Financial sharing evaluation system based on big data

Abstract

The invention discloses a financial sharing evaluation system based on big data, relates to the technical field of enterprise management, effectively solves the integration problem of heterogeneous financial data through a data integration module, and ensures the consistency and accuracy of the data. The personalized index module allows user-defined financial evaluation indexes and templates, so that the personalized service capability of the system is improved, and the requirements of specific departments are better met; the intelligent analysis module uses a big data technology and algorithm optimization to collect and analyze data in real time and construct a financial prediction model, so that the intelligent level is improved, and the system can effectively predict and manage complex financial risks; on the whole, the system improves the accuracy and adaptability of financial assessment through high customization and intelligent analysis, and optimizes the risk management and decision-making efficiency of enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise management, and in particular to a financial sharing evaluation system based on big data. Background Art

[0002] The financial sharing evaluation system originated from the shared service concept in the 1990s. The concept was first applied to large multinational companies and aimed to improve financial operation efficiency by centrally managing financial resources. With the rapid development of information technology, enterprises have gradually developed financial sharing centers from simple cost control tools to comprehensive financial management platforms. Early systems mainly relied on traditional ERP systems, with relatively simple functions, mainly realizing centralized storage of financial data and basic report generation. Entering the 21st century, technologies such as cloud computing, big data and artificial intelligence have brought new opportunities for the intelligence and automation of financial sharing evaluation systems. Modern financial sharing evaluation systems not only focus on the integration and sharing of financial data, but also focus on risk control, resource optimization and decision support. They are widely used in corporate groups, government agencies and non-profit organizations, providing strong guarantees for financial transparency and strategic execution.

[0003] However, when the existing financial sharing evaluation system is applied to enterprise groups, it often has the following technical shortcomings:

[0004] 1. Insufficient data integration: Although the financial shared evaluation system can integrate data from different business units, it is still difficult to integrate data from multiple sources and heterogeneous systems. For example, the data standards between business systems of different departments or subsidiaries are not unified, resulting in redundancy or conflict in the data sharing and analysis process, thus affecting the accuracy of the evaluation.

[0005] 2. Insufficient personalization: Existing systems are usually based on general evaluation indicators and templates, which are difficult to meet the personalized needs of enterprises in special financial management scenarios. For example, certain industry-specific financial risk points or performance indicators may not be fully considered in the system, limiting the system's adaptability in diverse application scenarios.

[0006] 3. Limited intelligence: Despite the introduction of artificial intelligence and big data analysis technologies, the intelligence capabilities of many systems are limited to basic report generation and simple predictive analysis. In terms of more complex financial risk identification and anomaly detection, the accuracy and applicability of existing algorithms still need to be improved. Summary of the invention

[0007] In view of the shortcomings of the prior art, the present invention provides a financial sharing evaluation system based on big data, which solves the problems mentioned in the background technology;

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a financial sharing evaluation system based on big data, including a data integration module, a personalized indicator module, an intelligent analysis module, a risk identification module and a financial management module;

[0009] The data integration module is used to collect departmental financial data of each department from multiple sources and heterogeneous financial systems, and pre-set a set of unified financial data format standards through a standardization processing tool; then, based on the financial data format standards, the collected departmental financial data is converted into a unified format;

[0010] The personalized indicator module is used to customize financial evaluation indicators and financial evaluation templates according to the specific financial management needs of the enterprise; wherein the financial evaluation template is based on the characteristics of the current department, inputs the department's financial risk points and department performance indicators, and generates a personalized financial evaluation template through a dynamic configuration tool;

[0011] The intelligent analysis module is used to analyze the financial health of the current department, predict and analyze the department's financial related data in a unified format by using big data analysis technology, build a financial forecasting model based on customized financial evaluation indicators and financial evaluation templates, and analyze and identify potential financial anomalies and risks of the current department based on the forecast results provided by the financial forecasting model;

[0012] The risk identification module is used to evaluate the potential financial risks of the current department based on the financial abnormality results provided by the intelligent analysis module; by calculating the risk assessment index Zpjx and evaluating it with the set risk threshold, it automatically issues risk warnings to managers and takes corresponding measures;

[0013] The financial management module implements targeted financial management measures based on risk warning; first, the financial deviation control threshold Q and the financial anomaly correlation threshold U are pre-set; then, the departmental financial related data between all departments are further integrated, by calculating the total harvest deviation value Dxy and the financial anomaly correlation index Gxz between all departments; and the harvest deviation value Dxy and the financial anomaly correlation index Gxz are evaluated and analyzed respectively, and finally, the financial strategies of the relevant departments are adjusted according to the evaluation and analysis content.

