Information verification and processing method of intelligent tax robot

Abstract

The embodiment of the invention discloses an information verification and processing method of an intelligent tax robot. According to the technical scheme provided by the embodiment of the invention, the real-time credit line of the taxpayer can be dynamically adjusted by combining the average credit line of the historical invoicing record of the system with the historical application information, the credit information, the operation information and the tax payment record of the taxpayer, so that the accuracy of invoice application business processing is improved; the business pressure of manual verification is relieved, and the tax business processing efficiency is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data processing technology, and in particular to a method for verifying and processing information of an intelligent tax robot. Background Art

[0002] At present, in tax scenarios, invoice application business mainly relies on the review of tax staff one by one. The credit limit of taxpayers is often set based on fixed rules or experience. With the rapid development of artificial intelligence science, digital robots using artificial intelligence technology have also been widely used. For example, by setting up tax robots to provide consultation on relevant issues when users handle taxes, the processing efficiency of various tax businesses can be improved.

[0003] However, the relevant tax robots generally only provide consulting services on tax issues, and the actual tax processing business is still performed by tax staff. Their auxiliary effect on tax business is relatively poor. With the increase in business volume, manual review of invoice applications is not only time-consuming and labor-intensive, but also prone to human errors or omissions, resulting in low review efficiency. The credit limit is difficult to accurately reflect the taxpayer's actual operating conditions and credit level, resulting in excessive or low credit limits, affecting business efficiency and financial security. Summary of the invention

[0004] The embodiment of the present application provides an information verification and processing method for an intelligent tax robot, which can dynamically adjust the taxpayer's real-time credit limit by combining the average credit limit of the system's historical invoicing records with the taxpayer's historical application information, credit information, business information and tax payment records, so as to improve the accuracy of invoice application business processing, alleviate the business pressure of manual verification, and improve the efficiency of tax business processing.

[0005] In a first aspect, an embodiment of the present application provides an information verification and processing method of a smart tax robot, comprising: Receive application materials information and invoice type application information for invoice application business input by the corresponding taxpayer; Review the application materials based on the set review rules, and if the application materials fail to pass the review, determine problematic materials that do not meet the review rules, and output corresponding material supplement suggestions based on the problematic materials; When the application materials information is reviewed and approved, the target field is extracted from the application materials information, the historical business database is queried according to the target field, the related invoice application business is obtained, and the average credit line information is determined based on the related invoice application business, and the target field includes the application industry, application area, business scale and registered capital information; the historical business database is queried based on the taxpayer information to determine the taxpayer's historical application information; the application adjustment coefficient is calculated based on the taxpayer's credit information, business information, and tax record; the real-time credit line is calculated based on the average credit line information, the historical application information and the application adjustment coefficient, and the taxpayer's current invoice application business is executed according to the real-time credit line.

[0006] Furthermore, the querying of the historical business database according to the target field to obtain the associated invoice claiming business, and determining the average credit limit information based on the associated invoice claiming business, includes: Constructing a database query statement according to the target field, querying a historical business database based on the database query statement, and determining a historical business database whose matching degree with the target field reaches a set threshold; The credit limit field information of each of the related invoice claiming businesses is extracted, and the average credit limit information is calculated based on the credit limit field information.

[0007] Furthermore, the calculation of the claim adjustment coefficient based on the taxpayer's credit information, business information, and tax payment record includes: Determine the corresponding indicator scores based on the taxpayer's credit information, business information, and tax records; The claim adjustment coefficient is calculated based on the weighted scores of each of the indicators.

[0008] Further, the calculating of the real-time credit limit according to the average credit limit information, the historical claim information and the claim adjustment coefficient includes: Calculating initial credit limit information based on the average credit limit information and the credit limit adjustment coefficient; A real-time credit limit is determined based on the initial claim limit information and the historical claim limit information.

[0009] Furthermore, the review of the application materials information based on the set review rules includes: The application materials information is input into a pre-built intelligent audit model, the text and structured data of the application materials information are identified based on the intelligent audit model, the corresponding audit indicators are determined, the audit indicators are compared with the set audit rules, and based on the comparison results, it is determined whether the application materials information has passed the audit.

[0010] Furthermore, the review rules are set based on the type, format, quantity, validity period, and content requirement information of the application materials.

[0011] Furthermore, the outputting of corresponding material supplement suggestions based on the problematic material information includes: Selecting a corresponding supplementary suggestion template based on the type of the problem material information, and determining corresponding supplementary content based on the problem material information; Generate corresponding material supplement suggestions based on the supplement suggestion template and the supplement content.

