Method and system for constructing model for predicting enterprise financial data

Abstract

The invention provides a model construction method and system for predicting enterprise financial data, and relates to the technical field of data scientificity, the cost-income ratio, gross profit rate, profit conversion rate and free cash flow ratio of an enterprise are calculated by extracting financial data of the enterprise in the quarter of the last year, and then a financial health index is generated; calculating an income change rate and an average profit rate of the industry in combination with historical financial data of other enterprises in the industry, generating a financial correction factor, predicting a financial safety index by using a neural network model, correcting the financial safety index through a regulation factor, obtaining a final financial safety index correction value, and setting a financial risk threshold value. And judging the financial health state of the enterprise. According to the method, the financial prediction model is constructed by collecting and processing the enterprise financial data and combining the industry financial correction factors, and dynamic evaluation and risk early warning of the enterprise financial health state are achieved.

Description

Technical Field

[0001] The present invention relates to the field of data science and technology, and in particular to a method and system for constructing a model for predicting corporate financial data. Background Art

[0002] In today's complex and ever-changing business environment, accurately predicting a company's financial data is of vital importance to management, investors and other stakeholders. Financial data forecasting can not only help companies deal with uncertainty, but also provide a reliable basis for strategic decision-making. The market environment is unpredictable, and external factors such as macroeconomic conditions, industry policies, and competitive situations will affect the company's financial performance. Through forecasting, companies can identify potential financial risks and opportunities in advance and take appropriate measures to deal with them. For example, predicting cash flow fluctuations can help avoid capital shortages, formulate financing plans in advance, and predict the company's income, expenditure, profit and other financial data, which can provide guidance for resource allocation. Companies can prepare budgets based on the results of forecasts to ensure the rational use of funds and resources and maximize capital returns.

[0003] In the existing financial analysis technology, it often relies on simple financial indicators and linear models. These indicators often cannot fully capture the nonlinear relationship between the financial data of enterprises, and it is difficult to fully reflect the complexity and dynamic changes of the financial status of enterprises. In addition, traditional financial analysis methods mostly rely on historical data and regular reports, such as quarterly reports and annual reports. Therefore, the analysis results are often delayed and cannot reflect the financial health of enterprises in real time. Enterprises may not be able to discover and respond to potential risks in time before financial problems occur, resulting in delayed decision-making, which affects the flexibility and adaptability of enterprises.

[0004] Traditional financial analysis methods often focus on past financial data and lack forward-looking forecasting capabilities. With the development of technology, companies need models that can predict future financial status, cash flow, profitability and other indicators to help companies make more accurate decisions. However, existing financial analysis methods usually lack sufficient forecasting capabilities and cannot effectively support long-term strategic decisions.

[0005] Therefore, it is necessary to provide a method and system for building a predictive enterprise financial data model to solve the above problems.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0007] The purpose of the present invention is to provide a coal mine supervision method and system based on video images to solve the problems raised in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A method for constructing a model for predicting enterprise financial data, the specific steps comprising:

[0010] Step 1: Extract characteristic parameter data based on the enterprise financial data of the previous quarter of the enterprise to be predicted, wherein the characteristic parameter data includes the enterprise's operating income, total expenditure, sales cost, total profit, net profit, total debt and free cash flow;

[0011] Step 2: Preprocessing the collected characteristic parameter data, combining the preprocessed business income, total expenditure, sales cost, total profit, net profit, total liabilities and free cash flow of the enterprise, and generating the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance respectively, wherein the preprocessing includes data cleaning and normalization of the collected characteristic parameter data;

[0012] Step 3: Calculate the financial health index of the enterprise using the generated cost input ratio, gross profit margin, profit conversion ratio and free cash flow ratio of the enterprise financials;

[0013] Step 4: Obtain the historical financial data of other companies in the industry to which the enterprise to be predicted belongs, calculate the income change rate and average profit rate of the industry to which the enterprise to be predicted belongs, and generate the financial correction factor of the industry to which the enterprise to be predicted belongs by combining the income change rate and the average profit rate;

[0014] Step 5: Establish a financial security prediction model, input the characteristic parameter data of the enterprise to be predicted into the financial security prediction model to obtain a financial security index, and use the calculated financial adjustment factor and financial health index to correct the financial security index to obtain a corrected value of the financial security index;

[0015] Step 6: Establish a financial risk threshold, compare the revised value of the financial security index with the financial risk threshold, and determine the health and safety status of the company's financial data.

