Finance and tax data processing method and processing system

Abstract

The invention discloses a finance and taxation data processing method and system, relates to the technical field of data storage processing, and classifies finance and taxation information resources into structured and unstructured data, so that an enterprise can more clearly know the composition of own data. The classification is beneficial to subsequent storage, query and analysis, data confusion is avoided, and the internal relation between structured and unstructured finance and tax data can be accurately found out through relevance evaluation. Therefore, the enterprise does not ignore data which seems to be independent but actually correlated, the data with remarkable correlation is integrated, the finance and taxation conditions of the enterprise can be reflected more comprehensively, the correlated data are stored in a unified mode, financial evaluation values and insight evaluation values are analyzed, multi-dimensional data factors are considered in the mode, and the enterprise finance and taxation evaluation efficiency is improved. Potential risks are judged according to the comprehensive risk assessment value, early warning display is carried out according to the risk types, and an enterprise can take corresponding measures according to specific risk conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of data storage and processing, and in particular to a financial and taxation data processing method and processing system. Background Art

[0002] With the continuous expansion of corporate business and the improvement of digitalization, the amount of financial and tax data has shown a rapid growth trend. Enterprises not only have to deal with traditional structured data such as financial statements and account books, but also have to deal with a large amount of unstructured data, such as electronic contracts, emails, scanned documents, etc. These massive data are scattered in different systems and platforms, which poses challenges to the effective management and utilization of data, prompting enterprises to seek more efficient data processing methods. Therefore, a financial and tax data processing method and processing system are needed.

[0003] Prior art, such as an invention patent application with announcement number CN118536815A, discloses a method, device, electronic device and storage medium for early warning of enterprise security risks, which obtains the target enterprise management data corresponding to the target enterprise and the associated enterprise management data corresponding to each target associated enterprise, determines the first enterprise risk assessment value and the first early warning level corresponding to the target enterprise, determines the second enterprise risk assessment value and the second early warning level corresponding to each target associated enterprise, determines the enterprise comprehensive risk assessment value corresponding to the target enterprise in combination with the target weight superposition rule, determines the early warning result corresponding to the target enterprise according to the enterprise comprehensive risk assessment value, and performs risk early warning according to the early warning result. This application can take into account the association relationship between enterprises, establish a scientific and rational enterprise risk early warning process, improve the accuracy and efficiency of enterprise risk early warning, and meet the existing enterprise risk early warning needs. This application is widely used in the field of enterprise management technology.

[0004] The above scheme has the following technical problems: 1. The structured financial and tax data and unstructured financial and tax data of the existing technology are usually stored in different systems or locations, making it difficult to establish effective associations. For example, structured data such as financial statements are stored in the company's financial system, while unstructured data such as contracts and emails may be scattered in the document management systems of various departments, resulting in the inability to directly communicate and collaborate between data, forming information islands, affecting the company's comprehensive understanding and comprehensive analysis of financial and tax information. Due to the lack of a systematic correlation evaluation and integration method, it is difficult to accurately explore the potential correlation between structured and unstructured data. This may cause the company to miss some important information associations, such as the association between data in market trend analysis reports and sales data in financial statements, and fail to provide a more comprehensive and in-depth basis for corporate decision-making.

[0005] 2. Existing technologies often focus on the analysis of structured financial and tax data, such as financial ratios and budget execution, while ignoring the risk information contained in unstructured data. Market dynamics, policy changes, customer feedback and other information in unstructured data have a significant impact on the financial and tax status of enterprises. If they are not included in the risk assessment system, the risk assessment results will not be comprehensive and accurate enough, and potential risks will not be discovered in a timely manner. There is a lack of unified storage and comprehensive analysis of data with significant correlations, which makes risk warning signals not timely and accurate enough. For example, an enterprise may not realize the risk until there are obvious problems in the financial statements, but fail to find relevant clues in the unstructured data in advance, resulting in missing the best time to respond to risks and increasing the company's losses. Summary of the invention

[0006] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide a financial and tax data processing method and processing system.

[0007] To solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a method for processing financial and tax data, including: Step 1, processing of financial and tax data: obtaining the financial and tax information resources of the target enterprise in the current period, and classifying the financial and tax information resources of the target enterprise in the current period, and then obtaining various unstructured financial and tax data and various structured financial and tax data.

[0008] Step 2: Correlation evaluation: Analyze the correlation adaptation value between each structured financial and tax data and each unstructured financial and tax data, and then evaluate whether the correlation between each structured financial and tax data and each unstructured financial and tax data is significant.

[0009] Step 3: Risk warning analysis: All structured financial and tax data with significant correlation and all unstructured financial and tax data are stored in the same node, so as to analyze the financial evaluation value and insight evaluation value corresponding to each node, and obtain the comprehensive risk evaluation value corresponding to the current cycle of the target enterprise.

[0010] Step 4. Early warning of risk type: Based on the comprehensive risk assessment value corresponding to the current cycle of the target enterprise, determine whether the current cycle of the target enterprise has potential risks. If the current cycle of the target enterprise has potential risks, obtain the risk type corresponding to the current cycle of the target enterprise and display an early warning.

[0011] Preferably, the acquisition of the target enterprise's current cycle corporate finance and tax information resources is specifically carried out as follows: A1. Use the report export function of the financial software to regularly generate financial statements and tax return forms, extract relevant financial and tax emails and attachments from the enterprise's email system, and scan paper invoices, contracts, and audit reports, and use OCR technology to convert them into editable texts, integrate the various types of collected data, and obtain the target enterprise's current cycle corporate finance and tax information resources.

