Intelligent tax integrated management system and method

Abstract

The application discloses an intelligent tax integrated management system and method, and belongs to the technical field of enterprise tax informatization. The system comprises a policy intelligent core layer, a multi-source data access layer, an intelligent calculation checking engine layer, a graph network fusion layer, a tax preferential policy intelligent declaration layer, an intelligent archival management layer of backup data, an intelligent archival management layer of electronic invoices, a declaration automation interface layer and an application display and interaction layer. The application builds an intelligent tax compliance system covering policy whole life cycle management, industry, financial and tax data fusion and closed loop management by constructing an industry, financial and tax unified knowledge graph, value-added tax two-way balance checking and root cause positioning, electronic invoice compulsory collection and four-property guarantee, tax preferential policy intelligent identification and declaration automation.

Description

Technical Field

[0001] This document relates to the field of intelligent tax management technology, and in particular to an integrated intelligent tax management system and method. Background Technology

[0002] Currently, enterprise tax software is mainly divided into four categories: policy information databases, official declaration clients, tax modules of financial software, and Excel verification tools. All of them have the following shortcomings: policy management is passive and lagging behind, and it is impossible to capture changes in regulations in real time; business, financial, and tax data are isolated from each other, resulting in low verification efficiency and easy errors; the assessment of the applicability of tax incentive policies relies on manual experience, lacking automated identification and matching mechanisms, and the declaration process is cumbersome with chaotic management of supporting documents; electronic invoice management suffers from the problem of paper-electronic separation, and the collection and archiving of XML source files lacks technical support, making it difficult to prove the four properties; the risk identification, early warning, and handling processes are broken, failing to form an effective governance closed loop.

[0003] CN117876127B discloses an intelligent tax system based on tax compliance operations. This system manages contract information through a smart contract management unit, and a tax identification module verifies the input and output invoices against the contract content. A real-time comparison module is integrated into the electronic tax return form to compare the tax-related information in the electronic return form with that in the tax identification module, ensuring data consistency. CN118170883A discloses a tax consultation method that analyzes user consultation questions and user data using a background analysis model, and combines this with a large language model for reasoning to provide personalized tax consultation.

[0004] However, none of the aforementioned existing technologies involve deep integration and graph network correlation analysis of business, finance and tax data. They lack the ability to attribute and locate the root causes of value-added tax differences in detail, and they have not achieved intelligent identification of tax incentive policies, automated generation of declaration processes, mandatory collection of electronic invoices, and solidified archiving of the four properties. Therefore, it is still difficult to build an intelligent tax compliance system that covers the entire life cycle management of policies, integration of business, finance and tax data, and closed-loop governance. Summary of the Invention

[0005] This invention provides an intelligent integrated tax management system and method to address the aforementioned problems.

[0006] According to an embodiment of the present invention, an intelligent integrated tax management system is provided, comprising: The policy intelligence hub is configured to automatically capture tax policy texts and perform structured parsing, make applicability judgments based on enterprise profiles, and generate a three-dimensional dynamic ledger. The multi-source data access layer is configured to connect to the enterprise's ERP system and e-tax bureau to acquire multi-source heterogeneous data and perform cleaning and standardization. The intelligent computing verification engine layer includes a multi-tax calculation engine, a two-way balance verification and detailed attribution verification model for value-added tax, and an automatic comparison module for property tax certificate information. The graph network fusion layer constructs a unified knowledge graph for business, finance, and taxation, with business contracts, financial vouchers, tax returns, and policies and regulations as nodes. The intelligent application layer for tax incentive policies includes an intelligent recognition engine for the applicability of incentive policies, an automatic generation engine for the application process, an intelligent verification module for supporting documents, and an intelligent association module for fixed assets and special equipment. The intelligent archiving management system for supporting documents is configured to establish an electronic ledger for applicable preferential policies, electronically archive supporting documents, and provide an interface for generating tax inspection document packages with one click. The intelligent archiving and management system for electronic invoices includes a multi-source heterogeneous acquisition module, a format verification and signature verification engine, a metadata automatic extraction and association module, and a four-dimensional protection and solidified archiving module. The application automation interface layer is configured to automatically fill in the application form and execute one-click application via an RPA robot. The application display and interaction layer is configured to centrally display the system's operating status and risk warning information.