[0014] Furthermore, the data integration module first collects departmental financial related data in real time from the financial software and databases used by different departments, and the departmental financial related data contains financial indicators, including income, cost, assets and liabilities; then uses a set of pre-set standardization processing tools, wherein the standardization processing tools define a set of unified financial data format standards, so that departmental financial related data collected from different sources can be recognized and processed by the system; after data standardization, all collected heterogeneous departmental financial related data are converted into a unified format, including data cleaning, format alignment and type conversion, and data verification and quality inspection are performed during the conversion process.

[0015] Furthermore, the personalized indicator module is used to collect the department's departmental financial risk points and departmental performance indicators; then, a set of dynamic configuration tools are used to process the department's financial risk points and departmental performance indicators; wherein the dynamic configuration tool has built-in multiple preset financial models and algorithms, which are used to automatically generate corresponding financial evaluation templates based on user input; wherein the financial evaluation template contains financial calculation formulas, and adjusts the financial evaluation indicators according to the specific needs of the department, so that the generated financial evaluation indicators are used to reflect the actual operating conditions and financial health of the department.

[0016] Furthermore, the intelligent analysis module includes a model building unit and a prediction analysis unit;

[0017] The model building unit builds a financial forecasting model that adapts to the specific needs of the department based on the financial evaluation template and financial evaluation indicators customized by the user through the personalized indicator module; by utilizing big data technology, real-time collection and combination of department characteristic information, historical financial data information and market environment information, through algorithm optimization and data training, a financial forecasting model that reflects the financial status of the department is formed.

[0018] Furthermore, the forecasting and analysis unit uses the established financial forecasting model to conduct in-depth analysis and forecasting of the departmental financial data in a unified format; the financial forecasting model is used to forecast the financial status of the current department within a fixed period in the future and output the forecast results; wherein the forecast results include the cash flow ratio Zlb, the debt ratio Zzb and the return on net assets Zsy,

[0019] The financial health of the current department Zjkd is obtained by extracting the forecast results and combining them with the following formula:

[0020]

[0021] By comparing and evaluating the preset financial health threshold Q with the financial health degree Zjkd, potential financial anomalies and risks can be automatically identified; the specific contents are as follows:

[0022] If the financial health Zjkd ≥ the financial health threshold Q, it means that the current financial situation of the department is normal and no additional financial intervention measures are required;

[0023] If the financial health Zjkd is less than the financial health threshold Q, it means that the financial situation of the current department is abnormal and there is a potential financial risk.

[0024] Furthermore, the risk identification module includes a risk calculation unit and an assessment and early warning unit:

[0025] The risk calculation unit is used to receive the financial abnormality results provided by the intelligent analysis module, and calculate and obtain the risk assessment index Zpjx of the current department in combination with the department's financial related data; the specific calculation process is as follows:

[0026]

[0027] In the formula, Ove represents the overdue accounts ratio in the department's financial data, Icr represents the loan interest coverage ratio in the department's financial data, Itr represents the inventory turnover rate in the department's financial data, and Dsa represents the accounts receivable turnover days in the department's financial data.

[0028] Furthermore, the assessment and early warning unit is used to preset a risk threshold R, conduct comparative assessment on the risk assessment index Zpjx, issue a risk warning and take corresponding countermeasures; the specific contents are as follows:

[0029] If the risk assessment index Zpjx ≤ risk threshold R, it means that the current financial risk level of the department is within the controllable range and no additional risk warning is needed; the response measures taken at this time include adjusting financial monitoring and budget management, and re-evaluating asset allocation and investment strategies;

[0030] If the risk assessment index Zpjx>risk threshold R, it means that the financial risk level of the current department is beyond the controllable range, and a risk warning notification is generated and sent to relevant managers; the response measures taken at this time include debt restructuring, fund allocation, and cost and expenditure control; at the same time, the financial management module is used to conduct a detailed analysis of the impact on the current department's financial risk level.

[0031] Further, the financial management module includes a financial data integration unit, a financial deviation analysis unit and a strategy adjustment and execution unit;

[0032] The financial data integration unit is used to collect and integrate departmental financial data from all departments according to the assessment results of the risk assessment index Zpjx; including the income, expenditure, assets and liabilities of each department; while maintaining the standardization of the data format of each department and the synchronous update frequency.