[0012] A2. Mark the various financial and tax data that meet the characteristics of structured financial and tax data in the financial and tax information resources of the target enterprise in the current period as structured financial and tax data, and mark the various financial and tax data that meet the characteristics of unstructured financial and tax data as unstructured financial and tax data.

[0013] Preferably, the analysis of the correlation adaptation value corresponding to each structured financial and tax data and each unstructured financial and tax data, the specific analysis process is as follows: B1, obtain the correlation data corresponding to each structured financial and tax data and each unstructured financial and tax data, the correlation data includes the Pearson correlation coefficient, the Spearman rank correlation coefficient, the mutual information value and the determination coefficient.

[0014] B2. The Pearson correlation coefficient, Spearman rank correlation coefficient, mutual information value and determination coefficient corresponding to each structured tax data and each unstructured tax data are recorded as , , and ,in, Indicates the number corresponding to each structured financial and tax data. , is a positive integer, Indicates the number corresponding to each unstructured financial and tax data. , Is a positive integer, substitute into the calculation formula: In the above example, the correlation adaptation value corresponding to each structured financial and tax data and each unstructured financial and tax data is obtained. ,in, , , , They are the standard Pearson correlation coefficient, standard Spearman rank correlation coefficient, standard mutual information value, and standard determination coefficient corresponding to the set structured financial and tax data and unstructured financial and tax data, respectively. , , , They are the weight factors corresponding to the Pearson correlation coefficient between the structured financial and taxation data and the unstructured financial and taxation data, the weight factors corresponding to the Spearman rank correlation coefficient, the weight factors corresponding to the mutual information value, and the weight factors corresponding to the determination coefficient.

[0015] Preferably, the evaluation of whether the correlation between each structured financial and tax data and each unstructured financial and tax data is significant is carried out as follows: the correlation adaptation value between each structured financial and tax data and each unstructured financial and tax data is compared with the set correlation adaptation value between the standard structured financial and tax data and the unstructured financial and tax data. If the correlation adaptation value between a certain structured financial and tax data and a certain unstructured financial and tax data is greater than or equal to the set correlation adaptation value between the standard structured financial and tax data and the unstructured financial and tax data, it means that the correlation between the structured financial and tax data and the unstructured financial and tax data is significant. If the correlation adaptation value between a certain structured financial and tax data and a certain unstructured financial and tax data is less than the set correlation adaptation value between the standard structured financial and tax data and the unstructured financial and tax data, it means that the correlation between the structured financial and tax data and the unstructured financial and tax data is not significant. In this way, it is evaluated whether the correlation between each structured financial and tax data and each unstructured financial and tax data is significant.

[0016] Preferably, the structured financial and tax data and the unstructured financial and tax data with significant correlation are stored in the same node. The specific storage process is as follows: if a certain structured financial and tax data and a certain unstructured financial and tax data are stored in the same node, a new field is added to the structured data table in the node, and the new field will store the unstructured financial and tax data in the node.

[0017] Preferably, the financial evaluation value corresponding to each structured financial and tax data in each node and the insight evaluation value corresponding to each unstructured financial and tax data are analyzed, and the specific analysis process is as follows: C1. Obtain the current ratio, debt-to-asset ratio and tax compliance rate corresponding to each structured financial and tax data in each node, and input the current ratio, debt-to-asset ratio and tax compliance rate corresponding to each structured financial and tax data in each node into the financial evaluation model, and output the financial evaluation value corresponding to each node.

[0018] C2. Obtain the number of negative news and risk-related keywords corresponding to each unstructured financial and tax data in each node, and input the number of negative news and risk-related keywords corresponding to each unstructured financial and tax data in each node into the insight evaluation model, and output the insight evaluation value corresponding to each node.

[0019] Preferably, the analysis obtains the comprehensive risk assessment value corresponding to the current cycle of the target enterprise. The specific analysis process is as follows: the financial assessment value and insight assessment value corresponding to each node are recorded as and ,in, Indicates the number corresponding to each node, , u is a positive integer, substitute into the calculation formula: The comprehensive risk assessment value corresponding to the current cycle of the target enterprise is obtained ,in, , They are the weight factors corresponding to the set node financial evaluation value and the weight factors corresponding to the insight evaluation value, and e represents a natural constant.

[0020] Preferably, the specific analysis process for judging whether the target enterprise has potential risks in the current cycle is as follows: comparing the comprehensive risk assessment value corresponding to the current cycle of the target enterprise with the set comprehensive risk assessment value interval corresponding to each risk type of the enterprise; if the comprehensive risk assessment value corresponding to the current cycle of the target enterprise is within the set comprehensive risk assessment value interval corresponding to a certain risk type of the enterprise, then it is judged that the target enterprise has potential risks in the current cycle; if none of the comprehensive risk assessment values ​​corresponding to the current cycle of the target enterprise are within the set comprehensive risk assessment value interval corresponding to a certain risk type of the enterprise, then it is judged that the target enterprise does not have potential risks in the current cycle.

[0021] Preferably, the risk type corresponding to the current cycle of the target enterprise is obtained and an early warning is displayed. The specific early warning process is as follows: D1. If the comprehensive risk assessment value corresponding to the current cycle of the target enterprise is within the set comprehensive risk assessment value interval corresponding to a certain risk type of the enterprise, then the risk type is recorded as the risk type corresponding to the current cycle of the target enterprise.

[0022] D2. If the risk type corresponding to the current cycle of the target enterprise is financial risk, a red flashing "financial risk" icon warning will be displayed on the home page and financial report page of the enterprise financial management system. When the mouse hovers over the icon, a brief risk warning will be displayed. At the same time, an email will be sent in time to notify the public relations team for processing.

