Invoice data processing method and related product

Abstract

The invention discloses an invoice data processing method and a related product. The method comprises the following steps: performing interface configuration on a target system; calling an invoice pool by using the configured interface, and performing multi-dimensional verification on invoice data in the invoice pool to obtain a verified invoice pool; the multi-dimensional verification at least comprises invoice number verification, key field verification and issuing time verification; and if the invoice pool is newly added with the invoice data, updating an input data value based on the newly added invoice data, and visually displaying the updated input data value. According to the invoice management and tax monitoring system and the invoice management and tax monitoring method, the core pain points of high adaptation cost, weak ability of checking true and false invoices, duplication checking lagging, statistical artificialization and the like in a traditional mode are solved, an integrated invoice management and tax monitoring system with automatic acquisition, intelligent checking, real-time updating and visual presentation is further constructed, and the intelligence, compliance and response agility of invoice data processing are remarkably improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to an invoice data processing method and related products. Background Technology

[0002] Several prominent issues exist in current invoice management and operations: First, the compatibility of data collection components is insufficient. Inconsistent interface standards across outdated business systems within the system mean that standardized data collection components often require additional custom development for each system, significantly increasing integration complexity and adaptation costs. Second, the accuracy of verification and deduplication mechanisms is limited. Existing solutions mostly rely on comparing invoice codes and invoice numbers, failing to effectively identify forged or altered invoices where "the invoice number is genuine, but key fields (such as amount, tax rate, and buyer / seller information) have been tampered with." Furthermore, delays in cross-system data synchronization hinder real-time deduplication, leaving the risk of duplicate reimbursements. Third, input tax credit statistics are severely lagging. Currently, data is manually collected daily from each subsidiary's system, which is not only inefficient but also fails to reflect the dynamic changes in the group's overall input tax credit in real time, restricting the ability to coordinate and flexibly allocate tax resources. These issues collectively constrain the automation, compliance, and efficiency of enterprise invoice management and tax operations. Summary of the Invention

[0003] To address the aforementioned issues, this application provides an invoice data processing method and related products, aiming to improve the intelligence, compliance, and responsiveness of invoice data processing.

[0004] The embodiments of this application disclose the following technical solutions:

[0005] The first aspect of this application provides an invoice data processing method, including:

[0006] Configure the interfaces of the target system;

[0007] The configured interface is used to call the invoice pool, and the invoice data in the invoice pool is validated in multiple dimensions to obtain the validated invoice pool; the multiple dimensions validation includes at least invoice number validation, key field validation and invoice time validation.

[0008] If new invoice data is added to the invoice pool, the input data value is updated based on the new invoice data, and the updated input data value is displayed visually.

[0009] Optionally, configuring the interface of the target system specifically includes:

[0010] Get the embedded script;

[0011] The embedded script is used to configure the interface of the target system.

[0012] Optionally, obtaining the embedded script specifically includes:

[0013] Obtain the business system interface identifier of the data acquisition component to be embedded;

[0014] Based on the interface identifier of the business system, query the interface specification library and retrieve the adaptation strategy that matches the interface identifier of the business system; the adaptation strategy includes at least the interface protocol and data format;

[0015] A configuration file is generated based on the adaptation strategy;

[0016] Adjust the interface data based on the configuration file to complete the configuration of the data acquisition component;

[0017] An embedded script is generated based on the configured acquisition component.

[0018] Optionally, the step of using the configured interface to call the invoice pool and performing multi-dimensional verification on the invoice data in the invoice pool to obtain a verified invoice pool specifically includes:

[0019] Use the configured interface to call the invoice pool and obtain the invoice data in the invoice pool;

[0020] The invoice data is validated in multiple dimensions, and deduplication is performed on the invoice data to obtain the validation results;

[0021] If the verification result indicates that the invoice data verification and deduplication are both passed, then the invoice data is retained to obtain the verified invoice pool;

[0022] If the verification result guarantees that the invoice data verification fails, then the invoice data is marked as abnormal data, and the verified invoice pool is obtained;

[0023] If the verification result guarantees that the invoice data failed the deduplication check, then the invoice data is marked as duplicate data, and the verified invoice pool is obtained.