[0033] Furthermore, the financial deviation analysis unit uses the integrated departmental financial related data to calculate the total deviation value Dxy of the harvest between all departments and the financial abnormality correlation index Gxz;

[0034] The specific calculation formula of the total yield deviation value Dxy and the financial abnormality correlation index Gxz is as follows:

[0035]

[0036] In the formula, n represents the total number of departments, i is an index, indicating the department number; Bss represents the actual income of the department in the department's financial related data, Bsb represents the actual cost of the department in the department's financial related data, and Bsl represents the actual profit of the department in the department's financial related data;

[0037] Bys represents the expected revenue of the department in the department's financial related data, Byb represents the expected cost of the department in the department's financial related data, and Byl represents the expected profit of the department in the department's financial related data;

[0038]

[0039] In the formula, n represents the total number of departments, i is the index, indicating the department number; Bss represents the actual income of the department in the department's financial related data, Bjy represents the inter-department transaction amount in the department's financial related data, Bzc represents the current department's capital income and expenditure rate in the department's financial related data, and Bzx represents the current department's budget execution rate in the department's financial related data.

[0040] Furthermore, the strategy adjustment and execution unit is used to compare and evaluate the preset financial deviation control threshold Q with the total yield deviation value Dxy, and then compare and evaluate the financial anomaly correlation threshold U with the financial anomaly correlation index Gxz. The specific evaluation contents are as follows:

[0041] When the total deviation value of harvest Dxy> the financial deviation control threshold Q, it means that the financial performance of the department has not met expectations;

[0042] When the total deviation value of the harvest Dxy ≤ the financial deviation control threshold Q, it means that the financial performance of the department has reached expectations;

[0043] When the financial abnormal correlation index Gxz ≥ the financial abnormal correlation threshold U, it means that there is a financial abnormal correlation risk and potential risk aggregation between the current department and other departments;

[0044] When the financial abnormal correlation index Gxz is less than the financial abnormal correlation threshold U, it means that the financial correlation and transaction activities between the current department and other departments are normal, and there is no financial abnormal correlation risk and potential risk accumulation;

[0045] Finally, the evaluation and analysis contents of the total deviation value Dxy of the harvest and the financial abnormal correlation index Gxz are comprehensively analyzed, and the financial strategies of the departments whose financial risk levels are beyond the controllable range are adjusted accordingly, specifically:

[0046] When the financial performance of a department does not meet expectations and there are abnormal financial correlation risks and potential risk aggregation between the current department and other departments, the current department will be marked and financial resources will be reallocated;

[0047] When the financial performance of a department does not meet expectations, but there is no abnormal financial correlation risk or potential risk aggregation between the current department and other departments, pay separate attention to the financial performance of the current department and analyze the cost structure and profit model of the current department at the same time;

[0048] When the financial performance of a department has met expectations, but there are abnormal financial correlation risks and potential risk accumulation between the current department and other departments, separate attention will be paid to the abnormal correlation risks of the current department, as well as the transactions and financial flows between the current department and other departments, and the audit and supervision mechanisms will be adjusted.

[0049] The present invention provides a financial sharing evaluation system based on big data, which has the following beneficial effects:

[0050] (1) This financial sharing evaluation system based on big data effectively solves the problem of data integration of multi-source and heterogeneous financial systems through the design of a data integration module. The module first collects financial-related data in real time from the financial software and databases used by different departments, covering a series of financial indicators such as income, cost, assets and liabilities. Subsequently, a set of pre-set standardized processing tools is used to define a set of unified financial data format standards to ensure that departmental financial-related data collected from different sources can be recognized and effectively processed by the system. After data standardization, all collected heterogeneous data are converted into a unified format, including data cleaning, format alignment and type conversion, and data verification and quality checks are performed during the conversion process. This method greatly improves the accuracy and consistency of data, eliminates redundancy or conflict caused by inconsistent data standards, and effectively improves the accuracy of evaluation.

[0051] (2) This financial sharing evaluation system based on big data, through the introduction of personalized indicator modules, enhances the flexibility and adaptability of the system in meeting specific financial management needs; this module allows users to customize financial evaluation indicators and templates according to the needs and characteristics of specific departments, so as to better reflect the actual operating conditions and financial health of the departments; through a set of dynamic configuration tools, it processes income data, departmental financial risk points and departmental performance indicators, which have multiple preset financial models and algorithms built in; these models and algorithms automatically generate corresponding financial evaluation templates based on user input, which contain financial calculation formulas, and can adjust the evaluation indicators according to the specific needs of the departments, so that the generated financial evaluation indicators are more in line with the needs of special financial management scenarios, thereby solving the shortcomings of the existing system in personalized services;

[0052] (3) In this financial sharing assessment system based on big data, the design of the intelligent analysis module significantly improves the intelligent processing capability of the system; the module includes a model building unit and a prediction analysis unit, wherein the model building unit builds a financial prediction model adapted to the needs of a specific department based on the financial assessment template and financial assessment indicators customized by the user through the personalized indicator module; by utilizing big data technology, real-time collection and combination of department characteristic information, historical financial data and market environment information, through algorithm optimization and data training, a financial prediction model that reflects the financial status of the department is formed; the prediction analysis unit uses these models to conduct in-depth analysis and prediction of departmental financial related data in a unified format, and provides data-driven advanced analysis such as financial risk identification and anomaly detection; this not only goes beyond the limitations of basic report generation and simple prediction analysis, but also significantly improves the accuracy and applicability of the algorithm, enabling the system to effectively predict and manage complex financial risks, thereby improving the intelligence level of the entire system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a schematic diagram of the framework structure of a financial sharing evaluation system based on big data in the present invention. DETAILED DESCRIPTION

[0054] 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.