[0007] According to an embodiment of the present invention, an intelligent integrated tax management method is provided, comprising: The policy intelligence hub automatically captures and parses tax policy texts, combines them with enterprise profiles to generate a three-dimensional dynamic policy ledger, and transmits the preferential policy ledger in the three-dimensional dynamic policy ledger to the intelligent archiving management layer for reference materials. Business, financial and tax data are collected through a multi-source data access layer, and a unified knowledge graph with business contracts, financial vouchers and tax returns as nodes is constructed in the graph network fusion layer. The intelligent computing verification engine layer performs two-way balance verification and detailed attribution verification of value-added tax, decomposes the total difference into multiple specific root causes, forces verification of the algebraic sum balance of the data on both sides, outputs a verification report if the verification passes, triggers an alarm in real time if the verification fails, and feeds back the difference root cause analysis results to the graph network fusion layer. The tax incentive policy intelligent declaration layer receives the three-dimensional dynamic policy ledger, automatically matches the preferential policies that enterprises can enjoy, generates a standardized declaration process for the successfully matched preferential policies and verifies the completeness of the supporting documents, transmits the successfully matched preferential policy items to the supporting documents intelligent archiving management layer, and transmits the preferential application data to the declaration automation interface layer. The intelligent archiving management system receives the preferential policy entries, establishes a three-level index structure to archive and store the reference documents, performs integrity verification before declaration, and recalls all related reference documents according to the three-level index structure to generate a data package output when a tax inspection instruction is received. The electronic invoice intelligent archiving management layer forcibly collects source files and XML files during the approval process, performs format verification and content signature verification, extracts metadata and automatically establishes associations, encapsulates verified invoices with four properties to form a standard archiving package, and feeds back the archiving associations to the graph network fusion layer. The declaration automation interface layer receives declaration data from the intelligent computing verification engine layer and preferential declaration data from the tax incentive policy intelligent declaration layer. The RPA robot automatically fills in the declaration form and executes one-click declaration. The declaration execution result is sent back to the policy intelligent hub layer to update the ledger declaration record. The application display and interaction layer centrally displays the coverage status of all tax types, ledger information, verification results, and risk warning information.

[0008] This invention constructs an intelligent tax compliance system covering the entire lifecycle management of policies, the integration of business, finance, and tax data, and closed-loop governance. This system is achieved through the construction of a unified knowledge graph for business, finance, and taxation; two-way balance verification and root cause analysis of value-added tax; mandatory collection and four-dimensional protection of electronic invoices; and intelligent identification and automated declaration of tax incentive policies. Compared with existing technologies, this invention enables proactive and dynamic management of tax policies, reducing the risk of policy lag; breaks down data silos between business, finance, and taxation, improving verification efficiency; avoids losses due to missed benefits through intelligent identification of preferential policies, shortening the declaration cycle; shortens the response time to tax inspections through a three-level index and one-click response for supporting documents; solves the paper-electronic separation problem at its source through mandatory collection, format verification, intelligent association, and four-dimensional encapsulation of electronic invoices, improving archiving efficiency and reducing compliance risks; accurately identifies assets eligible for preferential treatment through intelligent asset association; and achieves root cause analysis and processing suggestions through self-evolving diagnostics, constructing a complete governance closed loop from risk identification, early warning, processing to verification.

[0009] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a schematic diagram of the intelligent integrated tax management system according to an embodiment of the present invention; Figure 2 This is a flowchart of the intelligent integrated tax management method according to an embodiment of the present invention. Detailed Implementation

[0012] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0013] System Implementation Examples According to embodiments of the present invention, an intelligent integrated tax management system is provided. Figure 1 This is a schematic diagram of the intelligent integrated tax management system according to an embodiment of the present invention. Figure 1 As shown, the intelligent integrated tax management system of this invention specifically includes: The system comprises a policy intelligence hub layer, a multi-source data access layer, an intelligent computing verification engine layer, a graph network fusion layer, a tax incentive policy intelligent application layer, a document intelligent archiving management layer, an electronic invoice intelligent archiving management layer, an application automation interface layer, and an application display and interaction layer.

[0014] The policy intelligence hub is configured to automatically capture tax policy texts and perform structured parsing, make applicability judgments based on enterprise profiles, and generate a three-dimensional dynamic ledger.

[0015] In one specific implementation, the policy intelligence hub layer further includes a policy collection module, a policy analysis module, an enterprise profiling module, a policy matching module, a ledger management module, and a timeliness monitoring module.

[0016] The policy collection module automatically retrieves the latest tax policy and regulation texts from multiple sources, including the State Taxation Administration website, local tax bureau websites, and legal databases, via RPA or API interfaces on a regular basis. The retrieved file formats include, but are not limited to, PDF, Word, and HTML.

[0017] The policy analysis module uses OCR technology to perform image text recognition on scanned documents and natural language processing technology to perform structured analysis on the recognized text or digital original files, extracting key information such as policy name, document number, issuing unit, applicable conditions, calculation scope, preferential range, and effective period, and converting it into structured rule expressions. The applicable conditions include, but are not limited to, industry restrictions, regional restrictions, and enterprise size restrictions. The calculation scope includes, but is not limited to, the additional deduction ratio and the tax credit limit. The preferential range includes, but is not limited to, the tax rate and the tax reduction amount.