[0023] D3. If the risk type corresponding to the current cycle of the target enterprise is compliance risk, a yellow flashing "compliance risk" icon warning will be displayed on the homepage of the enterprise compliance management system and the relevant business process page. When the mouse hovers over the icon, a brief risk warning will be displayed. At the same time, on the compliance matters list page, compliance items with risks will be highlighted in red font, and an email will be sent in time to notify the public relations team for processing.

[0024] D4. If the risk type corresponding to the current cycle of the target enterprise is operational risk, a blue flashing "operational risk" icon warning will be displayed on the main interface of the enterprise business operation management system. When the mouse hovers over the icon, the specific type of operational risk will be displayed. In addition, on the specific business operation page, the risk operation steps will be marked with a red border, and an email will be sent in time to notify the public relations team for processing.

[0025] D5. If the risk type corresponding to the current cycle of the target enterprise is reputation risk, an orange flashing "reputation risk" icon will be displayed as a warning in the enterprise public relations management system and at the bottom of the enterprise official website homepage. When the mouse hovers over the icon, an overview of the current reputation risk will be displayed. At the same time, on the social media monitoring platform, negative topics involving the enterprise will be highlighted, and an email will be sent in time to notify the public relations team to handle it.

[0026] In a second aspect, the present invention provides a financial and tax data processing system, including: a financial and tax data processing module: used to obtain the financial and tax information resources of the target enterprise in the current period, and classify the financial and tax information resources of the target enterprise in the current period, so as to obtain various unstructured financial and tax data and various structured financial and tax data.

[0027] Correlation evaluation module: used to analyze the correlation adaptation value between each structured financial and tax data and each unstructured financial and tax data, and then evaluate whether the correlation between each structured financial and tax data and each unstructured financial and tax data is significant.

[0028] Risk warning analysis module: used to store all structured financial and tax data and unstructured financial and tax data with significant correlation in the same node, so as to analyze the financial evaluation value and insight evaluation value corresponding to each node, and obtain the comprehensive risk evaluation value corresponding to the current cycle of the target enterprise.

[0029] Risk type warning module: used to determine whether the target enterprise has potential risks in the current cycle based on the comprehensive risk assessment value corresponding to the current cycle of the target enterprise. If the target enterprise has potential risks in the current cycle, the risk type corresponding to the current cycle of the target enterprise is obtained and a warning is displayed.

[0030] The beneficial effects of the present invention are as follows: 1. The embodiment of the present invention classifies financial and tax information resources into structured and unstructured data, so that enterprises can more clearly understand the composition of their own data. This classification is helpful for subsequent storage, query and analysis, avoids data confusion, and improves the efficiency of data management. For example, structured data such as financial statements can be stored and managed in a predetermined form, and unstructured data such as contracts and emails can also be processed in a targeted manner, just like establishing an orderly folder system for messy files. At the same time, the evaluation of correlation can accurately find the intrinsic connection between structured and unstructured financial and tax data. This prevents enterprises from ignoring data that seems independent but is actually interrelated, and integrates data with significant correlation, which can more comprehensively reflect the financial and tax status of the enterprise. For example, the unstructured data of a procurement contract is associated with structured data such as procurement costs and accounts payable. After integration, the impact of procurement business on finance can be analyzed more deeply.

[0031] 2. In an embodiment of the present invention, the associated data is uniformly stored and analyzed for financial evaluation values ​​and insight evaluation values, and then a comprehensive risk evaluation value is obtained. This method takes into account multi-dimensional data factors. It includes not only structured data such as traditional financial indicators, but also information in unstructured data, such as market trend analysis reports, potential risk warnings in internal communication emails, etc. The comprehensive risk evaluation value obtained in this way reflects the risk status of the enterprise more comprehensively and accurately, avoiding the evaluation bias caused by a single data source. The comprehensive risk evaluation value can help enterprises gain in-depth insights into the potential risks hidden behind complex data. For example, through association analysis, information about the decline in market share of a certain product may be found, such as the correlation between unstructured data and the reduction in sales revenue of the product, thereby providing early warning of the financial risks that the relevant business lines of the product may face, so that the company has more time to prepare response strategies.

[0032] 3. In the embodiment of the present invention, potential risks are judged according to the comprehensive risk assessment value, and early warnings are displayed according to the risk type, so that enterprises can take corresponding measures for specific risk situations. Different risk types, such as financial risks, compliance risks, etc., have different response strategies. This targeted early warning allows relevant departments to act quickly. For example, for financial risks, financial strategies can be adjusted in time or funds can be prepared; for compliance risks, self-inspection and rectification can be carried out quickly. Accurate risk early warning provides strong support for the decision-making of the enterprise management. The management can adjust the business strategy and optimize resource allocation in time according to the early warning information to avoid major losses caused by the outbreak of risks. For example, after receiving the potential market risk early warning, the product development direction or market promotion strategy can be adjusted in advance to improve the initiative and flexibility of the enterprise to deal with risks and ensure the stable development of the enterprise. Through this systematic risk early warning mechanism, the overall risk response capability of the enterprise is enhanced. From data processing to risk assessment to early warning display, a complete closed loop is formed, enabling enterprises to intervene in time at different stages of risk development. This helps to reduce the impact of risks on enterprises, protect the asset security and reputation of enterprises, and enhance the survival and competitiveness of enterprises in complex market environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

[0034] Figure 1 The present invention is a flowchart of the steps for implementing the method.

[0035] Figure 2 It is a schematic diagram of the connection of the system modules of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments 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 creative work are within the scope of protection of the present invention.

[0037] Embodiments of the present invention Figure 1As shown, a method for processing financial and tax data includes: Step 1, processing of financial and tax data: obtaining the financial and tax information resources of the target enterprise in the current period, and classifying the financial and tax information resources of the target enterprise in the current period, and then obtaining various unstructured financial and tax data and various structured financial and tax data.