[0024] Optionally, the step of updating the input data value based on the newly added invoice data and visually displaying the updated input data value specifically includes:

[0025] Feature extraction is performed on the newly added invoice data to obtain feature data;

[0026] The input data value is updated based on the aforementioned feature data, and the updated input data value is then visualized.

[0027] If the newly added invoice data becomes invalid, the feature data corresponding to the newly added invoice data in the input data value will be dynamically deducted synchronously, and the updated input data value will be displayed visually.

[0028] Optionally, after calling the invoice pool using the configured interface and performing multi-dimensional verification on the invoice data in the invoice pool to obtain the verified invoice pool, the process further includes:

[0029] The invoice data in the verified invoice pool is standardized.

[0030] A second aspect of this application provides an invoice data processing apparatus, comprising:

[0031] The configuration module is used to configure the interfaces of the target system.

[0032] The verification module is used to call the invoice pool using the configured interface and perform multi-dimensional verification on the invoice data in the invoice pool to obtain a verified invoice pool; the multi-dimensional verification includes at least invoice number verification, key field verification and invoice time verification.

[0033] The update module is used to update the input data value based on the newly added invoice data if the invoice pool is updated, and to visualize the updated input data value.

[0034] A third aspect of this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the invoice data processing method provided in the first aspect.

[0035] The fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the invoice data processing method provided in the first aspect.

[0036] The fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the invoice data processing method provided in the first aspect.

[0037] Compared with the prior art, this application has the following beneficial effects:

[0038] This application includes configuring the interface of the target system; calling the invoice pool using the configured interface, and performing multi-dimensional verification on the invoice data in the invoice pool to obtain a verified invoice pool; the multi-dimensional verification includes at least invoice number verification, key field verification, and issuance time verification; if new invoice data is added to the invoice pool, the input data value is updated based on the new invoice data, and the updated input data value is visualized.

[0039] This application achieves flexible integration with various business systems within the group by standardizing the interface configuration of the target system. This eliminates the need to develop separate adaptation modules for each legacy system, significantly reducing integration costs and improving deployment efficiency. After configuration, it can automatically call the interface to access a unified invoice pool and obtain full or incremental invoice data. Multi-dimensional verification is performed on each invoice in the invoice pool: not only is the invoice number verified, but also key fields are logically consistent and verified for authenticity (e.g., comparing information returned from the tax platform), and the issuance time is considered to determine if it falls within a reasonable business cycle (e.g., preventing cross-period reimbursement). This multi-dimensional verification mechanism effectively identifies highly realistic counterfeit invoices with authentic invoice numbers but altered content, significantly improving verification accuracy. Simultaneously, based on the global invoice pool, it enables real-time deduplication across systems and subsidiaries, completely eliminating the risk of duplicate reimbursements.

[0040] When new valid invoice data is added to the invoice pool, the input tax data update logic is automatically triggered, accumulating or adjusting the corresponding entity's input tax amount in real time to ensure that tax data is always synchronized with business operations. The updated input tax data value is then dynamically displayed through a visualization component, allowing finance and tax personnel to monitor the input tax changes of the entire group and its individual units in real time. This application not only solves the core pain points of the traditional model, such as high adaptation costs, weak ability to verify the authenticity of invoices, delayed deduplication, and manual statistics, but also constructs an integrated invoice management and tax monitoring system with automatic collection, intelligent verification, real-time updates, and visual presentation, significantly improving the intelligence, compliance, and responsiveness of invoice data processing. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of this application or 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 of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 A flowchart illustrating an invoice data processing method provided in this application embodiment;

[0043] Figure 2 This is a structural diagram of an invoice data processing device provided in an embodiment of this application. Detailed Implementation