[0018] The enterprise profiling module is used to acquire or dynamically update enterprise profile data containing tags such as enterprise industry type, enterprise size, registered location, qualification certificates, personnel structure, R&D investment, and asset composition. Enterprise size specifically includes the number of employees, operating income, and total assets. Qualification certificates include, but are not limited to, high-tech enterprise certificates and software enterprise certificates. Personnel structure includes, but is not limited to, the proportion of R&D personnel and the number of disabled employees.

[0019] The policy matching module matches the structured rule expression with the enterprise profile data to automatically determine the applicability of each newly introduced policy to the current enterprise. The matching calculation includes comparison with industry catalogs, regional scope, scale indicators, and qualification conditions.

[0020] The ledger management module dynamically generates and maintains a three-dimensional dynamic ledger based on the matching results, namely, a ledger of newly issued policies, a ledger of applicable policies, and a ledger of preferential policies. The ledger of preferential policies specifically records the applicable period, amount enjoyed, and application status of the preferential policies that have been confirmed to be enjoyed.

[0021] The timeliness monitoring module monitors the timeliness status of various policies in the three-dimensional dynamic ledger in real time, including the effective date and the expiration date. When it detects that a preferential policy is about to expire, it automatically generates a renewal reminder or termination warning and pushes the warning information to the application display and interaction layer.

[0022] The multi-source data access layer is configured to connect to the enterprise's ERP system and the electronic tax bureaus of various provinces and cities to obtain multi-source heterogeneous data and perform cleaning and standardization.

[0023] In one specific implementation, the multi-source data access layer connects with the enterprise's ERP system, financial system, fixed asset management system, and human resources system through standardized API interfaces, synchronizing general ledger data, account balance sheets, voucher data, asset card information, payroll, and sales and purchase invoice ledgers in real time or on a scheduled basis. Simultaneously, this layer obtains the enterprise's tax digital account information, historical declaration data, and tax source registration information through a data interface with the e-tax bureau. This layer supports the parsing and import of multiple file formats, including Excel, PDF, XML, and JSON. The layer incorporates a data cleaning and standardization rule engine, performing format validation, field mapping, missing value handling, and outlier removal operations on data from different sources and in different formats, uniformly converting heterogeneous data into the system's internal standard data model, providing standardized data input for the upper-layer engine.

[0024] The intelligent computing verification engine layer includes a multi-tax calculation engine, a value-added tax two-way balance verification and detailed attribution verification model, and a property tax certificate information automatic comparison module.

[0025] In one specific implementation, the multi-tax calculation engine has built-in calculation logic templates for value-added tax, corporate income tax, property tax, land use tax, and stamp duty. Users can select the applicable tax type, tax payment period, and source of tax base through the configuration interface. The engine automatically retrieves standardized data to perform a trial calculation of the tax payable. The source of tax base includes accounting data or declaration data.

[0026] The VAT two-way balance verification and detailed attribution reconciliation model is specifically implemented as a left-right split reconciliation interface and backend logic. The system divides the reconciliation logic into a left logic area and a right logic area.

[0027] The left-hand logic area calculates the theoretical difference between the beginning and ending balances of VAT based on preset period data adjustment items, and generates the left-hand calculation result. The period data adjustment items include the carry-forward of the previous period, the transfer of input tax in the current period, and the amount of tax refund due under the exemption, deduction and refund policy.

[0028] The right-hand logic area automatically breaks down the total difference into six root causes according to preset attribution rules: tax present but not taxable, tax present but not taxable, tax rate difference, time difference, extra-price charge difference, and input tax transfer difference. It also calculates the sum of amounts for each type of root cause.

[0029] "Accounts have revenue but no tax category" refers to the difference between revenue recognized in the books but not recognized as sales by the tax authorities, and "tax has revenue but no accounts have tax category" refers to the difference between sales in the tax system but not recognized as revenue in the books. The system forcibly verifies the algebraic sum of the calculation results on the left and the sum of the categorized amounts on the right, and determines whether its absolute value is less than a preset threshold. If the verification passes, a verification report containing details of various root causes and handling suggestions is output. If the verification fails, an alarm is triggered in real time, the verification process is interrupted, and manual intervention is prompted to check the attribution logic.

[0030] The automatic comparison module for property tax certificate information is configured to obtain the enterprise's property ownership certificate, land use certificate, and lease contract certificate documents, use OCR technology to perform image recognition on the certificate documents, extract key fields such as the right holder's name, location address, land use right area, building area, and purpose, and use natural language processing technology to perform semantic parsing on the extracted key fields to generate structured certificate information records.