[0016] Furthermore, the collected characteristic parameter data is cleaned and normalized according to the following method:

[0017] Data cleaning of characteristic parameter data includes detection and deletion of outliers and duplicate data, and processing of missing values. Specifically, it uses statistical methods to identify outliers and duplicate data in characteristic parameter data, deletes outliers and duplicate data in characteristic parameter data, and uses the mean, median or mode of characteristic parameter data to fill in missing values ​​in characteristic parameter data;

[0018] The characteristic parameter data is normalized as minimum-maximum normalization, scaling the data to Within the range, all characteristic parameter data have the same scale, and the formula is:

[0019]

[0020] in, is the characteristic parameter data after normalization. is the original characteristic parameter data, is the minimum value of the same type of feature parameter data in the data set, It is the maximum value of the same type of feature parameter data in the data set.

[0021] Furthermore, the permutations and combinations are used to generate the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance, based on the following formula:

[0022]

[0023]

[0024]

[0025]

[0026] The expense-to-income ratio is used to measure a company's cost management and expense control, the gross profit margin is used to measure a company's core profitability, the profit conversion rate is used to measure a company's conversion efficiency from gross profit to net profit, and the free cash flow ratio is used to measure a company's debt-paying ability and financial risk.

[0027] Furthermore, the method for calculating the financial health index of an enterprise is based on:

[0028] Define the cost-to-income ratio, gross profit margin, profit conversion rate and free cash flow ratio of corporate finance as letters respectively. , , , , the comprehensive calculation of the enterprise's financial health index is based on the formula:

[0029]

[0030] in, Indicates the financial health index of the enterprise. , , , They represent the expense-to-income ratio, gross profit margin, profit conversion rate and free cash flow ratio of a company's finances respectively.

[0031] Furthermore, the financial correction factor of the industry to which the enterprise to be predicted belongs is generated by combining the income change rate and the average profit rate. The method is as follows:

[0032] Get the industry The operating income of other companies in the previous year and the previous year is calculated by comparing the absolute value of the difference between the operating income of the previous year and the previous year to the ratio of the previous year, and the average value is taken as the income change rate. The formula is:

[0033]

[0034] in, represents the industry's income change rate, , Other companies The annual operating income of the company last year and the year before last, Indicates the index of other companies in the same industry. , The number of other companies in the industry;

[0035] Get the industry The net profit and operating income of other companies last year are calculated and their ratio is taken as the average profit rate. The formula is:

[0036]

[0037] in, represents the average profit margin of the industry, For other companies The company’s net profit last year;

[0038] The financial correction factor is calculated based on the rate of change of collected revenue and the average profit margin of the industry, based on the formula:

[0039]

[0040] in, Represents the financial correction factor.

[0041] Furthermore, a financial security prediction model is established to obtain the revised value of the enterprise's financial security index, based on the following method:

[0042] A financial security prediction model is established, with the characteristic parameter data of the enterprise as input and the financial security index of the enterprise as output. The financial security prediction model adopts a neural network convolution structure, including an input layer, a hidden layer and an output layer. The input layer is responsible for receiving the processed characteristic parameter data; the hidden layer is used to process the characteristic parameter data. By applying multiple convolution kernels, the hidden layer can recognize complex characteristic patterns. By using the ReLu activation function, nonlinear relationships are introduced so that the model can fit complex characteristic relationships; an independent neuron is set in the output layer, which is responsible for converting the local and high-level feature representations extracted by the hidden layer into the final prediction results;

[0043] The financial adjustment factor and financial health index calculated are then used to correct the financial security index to obtain the revised value of the financial security index. The formula for calculating the revised value of the financial security index is:

[0044]

[0045] in, represents the financial health index, is the revised value of the financial security index, The financial security index.