[0055] Example 1

[0056] See also Figure 1,The present invention provides a financial sharing evaluation system based on big data, including a data integration module, a personalized indicator module, an intelligent analysis module, a risk identification module and a financial management module;

[0057] The data integration module is used to collect departmental financial data of each department from multiple sources and heterogeneous financial systems, and pre-set a set of unified financial data format standards through a standardization processing tool; then, based on the financial data format standards, the collected departmental financial data is converted into a unified format;

[0058] The personalized indicator module is used to customize financial evaluation indicators and financial evaluation templates according to the specific financial management needs of the enterprise; wherein the financial evaluation template is based on the characteristics of the current department, inputs the department's financial risk points and department performance indicators, and generates a personalized financial evaluation template through a dynamic configuration tool;

[0059] The intelligent analysis module is used to analyze the financial health of the current department, predict and analyze the department's financial related data in a unified format by using big data analysis technology, build a financial forecasting model based on customized financial evaluation indicators and financial evaluation templates, and analyze and identify potential financial anomalies and risks of the current department based on the forecast results provided by the financial forecasting model;

[0060] The risk identification module is used to evaluate the potential financial risks of the current department based on the financial abnormality results provided by the intelligent analysis module; by calculating the risk assessment index Zpjx and evaluating it with the set risk threshold, it automatically issues risk warnings to managers and takes corresponding measures;

[0061] The financial management module implements targeted financial management measures based on risk warning; first, the financial deviation control threshold Q and the financial anomaly correlation threshold U are pre-set; then, the departmental financial related data between all departments are further integrated, by calculating the total harvest deviation value Dxy and the financial anomaly correlation index Gxz between all departments; and the harvest deviation value Dxy and the financial anomaly correlation index Gxz are evaluated and analyzed respectively, and finally, the financial strategies of the relevant departments are adjusted according to the evaluation and analysis content.

[0062] In this embodiment, the data integration module collects departmental financial data from multi-source and heterogeneous financial systems, and presets a set of unified financial data format standards through a standardized processing tool, effectively integrating data and eliminating redundancy or conflict caused by inconsistent data standards; the personalized indicator module allows customization of financial evaluation indicators and templates according to specific enterprise needs, improves the accuracy and relevance of evaluation, and generates personalized financial evaluation templates for departmental characteristics through dynamic configuration tools, thereby enhancing the flexibility and application scope of the system; the intelligent analysis module uses big data technology to analyze and predict departmental financial data, builds a financial prediction model, and timely identifies and analyzes potential financial anomalies and risks to improve the foresight and accuracy of decision-making; the risk identification module calculates the risk assessment index Zpjx based on the intelligent analysis results, compares it with the set risk threshold, automatically issues risk warnings, and responds to financial risks in a timely manner; the financial management module takes targeted financial management measures based on risk warnings, integrates inter-departmental financial data, and adjusts departmental financial strategies based on the evaluation results by calculating the total deviation value Dxy of the harvest and the financial anomaly correlation index Gxz, optimizes resource allocation and risk management, and ensures the financial stability and healthy development of the enterprise.

[0063] Example 2

[0064] The data integration module first collects departmental financial data in real time from the financial software and databases used by different departments, and the departmental financial data contains financial indicators, including revenue, cost, assets and liabilities; then uses a set of pre-set standardization processing tools, where the standardization processing tools define a set of unified financial data format standards so that departmental financial data collected from different sources can be recognized and processed by the system; after data standardization, all collected heterogeneous departmental financial data are converted into a unified format, including data cleaning, format alignment and type conversion, and data verification and quality inspection are performed during the conversion process.

[0065] The personalized indicator module is used to collect the department's departmental financial risk points and departmental performance indicators; then, a set of dynamic configuration tools are used to process the departmental financial risk points and departmental performance indicators; the dynamic configuration tool has built-in multiple preset financial models and algorithms, which are used to automatically generate corresponding financial evaluation templates based on user input; the financial evaluation template contains financial calculation formulas, and adjusts the financial evaluation indicators according to the specific needs of the department, so that the generated financial evaluation indicators are used to reflect the actual operating conditions and financial health of the department.