[0012] In a second aspect, an embodiment of the present application provides an information verification and processing system for a smart tax robot, including: A receiving module, used to receive application material information and invoice type application information for invoice application business input by the corresponding taxpayer; A first review module is used to review the application materials information based on the set review rules, and if the application materials information fails to pass the review, determine the problematic materials information that does not meet the review rules, and output corresponding material supplement suggestions based on the problematic materials information; The second audit module is used to extract the target field from the application material information if the application material information is audited and passed, query the historical business database according to the target field, obtain the related invoice application business, and determine the average credit line information based on the related invoice application business, the target field includes the application industry, application area, business scale and registered capital information; query the historical business database based on the taxpayer information to determine the taxpayer's historical application information; calculate the application adjustment coefficient based on the taxpayer's credit information, business information, and tax record; calculate the real-time credit line according to the average credit line information, the historical application information and the application adjustment coefficient, and execute the taxpayer's current invoice application business according to the real-time credit line.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, including: memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the information verification and processing method of the intelligent tax robot as described in the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the information verification and processing method of the smart tax robot as described in the first aspect.

[0015] The embodiment of the present application receives application material information and invoice type application information for invoice application business input by the corresponding taxpayer; reviews the application material information based on the set review rules, and when the application material information fails to pass the review, determines the problematic material information that does not comply with the review rules, and outputs corresponding material supplement suggestions based on the problematic material information; when the application material information passes the review, extracts the target field from the application material information, queries the historical business database based on the target field, obtains the related invoice application business, and determines the average credit line information based on the related invoice application business, the target field includes the application industry, application area, business scale and registered capital information; queries the historical business database based on the taxpayer information to determine the taxpayer's historical application information; calculates the application adjustment coefficient based on the taxpayer's credit information, business information, and tax record; calculates the real-time credit line based on the average credit line information, the historical application information and the application adjustment coefficient, and executes the taxpayer's current invoice application business according to the real-time credit line. By adopting the above-mentioned technical means, it is possible to dynamically adjust the taxpayer's real-time credit limit by combining the average credit limit of the system's historical invoicing records with the taxpayer's historical application information, credit information, business information and tax payment records, so as to improve the accuracy of invoice application processing, alleviate the business pressure of manual verification, and improve the efficiency of tax business processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of an information verification and processing method of a smart tax robot provided in Example 1 of the present application; Figure 2 This is a schematic diagram of the interaction of the smart tax robot in Example 1 of the present application; Figure 3 It is a flow chart of generating material supplement suggestion in Example 1 of the present application; Figure 4 This is a flow chart for determining average credit limit information in Example 1 of the present application; Figure 5 is a calculation flow chart of the claim adjustment coefficient in Example 1 of the present application; Figure 6 is a flow chart for calculating the real-time credit limit in the first embodiment of the present application; Figure 7 It is a structural diagram of an information verification and processing system of a smart tax robot provided in Example 2 of the present application; Figure 8 It is a structural schematic diagram of an electronic device provided in Example 3 of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only part of the present application is shown in the accompanying drawings, but not all of the content. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0018] Embodiment 1: Figure 1 A flow chart of an information verification and processing method for a smart tax robot provided in Example 1 of the present application is given. The information verification and processing method for the smart tax robot provided in this embodiment can be executed by a smart tax robot, which can be implemented by software and / or hardware. The smart tax robot can be composed of two or more physical entities, or it can be composed of one physical entity.

[0019] The following description takes the intelligent tax robot as an example to describe the subject of the information verification and processing method of the intelligent tax robot. Figure 1 The information verification and processing method of the smart tax robot specifically includes: S110. Receive application material information and invoice type application information for invoice application business input by the corresponding taxpayer.

[0020] This application aims to dynamically adjust the real-time credit limit of taxpayers by combining the average credit limit of the system's historical invoicing records with the taxpayer's historical claim information, credit information, business information and tax records. The calculated real-time credit limit is compared with the invoice limit applied by the taxpayer. If the applied limit is within the real-time credit limit, the application is approved. For invoice application applications that meet the requirements, the smart tax robot automatically generates invoice numbers, invoicing information, etc., and notifies the taxpayer to collect or electronically push the invoice, thereby improving the efficiency of invoice application business processing.

[0021] Among them, by setting up smart tax robots in the tax hall to receive and process taxpayers' invoice application business, the efficiency and accuracy of tax services can be improved. Specifically, by deploying smart tax robots in corresponding locations in the tax hall, taxpayers can be ensured to find and use them easily. The robot has a user interaction interface, such as a touch screen, voice recognition and voice synthesis functions, so as to communicate effectively with taxpayers. By designing the operation interface, taxpayers are guided to gradually enter the application material information and ticket type application information required for the invoice application business. The robot can provide clear guidance and prompt information to help taxpayers understand the requirements of each step of the operation. Taxpayers enter the application material information and ticket type application information through the interface of the smart tax robot, including basic information of the company, tax registration number, invoice type, quantity, etc.