[0031] Subsequently, the module automatically compares the certificate information records with the tax source registration information and historical tax declaration data, identifies and marks risk points such as inconsistent area, failure to declare changes in use, and inconsistencies in the information of the right holder, and generates a certificate information difference report based on the comparison results, and marks the identified differences as risk items.

[0032] The graph network fusion layer constructs a unified knowledge graph of business, finance, and taxation, with business contracts, financial vouchers, tax returns, and policies and regulations as nodes.

[0033] In one specific implementation, the graph network fusion layer, based on a preset ontology model, imports business contracts, purchase orders, inbound and outbound slips, financial accounting vouchers, account balances, tax returns, and policy and regulatory nodes identified by the policy intelligence hub layer, synchronized from the multi-source data access layer, into the graph database as entity nodes. Simultaneously, it establishes edge relationships between nodes based on the business logic between the data. These edge relationships include, but are not limited to, contract-to-voucher relationships, voucher-to-tax-accrual relationships, and tax return-to-policy-reference relationships. This layer also provides a visual query interface for the knowledge graph, supporting users to perform penetrating queries, tracing directly from a single tax difference to the original financial vouchers and business contracts.

[0034] In a preferred embodiment, the graph network fusion layer uses nodes and edges in the knowledge graph as diagnostic reasoning paths, which are then invoked by the self-evolving diagnostic module of the intelligent computing verification engine layer. The self-evolving diagnostic module records the root cause analysis results and corresponding handling measures of historical verification discrepancies and feeds them back to the knowledge graph. When a similar discrepancy is detected again, it automatically invokes historical cases to generate a diagnostic conclusion containing predicted root causes and recommended handling schemes.

[0035] The intelligent tax incentive policy declaration layer includes an intelligent recognition engine for the applicability of incentive policies, an automatic declaration process generation engine, an intelligent verification module for supporting documents, and an intelligent association module for fixed assets and special equipment.

[0036] In one specific implementation, the intelligent recognition engine for the applicability of preferential policies constructs a corporate profile tag system that includes tags for industry type, company size, registered location, qualification certificates, personnel structure, and R&D investment. It also establishes a formal rule base for the applicability conditions of preferential policies. The rules in this rule base include, but are not limited to, companies registered within the Western Development Strategy catalogue and whose main business revenue accounts for more than 60%, whose number of disabled employees accounts for no less than 1.5% of their total workforce, and whose R&D expenses account for no less than 3% of their sales revenue. The engine performs multi-dimensional matching between the corporate profile tag data and the rules in the rule base to automatically identify a complete list of applicable tax preferential policies for the company. These tax preferential policies include stamp duty reduction and exemption, VAT refund for employment of disabled persons, additional deduction for corporate income tax, accelerated depreciation of fixed assets, investment tax credit for special equipment, and tax incentives under the Western Development Strategy.

[0037] The automatic application process generation engine, for each applicable preferential policy identified, calls the corresponding standardized application process template from the preset process template library to dynamically generate a visual application process diagram that includes nodes for qualification confirmation, document preparation, system entry, supplementary document upload, application form generation, internal approval, tax declaration, and result tracking. It also binds the responsible position, required document list, and processing time limit to each node.

[0038] The intelligent verification module for reference materials calls the reference material standard library when the data preparation node is triggered. It automatically compares the differences between the currently archived data and the standard requirements, identifies missing data, expired certificates, and format inconsistencies, and generates a correction list and sample references. The reference material standard library includes templates for R&D expense auxiliary accounts, lists of employment certificates for disabled persons, equipment purchase invoice standards, and technical appraisal report standards.

[0039] The fixed assets and special equipment intelligent association module is specifically used to synchronize the fixed asset inventory table with the fixed asset management system and obtain the asset number, asset category, purchase date, purchase amount and usage description fields.

[0040] Furthermore, the fixed assets and special equipment intelligent association module obtains the asset-related preferential policy items identified by the policy intelligent central layer. The asset-related preferential policy items include accelerated depreciation policy, one-time deduction policy and special equipment investment tax credit policy.

[0041] Furthermore, the fixed assets and special equipment intelligent association module matches the asset category, purchase amount and usage description of each fixed asset with the applicable conditions of the relevant preferential policies for each asset. For fixed assets that are successfully matched, the module automatically calculates the corresponding tax incentive amount and fills the calculation results into the corresponding column of the corporate income tax return.

[0042] Furthermore, the fixed assets and special equipment intelligent association module also marks the successfully matched fixed assets in the visual interface and generates a preferential confirmation form containing asset information, the name of the matching policy, and the preferential amount for review.

