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CN-122023042-A - Service data processing method and device, program product and electronic equipment

CN122023042ACN 122023042 ACN122023042 ACN 122023042ACN-122023042-A

Abstract

The invention discloses a business data processing method and a device, a program product and electronic equipment thereof, and relates to the field of financial science and technology or other related fields, wherein the processing method comprises the following steps: under the condition that the authorization of the target client is obtained, target business data of the target client are obtained, the target business data are identified, the target business label is determined, the target tax strategy corresponding to the target business label is determined based on a preset tax strategy association map, a preset configuration command is executed based on the target tax strategy, and a tax declaration guide file of the target client is generated. The invention solves the technical problem that the efficiency of tax declaration is lower because the business data cannot be processed efficiently in the related technology.

Inventors

  • LI XIN

Assignees

  • 中国工商银行股份有限公司

Dates

Publication Date
20260512
Application Date
20260130

Claims (10)

  1. 1. A method for processing service data, comprising: Under the condition of obtaining the authorization of a target client, obtaining target service data of the target client, identifying the target service data, and determining a target service tag; Determining a target tax strategy corresponding to the target service label based on a preset tax strategy association map, wherein the association relationship between the service label and the tax strategy is recorded in the preset tax strategy association map; And executing a preset configuration command based on the target tax strategy to generate a tax declaration guide file of the target client.
  2. 2. The processing method according to claim 1, further comprising, before executing a preset configuration command based on the target tax policy, generating a tax declaration guide file for the target client: collecting tax strategy files, and analyzing all the tax strategy files to generate revision information; And converting the revision information into the preset configuration command by adopting a preset generation model.
  3. 3. The method of processing according to claim 2, wherein the step of parsing all of the tax policy files to generate revision information includes: identifying the file type of each tax strategy file; carrying out entity extraction on the tax strategy file to obtain an entity set under the condition that the file type is a text type; if the file type is a form type, extracting a field from the tax strategy file to obtain a field set; Under the condition that the file type is an audio and video type, converting the tax strategy text into a text file, and extracting the text file to obtain supplementary revision information; And classifying the entity set, the field set and the supplementary revision information based on preset classification to obtain the revision information.
  4. 4. The processing method according to claim 2, characterized by further comprising, before converting the revision information into the preset configuration command using a preset generation model: Collecting historical tax strategies, and configuring each historical tax strategy to obtain a configuration command; constructing training data based on all the historical tax strategies and the configuration commands corresponding to the historical tax strategies; Training an initial generation model by adopting the training data, wherein the initial generation model is used for analyzing the input historical tax strategy to obtain a plurality of pieces of information, identifying the type of the information, and generating a prediction configuration command for the information based on the type of the information; And under the condition that the similarity between the predicted configuration command and the configuration command is larger than a preset similarity threshold, determining that training of the initial generation model is completed, and obtaining the preset generation model.
  5. 5. The processing method according to claim 2, wherein the step of converting the revision information into the preset configuration command using a preset generation model includes: identifying the type of the revision information; Generating a field configuration instruction by adopting the preset generation model under the condition that the type of the revision information is a field adjustment type; Generating a logic code by adopting the preset generation model under the condition that the type of the revision information is a rule change type; Generating a policy matching rule by adopting the preset generation model under the condition that the type of the revision information is a preferential policy class; and constructing the preset configuration command based on the field configuration instruction, the logic code and the strategy matching rule.
  6. 6. The processing method according to claim 2, characterized by further comprising, after converting the revision information into the preset configuration command using a preset generation model: Generating test cases based on the revision information, wherein each test case comprises expected output; constructing a test environment based on the preset configuration command; executing the test case in the test environment to obtain actual output; and determining a difference value between the actual output and the expected output, and adjusting the preset configuration command under the condition that the difference value is larger than a preset difference threshold value.
  7. 7. The processing method according to claim 1, further comprising, before determining a target tax policy corresponding to the target business label based on a preset tax policy association map: Collecting historical service data and constructing a service label based on the historical service data; for each business label, determining the association relationship between the business label and each tax strategy; Characterizing each business label and each tax strategy as a node, and characterizing the association relationship between the business label and the tax strategy as an edge; and constructing the preset tax strategy association map based on all the nodes and all the edges.
  8. 8. A service data processing apparatus, comprising: The system comprises an acquisition unit, a target service label and a target service identification unit, wherein the acquisition unit is used for acquiring target service data of a target client under the condition of acquiring authorization of the target client, identifying the target service data and determining the target service label; the determining unit is used for determining a target tax strategy corresponding to the target service label based on a preset tax strategy association map, wherein the association relation between the service label and the tax strategy is recorded in the preset tax strategy association map; and the generating unit is used for executing a preset configuration command based on the target tax strategy and generating a tax declaration guide file of the target client.
  9. 9. A computer program product comprising a non-volatile computer readable storage medium storing a computer program which, when executed by a processor, implements the method of processing traffic data according to any one of claims 1 to 7.
  10. 10. An electronic device comprising one or more processors and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of processing traffic data of any of claims 1-7.

