiving ends according to the preset distribution strategy specifically includes: sending the finally generated business bills to the corresponding business management end according to the business identification information, and sending the finally generated business bills to the corresponding financial management end according to the company identification information.

[0145] This application realizes the integration of business management and financial management at two levels, and generates the same business bills for business management and financial management, which is convenient for subsequent business and financial joint management and subsequent financial verification.

[0146] In this embodiment, the acquisition of the target data to be checked, the generation of the business bills, and the distribution of all the finally generated business bills to the corresponding receiving ends can be completed in combination with a timer or a trigger to achieve timing processing or trigger processing, which is more automated.

[0147] The present application obtains the target data to be checked; adds a first distinguishing mark to the data in the target data to be checked that meets the target adding requirements; templates all the target data to be checked that have been marked with the first distinguishing mark; identifies all the data that meet the reimbursement requirements in the target data to be checked that have been marked with the first distinguishing mark, and performs a second distinguishing mark; combines a preset bill generation template to generate business bills for all the target data to be checked that have been marked with the second distinguishing mark; and distributes all the business bills finally generated to the corresponding receiving end. The financial data processing method described in the present application is applied to a supply chain business system with complex billing data and many subsystems involved, so that the management service department can conduct efficient and comprehensive management of complex supply chain business data and billing data at the business and financial level.

[0148] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0149] The basic technologies of artificial intelligence generally include sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big financial data processing technology, operation / interaction systems, mechatronics, etc. Artificial intelligence software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0150] In the embodiment of the present application, by acquiring the target data to be checked; adding a first distinguishing mark to the data in the target data to be checked that meets the target adding requirements; template-organizing all the target data to be checked with the first distinguishing mark added; identifying all the data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added, and performing a second distinguishing mark; combining with the preset bill generation template, respectively generating business bills for all the target data to be checked with the second distinguishing mark; distributing all the business bills finally generated to the corresponding receiving end. The financial data processing method described in the present application is applied to the supply chain business system with complex billing data and many subsystems involved, so that the management service department can conduct efficient and comprehensive management of complex supply chain business data and billing data at the business and financial level.

[0151] Further references Figure 7 , as a response to the above Figure 2 In order to realize the method shown in the figure, the present application provides an embodiment of a financial data processing device, and the device embodiment is Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0152] like Figure 7 As shown, the financial data processing device 700 described in this embodiment includes: a target data acquisition module 701, a first distinguishing mark adding module 702, a template sorting module 703, a reimbursement determination field extraction module 704, a second distinguishing mark module 705, a business bill generation module 706 and a business bill distribution module 707. Among them:

[0153] The target data acquisition module 701 is used to acquire the target data to be checked, wherein the target data includes bill data;

[0154] A first distinguishing mark adding module 702, configured to add a first distinguishing mark to the data in the target data to be checked that meets the target adding requirement according to a preset mark adding strategy;

[0155] The templated sorting module 703 is used to sort all the target data to be checked with the first distinguishing mark added thereto according to a preset data sorting template, and obtain the templated sorting results corresponding to all the first distinguishing mark data respectively;

[0156] The reimbursement determination field extraction module 704 is used to extract the reimbursement determination fields corresponding to all the first distinguishing mark data from all the templated sorting results according to a preset reimbursement identification strategy, wherein the reimbursement identification strategy is provided by the target financial management terminal;

[0157] A second distinguishing mark module 705 is used to identify all data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added thereto based on the reimbursement determination field, and perform a second distinguishing mark;

[0158] The business bill generation module 706 is used to generate business bills for all the target data to be checked that have been marked with the second distinguishing mark, in combination with a preset bill generation template;

[0159] The business bill distribution module 707 is used to distribute all the business bills finally generated to the corresponding receiving ends according to the preset distribution strategy.

[0160] The present application obtains the target data to be checked; adds a first distinguishing mark to the data in the target data to be checked that meets the target adding requirements; templates all the target data to be checked that have been marked with the first distinguishing mark; identifies all the data that meet the reimbursement requirements in the target data to be checked that have been marked with the first distinguishing mark, and performs a second distinguishing mark; combines a preset bill generation template to generate business bills for all the target data to be checked that have been marked with the second distinguishing mark; and distributes all the business bills finally generated to the corresponding receiving end. The financial data processing method described in the present application is applied to a supply chain business system with complex billing data and many subsystems involved, so that the management service department can conduct efficient and comprehensive management of complex supply chain business data and billing data at the business and financial level.

[0161] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0162] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0163] To solve the above technical problems, the present application also provides a computer device. Figure 8 , Figure 8 This is a basic structural block diagram of the computer device in this embodiment.

[0164] The computer device 8 includes a memory 8a, a processor 8b, and a network interface 8c which are interconnected through a system bus. It should be noted that: Figure 8 Only a computer device 8 having a component memory 8a, a processor 8b, and a network interface 8c is shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital processor (DSP), an embedded device, etc.