[0022] like Figure 2 As shown, the taxpayer 11 interacts with the smart tax robot 12 to upload the application material information and ticket type application information for the invoice application business. Based on the collected application material information and ticket type application information for the invoice application business, the smart tax robot 12 connects to the background tax system 13 to execute the information verification and processing method of the smart tax robot of this application, and has realized efficient and accurate processing of the invoice application business.

[0023] S120. Review the application materials information based on the set review rules. If the application materials information fails the review, determine the problematic materials information that does not comply with the review rules, and output corresponding material supplement suggestions based on the problematic materials information.

[0024] Prior to this, a series of audit rules were set according to the requirements and regulations of the tax department. The audit rules include but are not limited to: Completeness of basic information: Check whether the basic information provided by the taxpayer (such as company name, tax registration number, registered address, etc.) is complete and without omission.

[0025] File format and specifications: Verify whether the format of the uploaded file meets the requirements (such as PDF, JPG, etc.), and whether the file content is clear and readable without any signs of modification.

[0026] Validity verification: Check whether the provided supporting documents (such as business license, tax registration certificate, etc.) are within the validity period.

[0027] Logical consistency: Check whether there are any logical contradictions or inconsistencies in the information in the material.

[0028] Special terms: For certain types of invoice claiming business, it is necessary to check whether it complies with specific policy regulations or restrictions.

[0029] The smart tax robot receives the application materials and ticket type application information submitted by the taxpayer through its user interface. Then, according to the preset review rules, the received application materials are reviewed item by item. The review process may include technical means such as text recognition, data analysis, and rule matching. During the review process, once problematic material information that does not comply with the review rules is found, the robot will immediately stop further review and move to the problem identification stage. At this stage, the robot determines which information or documents have problems and identifies the specific type and nature of the problem.

[0030] Based on the results of problem identification, the smart tax robot automatically generates corresponding material supplement suggestions. These suggestions will clearly inform taxpayers what information or documents need to be supplemented, as well as the specific requirements and formats for the supplement. At the same time, the robot can also provide sample templates or online guidance to help taxpayers complete the material supplement work faster. Automated audits through smart tax robots can significantly improve audit efficiency and accuracy. Robots are able to process large amounts of data in a short period of time, reducing the time and effort required for manual audits. At the same time, because robots are not affected by subjective factors, their audit results are more objective and consistent. In addition, robots can also improve the accuracy and efficiency of audits by continuously learning and optimizing algorithms.

[0031] Optionally, the application materials information is reviewed based on the set review rules, including: Input the application materials information into the pre-built intelligent audit model, identify the text and structured data of the application materials information based on the intelligent audit model, determine the corresponding audit indicators, compare the audit indicators with the set audit rules, and determine whether the application materials information has been audited based on the comparison results. The audit rules are set based on the type, format, quantity, validity period, and content requirements of the application materials.

[0032] By building a pre-trained intelligent audit model, the intelligent audit model is based on machine learning algorithms to identify and understand different types of application material information such as text and images. Among them, by collecting a large amount of historical application material information as training data, these data cover various situations, including compliant and non-compliant samples. Useful features are extracted from the training data. These features can be keywords, phrases, sentence structures in the text, or specific areas and shapes in the image. The model is trained using the extracted features and the corresponding labels (i.e., whether it has passed the audit). By continuously adjusting the parameters and structure of the model, its performance in identifying audit indicators is optimized. Then, the accuracy and generalization ability of the model are evaluated on an independent test set to ensure that it can maintain stable performance when processing new data.

[0033] After the model is implemented, taxpayers submit application materials through the user interface of the smart tax robot. This information may include text files (such as application forms, certification documents, etc.) and image files (such as scanned copies of business licenses, ID card photos, etc.). After receiving the input application materials information, the intelligent audit model first identifies text and structured data. For text files, the model automatically extracts key information such as company name, tax registration number, application amount, etc. For image files, the model uses OCR (optical character recognition) technology to convert the text in the image into an editable text format and further extracts structured data. Based on the identified text and structured data, the intelligent audit model further checks whether the key information is complete and without omissions, verifies whether the data in different sources or different fields are consistent, and verifies whether the application content meets tax requirements. In addition, the possible risks of the application can be evaluated based on historical data and empirical models. The intelligent audit model compares the determined audit indicators with the preset audit rules. These rules can exist in the form of logical expressions, decision trees, rule sets, etc., which are used to guide the audit process and determine whether the application materials information is compliant. Based on the comparison results, the intelligent audit model outputs the audit results of the application materials information. If all audit indicators meet the set audit rules, the application materials information will be deemed to have passed the audit; otherwise, problematic materials information that does not meet the rules will be identified and corresponding material supplement suggestions or rejection reasons will be generated.