[0066] The intelligent analysis module includes a model building unit and a prediction analysis unit;

[0067] The model building unit builds a financial forecasting model that adapts to the specific needs of the department based on the financial evaluation template and financial evaluation indicators customized by the user through the personalized indicator module; by utilizing big data technology, real-time collection and combination of department characteristic information, historical financial data information and market environment information, through algorithm optimization and data training, a financial forecasting model that reflects the financial status of the department is formed.

[0068] The forecasting and analysis unit uses the established financial forecasting model to conduct in-depth analysis and forecasting of the departmental financial data in a unified format; forecasts the financial status of the current department within a fixed period in the future through the financial forecasting model and outputs the forecast results; wherein the forecast results include the cash flow ratio Zlb, the debt ratio Zzb and the return on net assets Zsy,

[0069] The financial health of the current department Zjkd is obtained by extracting the forecast results and combining them with the following formula:

[0070]

[0071] By comparing and evaluating the preset financial health threshold Q with the financial health degree Zjkd, potential financial anomalies and risks can be automatically identified; the specific contents are as follows:

[0072] If the financial health Zjkd ≥ the financial health threshold Q, it means that the current financial situation of the department is normal and no additional financial intervention measures are required;

[0073] If the financial health Zjkd is less than the financial health threshold Q, it means that the financial situation of the current department is abnormal and there is a potential financial risk.

[0074] In this embodiment, the data integration module collects financial-related data in real time from the financial software and databases used by different departments, including financial indicators such as income, cost, assets and liabilities, and converts heterogeneous data into a unified format through a preset standardized processing tool to ensure data consistency and accuracy, thereby improving data processing efficiency and reducing errors;

[0075] The personalized indicator module allows the dynamic configuration tool to generate financial assessment templates based on user input according to the department's specific financial management needs. These templates include financial calculation formulas that reflect the actual operating conditions and financial health of the department, making financial assessments more in line with actual needs and enhancing the relevance of decision-making;

[0076] The intelligent analysis module uses big data technology to collect and analyze department characteristic information, historical financial data and market environment information in real time through the model building unit and the forecasting analysis unit, builds a financial forecasting model and predicts the financial status within a fixed period in the future. The output forecast results such as cash flow ratio Zlb, debt ratio Zzb and return on net assets Zsy are used to calculate the financial health Zjkd of the current department; the comparative evaluation of the financial health Zjkd and the preset financial health threshold Q automatically identifies potential financial anomalies and risks, ensures the normal financial status of the department, and adjusts strategies in time to deal with potential risks; the design of the entire system aims to improve financial transparency and decision-making quality, reduce enterprise operating risks, and enhance the financial health level and market competitiveness of the enterprise through scientific data integration and intelligent analysis.

[0077] Example 3

[0078] The risk identification module includes a risk calculation unit and an assessment and early warning unit:

[0079] The risk calculation unit is used to receive the financial abnormality results provided by the intelligent analysis module, and calculate and obtain the risk assessment index Zpjx of the current department in combination with the department's financial related data; the specific calculation process is as follows:

[0080]

[0081] In the formula, Ove represents the overdue accounts ratio in the department's financial data, Icr represents the loan interest coverage ratio in the department's financial data, Itr represents the inventory turnover rate in the department's financial data, and Dsa represents the accounts receivable turnover days in the department's financial data.

[0082] The evaluation and early warning unit is used to preset the risk threshold R, compare and evaluate the risk assessment index Zpjx, issue a risk warning and take corresponding response measures; the specific contents are as follows:

[0083] If the risk assessment index Zpjx ≤ risk threshold R, it means that the current financial risk level of the department is within the controllable range and no additional risk warning is needed; the response measures taken at this time include adjusting financial monitoring and budget management, and re-evaluating asset allocation and investment strategies;

[0084] If the risk assessment index Zpjx>risk threshold R, it means that the financial risk level of the current department is beyond the controllable range, and a risk warning notification is generated and sent to relevant managers; the response measures taken at this time include debt restructuring, fund allocation, and cost and expenditure control; at the same time, the financial management module is used to conduct a detailed analysis of the impact on the current department's financial risk level.

[0085] The financial management module includes a financial data integration unit, a financial deviation analysis unit and a strategy adjustment and execution unit;

[0086] The financial data integration unit is used to collect and integrate departmental financial data from all departments according to the assessment results of the risk assessment index Zpjx; including the income, expenditure, assets and liabilities of each department; while maintaining the standardization of the data format of each department and the synchronous update frequency.