[0038] It should be noted that the structured financial and tax data include: balance sheet, income statement, cash flow statement, etc., and the unstructured financial and tax data include: public comments on the company's financial status, various analysis reports, finance and tax-related emails, invoice scans and image materials, etc.

[0039] In a specific embodiment, the target enterprise's current cycle corporate finance and tax information resources are obtained, and the specific acquisition process is as follows: A1. Use the report export function of the financial software to regularly generate financial statements and tax return forms, extract relevant financial and tax emails and attachments from the company's email system, and scan paper invoices, contracts, and audit reports. Use OCR technology to convert them into editable text, integrate the collected data of various types, and obtain the target enterprise's current cycle corporate finance and tax information resources.

[0040] A2. Mark the various financial and tax data that meet the characteristics of structured financial and tax data in the financial and tax information resources of the target enterprise in the current period as structured financial and tax data, and mark the various financial and tax data that meet the characteristics of unstructured financial and tax data as unstructured financial and tax data.

[0041] It should be noted that the definition and characteristics of structured data are as follows: structured financial and tax data usually has a clear data format and structure, and is easy to store, query and analyze. For example, the data in the financial statement is presented in a table format, with each column representing a specific financial indicator and each row representing an accounting period or a business unit. The data in the tax return form also has a fixed format and filling requirements, including taxpayer information, tax items, amounts, etc. These data can be directly stored in a relational database and efficiently retrieved and analyzed through query languages ​​such as SQL. Marking the financial and tax data that meets the characteristics of structured financial and tax data as structured financial and tax data can facilitate subsequent data processing and analysis. The marking method can be judged based on the source, format and content of the data. For example, report data exported from financial software, electronic document data with a clear table structure, etc. can be directly marked as structured financial and tax data. The marked structured financial and tax data can be further classified and sorted, such as classified and stored according to the category of financial statements or the type of tax return form, so as to facilitate subsequent analysis and processing.

[0042] It is also necessary to explain the definition and characteristics of unstructured data: unstructured financial and tax data usually has no fixed format and structure, and is difficult to store and analyze directly. For example, the text content in financial and tax emails, the text and images in scanned paper documents, and the discussion content in meeting minutes are all unstructured financial and tax data. These data usually contain rich information, but further processing and analysis are required to extract useful financial and tax data. Marking financial and tax data that meet the characteristics of unstructured financial and tax data as unstructured financial and tax data can clarify the type and processing method of the data. The marking method can be judged based on the source, format and content of the data. For example, emails and attachments extracted from the email system, scanned paper document data, and financial and tax-related content in audio and video files can be marked as unstructured financial and tax data. The marked unstructured financial and tax data can be processed and analyzed using natural language processing, image recognition and other technologies to extract key information, such as financial indicators in emails, key terms in contract terms, opinions in audit reports, etc., so as to facilitate association and analysis with structured financial and tax data.

[0043] Step 2: Correlation evaluation: Analyze the correlation adaptation value between each structured financial and tax data and each unstructured financial and tax data, and then evaluate whether the correlation between each structured financial and tax data and each unstructured financial and tax data is significant.

[0044] In a specific embodiment, the analysis of the correlation adaptation value corresponding to each structured financial and tax data and each unstructured financial and tax data, the specific analysis process is as follows: B1, obtain the correlation data corresponding to each structured financial and tax data and each unstructured financial and tax data, the correlation data includes the Pearson correlation coefficient, the Spearman rank correlation coefficient, the mutual information value and the determination coefficient.

[0045] B2. The Pearson correlation coefficient, Spearman rank correlation coefficient, mutual information value and determination coefficient corresponding to each structured tax data and each unstructured tax data are recorded as , , and ,in, Indicates the number corresponding to each structured financial and tax data. , is a positive integer, Indicates the number corresponding to each unstructured financial and tax data. , Is a positive integer, substitute into the calculation formula: In the above example, the correlation adaptation value corresponding to each structured financial and tax data and each unstructured financial and tax data is obtained. ,in, , , , They are the standard Pearson correlation coefficient, standard Spearman rank correlation coefficient, standard mutual information value, and standard determination coefficient corresponding to the set structured financial and tax data and unstructured financial and tax data, respectively. , , , They are the weight factors corresponding to the Pearson correlation coefficient between the structured financial and taxation data and the unstructured financial and taxation data, the weight factors corresponding to the Spearman rank correlation coefficient, the weight factors corresponding to the mutual information value, and the weight factors corresponding to the determination coefficient.

[0046] It should be noted that , , , Both are greater than 0 and less than 1.

[0047] It should also be noted that through the summary of a large amount of research data and experimental data. According to professional institutions and research institutions, the standard Pearson correlation coefficient, standard Spearman rank correlation coefficient, standard mutual information value, and standard determination coefficient corresponding to structured taxation data and unstructured taxation data are set. At the same time, based on the professional knowledge and research basis of experts in the field, and discussed and confirmed with industry organizations or professional institutions. Experts set the weight factors corresponding to the Pearson correlation coefficient of structured taxation data and unstructured taxation data, the weight factors corresponding to the Spearman rank correlation coefficient, the weight factors corresponding to the mutual information value, and the weight factors corresponding to the determination coefficient based on their own experience and knowledge.

[0048] It should be noted again that the standard Pearson correlation coefficient, the standard Spearman rank correlation coefficient, the standard mutual information value, and the standard determination coefficient are the Pearson correlation coefficient threshold, the Spearman rank correlation coefficient threshold, the mutual information value threshold, and the determination coefficient threshold, respectively. For example, the standard Pearson correlation coefficient is 1, the standard Spearman rank correlation coefficient is 0.5, the standard mutual information value is 1, and the standard determination coefficient is 0.5.