[0034] Optionally, refer to Figure 3 , based on the problem material information, output corresponding material supplement suggestions, including: S1201, selecting a corresponding supplementary suggestion template based on the type of the problem material information, and determining corresponding supplementary content based on the problem material information; S1202: Generate corresponding material supplement suggestions based on the supplement suggestion template and supplement content.

[0035] During the tax claim materials review process, when problematic material information is found, in order to guide taxpayers to effectively supplement and improve the materials, specific material supplement suggestions can be output based on these problematic information.

[0036] Among them, based on the above-mentioned audit model, the type of the problematic material information is determined, and the system will select the corresponding template according to the preset supplementary suggestion template library. The template library contains various common problem types and their corresponding supplementary suggestion templates. Each template is designed to guide taxpayers on how to supplement materials for specific types of problems. Optionally, in special cases, although a general supplementary suggestion template is selected, the system may still need to be customized according to the specific circumstances of the problematic material information. For example, for the problem of "incomplete basic information of the enterprise", the template can provide a general supplementary list, but the system can further customize the suggestions based on the specific content missing in the submitted information (such as contact number, email address, etc.).

[0037] After selecting the appropriate supplementary suggestion template and making necessary customized adjustments, the system will fill the template with supplementary content. These supplementary contents include specific field names, format requirements, examples or links to relevant guidance documents, etc. After filling, the system will generate the final material supplementary suggestions based on the template and supplementary content. The generated supplementary suggestions are presented to taxpayers through the user interface of the smart tax robot. Suggestions can be presented in text form or contain multimedia elements such as images, links or buttons to enhance the user experience. Through the above steps, the smart tax robot can output targeted material supplementary suggestions based on the problem material information, helping taxpayers to quickly and accurately complete the application materials, improve the review pass rate and improve the overall service efficiency.

[0038] S130. When the application materials information is reviewed and approved, extract the target field from the application materials information, query the historical business database based on the target field, obtain the related invoice application business, and determine the average credit line information based on the related invoice application business. The target field includes the application industry, application area, business scale and registered capital information; query the historical business database based on the taxpayer information to determine the taxpayer's historical application information; calculate the application adjustment coefficient based on the taxpayer's credit information, business information and tax record; calculate the real-time credit line based on the average credit line information, historical application information and application adjustment coefficient, and execute the taxpayer's current invoice application business according to the real-time credit line.

[0039] In the tax system, when the application materials are reviewed and approved, the real-time credit limit of the taxpayer needs to be determined, and the invoice application business needs to be executed accordingly. First, extract the key target fields from the approved application materials. The target fields are used to evaluate the credit and qualifications of the taxpayer. The target fields include the application industry, application region, business scale, and registered capital information. Use the extracted target fields as query conditions to search for invoice application business records similar to the current taxpayer in the historical business database. These records will be used to calculate the average credit limit information.

[0040] Based on the related invoice claim businesses queried, the average credit limit of these businesses is calculated. The average credit limit reflects the average invoice limit granted to similar taxpayers in the past period of time. In addition, by querying the historical business database, the historical claim information of the current taxpayer is obtained. This information includes the taxpayer's past invoice claim records, claim limits, usage, etc., which is used to evaluate the taxpayer's historical behavior and credit status.

[0041] The claim adjustment coefficient is then calculated based on the taxpayer's credit information, business information, and tax records. The claim adjustment coefficient is used to adjust the average credit limit to more accurately reflect the taxpayer's current status and risk level. Finally, the taxpayer's real-time credit limit is calculated based on the average credit limit information, historical claim information, and the claim adjustment coefficient. According to the calculated real-time credit limit, the taxpayer's current invoice claim business is executed. If the claim limit is within the real-time credit limit, it will be approved; if it exceeds, further review or adjustment may be required.

[0042] In this way, automated review and real-time credit limit calculation can greatly reduce the workload of manual review, shorten the processing time of invoice application, and improve business processing efficiency. Through system automation, the possibility of human errors and omissions is reduced, and data accuracy and business processing reliability are improved. In addition, by combining historical data and real-time credit assessment, the credit limit is dynamically adjusted, making the credit limit closer to the actual operating conditions and credit level of the taxpayer, improving the security and efficiency of fund use. And taxpayers can complete invoice application through simple online operations, reducing the number of trips to the tax department and improving user experience.