[0044] As described above, current invoice management and operations face multiple challenges, severely hindering the digitalization of corporate finance and taxation. First, the compatibility of data collection components is poor: Numerous outdated business systems exist within the group, with varying interface protocols, data formats, and transmission standards. This makes it difficult to directly reuse a unified invoice collection component, often requiring customized development for each system, significantly increasing integration costs and implementation timelines. Second, verification and deduplication capabilities are weak: Existing mechanisms generally rely on simple comparisons based on invoice codes and numbers, failing to identify highly realistic counterfeit invoices where "the invoice number is genuine, but key fields (such as amount, tax rate, buyer / seller names, and tax IDs) have been maliciously altered." Furthermore, delays in data synchronization between systems make it difficult to eliminate the risk of duplicate reimbursements across systems. Third, input tax management is lagging: Currently, the reliance on manual extraction and aggregation of input tax data from each subsidiary's system daily is not only inefficient and error-prone but also fails to reflect the dynamic changes in the group's overall input tax amount in real time, severely impacting the agility and accuracy of tax planning, fund allocation, and compliant declarations.

[0045] In view of the above problems, this application provides an invoice data processing and generation method and related products. The method includes: configuring the interface of the target system; calling the invoice pool using the configured interface, and performing multi-dimensional verification on the invoice data in the invoice pool to obtain a verified invoice pool; the multi-dimensional verification includes at least invoice number verification, key field verification, and issuance time verification; if new invoice data is added to the invoice pool, the input data value is updated based on the new invoice data, and the updated input data value is visualized.

[0046] This application utilizes standardized interface configurations to flexibly connect with various new and existing business systems within the group, avoiding the need to develop separate adaptation modules for each heterogeneous system, significantly reducing integration costs and implementation cycles. It automatically accesses a unified invoice pool, performing multi-dimensional verification on each invoice, including the legality of the invoice number, the authenticity of key fields (such as amount, tax rate, and buyer / seller information), and the reasonableness of the issuance date. This effectively identifies highly realistic counterfeit invoices with "authentic invoice numbers but altered content," and enables real-time deduplication across systems and subsidiaries based on the global invoice pool, completely eliminating the risk of duplicate reimbursements. When a new valid invoice is added, the corresponding entity's input tax credit is automatically updated and dynamically displayed through a visualization component, allowing finance personnel to monitor tax data changes in real time, significantly improving the efficiency, compliance, and tax response agility of invoice management.

[0047] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0048] Figure 1 A flowchart of an invoice data processing method provided in this application embodiment is shown below. Figure 1 As shown, an invoice data processing method includes:

[0049] S101: Configure the interface of the target system.

[0050] This application does not limit the interface configuration method, such as obtaining the embedded script.

[0051] This application does not limit the method of obtaining the embedded script, such as obtaining the business system interface identifier of the data collection component to be embedded.

[0052] Developers can log in to the middle platform management backend and enter the business system identifier (such as "Old Procurement System V1.5") of the data collection component to be embedded.

[0053] Based on the interface identifier of the business system, query the interface specification library and retrieve the adaptation strategy that matches the interface identifier of the business system.

[0054] This application does not limit the specific content of the adaptation strategy. In one embodiment, the adaptation strategy includes at least the interface communication protocol (such as HTTP, HTTPS, SOAP, etc.) and the data exchange format (such as JSON, XML, etc.), and may further cover elements such as authentication methods, access control, field mapping rules, coding standards and error handling mechanisms, so as to fully adapt to the interface requirements of different systems.