[0087] The financial deviation analysis unit uses the integrated departmental financial related data to calculate the total deviation value Dxy and the financial abnormality correlation index Gxz between all departments;

[0088] The specific calculation formula of the total yield deviation value Dxy and the financial abnormality correlation index Gxz is as follows:

[0089]

[0090] In the formula, n represents the total number of departments, i is an index, indicating the department number; Bss represents the actual income of the department in the department's financial related data, Bsb represents the actual cost of the department in the department's financial related data, and Bsl represents the actual profit of the department in the department's financial related data;

[0091] Bys represents the expected revenue of the department in the department's financial related data, Byb represents the expected cost of the department in the department's financial related data, and Byl represents the expected profit of the department in the department's financial related data;

[0092]

[0093] In the formula, n represents the total number of departments, i is the index, indicating the department number; Bss represents the actual income of the department in the department's financial related data, Bjy represents the inter-department transaction amount in the department's financial related data, Bzc represents the current department's capital income and expenditure rate in the department's financial related data, and Bzx represents the current department's budget execution rate in the department's financial related data.

[0094] The strategy adjustment and execution unit is used to compare and evaluate the preset financial deviation control threshold Q with the total yield deviation value Dxy, and then compare and evaluate the financial anomaly correlation threshold U with the financial anomaly correlation index Gxz. The specific evaluation contents are as follows:

[0095] When the total deviation value of harvest Dxy> the financial deviation control threshold Q, it means that the financial performance of the department has not met expectations;

[0096] When the total deviation value of the harvest Dxy ≤ the financial deviation control threshold Q, it means that the financial performance of the department has reached expectations;

[0097] When the financial abnormal correlation index Gxz ≥ the financial abnormal correlation threshold U, it means that there is a financial abnormal correlation risk and potential risk aggregation between the current department and other departments;

[0098] When the financial abnormal correlation index Gxz is less than the financial abnormal correlation threshold U, it means that the financial correlation and transaction activities between the current department and other departments are normal, and there is no financial abnormal correlation risk and potential risk accumulation;

[0099] Finally, the evaluation and analysis contents of the total deviation value Dxy of the harvest and the financial abnormal correlation index Gxz are comprehensively analyzed, and the financial strategies of the departments whose financial risk levels are beyond the controllable range are adjusted accordingly, specifically:

[0100] When the financial performance of a department does not meet expectations and there are abnormal financial correlation risks and potential risk aggregation between the current department and other departments, the current department will be marked and financial resources will be reallocated;

[0101] When the financial performance of a department does not meet expectations, but there is no abnormal financial correlation risk or potential risk aggregation between the current department and other departments, pay separate attention to the financial performance of the current department and analyze the cost structure and profit model of the current department at the same time;

[0102] When the financial performance of a department has met expectations, but there are abnormal financial correlation risks and potential risk accumulation between the current department and other departments, separate attention will be paid to the abnormal correlation risks of the current department, as well as the transactions and financial flows between the current department and other departments, and the audit and supervision mechanisms will be adjusted.

[0103] In this embodiment, the risk calculation unit of the risk identification module receives the financial abnormality results provided by the intelligent analysis module and calculates the risk assessment index Zpjx in combination with financial related data such as the overdue account ratio Ove, the loan interest coverage ratio Icr, the inventory turnover rate Itr and the accounts receivable turnover days Dsa, so as to quantify the financial risk level of the department; the assessment and early warning unit compares the risk assessment index Zpjx with the preset risk threshold R, and can accurately identify whether the financial risk level exceeds the controllable range, and issue a risk warning, and at the same time take targeted measures such as adjusting financial monitoring, re-evaluating asset allocation or conducting debt restructuring to enhance the financial security of the enterprise;

[0104] The financial management module standardizes and synchronously updates the financial data of each department, such as income, expenditure, assets and liabilities, through the data integration unit to ensure the consistency and integrity of the data, and provide a reliable basis for subsequent analysis; the financial deviation analysis unit comprehensively evaluates the deviation between the department's financial performance and goals and the financial correlation anomalies between departments by calculating the total deviation value of the income Dxy and the financial anomaly correlation index Gxz; the strategy adjustment and execution unit implements targeted strategy adjustments by comparing the total deviation value of the income Dxy with the financial deviation control threshold Q and the financial anomaly correlation index Gxz with the financial anomaly correlation threshold U, to ensure the optimization of the department's financial status and the elimination of potential risks.

[0105] Among them, the overdue accounts ratio Ove reflects the department's ability to pay short-term debts, and a higher ratio may indicate liquidity risk; the loan interest coverage ratio Icr measures the department's ability to pay interest, and a lower ratio indicates greater debt pressure; the inventory turnover rate Itr is used to evaluate the efficiency of inventory management, and a low turnover rate may indicate inventory backlogs; the accounts receivable turnover days Dsa indicates the speed at which the department collects accounts receivable, and the longer the days, the worse the liquidity of funds; by calculating the risk assessment index Zpjx, the overall impact of these parameters on financial risk is comprehensively reflected, providing a quantitative basis for risk management; the total deviation value Dxy is used to evaluate the gap between the actual financial performance of the department and the expected target, helping to discover problems in cost control or revenue realization; the financial abnormal correlation index Gxz is used to measure the transaction correlation between departments and the abnormal risks that may be caused, providing management with a reference for optimizing department collaboration and controlling financial abnormalities.