[0049] In another specific embodiment, the evaluation of whether the correlation between each structured financial and tax data and each unstructured financial and tax data is significant is as follows: the correlation adaptation value between each structured financial and tax data and each unstructured financial and tax data is compared with the set standard structured financial and tax data and unstructured financial and tax data correlation adaptation value. If the correlation adaptation value between a certain structured financial and tax data and a certain unstructured financial and tax data is greater than or equal to the set standard structured financial and tax data and unstructured financial and tax data correlation adaptation value, then it means that the correlation between the structured financial and tax data and the unstructured financial and tax data is significant. If the correlation adaptation value between a certain structured financial and tax data and a certain unstructured financial and tax data is less than the set standard structured financial and tax data and unstructured financial and tax data correlation adaptation value, then it means that the correlation between the structured financial and tax data and the unstructured financial and tax data is not significant. In this way, it is evaluated whether the correlation between each structured financial and tax data and each unstructured financial and tax data is significant.

[0050] Step 3: Risk warning analysis: All structured financial and tax data with significant correlation and all unstructured financial and tax data are stored in the same node, so as to analyze the financial evaluation value and insight evaluation value corresponding to each node, and obtain the comprehensive risk evaluation value corresponding to the current cycle of the target enterprise.

[0051] In a specific embodiment, the structured financial and tax data and the unstructured financial and tax data with significant correlation are stored in the same node. The specific storage process is as follows: if a certain structured financial and tax data and a certain unstructured financial and tax data are stored in the same node, a new field is added to the structured data table in the node, and the new field will store the unstructured financial and tax data in the node.

[0052] In an embodiment of the present invention, financial and tax information resources are classified into structured and unstructured data, so that enterprises can more clearly understand the composition of their own data. This classification is helpful for subsequent storage, query and analysis, avoids data confusion, and improves the efficiency of data management. For example, structured data such as financial statements can be stored and managed in a predetermined form, and unstructured data such as contracts and emails can also be processed in a targeted manner, just like establishing an orderly folder system for messy files. At the same time, the evaluation of correlation can accurately find the intrinsic connection between structured and unstructured financial and tax data. This prevents enterprises from ignoring data that seems independent but is actually interrelated, and integrates data with significant correlation, which can more comprehensively reflect the financial and tax status of the enterprise. For example, the unstructured data of a procurement contract is associated with structured data such as procurement costs and accounts payable. After integration, the impact of procurement business on finance can be analyzed more deeply.

[0053] In a specific embodiment, the financial evaluation value corresponding to each structured financial and tax data in each node and the insight evaluation value corresponding to each unstructured financial and tax data are analyzed, and the specific analysis process is as follows: C1. Obtain the current ratio, debt-to-asset ratio and tax compliance rate corresponding to each structured financial and tax data in each node, and input the current ratio, debt-to-asset ratio and tax compliance rate corresponding to each structured financial and tax data in each node into the financial evaluation model, and output the financial evaluation value corresponding to each node.

[0054] It should be noted that the company's balance sheet and income statement, tax return and related tax records should be obtained. The current ratio is the ratio of current assets to current liabilities, the debt-to-asset ratio is the ratio of total liabilities to total assets, and the tax compliance rate refers to the ratio of the actual taxes paid by the company to the taxes payable.

[0055] It should also be noted that the analysis process of the financial evaluation value corresponding to each node is as follows: the current ratio, debt-to-asset ratio and tax compliance rate corresponding to each structured financial and tax data in each node are normalized, and the current ratio, debt-to-asset ratio and tax compliance rate corresponding to each structured financial and tax data in each node after processing are recorded as , and , substitute into the analysis formula: , get the financial evaluation value corresponding to each node , , , They are the weight coefficients corresponding to the set structured financial and tax data flow ratio, the weight coefficient corresponding to the asset-liability ratio, and the weight coefficient corresponding to the tax compliance rate. i represents the number corresponding to each node, and i is a positive integer. Indicates the number corresponding to each structured financial and tax data. Is a positive integer.

[0056] C2. Obtain the number of negative news and risk-related keywords corresponding to each unstructured financial and tax data in each node, and input the number of negative news and risk-related keywords corresponding to each unstructured financial and tax data in each node into the insight evaluation model, and output the insight evaluation value corresponding to each node.

[0057] It should be noted that sentiment analysis tools or algorithms are used to perform sentiment classification on the texts in various unstructured financial and taxation data, determine the sentiment tendency of the news, and count the number of news marked as negative after sentiment analysis.

[0058] It should also be noted that the analysis process of the insight evaluation value corresponding to each node is as follows: the number of negative news and the number of risk-related keywords corresponding to each unstructured financial and taxation data in each node are normalized, and the number of negative news and the number of risk-related keywords corresponding to each unstructured financial and taxation data in each node after processing are recorded as and , substitute into the analysis formula: , get the insight evaluation value corresponding to each node , , They are the weight coefficients corresponding to the number of negative news on unstructured financial and taxation data and the weight coefficients corresponding to the number of risk-related keywords, respectively. i represents the number corresponding to each node, i is a positive integer, and h represents the number corresponding to each structured financial and taxation data, h is a positive integer. In a specific embodiment, the analysis obtains the comprehensive risk assessment value corresponding to the current cycle of the target enterprise. The specific analysis process is as follows: the financial assessment value and insight assessment value corresponding to each node are recorded as and ,in, Indicates the number corresponding to each node, , Is a positive integer, substitute into the calculation formula: The comprehensive risk assessment value corresponding to the current cycle of the target enterprise is obtained ,in, , They are the weight factors corresponding to the set node financial evaluation value and the weight factors corresponding to the insight evaluation value, and e represents a natural constant.

