Tax data synchronization method and device, equipment and storage medium

Abstract

The invention discloses a tax data synchronization method, device and equipment and a storage medium, and the method comprises the steps: building a data correction task after the abnormality of tax data is detected through any target system in a general ledger system, a full tax system and a value-added tax management system, and writing the data correction task into a task pool corresponding to a data warehouse; the method comprises the following steps: distributing a correction request to other systems through a target system according to a task identifier in a task pool, so that the other systems determine abnormal tax data in a data warehouse; and performing correction operation on the abnormal tax data in the data warehouse through other systems, and determining a state code corresponding to a correction result. According to the technical scheme of the embodiment of the invention, bidirectional data synchronization between the financial system and the tax system can be realized, the synchronization efficiency of the tax data is improved, and the risk of abnormal tax data is effectively controlled.

Description

Technical Field

[0001] The present invention relates to the field of enterprise digital management technology, and in particular to a tax data synchronization method, device, equipment and storage medium. Background Art

[0002] Currently, a company's financial system and tax system usually maintain system data independently and cannot automatically synchronize data in a timely manner. The tax numbers and branch data corresponding to the two associated systems may be inconsistent. For example, the VAT invoice cancellation rate of a company is as high as 12% due to the failure to synchronize the tax numbers.

[0003] In the existing technology, there is a lack of an effective technical means to achieve dynamic linkage between organizational information and tax data between the financial system and the tax system. Summary of the Invention

[0004] The present invention provides a tax data synchronization method, apparatus, device and storage medium, which can realize two-way data synchronization between a financial system and a tax system, improve the synchronization efficiency of tax data, and effectively control the risk of abnormal tax data.

[0005] According to one aspect of the present invention, a tax data synchronization method is provided, the method comprising:

[0006] In the general ledger system, all-tax system, and value-added tax management system, when any target system detects an anomaly in tax data, a data correction task is created and written into the corresponding task pool in the data warehouse;

[0007] Distributing the correction request to the remaining systems according to the task identifier in the task pool through the target system, so that the remaining systems can identify abnormal tax data in the data warehouse;

[0008] Use other systems to perform correction operations on abnormal tax data in the data warehouse and determine the status code corresponding to the correction results.

[0009] Optionally, after correcting the abnormal tax data in the data warehouse through other systems and determining the status code corresponding to the correction result, the following steps are also included:

[0010] generating a correction report matching the data correction task according to the status code determined by the remaining systems;

[0011] The correction report is sent to the target system, so that the target system determines whether to trigger a notification mechanism according to the correction report.

[0012] Optionally, distributing the correction request to other systems according to the task identifier in the task pool by the target system includes:

[0013] Generate a correction request by the target system according to the task identifier in the task pool and the correction parameter corresponding to the data correction task;

[0014] The revision request is distributed to the remaining systems via the target system.

[0015] Optionally, after corrective actions are performed on abnormal tax data in the data warehouse through other systems, this also includes:

[0016] Through other systems, a pre-trained data cleaning engine is used to identify whether the hierarchical institutions corresponding to abnormal tax data are omitted;

[0017] If so, the remaining systems will be used to complete the missing target hierarchical organizations and generate target tax data that matches the target hierarchical organizations.

[0018] Optionally, before using the pre-trained data cleaning engine through other systems to identify whether the hierarchical organization corresponding to the abnormal tax data is omitted, the following is also included:

[0019] Acquire a plurality of training samples, wherein the training samples include a plurality of hierarchical organizations associated with tax data;

[0020] Inputting the plurality of training samples into a neural network model, and iteratively training the neural network model using the plurality of training samples so that the neural network model learns the tree structure corresponding to the hierarchical structure in the training samples;

[0021] The trained neural network model is used as the data cleaning engine.

[0022] Optionally, after corrective actions are performed on abnormal tax data in the data warehouse through other systems, this also includes:

[0023] By adopting the policy compliance verification library through other systems, the policy parameters associated with abnormal tax data are updated in real time.