Description

Service data processing method and device, program product and electronic equipment Technical Field The invention relates to the field of financial science and technology, in particular to a business data processing method and device, a program product and electronic equipment. Background Along with the acceleration of the digitized transformation of tax administration, the optimization iteration frequency of the enterprise tax strategy is obviously improved. The method comprises the steps of (1) manually disassembling policy files sentence by sentence, identifying revising key points and manually adjusting system configuration, wherein the adaption period is as long as 1-2 weeks, so that the requirement of quick declaration of enterprises after policy release cannot be met, client complaints are easily caused particularly when the declaration period is close, (2) the manual cost is high, the error rate is high, the policy analysis and the system adaption are completed cooperatively by professionals and developers, the cross-role communication cost is high, the manual understanding of complex policies (such as investment tax prevention rules) is easy to deviate, the system configuration is wrong, and enterprise declaration errors are caused, 3) financial scene adaption is not required, the existing engine does not consider the special service characteristics of financial enterprises (such as special equipment investment amount prevention corresponding to green credit projects, and the like), the special policy requirement of the financial enterprises cannot be automatically matched, additional manual intervention is required, and (4) the adaption effect is lack of dynamic verification, the correctness of the configuration is required to be verified manually, the test scene summarization is low, and the problem under multiple conditions (such as the allocation of a tax division mechanism after the policy adaption is completed is difficult to find out, and the rule summarization is difficult to be carried out. Therefore, a policy dynamic adaptation engine for adapting to financial scenarios is needed to improve the efficiency and compliance of financial institutions in tax declaration services for enterprises. For the above problems, no effective solution has been proposed at present. Disclosure of Invention The embodiment of the invention provides a business data processing method, a device, a program product and electronic equipment thereof, which at least solve the technical problem that the efficiency of tax declaration is low because the business data cannot be processed efficiently in the related technology. According to one aspect of the embodiment of the invention, a business data processing method is provided, and the business data processing method comprises the steps of obtaining target business data of a target client under the condition of obtaining authorization of the target client, identifying the target business data, determining a target business label, determining a target tax strategy corresponding to the target business label based on a preset tax strategy association map, wherein the association relation between the business label and the tax strategy is recorded in the preset tax strategy association map, and executing a preset configuration command based on the target tax strategy to generate a tax declaration guide file of the target client. Further, before the target tax strategy is based, the preset configuration command is executed, and the tax declaration guide file of the target client is generated, the method further comprises the steps of collecting tax strategy files, analyzing all the tax strategy files to generate revision information, and converting the revision information into the preset configuration command by adopting a preset generation model. The method comprises the steps of analyzing all tax strategy files to generate revision information, wherein the step of analyzing all tax strategy files to generate revision information comprises the steps of identifying the file type of each tax strategy file, extracting entities from the tax strategy files to obtain an entity set when the file type is a text type, extracting fields from the tax strategy files to obtain a field set when the file type is a form type, converting tax strategy files into text files when the file type is an audio/video type, extracting the text files to obtain supplementary revision information, and classifying the entity set, the field set and the supplementary revision information based on preset classification to obtain the revision information. The method comprises the steps of acquiring historical tax strategies, configuring each historical tax strategy to obtain configuration commands, constructing training data based on all the historical tax strategies and the configuration commands corresponding to the historical tax strategies, training an initial generation model by the training data, an