[0055] Furthermore, this application does not limit the construction method of the interface specification library. For example, it can rely on the official interface of the tax bureau and integrate authoritative data from multiple sources, including various invoice acquisition methods such as manual entry, OCR recognition, and QR code collection, covering invoice data in all scenarios. On this basis, it systematically collects the interface protocols, data structures, and interaction specifications of mainstream business systems (such as SAP, Yonyou, Kingdee, etc.) used by the group headquarters and its subsidiaries, as well as legacy systems, and continuously accumulates them into a structured interface specification library. As the core support of the adaptive module, the interface specification library not only ensures the authority and integrity of the invoice data source, but also significantly improves the compatibility with heterogeneous systems and the efficiency of automated adaptation.

[0056] A configuration file is generated based on the adaptation strategy.

[0057] Adjust the interface data based on the configuration file to complete the configuration of the data acquisition component.

[0058] Based on the aforementioned adaptation strategy, a corresponding adaptation configuration file is automatically generated. The interface behavior and data processing logic of the data collection component are then dynamically adjusted according to this configuration file, thereby achieving precise component configuration. Specifically, the interface call parameters of the data collection component (such as request headers, authentication tokens, timeouts, and retries) and data parsing rules (such as field mappings, date formats, and numerical precision) can be automatically modified. For example, when the target system only supports XML format, the default JSON data output by the data collection component can be automatically converted into an XML structure conforming to the target specification, ensuring seamless data integration. The entire process requires no manual coding intervention, achieving highly efficient integration through "strategy-driven, automatic adaptation."

[0059] An embedded script is generated based on the configured acquisition component.

[0060] After the data collection component is configured, a corresponding embedding script is automatically generated. This embedding script is a lightweight, directly integrateable front-end code snippet. Developers simply need to copy and paste it into the target business system's page to complete component deployment, truly achieving "one-click embedding." Outputs include the adapted data collection component configuration file and the embedding script. Actual testing has shown an overall adaptation success rate exceeding 95%, significantly reducing the cost and technical barriers to modifying legacy or non-standard systems.

[0061] Once the embedded script is determined, the interface configuration of the target system is performed using the embedded script.

[0062] Once deployed, end-to-end test requests can be automatically initiated. Specifically, this can include: simulating the collection of a test invoice and uploading it to the middleware platform to verify data completeness, field accuracy, and format compliance. If the test passes, the system is marked as successfully adapted; if it fails, the specific reasons for the deviation are accurately reported (e.g., "XML structure mismatch," "date format parsing error," or "interface timeout") to assist in quickly locating and fixing problems.

[0063] All successfully generated adaptation configuration files are persistently stored in the system. When the business system calls the data collection component again, it can directly reuse the existing configuration without repeating the identification, generation, and testing process, achieving "configuration once, reuse long-term" and significantly improving integration efficiency and operational consistency.

[0064] When an employee selects an invoice from the official invoice pool in the reimbursement system and submits a reimbursement application, the system will automatically trigger a verification process: synchronously extract the full structured information of the invoice (including invoice code, invoice number, amount, tax rate, seller's taxpayer identification number, buyer information, and issuance date, etc.), and verify the extracted full structured information, that is, execute S102: use the configured interface to call the invoice pool, and perform multi-dimensional verification on the invoice data in the invoice pool to obtain the verified invoice pool.

[0065] This application does not limit the specific implementation method of multi-dimensional verification. Given the wide range of invoice data sources, heterogeneous formats, and the risk of tampering or forgery, to effectively ensure the validity of verification, the multi-dimensional verification should at least include invoice number verification, key field verification (such as amount, tax rate, seller's taxpayer identification number, etc.), and issuance time verification. In practical applications, verification dimensions can be dynamically expanded according to the risk level of the business scenario, industry regulatory requirements, or enterprise internal control strategies. For example, this could include: performing a precision comparison of the amount within a tolerance range (e.g., allowing an error of ±0.01 yuan), verifying whether the selected tax rate matches the goods or service category, determining whether the issuance date is within the valid reimbursement window, or verifying the authenticity and validity of the seller's identification number by connecting to the tax registration database. Through the above multi-level, configurable verification mechanism, an intelligent verification system covering all elements of an invoice, combining flexibility and high accuracy, is constructed. This effectively identifies highly realistic counterfeit invoices with "authentic invoice numbers but altered content," significantly improving risk control capabilities and compliance levels.