[0046] Furthermore, the revised value of the financial security index output by the model is compared with the financial risk threshold to determine the health status of the company's financial data. The logical formula is:

[0047]

[0048] in, Represents a logical value for judging the health status of an enterprise's financial data. When the revised value of the enterprise financial security index does not exceed the financial risk threshold, it indicates that there is no potential risk in the enterprise financial data at this time and it can be maintained; when When the revised value of the enterprise's financial security index exceeds the financial risk threshold, it indicates that the enterprise's financial data is at risk and needs to be monitored and adjusted; is the financial risk threshold.

[0049] The present invention also provides a system for constructing a forecast enterprise financial data model, the system being used to execute the above-mentioned method for constructing a forecast enterprise financial data model, comprising:

[0050] An enterprise financial characteristic data collection module, which is used to extract characteristic parameter data based on the enterprise financial data of the enterprise to be predicted in the previous quarter of the previous year, and the characteristic parameter data includes the enterprise's operating income, total expenditure, sales cost, total profit, net profit, total liabilities and free cash flow;

[0051] A feature data preprocessing module, which is used to preprocess the collected feature parameter data, and to generate the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise's finance by permutation and combination according to the preprocessed business income, total overhead expenditure, sales cost, total profit, net profit, total liabilities and free cash flow. The preprocessing includes data cleaning and normalization of the collected feature parameter data;

[0052] A financial health index generation module, the financial health index generation module is used to calculate the financial health index of the enterprise by using the generated cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance;

[0053] A financial correction factor generation module, which is used to obtain historical financial data of other companies in the industry to which the enterprise to be predicted belongs, so as to calculate the income change rate and average profit rate of the industry to which the enterprise to be predicted belongs, and to generate a financial correction factor for the industry to which the enterprise to be predicted belongs by combining the income change rate and the average profit rate;

[0054] Constructing a financial security prediction model module, the financial security prediction model construction module is used to establish a financial security prediction model, input the characteristic parameter data of the enterprise to be predicted into the financial security prediction model to obtain a financial security index, and use the calculated financial adjustment factor and financial health index to correct the financial security index to obtain a financial security index correction value;

[0055] The risk warning module is used to establish a financial risk threshold, compare the financial security index correction value with the financial risk threshold, and determine the health and safety status of the company's financial data.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention uses a series of data preprocessing and calculation methods, combined with the industry's financial data, to accurately evaluate and predict the financial health of an enterprise. By extracting and preprocessing the features of the enterprise's financial data, key financial indicators such as the cost input ratio, gross profit margin, profit conversion rate, and free cash flow ratio are generated, and the enterprise's financial health index is further calculated. The financial correction factor is generated by combining the industry's revenue change rate and average profit margin, and the financial security index is corrected through a neural network model, ultimately helping the enterprise to accurately identify its financial security risks, and providing the enterprise with more accurate financial health assessments and risk warnings. Through the quantified financial health index and security index correction value, the financial status of the enterprise can be dynamically monitored and adjusted according to industry standards to ensure timely detection of potential financial problems, thereby helping the enterprise to optimize financial decisions, reduce financial risks, and improve its long-term development stability;

[0058] In addition, the present invention also calculates the financial correction factor by introducing the industry's historical financial data, and corrects the financial security index based on the factor and the calculated financial health index, so that the judgment standard of the company's financial health can be dynamically adjusted according to the industry characteristics and changes in the economic environment. This correction mechanism makes the judgment of the company's financial health index more accurate, avoids the risk of misjudgment that may be caused by relying solely on static indicators, and improves the flexibility and adaptability of the risk warning system, so that it has higher practical value in actual applications.

[0059] The present invention solves the limitations of traditional financial forecasting methods through multi-dimensional financial data collection, convolutional neural network modeling, introduction of industry correction factors and dynamic adjustment mechanism, improves the accuracy and efficiency of predicting the financial health status of enterprises, enhances the flexibility and adaptability of the risk early warning system, and has higher practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a schematic diagram of the overall method flow of the present invention.