[0106] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A financial sharing evaluation system based on big data, characterized by: Including data integration module, personalized indicator module, intelligent analysis module, risk identification module and financial management module; The data integration module is used to collect departmental financial data of each department from multiple sources and heterogeneous financial systems, and pre-set a set of unified financial data format standards through a standardization processing tool; then, based on the financial data format standards, the collected departmental financial data is converted into a unified format; The personalized indicator module is used to customize financial evaluation indicators and financial evaluation templates according to the specific financial management needs of the enterprise; wherein the financial evaluation template is based on the characteristics of the current department, inputs the department's financial risk points and department performance indicators, and generates a personalized financial evaluation template through a dynamic configuration tool; The intelligent analysis module is used to analyze the financial health of the current department, predict and analyze the department's financial related data in a unified format by using big data analysis technology, build a financial forecasting model based on customized financial evaluation indicators and financial evaluation templates, and analyze and identify potential financial anomalies and risks of the current department based on the forecast results provided by the financial forecasting model; The risk identification module is used to evaluate the potential financial risks of the current department based on the financial abnormality results provided by the intelligent analysis module; by calculating the risk assessment index Zpjx and evaluating it with the set risk threshold, it automatically issues risk warnings to managers and takes corresponding measures; The financial management module implements targeted financial management measures based on risk warning; first, the financial deviation control threshold Q and the financial anomaly correlation threshold U are pre-set; then, the departmental financial related data between all departments are further integrated, by calculating the total harvest deviation value Dxy and the financial anomaly correlation index Gxz between all departments; and the harvest deviation value Dxy and the financial anomaly correlation index Gxz are evaluated and analyzed respectively, and finally, the financial strategies of the relevant departments are adjusted according to the evaluation and analysis content.

2. The financial sharing evaluation system based on big data according to claim 1 is characterized by: The data integration module first collects departmental financial data in real time from the financial software and databases used by different departments, and the departmental financial data contains financial indicators, including revenue, cost, assets and liabilities; then uses a set of pre-set standardization processing tools, where the standardization processing tools define a set of unified financial data format standards so that departmental financial data collected from different sources can be recognized and processed by the system; after data standardization, all collected heterogeneous departmental financial data are converted into a unified format, including data cleaning, format alignment and type conversion, and data verification and quality inspection are performed during the conversion process.

3. The financial sharing evaluation system based on big data according to claim 1 is characterized by: The personalized indicator module is used to collect the department's departmental financial risk points and departmental performance indicators; then a set of dynamic configuration tools are introduced to process the departmental financial risk points and departmental performance indicators; wherein the dynamic configuration tool has built-in multiple preset financial models and algorithms, which are used to automatically generate corresponding financial evaluation templates according to user input; The financial evaluation template contains financial calculation formulas and adjusts financial evaluation indicators according to the specific needs of the department, so that the generated financial evaluation indicators are used to reflect the actual operating conditions and financial health of the department.

4. The financial sharing evaluation system based on big data according to claim 1 is characterized by: The intelligent analysis module includes a model building unit and a prediction analysis unit; The model building unit builds a financial forecasting model that adapts to the specific needs of the department based on the financial evaluation template and financial evaluation indicators customized by the user through the personalized indicator module; by utilizing big data technology, real-time collection and combination of department characteristic information, historical financial data information and market environment information, through algorithm optimization and data training, a financial forecasting model that reflects the financial status of the department is formed.

5. The financial sharing evaluation system based on big data according to claim 4 is characterized by: The forecasting and analysis unit uses the established financial forecasting model to conduct in-depth analysis and forecasting of the departmental financial data in a unified format; forecasts the financial status of the current department within a fixed period in the future through the financial forecasting model and outputs the forecast results; wherein the forecast results include the cash flow ratio Zlb, the debt ratio Zzb and the return on net assets Zsy, The financial health of the current department Zjkd is obtained by extracting the forecast results and combining them with the following formula: By comparing and evaluating the preset financial health threshold Q with the financial health degree Zjkd, potential financial anomalies and risks can be automatically identified; the specific contents are as follows: If the financial health Zjkd ≥ the financial health threshold Q, it means that the current financial situation of the department is normal and no additional financial intervention measures are required; If the financial health Zjkd is less than the financial health threshold Q, it means that the financial situation of the current department is abnormal and there is a potential financial risk.