[0043] The intelligent archiving management system for reference materials is configured to establish an electronic ledger of applicable preferential policies, electronically archive reference materials, and provide an interface for generating one-click data packages for tax inspections.

[0044] In one specific implementation, the intelligent archiving management layer for reference materials includes a ledger creation module, an archiving storage module, an integrity verification module, and a rapid response module.

[0045] The ledger creation module establishes an electronic ledger for each identified applicable preferential policy, recording the policy name, document number, applicable period, amount enjoyed, and application records. It supports multi-dimensional retrieval and statistics by policy type, tax type, and year.

[0046] The archiving and storage module stores the reference materials electronically according to a three-level index structure of preferential policy type, applicable year, and asset project. It scans and stores the reference materials for various preferential policies electronically and in a structured manner, and establishes the association between the materials and preferential policies, application period, and asset project. The reference materials include contracts, invoices, certificates, and reports.

[0047] The integrity verification module automatically performs an integrity check before each preferential policy application, compares the archived data with the requirements of the reference data standard library, identifies missing items and generates correction guidelines, thus shifting the risk of missing data from post-event inspection to pre-event prevention.

[0048] When the rapid response module receives a tax inspection instruction containing the inspection year and policy type, it recalls all related supporting documents according to the three-level index structure, automatically generates and outputs a sealed data package containing a document list, photocopies of original vouchers, a description of the relationship, and an index directory, achieving a response time of seconds.

[0049] The intelligent archiving management layer for electronic invoices includes a multi-source heterogeneous acquisition module, a format verification and signature verification engine, a metadata automatic extraction and association module, and a four-dimensional protection and solidified archiving module.

[0050] In one specific implementation, the multi-source heterogeneous acquisition module further includes a forced acquisition submodule and a multi-channel convergence submodule.

[0051] The mandatory data collection submodule sets up a mandatory upload interception point in the reimbursement or payment approval process, requiring the submitter to simultaneously upload the PDF or OFD source file of the electronic invoice and the XML structured data file; otherwise, the application cannot proceed to the next approval stage.

[0052] The multi-channel aggregation submodule supports integration with multiple systems including the electronic tax bureau's digital tax account, WeChat Wallet, Alipay Wallet, and corporate email, enabling proactive batch retrieval and passive reception of invoice data to form a unified invoice pool.

[0053] The format verification and signature verification engine performs schema compliance verification and digital signature validity verification based on the State Taxation Administration root certificate on the uploaded XML file to prevent fake source files or tampered files from being mixed into the archiving system. The engine also performs verification in real time when the file is uploaded, and files that fail the verification are blocked and prompted to be re-uploaded.

[0054] The automatic metadata extraction and association module includes a metadata extraction submodule and a voucher automatic association submodule. The metadata extraction submodule parses the validated XML file and automatically extracts full invoice metadata, including invoice code, invoice number, invoice date, amount, tax rate, and product details, forming a searchable and computable metadata database. The voucher automatic association submodule pre-associates the invoice metadata with accounting voucher numbers, contract numbers, and inbound / outbound slip numbers based on matching rules for time, amount, supplier name, and business order number, generating a unique association verification code. Invoices that cannot be automatically associated are pushed to a manual processing pool for manual confirmation.

[0055] The four-integrity protection and solidified archiving module includes an integrity verification submodule, an anti-tampering and archiving encapsulation submodule, and a non-intrusive archiving submodule.

[0056] The integrity verification submodule periodically pulls all invoice data from the tax digital account and compares it with the locally stored records. If it detects that an invoice is missing its corresponding source file locally, it is marked as an orphan invoice and a supplementary entry list is generated and pushed to relevant personnel.

[0057] The anti-tampering and archiving encapsulation submodule uses a hash algorithm to generate integrity verification values ​​for verified invoices, connects to an authoritative timestamp service, and encapsulates and generates a standard archive information package containing source files, metadata, relationships, operation logs, timestamps, and integrity verification values. The archive package supports exporting to PDF / A or METS format.

[0058] The seamless archiving submodule enables the above archiving process to be completed automatically in the background without the user's awareness.

[0059] The automated application interface layer is configured to automatically fill in the application form and execute a one-click application via an RPA robot.

[0060] In one specific implementation, the declaration automation interface layer uses RPA robot technology to simulate manual operation, automatically logs into the electronic tax bureau system, automatically fills the declaration data generated by the intelligent calculation and verification engine layer and the preferential declaration data generated by the tax incentive policy intelligent declaration layer into the corresponding declaration form columns, and triggers the declaration submission operation.