[0061] Figure 2 It is a schematic diagram of the system module flow of the present invention. DETAILED DESCRIPTION

[0062] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0063] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0064] Example:

[0065] See also Figure 1 , the present invention provides a technical solution:

[0066] A method for constructing a model for predicting enterprise financial data, the specific steps comprising:

[0067] Step 1: Extract characteristic parameter data based on the enterprise financial data of the previous quarter of the enterprise to be predicted, wherein the characteristic parameter data includes the enterprise's operating income, total expenditure, sales cost, total profit, net profit, total debt and free cash flow;

[0068] Step 2: Preprocessing the collected characteristic parameter data, combining the preprocessed business income, total expenditure, sales cost, total profit, net profit, total liabilities and free cash flow of the enterprise, and generating the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance respectively, wherein the preprocessing includes data cleaning and normalization of the collected characteristic parameter data;

[0069] Step 3: Calculate the financial health index of the enterprise using the generated cost input ratio, gross profit margin, profit conversion ratio and free cash flow ratio of the enterprise financials;

[0070] Step 4: Obtain the historical financial data of other companies in the industry to which the enterprise to be predicted belongs, calculate the income change rate and average profit rate of the industry to which the enterprise to be predicted belongs, and generate the financial correction factor of the industry to which the enterprise to be predicted belongs by combining the income change rate and the average profit rate;

[0071] Step 5: Establish a financial security prediction model, input the characteristic parameter data of the enterprise to be predicted into the financial security prediction model to obtain a financial security index, and use the calculated financial adjustment factor and financial health index to correct the financial security index to obtain a corrected value of the financial security index;

[0072] Step 6: Establish a financial risk threshold, compare the revised value of the financial security index with the financial risk threshold, and determine the health and safety status of the company's financial data.

[0073] It should be noted that data cleaning ensures the accuracy and consistency of data by removing outliers, duplicate data, and filling missing values, avoiding the negative impact of incomplete or erroneous data on model training. Specifically, using statistical methods to identify outliers and duplicate data and using the mean, median, or mode to fill missing values ​​can help improve the quality of data and thus improve the prediction accuracy of the model. Secondly, data normalization uses the minimum-maximum normalization method to scale all feature parameters to The same scale of the features eliminates the interference of different feature value ranges on model training and ensures that each feature has the same weight during model training. This not only speeds up the convergence of the model, but also avoids some features dominating the model training due to their large value range, further enhancing the stability and reliability of the prediction results.

[0074] Therefore, it is necessary to clean and normalize the collected characteristic parameter data, and the method is as follows:

[0075] Data cleaning of characteristic parameter data includes detection and deletion of outliers and duplicate data, and processing of missing values. Specifically, it uses statistical methods to identify outliers and duplicate data in characteristic parameter data, deletes outliers and duplicate data in characteristic parameter data, and uses the mean, median or mode of characteristic parameter data to fill in missing values ​​in characteristic parameter data;

[0076] The characteristic parameter data is normalized as minimum-maximum normalization, scaling the data to Within the range, all characteristic parameter data have the same scale, and the formula is:

[0077]

[0078] in, is the characteristic parameter data after normalization. is the original characteristic parameter data, is the minimum value of the same type of feature parameter data in the data set, It is the maximum value of the same type of feature parameter data in the data set.

[0079] It should be noted that the expense-to-income ratio, gross profit margin, profit conversion rate and free cash flow ratio are key indicators for measuring a company's financial health and operational efficiency. The expense-to-income ratio reflects a company's cost control and expense management capabilities, and can reveal a company's management level in terms of expenditure; the gross profit margin measures a company's core profitability and is an important indicator for evaluating the basic profitability of a company's products or services; the profit conversion rate reflects the efficiency of a company's conversion of gross profit into net profit, and reflects the quality of profitability during operations; the free cash flow ratio reveals a company's debt-paying ability and financial risk, and reflects the funds available for reinvestment or shareholder returns after a company meets short-term financial obligations. Combining these indicators into a financial feature vector helps to comprehensively and accurately assess a company's financial status, and provides multi-dimensional financial health information, thereby providing strong support for financial risk prediction and decision-making.