[0066] This application does not limit the specific verification method. For example, the invoice data in the invoice pool can be obtained by calling the configured interface.

[0067] The invoice data is validated in multiple dimensions, and deduplication is performed on the invoice data to obtain the validation results.

[0068] If the verification result indicates that the invoice data verification and deduplication are both passed, then the invoice data is retained to obtain the verified invoice pool;

[0069] In practice, the invoice will be automatically marked as "Pending Review," and the verified result, along with the structured invoice information, will be returned to the reimbursement system, triggering subsequent approval and reimbursement processes. Once the reimbursement process is completed (e.g., financial approval and payment), the invoice status will be immediately updated to "Reimbursed," and it will be simultaneously written to the global deduplication cache pool to ensure its real-time effectiveness across the group. This effectively prevents the same invoice from being submitted repeatedly in other business systems (such as procurement and travel), ensuring the timeliness and reliability of the deduplication mechanism.

[0070] If the verification result guarantees that the invoice data verification fails, the invoice data is marked as abnormal data, and the verified invoice pool is obtained.

[0071] If the verification result indicates that the invoice data fails verification, the system marks the invoice data as "abnormal data" and includes it in the verified invoice pool for auditing and traceability. In practice, each key field of the invoice (such as amount, tax rate, seller identification number, invoice date, etc.) is compared field-by-field with authoritative data in the official invoice pool. If any field deviates beyond a preset tolerance threshold (e.g., an amount difference exceeding 0.5 yuan or a relative error exceeding 5%), it is considered abnormal. At this point, not only is the reimbursement process blocked, but the user is also given precise feedback on the abnormality, such as a message: "The invoice amount deviates from the official data by 0.5 yuan; please verify." This mechanism, while preventing fake or tampered invoices, provides explainable and actionable verification results, balancing risk control strength and user experience.

[0072] If the verification result guarantees that the invoice data failed the deduplication check, then the invoice data is marked as duplicate data, and the verified invoice pool is obtained.

[0073] If the verification result shows that the invoice data fails the deduplication check, meaning that the invoice has already been used in other business systems within the group, it will be marked as "duplicate data" and included in the verified invoice pool for audit tracking and risk control. In practice, relying on a cross-system real-time deduplication cache pool, a comparison is completed within 1 second after the invoice is submitted, covering all connected systems such as reimbursement, procurement, and travel. The invoice's current status (such as "pending reimbursement", "reimbursed", "voided", or "red-inked") is used for accurate judgment.

[0074] This application boasts a verification accuracy rate exceeding 99.5%, with plagiarism detection response delays controlled within seconds, ensuring real-time and effective risk control. For instance, when a user attempts to submit an invoice already reimbursed in the procurement system, it will be immediately intercepted and a clear message will be returned: "This invoice was reimbursed in the procurement system on 2025-11-10, submitted by: Zhang San," clearly demonstrating the source of the conflict, effectively preventing duplicate reimbursements, and improving financial compliance and audit efficiency.

[0075] S103: If new invoice data is added to the invoice pool, the input data value is updated based on the new invoice data, and the updated input data value is displayed visually.

[0076] This application does not limit the method for updating the input tax amount (i.e., input data value). In one specific implementation, when the official invoice pool undergoes data changes (such as the addition of a valid invoice), the system automatically triggers a data change notification mechanism. The dynamic quota statistics module receives the notification in real time and performs structured feature extraction on the newly added invoice data to obtain feature data (i.e., feature extraction is performed on the newly added invoice data to obtain feature data), such as: tax amount of 130,000 yuan, subsidiary company A, and tax period of November 2025, etc.