[0165] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0166] The memory 8a includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 8a can be an internal storage unit of the computer device 8, such as a hard disk or memory of the computer device 8. In other embodiments, the memory 8a can also be an external storage device of the computer device 8, such as a plug-in hard disk equipped on the computer device 8, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Of course, the memory 8a can also include both the internal storage unit of the computer device 8 and its external storage device. In this embodiment, the memory 8a is generally used to store the operating system and various application software installed on the computer device 8, such as a computer-readable instruction of a financial data processing method, etc. In addition, the memory 8a can also be used to temporarily store various types of data that have been output or are to be output.

[0167] The processor 8b may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other financial data processing chips in some embodiments. The processor 8b is generally used to control the overall operation of the computer device 8. In this embodiment, the processor 8b is used to run the computer-readable instructions or process data stored in the memory 8a, such as computer-readable instructions for running the financial data processing method.

[0168] The network interface 8c may include a wireless network interface or a wired network interface. The network interface 8c is generally used to establish a communication connection between the computer device 8 and other electronic devices.

[0169] The computer device proposed in this embodiment belongs to the field of supply chain management technology and is applied to business and financial data processing scenarios. This application obtains the target data to be checked; adds a first distinguishing mark to the data in the target data to be checked that meets the target adding requirements; templates all the target data to be checked with the first distinguishing mark added; identifies all the data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added, and performs a second distinguishing mark; combines the preset bill generation template to generate business bills for all the target data to be checked that have been marked with the second distinguishing mark; and distributes all the business bills finally generated to the corresponding receiving end. The financial data processing method described in this application is applied to the supply chain business system with complex billing data and many subsystems involved, so that the management service department can conduct efficient and comprehensive management of complex supply chain business data and billing data at the business and financial level.

[0170] The present application also provides another embodiment, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by a processor to enable the processor to perform the steps of the financial data processing method as described above.

[0171] The computer-readable storage medium proposed in this embodiment belongs to the field of supply chain management technology and is applied to business and financial data processing scenarios. This application obtains the target data to be checked; adds a first distinguishing mark to the data in the target data to be checked that meets the target adding requirements; templates all the target data to be checked with the first distinguishing mark added; identifies all the data that meet the reimbursement requirements in the target data to be checked with the first distinguishing mark added, and performs a second distinguishing mark; combines the preset bill generation template to generate business bills for all the target data to be checked that have been marked with the second distinguishing mark; and distributes all the business bills finally generated to the corresponding receiving end. The financial data processing method described in this application is applied to a supply chain business system with complex billing data and many subsystems involved, so that the management service department can conduct efficient and comprehensive management of complex supply chain business data and billing data at the business and financial level.

[0172] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0173] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A financial data processing method, characterized in that: The steps include: Acquiring target data to be verified, wherein the target data includes billing data; According to a preset tag adding strategy, a first distinguishing tag is added to the data in the target data to be checked that meets the target adding requirements; Arrange all the target data to be verified that have the first distinguishing mark added thereto according to a preset data arrangement template, and obtain templated arrangement results corresponding to all the first distinguishing mark data respectively; Extracting, from all templated sorting results, reimbursement determination fields corresponding to all first distinguishing mark data according to a preset reimbursement identification strategy provided by the target financial management terminal; Based on the reimbursement determination field, identifying all data that meet the reimbursement requirements in the target data to be checked that has been marked with the first distinction, and performing a second distinction mark; Combined with the preset bill generation template, business bills are generated for all target data to be verified that have been marked with the second distinction mark; According to the preset distribution strategy, all business bills generated in the end are distributed to the corresponding receiving end.

2. The financial data processing method according to claim 1, characterized in that: The step of obtaining the target data to be verified specifically includes: Acquire target data to be checked from multiple data sources based on the SOA integrated service architecture provided by the target checking business system, wherein the SOA integrated service architecture supports SSO single point integration, interface integration, ETL data mart integration, and Web service integration; The step of obtaining target data to be verified from multiple data sources includes: Combined with the Restful API call, the target data to be verified is obtained from multiple data sources in a synchronous acquisition mode, and Utilize message queues to obtain target data to be verified from multiple data sources in an asynchronous manner.

3. The financial data processing method according to claim 1, characterized in that: The step of adding a first distinguishing mark to the data that meets the target adding requirements in the target data to be checked according to the preset mark adding strategy specifically includes: Retrieving the supply and demand business record log from the business monitoring component of the target supply chain system to determine whether the generation of the target data to be verified complies with the preset business logic rules; If the generation of the target data to be checked complies with the preset business logic rules, a confirmation pass mark, i.e., the first distinguishing mark, is added to the target data to be checked; If the generation of the target data to be checked does not comply with the preset business logic rules, a prompt indicating that the target data to be checked is generated incorrectly is sent to the target monitoring terminal.

4. The financial data processing method according to claim 1, characterized in that: Before executing the step of arranging all target data to be verified with the first distinguishing mark added thereto according to the preset data arrangement template to obtain templated arrangement results corresponding to all the first distinguishing mark data, the method further includes: Create corresponding data sorting templates based on all supply and demand relationships involved in the target supply chain system. Different data sorting templates correspond to different supply and demand relationships. Obtaining data sorting templates corresponding to all supply and demand relationships as the preset data sorting template; Deploying the preset data sorting template into a preset text content extraction model; The preset text content extraction model is automatically trained using pre-constructed training samples to obtain a text content extraction model that has completed automatic extraction training, wherein the training samples include target data to be verified that are simulated and generated based on all the supply and demand relationships.