[0043] Optionally, refer to Figure 4 , query the historical business database according to the target field, obtain the related invoice claim business, and determine the average credit limit information based on the related invoice claim business, including: S1301, construct a database query statement according to the target field, query the historical business database based on the database query statement, and determine the historical business database whose matching degree with the target field reaches a set threshold; S1302. Extract the credit limit field information of each associated invoice claim business, and calculate the average credit limit information based on the credit limit field information.

[0044] In the process of querying the historical business database according to the target field to obtain the associated invoice claim business and determining the average credit line information based on these businesses, first clarify the target fields that need to be extracted from the claim material information, namely, the claim industry, claim region, business scale and registered capital information. According to these target fields, construct the corresponding SQL query statement (or other database query language). The query statement is designed to match similar fields stored in the historical business database and filter out historical business records whose matching degree with the target field reaches the set threshold. This threshold can be set according to actual conditions, such as similarity score, range of specific field values, etc. Submit the constructed query statement to the historical business database for execution. The database will return a set of historical business records whose matching degree with the target field reaches the set threshold. From the returned record set, further filter out records directly related to the invoice claim business, that is, the associated invoice claim business.

[0045] For each associated invoice claim business screened out in the above step S1301, the credit line field information is extracted from its record. This field records the invoice line granted for each claim business. When extracting the credit line field information, some data cleaning work can be performed, such as removing null values, abnormal values, or erroneous data entries to ensure the quality of data used for calculations. Based on the cleaned credit line field information, calculate the average credit line of all associated invoice claim businesses. This can be achieved by adding up all credit line values ​​and then dividing them by the number of associated businesses. The calculated average credit line information is output for use in subsequent steps, such as calculating real-time credit lines or as a basis for other decisions.

[0046] Through the above steps, the related invoice claim business can be effectively obtained from the historical business database based on the target field, and the average credit limit information can be determined based on these businesses, thereby providing strong support for subsequent invoice claim business processing.

[0047] Optionally, refer to Figure 5 , calculate the claim adjustment coefficient based on the taxpayer's credit information, business information, and tax record, including: S1303, determining corresponding indicator scores based on the taxpayer's credit information, business information, and tax payment records; S1304. Calculate the claim adjustment coefficient based on the weighted scores of each indicator.

[0048] When calculating the taxpayer's claim adjustment coefficient, the taxpayer's credit information is evaluated according to the preset credit scoring rules. For example, if it involves quantitative scoring of indicators such as the number of overdue times, the number of overdue days, and the amount of default, a score value reflecting the taxpayer's credit status is obtained. For business information scoring, by obtaining information such as the taxpayer's financial statements, business scale, industry status, market competitiveness, etc., the taxpayer's business stability, profitability, growth potential and other factors are analyzed, and then by comparing industry standards or historical data, a corresponding score is given to obtain a score value reflecting the taxpayer's business status. For tax record scoring, the taxpayer's historical tax records are used to score according to various indicators in the tax records (such as declaration accuracy, tax payment timeliness, tax audit results, etc.) to obtain a score value reflecting the taxpayer's tax compliance. This application does not impose fixed restrictions on specific scoring rules, and will not be elaborated here.

[0049] According to actual needs, appropriate weights are determined for credit information scores, business information scores, and tax record scores. These weights reflect the importance of different indicators in the calculation of the application adjustment coefficient. The weighted average calculation method is used to multiply the scores of each indicator by their corresponding weights, and then add the results to obtain the preliminary value of the application adjustment coefficient. The calculation formula is as follows: Application adjustment coefficient = credit information score x credit weight + business information score x business weight + tax record score x tax weight.

[0050] In this way, based on the taxpayer's credit information, business information and tax records, we can comprehensively and objectively assess their credit status and application risk, and thus calculate a reasonable application adjustment coefficient.

[0051] Optionally, refer to Figure 6 , calculate the real-time credit limit based on average credit limit information, historical claim information and claim adjustment coefficient, including: S1305. Calculate the initial credit limit information based on the average credit limit information and the credit limit adjustment coefficient; S1306. Determine the real-time credit limit based on the initial application limit information and historical application information.