[0024] Optionally, the full tax system includes: a value-added tax system, a corporate income tax system, and an individual tax system;

[0025] Perform corrective actions on anomalous tax data in the data warehouse through the remaining systems, including:

[0026] Perform corrective actions on abnormal tax data in the data warehouse through other systems according to pre-set data priorities.

[0027] According to another aspect of the present invention, a tax data synchronization device is provided, the device comprising:

[0028] The task creation module is used to create a data correction task after detecting an anomaly in tax data in any target system, such as the general ledger system, the all-tax system, and the value-added tax management system, and write the data correction task into the task pool corresponding to the data warehouse;

[0029] a request distribution module, configured to distribute the correction request to the remaining systems through the target system according to the task identifier in the task pool, so that the remaining systems can determine the abnormal tax data in the data warehouse;

[0030] The data correction module is used to perform correction operations on abnormal tax data in the data warehouse through other systems and determine the status code corresponding to the correction result.

[0031] According to another aspect of the present invention, an electronic device is provided, comprising:

[0032] at least one processor; and

[0033] a memory communicatively connected to the at least one processor; wherein,

[0034] The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the tax data synchronization method according to any embodiment of the present invention.

[0035] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the tax data synchronization method described in any embodiment of the present invention when executed.

[0036] The technical solution provided by the embodiment of the present invention establishes a data correction task after any target system detects an abnormality in tax data in the general ledger system, the all-tax type system, and the value-added tax management system, writes the data correction task into the task pool corresponding to the data warehouse, distributes the correction request to the remaining systems according to the task identifier through the target system, so that the remaining systems determine the abnormal tax data in the data warehouse and perform the correction operation, and finally determine the status code corresponding to the correction result. This technical means can realize two-way data synchronization between the financial system and the tax system, improve the synchronization efficiency of the tax data, and effectively control the risks of abnormal tax data.

[0037] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 is a flowchart of a tax data synchronization method provided according to an embodiment of the present invention;

[0040] Figure 2 is a flowchart of another tax data synchronization method provided according to an embodiment of the present invention;

[0041] Figure 3 This is a structural diagram of a tax data synchronization device provided according to an embodiment of the present invention;

[0042] Figure 4 It is a structural diagram of an electronic device for implementing the tax data synchronization method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0044] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0045] Figure 1This is a flow chart of a tax data synchronization method provided by an embodiment of the present invention. This embodiment is applicable to situations where tax data synchronization is performed between a financial system and a tax system. The method can be executed by a tax data synchronization device, which can be implemented in the form of hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0046] Step 110: After detecting an anomaly in tax data in any target system, in the general ledger system, the all-tax system, or the value-added tax management system (VMS), a data correction task is created and written into a task pool corresponding to the data warehouse.

[0047] In this embodiment, when any of the general ledger system, the all-tax system, and the value-added tax management system detects an anomaly in the tax data, the system can be used as the target system, and a data correction task can be established by the target system.

[0048] Assume that the value-added tax management system scans the corporate tax number through a preset rule engine and identifies cross-regional tax number anomalies (such as conflicts in tax numbers at the place of registration or place of business). It can then create a unified data correction task, which includes the abnormal tax number and the scope of impact (value-added tax, income tax, personal income tax, etc.), and write the data correction task into the task pool corresponding to the data warehouse.

[0049] Specifically, if the target system detects an anomaly in tax data, it can trigger a corresponding alert mode based on the anomaly level. For example, if the VAT management system detects an anomaly in the tax number field of an invoice, it can trigger three levels of alerts: automatically blocking the invoicing process; sending an email to the tax manager; and freezing the associated institution if the issue is not addressed within 48 hours.

[0050] Step 120 : The target system distributes the correction request to other systems according to the task identification (Identity document, ID) in the task pool, so that the other systems can determine the abnormal tax data in the data warehouse.