[0059] It should be noted that , Both are greater than 0 and less than 1.

[0060] It should also be noted that the weight factors corresponding to the node financial evaluation value and the weight factors corresponding to the insight evaluation value are set by experts based on their own experience and knowledge, based on the professional knowledge and research of field experts and after discussion and confirmation with industry organizations or professional institutions.

[0061] Step 4. Early warning of risk type: Based on the comprehensive risk assessment value corresponding to the current cycle of the target enterprise, determine whether the current cycle of the target enterprise has potential risks. If the current cycle of the target enterprise has potential risks, obtain the risk type corresponding to the current cycle of the target enterprise and display an early warning.

[0062] In a specific embodiment, the determination of whether the target enterprise has potential risks in the current cycle is performed by comparing the comprehensive risk assessment value corresponding to the current cycle of the target enterprise with the set comprehensive risk assessment value interval corresponding to each risk type of the enterprise. If the comprehensive risk assessment value corresponding to the current cycle of the target enterprise is within the set comprehensive risk assessment value interval corresponding to a certain risk type of the enterprise, then the target enterprise is judged to have potential risks in the current cycle. If none of the comprehensive risk assessment values ​​corresponding to the current cycle of the target enterprise are within the set comprehensive risk assessment value interval corresponding to a certain risk type of the enterprise, then it is determined that the target enterprise does not have potential risks in the current cycle.

[0063] In an embodiment of the present invention, the associated data is uniformly stored and analyzed for financial evaluation values ​​and insight evaluation values, thereby obtaining a comprehensive risk evaluation value. This approach takes into account multi-dimensional data factors. It includes not only structured data such as traditional financial indicators, but also information in unstructured data, such as market trend analysis reports, potential risk warnings in internal communication emails, etc. The comprehensive risk evaluation value obtained in this way reflects the risk status of the enterprise more comprehensively and accurately, avoiding the evaluation bias caused by a single data source. The comprehensive risk evaluation value can help enterprises gain in-depth insights into potential risks hidden behind complex data. For example, through association analysis, information about a decline in the market share of a product may be found, such as the correlation between unstructured data and the reduction in sales revenue of the product, thereby providing early warning of the financial risks that may be faced by the product's related business lines, allowing the company to have more time to prepare response strategies.

[0064] In another specific embodiment, the risk type corresponding to the current cycle of the target enterprise is obtained, and an early warning is displayed. The specific early warning process is as follows: D1. If the comprehensive risk assessment value corresponding to the current cycle of the target enterprise is within the comprehensive risk assessment value interval corresponding to a certain risk type of the set enterprise, then the risk type is recorded as the risk type corresponding to the current cycle of the target enterprise.

[0065] D2. If the risk type corresponding to the current cycle of the target enterprise is financial risk, a red flashing "financial risk" icon warning will be displayed on the home page and financial report page of the enterprise financial management system. When the mouse hovers over the icon, a brief risk warning will be displayed. At the same time, an email will be sent in time to notify the public relations team for processing.

[0066] D3. If the risk type corresponding to the current cycle of the target enterprise is compliance risk, a yellow flashing "compliance risk" icon warning will be displayed on the homepage of the enterprise compliance management system and the relevant business process page. When the mouse hovers over the icon, a brief risk warning will be displayed. At the same time, on the compliance matters list page, compliance items with risks will be highlighted in red font, and an email will be sent in time to notify the public relations team for processing.

[0067] D4. If the risk type corresponding to the current cycle of the target enterprise is operational risk, a blue flashing "operational risk" icon warning will be displayed on the main interface of the enterprise business operation management system. When the mouse hovers over the icon, the specific type of operational risk will be displayed. In addition, on the specific business operation page, the risk operation steps will be marked with a red border, and an email will be sent in time to notify the public relations team for processing.

[0068] D5. If the risk type corresponding to the current cycle of the target enterprise is reputation risk, an orange flashing "reputation risk" icon will be displayed as a warning in the enterprise public relations management system and at the bottom of the enterprise official website homepage. When the mouse hovers over the icon, an overview of the current reputation risk will be displayed. At the same time, on the social media monitoring platform, negative topics involving the enterprise will be highlighted, and an email will be sent in time to notify the public relations team to handle it.

[0069] In the embodiment of the present invention, potential risks are judged according to the comprehensive risk assessment value, and early warning is displayed according to the risk type, so that the enterprise can take corresponding measures according to the specific risk situation. Different risk types, such as financial risk, compliance risk, etc., have different response strategies. This targeted early warning can allow relevant departments to act quickly. For example, for financial risks, financial strategies can be adjusted in time or funds can be prepared; for compliance risks, self-inspection and rectification can be carried out quickly, and accurate risk early warning provides strong support for the decision-making of the enterprise management. The management can adjust the business strategy and optimize resource allocation in time according to the early warning information to avoid major losses caused by the outbreak of risks. For example, after receiving the potential market risk early warning, the product research and development direction or market promotion strategy can be adjusted in advance, the initiative and flexibility of the enterprise to deal with risks can be improved, and the stable development of the enterprise can be guaranteed. Through this systematic risk early warning mechanism, the overall risk response ability of the enterprise is enhanced. From data processing to risk assessment to early warning display, a complete closed loop is formed, enabling enterprises to intervene in time at different stages of risk development. This helps to reduce the impact of risks on enterprises, protect the asset security and reputation of enterprises, and enhance the survival and competitiveness of enterprises in complex market environments.