6. The financial sharing evaluation system based on big data according to claim 1 is characterized by: The risk identification module includes a risk calculation unit and an assessment and early warning unit: The risk calculation unit is used to receive the financial abnormality results provided by the intelligent analysis module, and calculate and obtain the risk assessment index Zpjx of the current department in combination with the department's financial related data; the specific calculation process is as follows: In the formula, Ove represents the overdue accounts ratio in the department's financial data, Icr represents the loan interest coverage ratio in the department's financial data, Itr represents the inventory turnover rate in the department's financial data, and Dsa represents the accounts receivable turnover days in the department's financial data.

7. The financial sharing evaluation system based on big data according to claim 6 is characterized by: The evaluation and early warning unit is used to preset the risk threshold R, compare and evaluate the risk assessment index Zpjx, issue a risk warning and take corresponding response measures; the specific contents are as follows: If the risk assessment index Zpjx ≤ risk threshold R, it means that the current financial risk level of the department is within the controllable range and no additional risk warning is needed; the response measures taken at this time include adjusting financial monitoring and budget management, and re-evaluating asset allocation and investment strategies; If the risk assessment index Zpjx>risk threshold R, it means that the financial risk level of the current department is beyond the controllable range, and a risk warning notice is generated and sent to relevant managers; The response measures taken at this time include debt restructuring, fund allocation, and cost and expenditure control; at the same time, the financial management module is used to conduct a detailed analysis of the impact on the current department's financial risk level.

8. The financial sharing evaluation system based on big data according to claim 7 is characterized by: The financial management module includes a financial data integration unit, a financial deviation analysis unit and a strategy adjustment and execution unit; The financial data integration unit is used to collect and integrate departmental financial related data from all departments according to the evaluation results of the risk evaluation index Zpjx; This includes the revenue, expenditure, assets and liabilities of each department; at the same time, the data format of each department is kept standardized and updated synchronously.

9. The financial sharing evaluation system based on big data according to claim 8 is characterized by: The financial deviation analysis unit uses the integrated departmental financial related data to calculate the total deviation value Dxy and the financial abnormality correlation index Gxz between all departments; The specific calculation formula of the total yield deviation value Dxy and the financial abnormality correlation index Gxz is as follows: In the formula, n represents the total number of departments, i is an index, indicating the department number; Bss represents the actual income of the department in the department's financial related data, Bsb represents the actual cost of the department in the department's financial related data, and Bsl represents the actual profit of the department in the department's financial related data; Bys represents the expected revenue of the department in the department's financial related data, Byb represents the expected cost of the department in the department's financial related data, and Byl represents the expected profit of the department in the department's financial related data; In the formula, n represents the total number of departments, i is the index, indicating the department number; Bss represents the actual income of the department in the department's financial related data, Bjy represents the inter-department transaction amount in the department's financial related data, Bzc represents the current department's capital income and expenditure rate in the department's financial related data, and Bzx represents the current department's budget execution rate in the department's financial related data.

10. The financial sharing evaluation system based on big data according to claim 9 is characterized in that: The strategy adjustment and execution unit is used to compare and evaluate the preset financial deviation control threshold Q with the total yield deviation value Dxy, and then compare and evaluate the financial anomaly correlation threshold U with the financial anomaly correlation index Gxz. The specific evaluation contents are as follows: When the total deviation value of harvest Dxy> the financial deviation control threshold Q, it means that the financial performance of the department has not met expectations; When the total deviation value of the harvest Dxy ≤ the financial deviation control threshold Q, it means that the financial performance of the department has reached expectations; When the financial abnormal correlation index Gxz ≥ the financial abnormal correlation threshold U, it means that there is a financial abnormal correlation risk and potential risk aggregation between the current department and other departments; When the financial abnormal correlation index Gxz is less than the financial abnormal correlation threshold U, it means that the financial correlation and transaction activities between the current department and other departments are normal, and there is no financial abnormal correlation risk and potential risk accumulation; Finally, the evaluation and analysis contents of the total deviation value Dxy of the harvest and the financial abnormal correlation index Gxz are comprehensively analyzed, and the financial strategies of the departments whose financial risk levels are beyond the controllable range are adjusted accordingly, specifically: When the financial performance of a department does not meet expectations and there are abnormal financial correlation risks and potential risk aggregation between the current department and other departments, the current department will be marked and financial resources will be reallocated; When the financial performance of a department does not meet expectations, but there is no abnormal financial correlation risk or potential risk aggregation between the current department and other departments, pay separate attention to the financial performance of the current department and analyze the cost structure and profit model of the current department at the same time; When the financial performance of a department has met expectations, but there are abnormal financial correlation risks and potential risk accumulation between the current department and other departments, separate attention will be paid to the abnormal correlation risks of the current department, as well as the transactions and financial flows between the current department and other departments, and the audit and supervision mechanisms will be adjusted.

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