[0051] In a specific embodiment, assuming that the target system is a value-added tax management system, the value-added tax management system can distribute correction requests to the general ledger system and the all-tax type system. After receiving the correction requests, the general ledger system and the all-tax type system can determine the abnormal tax data in the corresponding data warehouse based on the abnormal tax numbers and impact scope involved in the correction requests.

[0052] Step 130: Perform correction operations on the abnormal tax data in the data warehouse through other systems, and determine the status code corresponding to the correction result.

[0053] In this step, the remaining systems, except the target system, can perform correction operations on the abnormal tax data and determine the status code corresponding to the correction result. For example, if the correction is successful, the status code is 1, and if the correction fails, the status code is 0. The specific method of setting the status code can be adjusted according to actual conditions and is not limited in this embodiment.

[0054] In a specific embodiment, assuming that the target system is a general ledger system, after the general ledger system distributes a correction request to the value-added tax management system and the all-tax type system, the value-added tax management system and the all-tax type system can correct the abnormal tax data in the tax registration database and feed back the correction results to the general ledger system.

[0055] In one implementation of this embodiment, the all-tax system includes a value-added tax system, a corporate income tax system, and an individual tax system. Correcting abnormal tax data in the data warehouse using the remaining systems includes correcting the abnormal tax data in the data warehouse using the remaining systems according to a preset data priority.

[0056] For example, assuming that the VAT management system detects a cross-regional tax number anomaly and distributes the correction request to other systems, the VAT system can adjust the tax numbers associated with the input and output invoices; the corporate income tax system can update the advance payment declaration entity information; and the personal tax system can synchronize the employee withholding and payment location.

[0057] The technical solution provided by the embodiment of the present invention establishes a data correction task after any target system detects an abnormality in tax data in the general ledger system, the all-tax type system, and the value-added tax management system, writes the data correction task into the task pool corresponding to the data warehouse, distributes the correction request to the remaining systems according to the task identifier through the target system, so that the remaining systems determine the abnormal tax data in the data warehouse and perform the correction operation, and finally determines the status code corresponding to the correction result. This technical solution provides a two-way data synchronization method between the financial system and the tax system, that is, after the general ledger system detects abnormal data, it can positively notify the tax system to repair the abnormal data, and after the tax system detects abnormal data, it can reversely notify the financial system to repair the abnormal data, thereby realizing a closed loop of "business abnormality-tax correction-financial update", improving the synchronization efficiency of tax data, and effectively controlling the risks of abnormal tax data.

[0058] Figure 2 A flowchart of another tax data synchronization method provided by an embodiment of the present invention is shown in FIG. Figure 2 As shown, the method includes:

[0059] Step 210: After detecting an anomaly in tax data through any target system in the general ledger system, the all-tax system, and the value-added tax management system, a data correction task is established and written into the task pool corresponding to the data warehouse.

[0060] Step 220: The target system generates a correction request according to the task identifier in the task pool and the correction parameters corresponding to the data correction task, and distributes the correction request to other systems so that the other systems can determine abnormal tax data in the data warehouse.

[0061] In this step, taking the VAT management system as an example, assuming that the VAT management system identifies a cross-region tax number anomaly, a correction request can be generated based on the ID of the data correction task and the correction parameters (such as the correct tax number, effective time, etc.).

[0062] Step 230: Perform correction operations on the abnormal tax data in the data warehouse through other systems.

[0063] Step 240: Use the pre-trained data cleaning engine through the remaining systems to identify whether the hierarchical organization corresponding to the abnormal tax data is missing. If so, execute step 250; if not, execute step 260.

[0064] In this embodiment, the data cleaning engine integrates dynamic hierarchical reconstruction technology, enabling automatic repair of hierarchical organizations corresponding to abnormal tax data. Specifically, the data cleaning engine can automatically complete a four-level organizational tree structure. For example, if it detects a missing intermediate level between "Organization A - Organization B," it can trigger an alert and generate repair suggestions.