[0077] Based on the extracted feature data, multi-level credit limit update logic can be executed synchronously. For example, Company A's input tax credit limit for November 2025 will automatically increase by 130,000 yuan, and the group-level total input tax credit limit for November 2025 will also be increased by 130,000 yuan accordingly, ensuring that the aggregated data is consistent with the details and is accurate in real time. All changes are recorded in the credit limit change log, including the source invoice number, change time, increase / decrease amount, operation type (such as "add" or "cancel"), and related business systems, achieving full-chain traceability and providing complete data support for subsequent audits, reconciliation, and tax analysis.

[0078] The input data value is updated based on the aforementioned feature data, and the updated input data value is then visualized.

[0079] Based on the extracted feature data, the corresponding input tax data values ​​are automatically updated, and the updated results are pushed to the visualization engine for dynamic display in real time. The updated input tax data is instantly synchronized to the group's financial visualization dashboard, comprehensively presenting key indicators such as the available credit for each subsidiary in the current month, the cumulative credit for the year, and the month-on-month / year-on-year change trends. It also supports flexible filtering and drill-down analysis by subsidiary, tax period, tax type, and other dimensions. For example, after logging into the system, the financial staff of Company A can view the company's latest input tax credit and detailed composition in real time. The system also supports one-click export of credit detail reports, in which each record is associated with the original invoice information (such as invoice code, invoice date, seller name, tax amount, etc.), facilitating reconciliation, auditing, and tax planning.

[0080] This application does not limit the specific form of visualization; various methods such as interactive charts, trend curves, heatmaps, and data tables can be used. The core objective is to achieve intuitive data presentation and efficient insight. The final output includes real-time input tax credit data, multi-dimensional visualization reports, and a complete credit change log. These three elements work together to ensure the real-time nature, accuracy, and traceability of tax data, providing strong support for group tax planning and financial decision-making.

[0081] If the newly added invoice data becomes invalid, the feature data corresponding to the newly added invoice data in the input data value will be dynamically deducted synchronously, and the updated input data value will be displayed visually.

[0082] If the newly added invoice data subsequently changes status such as being voided or reversed, the system will automatically trigger a dynamic reverse adjustment mechanism based on real-time updates from the official invoice pool. Specifically, this may include: upon detecting a change event, immediately deducting the original characteristic data (such as tax amount, period, and entity affiliation) of the invoice from the input tax credit limit of the corresponding subsidiary and group level, ensuring that tax data remains consistent with business facts. Simultaneously, the system generates a credit limit reduction log, fully recording the operation time, associated invoice number, deducted amount, reason for the change (such as "invoice voided" or "reverse cancellation"), and scope of impact.

[0083] The updated input tax data is then pushed to the visualization platform and reflected in real time in the group's financial dashboard and the views of each subsidiary, ensuring that all users see the latest and most accurate available amount. Through this closed-loop linkage mechanism, the risk of tax declaration deviations or overspending due to the failure to promptly remove voided invoices is effectively avoided, comprehensively maintaining the rigor and compliance of input tax management.

[0084] To ensure the consistency, comparability, and reliability of invoice data and subsequent processing, this application further proposes to standardize the invoice data in the verified invoice pool. This standardization includes, but is not limited to: unifying the monetary unit (e.g., converting "yuan" to a standard numerical format), standardizing date representation (unifying it to YYYY-MM-DD format), normalizing company names and taxpayer identification numbers (mapping them to the group organization master data code), standardizing tax rate expressions (e.g., unifying it to "13%" instead of "0.13" or "13"), and performing format verification and completion on key fields such as invoice codes and invoice numbers. Through these standardization operations, data heterogeneity issues caused by differences in source systems, input habits, or OCR recognition errors are eliminated, providing a high-quality, structurally unified data foundation for subsequent intelligent verification, quota statistics, cross-system deduplication, and visualization analysis, comprehensively improving the automation level and data governance capabilities of invoice management.