[0061] Furthermore, this layer supports breakpoint resume and exception rollback mechanisms. When a network interruption or system anomaly occurs during the declaration process, it automatically resumes from the breakpoint or rolls back to the state before the declaration, ensuring the stability and reliability of the declaration process. This layer also collaborates with the intelligent declaration layer for tax incentive policies to achieve automatic filling in of incentive policies and automatic uploading of supporting documents.

[0062] The application display and interaction layer is configured to centrally display the system's operating status and risk warning information.

[0063] In one specific implementation, the application display and interaction layer provides a visual user interface that centrally displays the full tax coverage status, three-dimensional dynamic ledger, intelligent verification results, list of applicable preferential policies, declaration process dashboard, dashboard of complete supporting documents, electronic invoice archiving status dashboard, tax inspection data package generation portal, declaration calendar, and risk warning information.

[0064] The electronic invoice archiving status dashboard specifically displays invoice pool statistics, archiving completeness, relationship graphs, and orphan invoice alerts. Users can use this interface to configure parameters, approve processes, view results, and export data.

[0065] Method Implementation Examples According to embodiments of the present invention, an intelligent integrated tax management method is provided. Figure 2 This is a flowchart of the intelligent integrated tax management method according to an embodiment of the present invention, such as... Figure 2 As shown, the intelligent integrated tax management method according to an embodiment of the present invention specifically includes: The policy intelligence hub automatically captures and parses tax policy texts, combines them with enterprise profiles to generate a three-dimensional dynamic policy ledger, and transmits the preferential policy ledger in the three-dimensional dynamic policy ledger to the intelligent archiving management layer for reference materials. Business, financial and tax data are collected through a multi-source data access layer, and a unified knowledge graph with business contracts, financial vouchers and tax returns as nodes is constructed in the graph network fusion layer. The intelligent computing verification engine layer performs two-way balance verification and detailed attribution verification of value-added tax, decomposes the total difference into multiple specific root causes, forces verification of the algebraic sum balance of the data on both sides, outputs a verification report if the verification passes, triggers an alarm in real time if the verification fails, and feeds back the difference root cause analysis results to the graph network fusion layer. The tax incentive policy intelligent declaration layer receives the three-dimensional dynamic policy ledger, automatically matches the preferential policies that enterprises can enjoy, generates a standardized declaration process for the successfully matched preferential policies and verifies the completeness of the supporting documents, transmits the successfully matched preferential policy items to the supporting documents intelligent archiving management layer, and transmits the preferential application data to the declaration automation interface layer. The intelligent archiving management system receives the preferential policy entries, establishes a three-level index structure to archive and store the reference documents, performs integrity verification before declaration, and recalls all related reference documents according to the three-level index structure to generate a data package output when a tax inspection instruction is received. The electronic invoice intelligent archiving management layer forcibly collects source files and XML files during the approval process, performs format verification and content signature verification, extracts metadata and automatically establishes associations, encapsulates verified invoices with four properties to form a standard archiving package, and feeds back the archiving associations to the graph network fusion layer. The declaration automation interface layer receives declaration data from the intelligent computing verification engine layer and preferential declaration data from the tax incentive policy intelligent declaration layer. The RPA robot automatically fills in the declaration form and executes one-click declaration. The declaration execution result is sent back to the policy intelligent hub layer to update the ledger declaration record. The application display and interaction layer centrally displays the coverage status of all tax types, ledger information, verification results, and risk warning information.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent integrated tax management system, characterized in that, include: The policy intelligence hub layer is used to automatically capture tax policy texts and perform structured parsing, make applicability judgments based on enterprise profiles, and generate a three-dimensional dynamic ledger. The multi-source data access layer is used to connect with enterprise ERP systems and e-tax bureaus to acquire multi-source heterogeneous data and perform cleaning and standardization. The intelligent computing verification engine layer includes a multi-tax calculation engine, a two-way balance verification and detailed attribution verification model for value-added tax, and an automatic comparison module for property tax certificate information. The graph network fusion layer is used to construct a unified business, finance, and tax knowledge graph with business contracts, financial vouchers, tax returns, and policies and regulations as nodes. The intelligent application layer for tax incentive policies includes an intelligent recognition engine for the applicability of incentive policies, an automatic generation engine for the application process, an intelligent verification module for supporting documents, and an intelligent association module for fixed assets and special equipment. The intelligent archiving management system for reference documents is used to establish an electronic ledger of applicable preferential policies, electronically archive reference documents, and provide an interface for generating one-click data packages for tax inspections. The intelligent archiving and management system for electronic invoices includes a multi-source heterogeneous acquisition module, a format verification and signature verification engine, a metadata automatic extraction and association module, and a four-dimensional protection and solidified archiving module. The application automation interface layer is used to automatically fill in the application form and perform one-click application via RPA robots; The application display and interaction layer is used to centrally display the system's operating status and risk warning information.