[0065] Step 250: Use other systems to complete the missing target hierarchical organizations and generate target tax data that matches the target hierarchical organizations.

[0066] In this step, the system can use the data cleaning engine to complete the missing target hierarchical organizations, and then generate target tax data that matches the target hierarchical organizations.

[0067] For example, assuming the data cleansing engine obtains the following organizational information "XX Business Unit - XX City Branch - XX District Sales Department" and identifies that the organizational information is missing the fourth-level organization, it can complete the fourth-level organization "XX District Sales Department First Branch" and generate matching tax data for the organization (for example, the special VAT number 310115XXXXXXX).

[0068] In one implementation of this embodiment, before using a pre-trained data cleaning engine through other systems to identify whether the hierarchical structure corresponding to the abnormal tax data is omitted, it also includes: obtaining multiple training samples, wherein the training samples include multiple hierarchical structures associated with the tax data; inputting the multiple training samples into a neural network model, and using the multiple training samples to iteratively train the neural network model so that the neural network model learns the tree structure corresponding to the hierarchical structure in the training samples; and using the trained neural network model as the data cleaning engine.

[0069] The advantage of this setting is that compared to the existing system which cannot automatically maintain the information of institutions below level four and uses manual step-by-step entry, the data cleaning engine can effectively improve the efficiency of maintaining institutional information and reduce the time and labor costs consumed in the institutional information maintenance process.

[0070] Step 260: Use the policy compliance verification library through other systems to update the policy parameters associated with the abnormal tax data in real time.

[0071] In the existing technology, when the system maintains tax data, it is difficult to update the tax data in a timely manner according to changes in tax policies. To address this, this embodiment also provides a way to achieve policy parameter atomization, that is, to break down complex tax policies into configurable rule units and integrate them into a policy compliance verification library.

[0072] For example, if the quarterly operating income of a branch is greater than or equal to 5 million, the "local payment mark" can be enabled for the tax data; conversely, if the operating income is less than 5 million, the "reason for not locally allocating" in the tax data can be selected as "tax incentives for small and micro enterprises."

[0073] The advantage of this setting is that compared with the problem of lagging tax data policy adaptation in existing technologies, it can effectively improve the synchronization efficiency of tax data.

[0074] Step 270: Determine the status code corresponding to the correction result through the remaining systems, and generate a correction report matching the data correction task based on the status code determined by the remaining systems.

[0075] In this step, specifically, the correction report may include the amount of data that was corrected successfully and detailed information about the data that failed to be corrected.

[0076] Step 280: Send the correction report to the target system, so that the target system determines whether to trigger a notification mechanism according to the correction report.

[0077] In this step, specifically, assuming that the correction report includes data that failed to be corrected, the target system can trigger a notification mechanism to enable corresponding staff to review the data.

[0078] The technical solution provided by the embodiment of the present invention is as follows: in the general ledger system, the all-tax type system and the value-added tax management system, after any target system detects that the tax data is abnormal, a data correction task is established and written into the task pool of the data warehouse; the target system generates a correction request based on the task identifier and the correction parameters and distributes it to the remaining systems, so that the remaining systems determine the abnormal tax data in the data warehouse and perform the correction operation; the remaining systems use the data cleaning engine to identify whether the hierarchical organization is missing; if so, the target hierarchical organization with omissions is completed, and target tax data matching the target hierarchical organization is generated; the remaining systems use the policy compliance verification library to update the policy parameters associated with the abnormal tax data in real time; the remaining systems determine the status code corresponding to the correction result, generate a correction report matching the data correction task, and the target system determines whether to trigger the notification mechanism based on the correction report. This technical solution can realize two-way data synchronization between the financial system and the tax system, improve the synchronization efficiency of the tax data, and effectively control the risks of abnormal tax data.