[0052] When calculating the real-time credit limit, this application combines the average credit limit information, historical claim information, and claim adjustment coefficient to come up with a reasonable limit that is in line with the taxpayer's current situation. Among them, the average credit limit information and claim adjustment coefficient are obtained from the above steps. The average credit limit information and claim adjustment coefficient are used to calculate the initial claim limit. The calculation formula is as follows: Initial credit limit = average credit limit x credit adjustment factor The initial claim limit is determined by making appropriate adjustments to the average credit limit based on factors such as the taxpayer's credit status, business conditions, and tax payment records to arrive at an initial claim limit that is closer to the taxpayer's actual situation.

[0053] Then, the real-time credit limit is determined based on the initial claim limit information and the historical claim limit information, and the maximum value is selected as the real-time credit limit. Alternatively, it is determined whether the initial claim limit information exceeds the historical claim limit information to reach the set threshold. If so, the average or maximum value of the historical claim limit information is used as the historical claim limit information. Otherwise, the initial claim limit information is used as the real-time credit limit. By comprehensively considering multiple factors such as the average credit limit, historical claim information, and claim adjustment coefficient, a real-time credit limit that is both reasonable and in line with the current situation of the taxpayer is obtained. It can more effectively manage invoice claim business, reduce credit risk, and improve service efficiency.

[0054] As described above, by receiving the application material information and invoice type application information for invoice application business input by the corresponding taxpayer; reviewing the application material information based on the set review rules, and in the case where the application material information fails to pass the review, determining the problematic material information that does not comply with the review rules, and outputting corresponding material supplement suggestions based on the problematic material information; in the case where the application material information passes the review, extracting the target field from the application material information, querying the historical business database according to the target field, obtaining the related invoice application business, and determining the average credit line information based on the related invoice application business, the target field includes the application industry, application area, business scale and registered capital information; querying the historical business database based on the taxpayer information to determine the taxpayer's historical application information; calculating the application adjustment coefficient based on the taxpayer's credit information, business information and tax record; calculating the real-time credit line according to the average credit line information, historical application information and application adjustment coefficient, and executing the taxpayer's current invoice application business according to the real-time credit line. By adopting the above-mentioned technical means, it is possible to dynamically adjust the taxpayer's real-time credit limit by combining the average credit limit of the system's historical invoicing records with the taxpayer's historical application information, credit information, business information and tax payment records, so as to improve the accuracy of invoice application processing, alleviate the business pressure of manual verification, and improve the efficiency of tax business processing.

[0055] Embodiment 2: Based on the above embodiments, Figure 7 This is a schematic diagram of the structure of an information verification and processing system of a smart tax robot provided in Example 2 of this application. Figure 7 The information verification and processing system of the smart tax robot provided in this embodiment specifically includes: The receiving module 21 is used to receive the application material information and invoice type application information for invoice application business input by the corresponding taxpayer; The first review module 22 is used to review the application materials information based on the set review rules, and if the application materials information fails to pass the review, determine the problematic materials information that does not meet the review rules, and output corresponding material supplement suggestions based on the problematic materials information; The second audit module 23 is used to extract the target field from the application material information when the application material information is audited, query the historical business database according to the target field, obtain the related invoice application business, and determine the average credit line information based on the related invoice application business, the target field includes the application industry, application area, business scale and registered capital information; query the historical business database based on the taxpayer information to determine the taxpayer's historical application information; calculate the application adjustment coefficient based on the taxpayer's credit information, business information, and tax record; calculate the real-time credit line according to the average credit line information, the historical application information and the application adjustment coefficient, and execute the taxpayer's current invoice application business according to the real-time credit line.

[0056] Specifically, the historical business database is queried according to the target field to obtain the associated invoice claim business, and the average credit limit information is determined based on the associated invoice claim business, including: Construct a database query statement according to the target field, query the historical business database based on the database query statement, and determine the historical business database whose matching degree with the target field reaches the set threshold; Extract the credit limit field information of each related invoice claim business, and calculate the average credit limit information based on the credit limit field information.

[0057] Specifically, the claim adjustment coefficient is calculated based on the taxpayer's credit information, business information, and tax records, including: Determine the corresponding indicator scores based on the taxpayer's credit information, business information, and tax records; The claim adjustment coefficient is calculated based on the weighted scores of each indicator.

[0058] Specifically, the real-time credit limit is calculated based on the average credit limit information, historical application information and application adjustment coefficient, including: Calculate the initial credit limit information based on the average credit limit information and the credit limit adjustment coefficient; Determine the real-time credit limit based on the initial application limit information and historical application information.

[0059] Specifically, the application materials are reviewed based on the set review rules, including: Input the application materials information into the pre-built intelligent audit model, identify the text and structured data of the application materials information based on the intelligent audit model, determine the corresponding audit indicators, compare the audit indicators with the set audit rules, and determine whether the application materials information has passed the audit based on the comparison results.