[0070] Embodiments of the present invention Figure 2 As shown, a financial and taxation data processing system includes: a financial and taxation data processing module, a correlation evaluation module, a risk warning analysis module and a risk type warning module.

[0071] Financial and tax data processing module: used to obtain the financial and tax information resources of the target enterprise in the current period, and classify the financial and tax information resources of the target enterprise in the current period, and then obtain various unstructured financial and tax data and various structured financial and tax data; Relevance evaluation module: used to analyze the relevance adaptation value between each structured fiscal and taxation data and each unstructured fiscal and taxation data, and then evaluate whether the relevance between each structured fiscal and taxation data and each unstructured fiscal and taxation data is significant; Risk warning analysis module: used to store various structured financial and tax data and various unstructured financial and tax data with significant correlation in the same node, so as to analyze the financial evaluation value and insight evaluation value corresponding to each node, and obtain the comprehensive risk evaluation value corresponding to the current cycle of the target enterprise; Risk type warning module: used to determine whether the target enterprise has potential risks in the current cycle based on the comprehensive risk assessment value corresponding to the current cycle of the target enterprise. If the target enterprise has potential risks in the current cycle, the risk type corresponding to the current cycle of the target enterprise is obtained and a warning is displayed.

[0072] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they shall all fall within the protection scope of the present invention.

Claims

1. A method for processing financial and tax data, characterized in that: include: Step 1: Processing of financial and tax data: Obtain the financial and tax information resources of the target enterprise in the current period, and classify the financial and tax information resources of the target enterprise in the current period, and then obtain various unstructured financial and tax data and various structured financial and tax data; Step 2: Evaluation of correlation: Analyze the correlation adaptation value between each structured fiscal and taxation data and each unstructured fiscal and taxation data, and then evaluate whether the correlation between each structured fiscal and taxation data and each unstructured fiscal and taxation data is significant; Step 3: Risk warning analysis: All structured financial and tax data and unstructured financial and tax data with significant correlation are stored in the same node, so as to analyze the financial evaluation value and insight evaluation value corresponding to each node, and obtain the comprehensive risk evaluation value corresponding to the current cycle of the target enterprise; Step 4. Early warning of risk type: Based on the comprehensive risk assessment value corresponding to the current cycle of the target enterprise, determine whether the current cycle of the target enterprise has potential risks. If the current cycle of the target enterprise has potential risks, obtain the risk type corresponding to the current cycle of the target enterprise and display an early warning.

2. A method for processing financial and tax data according to claim 1, characterized in that: The specific acquisition process of obtaining the target enterprise's current cycle corporate finance and taxation information resources is as follows: A1. Use the report export function of financial software to generate financial statements and tax declaration forms regularly, extract relevant financial and tax emails and attachments from the company's email system, scan paper invoices, contracts, and audit reports, and use OCR technology to convert them into editable text. Integrate the collected data to obtain the target company's current cycle corporate finance and tax information resources; A2. Mark the various financial and tax data that meet the characteristics of structured financial and tax data in the financial and tax information resources of the target enterprise in the current period as structured financial and tax data, and mark the various financial and tax data that meet the characteristics of unstructured financial and tax data as unstructured financial and tax data.

3. A method for processing financial and tax data as claimed in claim 2, characterized in that: The analysis of the correlation adaptation value corresponding to each structured financial and taxation data and each unstructured financial and taxation data is specifically performed as follows: B1. Obtain the correlation data corresponding to each structured financial and taxation data and each unstructured financial and taxation data, the correlation data including the Pearson correlation coefficient, the Spearman rank correlation coefficient, the mutual information value and the determination coefficient; B2. The Pearson correlation coefficient, Spearman rank correlation coefficient, mutual information value and determination coefficient corresponding to each structured tax data and each unstructured tax data are recorded as , , and ,in, Indicates the number corresponding to each structured financial and tax data. , is a positive integer, Indicates the number corresponding to each unstructured financial and tax data. , h is a positive integer, substitute it into the calculation formula: In the above example, the correlation adaptation value corresponding to each structured financial and tax data and each unstructured financial and tax data is obtained. ,in, , , , They are the standard Pearson correlation coefficient, standard Spearman rank correlation coefficient, standard mutual information value, and standard determination coefficient corresponding to the set structured financial and tax data and unstructured financial and tax data, respectively. , , , They are the weight factors corresponding to the Pearson correlation coefficient between the structured financial and taxation data and the unstructured financial and taxation data, the weight factors corresponding to the Spearman rank correlation coefficient, the weight factors corresponding to the mutual information value, and the weight factors corresponding to the determination coefficient.

4. A method for processing financial and tax data as claimed in claim 3, characterized in that: The specific evaluation process of evaluating whether the correlation between each structured financial and taxation data and each unstructured financial and taxation data is significant is as follows: Compare the correlation adaptation value between each structured fiscal and tax data and each unstructured fiscal and tax data with the set correlation adaptation value between the standard structured fiscal and tax data and the unstructured fiscal and tax data. If the correlation adaptation value between a certain structured fiscal and tax data and a certain unstructured fiscal and tax data is greater than or equal to the set correlation adaptation value between the standard structured fiscal and tax data and the unstructured fiscal and tax data, it means that the correlation between the structured fiscal and tax data and the unstructured fiscal and tax data is significant. If the correlation adaptation value between a certain structured fiscal and tax data and a certain unstructured fiscal and tax data is less than the set correlation adaptation value between the standard structured fiscal and tax data and the unstructured fiscal and tax data, it means that the correlation between the structured fiscal and tax data and the unstructured fiscal and tax data is not significant. In this way, evaluate whether the correlation between each structured fiscal and tax data and each unstructured fiscal and tax data is significant.