[0079] Figure 3 A schematic diagram of a tax data synchronization device provided by an embodiment of the present invention is provided. The device is applied to electronic devices such as Figure 3 As shown, the device includes: a task establishment module 310, a request distribution module 320 and a data correction module 330.

[0080] The task creation module 310 is used to create a data correction task after detecting an anomaly in tax data in any target system in the general ledger system, the all-tax system, and the value-added tax management system, and write the data correction task into the task pool corresponding to the data warehouse;

[0081] a request distribution module 320 for distributing the correction request to the remaining systems through the target system according to the task identifier in the task pool, so that the remaining systems can determine the abnormal tax data in the data warehouse;

[0082] The data correction module 330 is used to perform correction operations on abnormal tax data in the data warehouse through other systems and determine the status code corresponding to the correction result.

[0083] The technical solution provided by the embodiment of the present invention establishes a data correction task after any target system detects an abnormality in tax data in the general ledger system, the all-tax type system, and the value-added tax management system, writes the data correction task into the task pool corresponding to the data warehouse, distributes the correction request to the remaining systems according to the task identifier through the target system, so that the remaining systems determine the abnormal tax data in the data warehouse and perform the correction operation, and finally determines the status code corresponding to the correction result. This technical solution provides a two-way data synchronization method between the financial system and the tax system, that is, after the general ledger system detects abnormal data, it can positively notify the tax system to repair the abnormal data, and after the tax system detects abnormal data, it can reversely notify the financial system to repair the abnormal data, thereby realizing a closed loop of "business abnormality-tax correction-financial update", improving the synchronization efficiency of tax data, and effectively controlling the risks of abnormal tax data.

[0084] Based on the above embodiment, the full tax system includes: a value-added tax system, a corporate income tax system, and an individual tax system;

[0085] The device further comprises:

[0086] A report generation module, configured to generate a correction report matching the data correction task according to the status code determined by the remaining systems;

[0087] a report sending module, configured to send the correction report to the target system, so that the target system determines whether to trigger a notification mechanism according to the correction report;

[0088] The engine acquisition module is used to obtain multiple training samples, each of which includes a hierarchical structure associated with multiple tax data; input the multiple training samples into a neural network model, and use the multiple training samples to iteratively train the neural network model so that the neural network model learns the tree structure corresponding to the hierarchical structure in the training samples; and use the trained neural network model as the data cleaning engine.

[0089] The request distribution module 320 includes:

[0090] a request generating unit, configured to generate a correction request through the target system according to the task identifier in the task pool and the correction parameters corresponding to the data correction task;

[0091] A distribution unit is used to distribute the correction request to other systems through the target system.

[0092] The data correction module 330 includes:

[0093] The hierarchical identification unit is used to identify whether the hierarchical organization corresponding to the abnormal tax data is missing through the rest of the system using a pre-trained data cleaning engine;

[0094] The hierarchical repair unit is used to complete the missing target hierarchical organizations through other systems and generate target tax data that matches the target hierarchical organizations;

[0095] The parameter update unit is used to update the policy parameters associated with abnormal tax data in real time by using the policy compliance verification library through other systems;

[0096] The priority processing unit is used to perform correction operations on abnormal tax data in the data warehouse according to pre-set data priorities through other systems.

[0097] The above device can execute the methods provided by all the above embodiments of the present invention, and has the corresponding functional modules and beneficial effects of executing the above methods. For technical details not fully described in the embodiments of the present invention, please refer to the methods provided by all the above embodiments of the present invention.

[0098] Figure 4 A schematic diagram of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0099] like Figure 4 As shown, electronic device 10 includes at least one processor 11 and memory, such as read-only memory (ROM) 12 and random access memory (RAM) 13, communicatively connected to at least one processor 11. The memory stores computer programs executable by the at least one processor. Processor 11 can perform various appropriate actions and processes based on the computer programs stored in ROM 12 or loaded from storage unit 18 into RAM 13. RAM 13 can also store various programs and data required for the operation of electronic device 10. Processor 11, ROM 12, and RAM 13 are interconnected via bus 14. An input / output (I / O) interface 15 is also connected to bus 14.