[0060] Specifically, the review rules are set based on the type, format, quantity, validity period, and content requirement information of the application materials.

[0061] Specifically, based on the problem material information, corresponding material supplement suggestions are output, including: Select a corresponding supplementary suggestion template based on the type of the problem material information, and determine the corresponding supplementary content based on the problem material information; Generate corresponding material supplement suggestions based on the supplement suggestion template and supplement content.

[0062] As described above, by receiving the application material information and invoice type application information for invoice application business input by the corresponding taxpayer; reviewing the application material information based on the set review rules, and in the case where the application material information fails to pass the review, determining the problematic material information that does not comply with the review rules, and outputting corresponding material supplement suggestions based on the problematic material information; in the case where the application material information passes the review, extracting the target field from the application material information, querying the historical business database according to the target field, obtaining the related invoice application business, and determining the average credit line information based on the related invoice application business, the target field includes the application industry, application area, business scale and registered capital information; querying the historical business database based on the taxpayer information to determine the taxpayer's historical application information; calculating the application adjustment coefficient based on the taxpayer's credit information, business information and tax record; calculating the real-time credit line according to the average credit line information, historical application information and application adjustment coefficient, and executing the taxpayer's current invoice application business according to the real-time credit line. By adopting the above-mentioned technical means, it is possible to dynamically adjust the taxpayer's real-time credit limit by combining the average credit limit of the system's historical invoicing records with the taxpayer's historical application information, credit information, business information and tax payment records, so as to improve the accuracy of invoice application processing, alleviate the business pressure of manual verification, and improve the efficiency of tax business processing.

[0063] The information verification and processing system of the smart tax robot provided in the second embodiment of the present application can be used to execute the information verification and processing method of the smart tax robot provided in the above-mentioned first embodiment, and has corresponding functions and beneficial effects.

[0064] Embodiment three: Embodiment 3 of the present application provides an electronic device, referring to Figure 8The electronic device includes: a processor 31, a memory 32, a communication module 33, an input device 34 and an output device 35. The number of processors in the electronic device can be one or more, and the number of memories in the electronic device can be one or more. The processor, memory, communication module, input device and output device of the electronic device can be connected via a bus or other means.

[0065] As a computer-readable storage medium, the memory can be used to store software programs, computer executable programs and modules, such as the program instructions / modules corresponding to the information verification and processing method of the smart tax robot described in any embodiment of the present application (for example, the various modules in the information verification and processing system of the smart tax robot). The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the device, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0066] The communication module is used for data transmission.

[0067] The processor executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory, thereby realizing the information verification and processing method of the above-mentioned smart tax robot.

[0068] The input device can be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device can include display devices such as display screens.

[0069] The electronic device provided above can be used to execute the information verification and processing method of the smart tax robot provided in the above embodiment 1, and has corresponding functions and beneficial effects.

[0070] Embodiment 4: The embodiment of the present application also provides a storage medium containing computer executable instructions, which are used to execute a method for information verification and processing of a smart tax robot when executed by a computer processor. The method for information verification and processing of the smart tax robot includes: receiving application material information and invoice type application information for invoice application business input by the corresponding taxpayer; reviewing the application material information based on the set review rules, and if the application material information fails to pass the review, determining the problematic material information that does not meet the review rules, and outputting corresponding material supplement suggestions based on the problematic material information; after the application material information is reviewed, If the information has passed, the target field is extracted from the application material information, and the historical business database is queried according to the target field to obtain the related invoice application business. The average credit line information is determined based on the related invoice application business. The target fields include the application industry, application area, business scale and registered capital information; the historical business database is queried based on the taxpayer information to determine the taxpayer's historical application information; the application adjustment coefficient is calculated based on the taxpayer's credit information, business information and tax record; the real-time credit line is calculated based on the average credit line information, historical application information and application adjustment coefficient, and the taxpayer's current invoice application business is executed according to the real-time credit line.

[0071] Storage medium - any of various types of memory devices or storage devices. The term "storage medium" is intended to include: installation media, such as CD-ROM, floppy disk or tape device; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (such as hard disk or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the first computer system in which the program is executed, or may be located in a different second computer system, which is connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media residing in different locations (for example, in different computer systems connected by a network). The storage medium may store program instructions (for example, embodied as a computer program) that can be executed by one or more processors.

[0072] Of course, the storage medium containing computer executable instructions provided in the embodiment of the present application, whose computer executable instructions are not limited to the information verification and processing method of the smart tax robot as described above, can also execute related operations in the information verification and processing method of the smart tax robot provided in any embodiment of the present application.