[0085] This application effectively addresses the core pain points that have long plagued in invoice management, such as data fragmentation, weak verification, delayed deduplication, and lagging tax statistics. It breaks down data barriers between various business systems, including reimbursement, procurement, and financial accounting, and builds a unified and authoritative invoice data source based on the official interface of the tax bureau, truly achieving "one-time collection, global sharing." At the integration level, it has a built-in interface specification library that can automatically identify the target system's interface type (such as HTTP / HTTPS, SOAP), data format (JSON / XML), and authentication method, and automatically generate adaptation configuration files and one-click embedding scripts based on matching strategies. Developers only need to embed the script into the front-end page to complete the deployment of the collection component, without modifying the original system architecture, significantly reducing the adaptation cost and digital upgrade threshold for legacy systems.

[0086] After an invoice is collected or selected and submitted by an employee, the official invoice pool data is immediately accessed to perform high-precision multi-field comparison and verification. This not only verifies the invoice number but also simultaneously verifies the consistency of key fields such as amount, tax rate, and seller's taxpayer identification number, effectively identifying highly realistic counterfeit invoices with "authentic invoice numbers but altered content." At the same time, relying on a cross-system real-time deduplication cache pool, duplicate detection is completed within 1 second across the entire group. Combined with a four-state identification system of "pending reimbursement / reimbursed / voided / red-ink reversal," duplicate reimbursement behavior is accurately intercepted, ensuring that each invoice has a clear status, unique usage, and is fully traceable.

[0087] In terms of tax management, when new or voided invoices are added to the official invoice pool, the input tax credit limit is adjusted within 5 seconds, and the updated results are pushed to the visual dashboard in real time. This allows financial personnel of the group and its subsidiaries to view multi-dimensional views such as the monthly limit, cumulative trends, and horizontal comparisons, and can export limit reports with associated original invoice details. All limit changes are recorded in a complete log and are deeply integrated with verification, deduplication, and status management to ensure the real-time nature, accuracy, and compliance of tax data.

[0088] Figure 2 A structural diagram of an invoice data processing device provided in an embodiment of this application is shown below. Figure 2 As shown, based on the invoice data processing method provided in the preceding embodiments, this application also provides an invoice data processing apparatus, including:

[0089] The configuration module is used to configure the interfaces of the target system.

[0090] The verification module is used to call the invoice pool using the configured interface and perform multi-dimensional verification on the invoice data in the invoice pool to obtain a verified invoice pool; the multi-dimensional verification includes at least invoice number verification, key field verification and invoice time verification.

[0091] The update module is used to update the input data value based on the newly added invoice data if the invoice pool is updated, and to visualize the updated input data value.

[0092] As one optional specific embodiment, the configuration module specifically includes:

[0093] The retrieval unit is used to retrieve the embedded script.

[0094] The configuration unit is used to configure the interface of the target system using the embedded script.

[0095] As one optional embodiment, the acquisition unit is specifically used for:

[0096] Obtain the business system interface identifier of the data acquisition component to be embedded; query the interface specification library based on the business system interface identifier and retrieve the adaptation strategy that matches the business system interface identifier; the adaptation strategy includes at least the interface protocol and data format; generate a configuration file based on the adaptation strategy; adjust the interface data based on the configuration file to complete the configuration of the data acquisition component; generate an embedding script based on the configured data acquisition component.

[0097] As one optional specific embodiment, the verification module is specifically used for:

[0098] The invoice pool is accessed via the configured interface to obtain invoice data. Multi-dimensional validation and deduplication checks are performed on the invoice data to obtain validation results. If the validation results indicate that both validation and deduplication checks of the invoice data pass, the invoice data is retained, resulting in a validated invoice pool. If the validation results guarantee that the invoice data validation fails, the invoice data is marked as abnormal data, resulting in a validated invoice pool. If the validation results guarantee that the invoice data deduplication checks fail, the invoice data is marked as duplicate data, resulting in a validated invoice pool.