5. The financial data processing method according to claim 4, characterized in that: The step of arranging all target data to be verified with the first distinguishing mark added thereto according to a preset data arranging template to obtain templated arranging results corresponding to all data with the first distinguishing mark respectively includes: Inputting all the target data to be checked with the first distinguishing mark added thereto into the text content extraction model that has been trained by the automatic extraction; Identifying, by means of a text content recognition component in the text content extraction model, data arrangement templates corresponding to all target data to be verified that have been marked with the first distinguishing mark; Extracting text content from all target data to be verified that have the first distinguishing mark added thereto by using the text content extraction component in the text content extraction model, and filling the text content extraction results into a corresponding data sorting template; Obtain templated sorting results corresponding to all first distinguishing mark data output by the text content extraction model.

6. The financial data processing method according to claim 1 or 5, characterized in that: The preset reimbursement identification strategy includes a first identification strategy, a second identification strategy, a third identification strategy, and a fourth identification strategy; the reimbursement determination field includes a first determination field, a second determination field, a third determination field, and a fourth determination field; and before executing the step of extracting the reimbursement determination fields corresponding to all first distinguishing mark data from all templated sorting results according to the preset reimbursement identification strategy, the method further includes: An automated determination model is generated based on the first, second, third, and fourth identification strategies, wherein the first identification strategy specifies a first determination field for determining, based on the first determination field, whether the corresponding first distinguishing mark data complies with a proposed business budget range; the second identification strategy specifies a second determination field for determining, based on the second determination field, whether the corresponding first distinguishing mark data complies with a proposed expense usage standard; the third identification strategy specifies a third determination field for determining, based on the third determination field, whether the corresponding first distinguishing mark data complies with a statutory business scope; and the fourth identification strategy specifies a fourth determination field for determining, based on the fourth determination field, whether the corresponding first distinguishing mark data complies with a statutory reimbursement business type. The step of extracting the reimbursement determination fields corresponding to all first distinguishing mark data from all templated sorting results according to the preset reimbursement identification strategy specifically includes: extracting first determination fields of all first distinguishing mark data from all templated sorting results according to the first recognition strategy; extracting the second determination fields of all first distinguishing mark data from all templated sorting results according to the second recognition strategy; extracting the third determination fields of all first distinguishing mark data from all templated sorting results according to the third recognition strategy; According to the fourth recognition strategy, the fourth determination fields of all first distinguishing mark data are extracted from all templated sorting results.

7. The financial data processing method according to claim 6, characterized in that: The step of identifying all data that meet the reimbursement requirements in the target data to be verified with the first distinguishing mark added thereto based on the reimbursement determination field and performing the second distinguishing mark includes: inputting the reimbursement decision fields into the automated decision model; Identify whether the target data to be checked, to which the first distinguishing mark is currently added, conforms to the proposed business budget range according to the first identification strategy and the first determination field in the reimbursement determination field; Identify whether the target data to be checked, to which the first distinguishing mark is currently added, meets the proposed expense usage standard according to the second identification strategy and the second determination field in the reimbursement determination field; identifying, according to the third identification strategy and the third determination field in the reimbursement determination field, whether the target data to be checked, to which the first distinguishing mark is currently added, complies with the legal business scope; Identifying whether the target data to be checked, to which the first distinguishing mark is currently added, complies with the statutory reimbursement business type according to the fourth identification strategy and the fourth determination field in the reimbursement determination field; If the target data to be checked that has been marked with the first distinction is in compliance with the proposed business budget range, the proposed expense usage standards, the statutory business scope, and the statutory reimbursement business type, a second distinction is added to it. Otherwise, a prompt message indicating that reimbursement will not be made is sent to the target data source.

8. A financial data processing device, characterized in that: include: A target data acquisition module, configured to acquire target data to be verified, wherein the target data includes bill data; A first distinguishing mark adding module, configured to add a first distinguishing mark to the data in the target data to be checked that meets the target adding requirements according to a preset mark adding strategy; A templated sorting module is used to sort all the target data to be checked that have been added with the first distinguishing mark according to a preset data sorting template, and obtain templated sorting results corresponding to all the first distinguishing mark data respectively; a reimbursement determination field extraction module, configured to extract, from all templated sorting results, the reimbursement determination fields corresponding to all first distinguishing mark data, according to a preset reimbursement identification strategy provided by the target financial management terminal; A second distinguishing mark module is configured to identify, based on the reimbursement determination field, all data that meets the reimbursement requirements in the target data to be checked and to which the first distinguishing mark is added, and perform a second distinguishing mark; A business bill generation module is used to generate business bills for all target data to be verified that have been marked with the second distinguishing mark, in combination with a preset bill generation template; The business bill distribution module is used to distribute all the business bills finally generated to the corresponding receiving ends according to the preset distribution strategy.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the financial data processing method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the financial data processing method according to any one of claims 1 to 7.

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