2. The system according to claim 1, characterized in that, The VAT two-way balance verification and detailed attribution verification model specifically includes: The verification logic is divided into a left logic area and a right logic area; The left-hand logic area is used to calculate the difference between the beginning and ending balances of value-added tax based on preset period data adjustment items, and generate the left-hand calculation result; The right-hand logic area is used to automatically break down the differences into six root causes: tax present but not tax present, tax present but not tax present, tax rate difference, time difference, extra-price charge difference, and input tax transfer difference, and to calculate the sum of the corresponding categories for each root cause. The system performs a mandatory check to verify whether the absolute value of the algebraic sum between the calculation result on the left and the total sum of categories is less than a preset threshold. If the check passes, a verification report containing details of various root causes is output. If the check fails, an alarm is triggered in real time.

3. The system according to claim 1, characterized in that, The policy intelligence hub layer includes: The policy data collection module is used to automatically capture tax policy and regulation texts from multiple sources. The policy analysis module uses OCR and natural language processing technologies to perform structured analysis on the captured policy and regulatory texts, extracting structured rule expressions that include applicable conditions, calculation methods, preferential rates, and effective periods. The Enterprise Profile module is used to obtain enterprise profile data that includes tags such as enterprise industry type, enterprise size, registered location, qualification certificates, personnel structure, and R&D investment. The policy matching module matches and calculates the structured rule expressions with the enterprise profile data, and automatically determines the applicability of each policy to the current enterprise. The ledger management module dynamically generates and maintains a three-dimensional dynamic ledger that includes ledgers of newly introduced policies, applicable policies, and preferential policies, based on the judgment results. The timeliness monitoring module monitors the timeliness status of various policies in the three-dimensional dynamic ledger. When it detects that a preferential policy is about to expire, it automatically generates a renewal reminder or termination warning.

4. The system according to claim 1, characterized in that, In the intelligent declaration layer of the aforementioned tax incentive policy: The intelligent recognition engine for the applicability of preferential policies is used to construct an enterprise profile tag system that includes tags such as industry type, enterprise size, place of registration, qualification certificates, personnel structure and R&D investment, and to establish a formal rule base for the application conditions of preferential policies. The enterprise profile tag data is matched with the rules in the rule base in multiple dimensions to automatically identify the list of all tax preferential policies applicable to the enterprise. The automatic application process generation engine is specifically used to call the corresponding standardized application process template from the preset process template library for each applicable preferential policy identified, and dynamically generate a visual application process diagram that includes qualification confirmation nodes, document preparation nodes, system filling nodes, internal approval nodes and application tracking nodes, and binds the responsible position, required document list and processing time limit to each node. The intelligent verification module for reference materials is specifically used to call the reference material standard library when the data preparation node is triggered, automatically compare the differences between the currently archived data and the standard requirements, and generate a correction list.

5. The system according to claim 1, characterized in that, The intelligent archiving management layer for reference materials includes: The ledger creation module establishes an electronic ledger for each identified applicable preferential policy, recording the policy name, document number, applicable period, amount received, and application records; The archive storage module stores reference materials electronically according to a three-level index structure of preferential policy type, applicable year, and asset project; The integrity verification module automatically performs an integrity check before each preferential policy application, compares the archived data with the requirements of the reference data standard library, identifies missing items, and generates correction guidelines. The rapid response module, upon receiving a tax inspection instruction containing the inspection year and policy type, retrieves all related supporting documents based on the three-level index structure, automatically generates and outputs a sealed data package containing a document list, photocopies of original vouchers, a description of the relationship, and an index directory.

6. The system according to claim 1, characterized in that, The intelligent archiving management layer for electronic invoices includes: The mandatory data collection module sets up a mandatory upload interception point in the reimbursement or payment approval process, requiring the submitter to simultaneously upload the PDF or OFD source file of the electronic invoice and the XML structured data file; The verification and signature module performs schema compliance verification and digital signature validity verification based on the State Taxation Administration's root certificate on the uploaded XML file. The metadata extraction module parses the verified XML file and automatically extracts full invoice metadata, including invoice code, invoice number, invoice date, amount, tax rate, and product details. The association module pre-associates invoice metadata with accounting voucher number, contract number, and inbound / outbound slip number based on matching rules of time, amount, supplier name, and business order number, and generates a unique association verification code. The comparison and discovery module periodically pulls all invoice data from the tax digital account and performs a two-way comparison with the local storage records. If it detects that an invoice is missing its corresponding source file locally, it is marked as an orphan invoice and a supplementary entry list is generated. The encapsulation and archiving module uses a hash algorithm to generate integrity verification values ​​for verified invoices, connects to an authoritative timestamp service, and encapsulates and generates a standard archive information package containing source files, metadata, relationships, operation logs, timestamps, and integrity verification values.