[0099] As one optional specific embodiment, the update module is specifically used for:

[0100] Feature extraction is performed on the newly added invoice data to obtain feature data; the input data value is updated based on the feature data, and the updated input data value is visualized; if the newly added invoice data is voided, the feature data corresponding to the newly added invoice data is dynamically and synchronously deducted from the input data value, and the updated input data value is visualized.

[0101] As an optional specific embodiment, the device further includes:

[0102] A processing template is used to standardize the invoice data in the verified invoice pool.

[0103] This application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement an invoice data processing method.

[0104] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements an invoice data processing method.

[0105] This application provides a computer program product, including a computer program that, when executed by a processor, implements an invoice data processing method.

[0106] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device and equipment embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device and equipment embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components indicated as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the solution in this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0107] The above description is merely one specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for processing invoice data, characterized in that, The method includes: Configure the interfaces of the target system; The configured interface is used to call the invoice pool, and the invoice data in the invoice pool is validated in multiple dimensions to obtain the validated invoice pool; the multiple dimensions validation includes at least invoice number validation, key field validation and invoice time validation. If new invoice data is added to the invoice pool, the input data value is updated based on the new invoice data, and the updated input data value is displayed visually.

2. The invoice data processing method according to claim 1, characterized in that, The interface configuration of the target system specifically includes: Get the embedded script; The embedded script is used to configure the interface of the target system.

3. The invoice data processing method according to claim 2, characterized in that, The acquisition of the embedded script specifically includes: Obtain the business system interface identifier of the data acquisition component to be embedded; Based on the interface identifier of the business system, query the interface specification library and retrieve the adaptation strategy that matches the interface identifier of the business system; the adaptation strategy includes at least the interface protocol and data format; A configuration file is generated based on the adaptation strategy; Adjust the interface data based on the configuration file to complete the configuration of the data acquisition component; An embedded script is generated based on the configured acquisition component.

4. The invoice data processing method according to claim 1, characterized in that, The process of using the configured interface to call the invoice pool and performing multi-dimensional verification on the invoice data in the invoice pool to obtain a verified invoice pool specifically includes: Use the configured interface to call the invoice pool and obtain the invoice data in the invoice pool; The invoice data is validated in multiple dimensions, and deduplication is performed on the invoice data to obtain the validation results; If the verification result indicates that the invoice data verification and deduplication are both passed, then the invoice data is retained to obtain the verified invoice pool; If the verification result guarantees that the invoice data verification fails, then the invoice data is marked as abnormal data, and the verified invoice pool is obtained; If the verification result guarantees that the invoice data failed the deduplication check, then the invoice data is marked as duplicate data, and the verified invoice pool is obtained.

5. The invoice data processing method according to claim 1, characterized in that, The process of updating the input data value based on newly added invoice data and visually displaying the updated input data value specifically includes: Feature extraction is performed on the newly added invoice data to obtain feature data; The input data value is updated based on the aforementioned feature data, and the updated input data value is then visualized. If the newly added invoice data becomes invalid, the feature data corresponding to the newly added invoice data in the input data value will be dynamically deducted synchronously, and the updated input data value will be displayed visually.

6. The invoice data processing method according to claim 1, characterized in that, After calling the invoice pool using the configured interface and performing multi-dimensional verification on the invoice data in the invoice pool to obtain the verified invoice pool, the process further includes: The invoice data in the verified invoice pool is standardized.

7. An invoice data processing device, characterized in that, The invoice data processing device includes: The configuration module is used to configure the interfaces of the target system. The verification module is used to call the invoice pool using the configured interface and perform multi-dimensional verification on the invoice data in the invoice pool to obtain a verified invoice pool; the multi-dimensional verification includes at least invoice number verification, key field verification and invoice time verification. The update module is used to update the input data value based on the newly added invoice data if the invoice pool is updated, and to visualize the updated input data value.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the invoice data processing method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the invoice data processing method according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the invoice data processing method according to any one of claims 1-6.

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