[0100] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0101] Processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processor, controller, microcontroller, etc. Processor 11 executes the various methods and processes described above, such as the tax data synchronization method.

[0102] In some embodiments, the tax data synchronization method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the tax data synchronization method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the tax data synchronization method in any other suitable manner (e.g., via firmware).

[0103] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0104] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0105] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or apparatus. A computer-readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0106] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device that has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0107] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0108] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0109] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0110] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A tax data synchronization method, characterized in that: The method comprises: In the general ledger system, all-tax system, and value-added tax management system, when any target system detects an anomaly in tax data, a data correction task is created and written into the corresponding task pool in the data warehouse; Distributing the correction request to the remaining systems according to the task identifier in the task pool through the target system, so that the remaining systems can identify abnormal tax data in the data warehouse; Use other systems to perform correction operations on abnormal tax data in the data warehouse and determine the status code corresponding to the correction results.

2. The method according to claim 1, characterized in that After correcting abnormal tax data in the data warehouse through other systems and determining the status code corresponding to the correction result, the following steps are also included: generating a correction report matching the data correction task according to the status code determined by the remaining systems; The correction report is sent to the target system, so that the target system determines whether to trigger a notification mechanism according to the correction report.

3. The method according to claim 1, characterized in that The target system distributes the correction request to other systems according to the task identifier in the task pool, including: Generate a correction request by the target system according to the task identifier in the task pool and the correction parameter corresponding to the data correction task; The revision request is distributed to the remaining systems via the target system.

4. The method according to claim 1, wherein After corrective action is performed on unusual tax data in the data warehouse through the remaining systems, this also includes: Through other systems, a pre-trained data cleaning engine is used to identify whether the hierarchical institutions corresponding to abnormal tax data are omitted; If so, the remaining systems will be used to complete the missing target hierarchical organizations and generate target tax data that matches the target hierarchical organizations.

5. The method according to claim 4, characterized in that Before using the pre-trained data cleaning engine through other systems to identify whether the hierarchical organization corresponding to the abnormal tax data has been missed, it also includes: Acquire a plurality of training samples, wherein the training samples include a plurality of hierarchical organizations associated with tax data; Inputting the plurality of training samples into a neural network model, and iteratively training the neural network model using the plurality of training samples so that the neural network model learns the tree structure corresponding to the hierarchical structure in the training samples; The trained neural network model is used as the data cleaning engine.

6. The method according to claim 1, characterized in that After corrective action is performed on unusual tax data in the data warehouse through the remaining systems, this also includes: By adopting the policy compliance verification library through other systems, the policy parameters associated with abnormal tax data are updated in real time.

7. The method according to claim 1, characterized in that The full tax system includes: value-added tax system, corporate income tax system and individual tax system; Perform corrective actions on anomalous tax data in the data warehouse through the remaining systems, including: Perform corrective actions on abnormal tax data in the data warehouse through other systems according to pre-set data priorities.

8. A tax data synchronization device, characterized in that: The device comprises: The task creation module is used to create a data correction task after detecting an anomaly in tax data in any target system, such as the general ledger system, the all-tax system, and the value-added tax management system, and write the data correction task into the task pool corresponding to the data warehouse; a request distribution module, configured to distribute the correction request to the remaining systems through the target system according to the task identifier in the task pool, so that the remaining systems can determine the abnormal tax data in the data warehouse; The data correction module is used to perform correction operations on abnormal tax data in the data warehouse through other systems and determine the status code corresponding to the correction result.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the tax data synchronization method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the tax data synchronization method according to any one of claims 1 to 7 when executed.

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