5. A method for processing financial and tax data as claimed in claim 4, characterized in that: The structured financial and taxation data and the unstructured financial and taxation data with significant correlation are uniformly stored in the same node. The specific storage process is as follows: If certain structured financial and taxation data and certain unstructured financial and taxation data are stored in the same node, a new field is added to the structured data table in the node, and the new field will store a pointer to the unstructured financial and taxation data in the node.

6. A method for processing financial and tax data according to claim 1, characterized in that: The specific analysis process of analyzing the financial evaluation value corresponding to each structured financial and taxation data and the insight evaluation value corresponding to each unstructured financial and taxation data in each node is as follows: C1. Obtain the current ratio, debt-to-asset ratio and tax compliance rate corresponding to each structured financial and tax data in each node, and input the current ratio, debt-to-asset ratio and tax compliance rate corresponding to each structured financial and tax data in each node into the financial evaluation model, and output the financial evaluation value corresponding to each node; C2. Obtain the number of negative news and risk-related keywords corresponding to each unstructured financial and tax data in each node, and input the number of negative news and risk-related keywords corresponding to each unstructured financial and tax data in each node into the insight evaluation model, and output the insight evaluation value corresponding to each node.

7. A method for processing financial and tax data according to claim 6, characterized in that: The analysis obtains the comprehensive risk assessment value corresponding to the current cycle of the target enterprise. The specific analysis process is as follows: The financial evaluation value and insight evaluation value corresponding to each node are respectively recorded as and ,in, Indicates the number corresponding to each node, , u is a positive integer, substitute into the calculation formula: The comprehensive risk assessment value corresponding to the current cycle of the target enterprise is obtained ,in, , They are the weight factors corresponding to the set node financial evaluation value and the weight factors corresponding to the insight evaluation value, and e represents a natural constant.

8. A method for processing financial and tax data according to claim 7, characterized in that: The specific analysis process for judging whether the target enterprise has potential risks in the current cycle is as follows: The comprehensive risk assessment value corresponding to the current cycle of the target enterprise is compared with the comprehensive risk assessment value interval corresponding to each risk type of the enterprise. If the comprehensive risk assessment value corresponding to the current cycle of the target enterprise is within the comprehensive risk assessment value interval corresponding to a certain risk type of the enterprise, it is judged that the current cycle of the target enterprise has potential risks. If the comprehensive risk assessment values ​​corresponding to the current cycle of the target enterprise are not within the comprehensive risk assessment value interval corresponding to a certain risk type of the enterprise, it is judged that the current cycle of the target enterprise does not have potential risks.

9. A method for processing financial and tax data according to claim 8, characterized in that: The risk type corresponding to the current cycle of the target enterprise is obtained, and an early warning display is performed. The specific early warning process is as follows: D1. If the comprehensive risk assessment value corresponding to the current cycle of the target enterprise is within the comprehensive risk assessment value range corresponding to a certain risk type of the enterprise, then the risk type is recorded as the risk type corresponding to the current cycle of the target enterprise; D2. If the risk type corresponding to the current cycle of the target enterprise is financial risk, a red flashing "financial risk" icon will be displayed as an early warning on the homepage and financial report page of the enterprise's financial management system. When the mouse hovers over the icon, a brief risk warning will be displayed. At the same time, an email will be sent in a timely manner to notify the public relations team to handle the matter; D3. If the risk type corresponding to the current cycle of the target enterprise is compliance risk, a yellow flashing "compliance risk" icon warning will be displayed on the homepage of the enterprise compliance management system and related business process pages. When the mouse hovers over the icon, a brief risk warning will be displayed. At the same time, on the compliance items list page, compliance items with risks will be highlighted in red font, and an email will be sent in time to notify the public relations team to handle it; D4. If the risk type corresponding to the current cycle of the target enterprise is operational risk, a blue flashing "operational risk" icon will be displayed as an early warning on the main interface of the enterprise business operation management system. When the mouse hovers over the icon, the specific type of operational risk will be displayed. In addition, on the specific business operation page, the risk operation steps will be marked with a red border, and an email will be sent in a timely manner to notify the public relations team to handle the matter; D5. If the risk type corresponding to the current cycle of the target enterprise is reputation risk, an orange flashing "reputation risk" icon will be displayed as a warning in the enterprise public relations management system and at the bottom of the enterprise official website homepage. When the mouse hovers over the icon, an overview of the current reputation risk will be displayed. At the same time, on the social media monitoring platform, negative topics involving the enterprise will be highlighted, and an email will be sent in time to notify the public relations team to handle it.

10. A financial and tax data processing system for executing the financial and tax data processing method according to any one of claims 1 to 9, characterized in that: include: Financial and tax data processing module: used to obtain the financial and tax information resources of the target enterprise in the current period, and classify the financial and tax information resources of the target enterprise in the current period, and then obtain various unstructured financial and tax data and various structured financial and tax data; Relevance evaluation module: used to analyze the relevance adaptation value between each structured fiscal and taxation data and each unstructured fiscal and taxation data, and then evaluate whether the relevance between each structured fiscal and taxation data and each unstructured fiscal and taxation data is significant; Risk warning analysis module: used to store various structured financial and tax data and various unstructured financial and tax data with significant correlation in the same node, so as to analyze the financial evaluation value and insight evaluation value corresponding to each node, and obtain the comprehensive risk evaluation value corresponding to the current cycle of the target enterprise; Risk type warning module: used to determine whether the target enterprise has potential risks in the current cycle based on the comprehensive risk assessment value corresponding to the current cycle of the target enterprise. If the target enterprise has potential risks in the current cycle, the risk type corresponding to the current cycle of the target enterprise is obtained and a warning is displayed.

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