7. The system according to claim 1, characterized in that, The graph network fusion layer is specifically used for: The nodes and edges in the knowledge graph are used as diagnostic reasoning paths based on the pre-defined entity relationship graph. The intelligent computing verification engine layer also includes a self-evolving diagnostic module, which records the root cause analysis results and corresponding handling measures of historical verification differences and feeds them back to the knowledge graph. When a similar difference is detected again, it automatically calls historical cases to generate a diagnostic conclusion that includes predicted root causes and recommended handling solutions.

8. The system according to claim 1, characterized in that, The intelligent application layer for tax incentive policies also includes an intelligent association module for fixed assets and special equipment. This intelligent association module for fixed assets and special equipment is specifically used for: The fixed asset inventory list is synchronized with the fixed asset management system. The inventory list includes asset number, asset category, purchase date, purchase amount and usage description. Obtain the asset-related preferential policy items identified in the three-dimensional dynamic ledger, including accelerated depreciation policy, one-time deduction policy, and special equipment investment tax credit policy; The system matches the asset category, purchase amount, and usage description of each fixed asset with the applicable conditions of the relevant preferential policies for each asset. For fixed assets that are successfully matched, the system automatically calculates the corresponding tax incentive amount and fills the calculation results into the corresponding column of the corporate income tax return. Mark the successfully matched fixed assets in the visual interface and generate a discount confirmation form containing asset information, the name of the matching policy, and the discount amount for review.

9. The system according to claim 1, characterized in that, The automatic comparison module for property tax certificate information in the intelligent computing verification engine layer is specifically used for: Obtain the enterprise's property ownership certificates, which include property ownership certificates, land use certificates, and lease agreements; Using OCR technology, the property ownership certificate document was image-recognized to extract key fields including the name of the right holder, the address, the land use area, the building area and use of the property; Natural language processing technology is used to perform semantic parsing on the key fields of the certificate to generate structured certificate information records; Obtain enterprise tax source registration information and historical tax declaration data; The key fields of the certificate in the certificate information record are automatically compared with the tax source registration information and historical tax declaration data to identify discrepancies including area discrepancies, changes in use, and inconsistencies in the information of the right holder; A warrant information discrepancy report is generated based on the comparison results, and the identified discrepancies are marked with risk indicators.

10. An intelligent integrated tax management method, applied to the system described in any one of claims 1 to 9, characterized in that, include: The policy intelligence hub automatically captures and parses tax policy texts, combines them with enterprise profiles to generate a three-dimensional dynamic policy ledger, and transmits the preferential policy ledger in the three-dimensional dynamic policy ledger to the intelligent archiving management layer for reference materials. Business, financial and tax data are collected through a multi-source data access layer, and a unified knowledge graph with business contracts, financial vouchers and tax returns as nodes is constructed in the graph network fusion layer. The intelligent computing verification engine layer performs two-way balance verification and detailed attribution verification of value-added tax, decomposes the total difference into multiple specific root causes, forces verification of the algebraic sum balance of the data on both sides, outputs a verification report if the verification passes, triggers an alarm in real time if the verification fails, and feeds back the difference root cause analysis results to the graph network fusion layer. The tax incentive policy intelligent declaration layer receives the three-dimensional dynamic policy ledger, automatically matches the preferential policies that enterprises can enjoy, generates a standardized declaration process for the successfully matched preferential policies and verifies the completeness of the supporting documents, transmits the successfully matched preferential policy items to the supporting documents intelligent archiving management layer, and transmits the preferential application data to the declaration automation interface layer. The intelligent archiving management system receives the preferential policy entries, establishes a three-level index structure to archive and store the reference documents, performs integrity verification before declaration, and recalls all related reference documents according to the three-level index structure to generate a data package output when a tax inspection instruction is received. The electronic invoice intelligent archiving management layer forcibly collects source files and XML files during the approval process, performs format verification and content signature verification, extracts metadata and automatically establishes associations, encapsulates verified invoices with four properties to form a standard archiving package, and feeds back the archiving associations to the graph network fusion layer. The declaration automation interface layer receives declaration data from the intelligent computing verification engine layer and preferential declaration data from the tax incentive policy intelligent declaration layer. The RPA robot automatically fills in the declaration form and executes one-click declaration. The declaration execution result is sent back to the policy intelligent hub layer to update the ledger declaration record. The application display and interaction layer centrally displays the coverage status of all tax types, ledger information, verification results, and risk warning information.

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