[0073] The information verification and processing system, storage medium and electronic device of the smart tax robot provided in the above embodiments can execute the information verification and processing method of the smart tax robot provided in any embodiment of the present application. For technical details not described in detail in the above embodiments, please refer to the information verification and processing method of the smart tax robot provided in any embodiment of the present application.

[0074] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A method for verifying and processing information of a smart tax robot, characterized in that: include: Receive application materials information and invoice type application information for invoice application business input by the corresponding taxpayer; Review the application materials based on the set review rules, and if the application materials fail to pass the review, determine problematic materials that do not meet the review rules, and output corresponding material supplement suggestions based on the problematic materials; When the application materials information is reviewed and approved, the target field is extracted from the application materials information, the historical business database is queried according to the target field, the related invoice application business is obtained, and the average credit line information is determined based on the related invoice application business, and the target field includes the application industry, application area, business scale and registered capital information; the historical business database is queried based on the taxpayer information to determine the taxpayer's historical application information; the application adjustment coefficient is calculated based on the taxpayer's credit information, business information, and tax record; the real-time credit line is calculated based on the average credit line information, the historical application information and the application adjustment coefficient, and the taxpayer's current invoice application business is executed according to the real-time credit line.

2. The information verification and processing method of the intelligent tax robot according to claim 1 is characterized in that: The querying of the historical business database according to the target field to obtain the associated invoice claiming business, and determining the average credit limit information based on the associated invoice claiming business, includes: Constructing a database query statement according to the target field, querying a historical business database based on the database query statement, and determining a historical business database whose matching degree with the target field reaches a set threshold; The credit limit field information of each of the related invoice claiming businesses is extracted, and the average credit limit information is calculated based on the credit limit field information.

3. The information verification and processing method of the intelligent tax robot according to claim 1 is characterized in that: The calculation of the claim adjustment coefficient based on the taxpayer's credit information, business information, and tax payment record includes: Determine the corresponding indicator scores based on the taxpayer's credit information, business information, and tax records; The claim adjustment coefficient is calculated based on the weighted scores of each of the indicators.

4. The information verification and processing method of the intelligent tax robot according to claim 1 is characterized in that: The calculating of the real-time credit limit according to the average credit limit information, the historical application information and the application adjustment coefficient includes: Calculating initial credit limit information based on the average credit limit information and the credit limit adjustment coefficient; A real-time credit limit is determined based on the initial claim limit information and the historical claim limit information.

5. The information verification and processing method of the intelligent tax robot according to claim 1 is characterized in that: The review of the application materials based on the set review rules includes: The application materials information is input into a pre-built intelligent audit model, the text and structured data of the application materials information are identified based on the intelligent audit model, the corresponding audit indicators are determined, the audit indicators are compared with the set audit rules, and based on the comparison results, it is determined whether the application materials information has passed the audit.

6. The information verification and processing method of the intelligent tax robot according to claim 5 is characterized in that: The review rules are set based on the type, format, quantity, validity period, and content requirement information of the application materials.

7. The information verification and processing method of the intelligent tax robot according to claim 1 is characterized in that: The outputting corresponding material supplement suggestions based on the problematic material information includes: Selecting a corresponding supplementary suggestion template based on the type of the problem material information, and determining corresponding supplementary content based on the problem material information; Generate corresponding material supplement suggestions based on the supplement suggestion template and the supplement content.

8. An information verification and processing system for a smart tax robot, characterized in that: include: A receiving module, used to receive application material information and invoice type application information for invoice application business input by the corresponding taxpayer; A first review module is used to review the application materials information based on the set review rules, and if the application materials information fails to pass the review, determine the problematic materials information that does not meet the review rules, and output corresponding material supplement suggestions based on the problematic materials information; The second audit module is used to extract the target field from the application material information if the application material information is audited and passed, query the historical business database according to the target field, obtain the related invoice application business, and determine the average credit line information based on the related invoice application business, the target field includes the application industry, application area, business scale and registered capital information; query the historical business database based on the taxpayer information to determine the taxpayer's historical application information; calculate the application adjustment coefficient based on the taxpayer's credit information, business information, and tax record; calculate the real-time credit line according to the average credit line information, the historical application information and the application adjustment coefficient, and execute the taxpayer's current invoice application business according to the real-time credit line.

9. An electronic device, characterized in that: include: memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the information verification and processing method of the intelligent tax robot as described in any one of claims 1-7.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions, when executed by a computer processor, are used to execute the information verification and processing method of the smart tax robot as described in any one of claims 1-7.

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