[0080] Therefore, it is necessary to perform permutations and combinations to generate the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance respectively, based on the following formula:

[0081]

[0082]

[0083]

[0084]

[0085] The expense-to-income ratio is used to measure a company's cost management and expense control, the gross profit margin is used to measure a company's core profitability, the profit conversion rate is used to measure a company's conversion efficiency from gross profit to net profit, and the free cash flow ratio is used to measure a company's debt-paying ability and financial risk.

[0086] It should be noted that the company's financial health index is a comprehensive indicator to measure the company's overall financial status, which can help management, investors and analysts quickly identify the company's financial stability and potential risks. By combining key financial indicators such as the cost-to-income ratio, gross profit margin, profit conversion rate and free cash flow ratio, the financial health index can comprehensively reflect the company's profitability, cost control ability, cash flow status and profit conversion efficiency, thereby providing data support for decision-making, ensuring that the company maintains financial stability in the fierce market competition and promoting long-term sustainable development.

[0087] Therefore, it is necessary to calculate the financial health index of the enterprise, based on the following method:

[0088] Define the cost-to-income ratio, gross profit margin, profit conversion rate and free cash flow ratio of corporate finance as letters respectively. , , , , the comprehensive calculation of the enterprise's financial health index is based on the formula:

[0089]

[0090] in, Represents the financial health index of the enterprise. , , , They represent the expense-to-income ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise's finance respectively; in the above formula, the larger the expense-to-income ratio, the smaller the financial health index, which means that the enterprise needs to pay higher expenses for its income, which may lead to a reduction in profit margins, thus affecting the overall financial health. A larger expense-to-income ratio usually indicates a lower financial health index, suggesting that the enterprise may face higher operating costs and greater financial pressure; the larger the gross profit margin, profit conversion rate and free cash flow ratio, the larger the financial health index, among which the larger the gross profit margin, the higher the proportion of profit retained by the enterprise in the income, which means that the company has a stronger ability to control costs in the production or sales process and a larger profit margin, which helps to improve the financial health index; the larger the profit conversion rate, the more effectively the enterprise's profits can be converted into actual net income and net profit, reflecting the excellent performance of the enterprise's management in resource allocation and operational efficiency, and enhancing the overall financial health; the larger the free cash flow ratio, the more it means that the enterprise can still generate sufficient cash flow after deducting necessary capital expenditures, which provides the enterprise with more financial flexibility and risk resistance, and can support expansion, debt repayment and cope with sudden economic pressures.

[0091] It should be noted that the income change rate of an industry can reflect the growth or decline trend of the income of the entire industry in different time periods, which is very important for evaluating the competitive position of enterprises in the industry. If the industry income grows rapidly, the enterprise may be in a good market environment, otherwise it may face the risk of overall shrinkage of the industry. Including the income change rate in the calculation of the correction factor will help the adjustment of the company's financial situation to better adapt to changes in the industry; the average profit margin of the industry reflects the ability of companies in the industry to convert income into profits. By calculating the average profit margin of multiple companies in the industry, the impact of the special circumstances of individual companies can be eliminated, and the profitability of the entire industry can be more accurately reflected. This provides an industry standard for evaluating the profitability of enterprises, making the evaluation of the financial health index more objective and fair.

[0092] Therefore, the financial correction factor of the industry to be predicted for the enterprise is generated by combining the income change rate and the average profit margin. The method is as follows:

[0093] Get the industry The operating income of other companies in the previous year and the previous year is calculated by comparing the absolute value of the difference between the operating income of the previous year and the previous year to the ratio of the previous year, and the average value is taken as the income change rate. The formula is:

[0094]

[0095] in, represents the industry's income change rate, , Other companies The annual operating income of the company last year and the year before last, Indicates the index of other companies in the same industry. , The number of other companies in the industry;

[0096] Get the industry The net profit and operating income of other companies last year are calculated and their ratio is taken as the average profit rate. The formula is:

[0097]

[0098] in, represents the average profit margin of the industry, For other companies The company’s net profit last year;

[0099] The financial correction factor is calculated based on the rate of change of collected revenue and the average profit margin of the industry, based on the formula:

[0100]

[0101] in, represents the financial correction factor; in the above formula, The larger the value, the better, resulting in There are two reasons why the value increases. The first is that the average profit margin of the industry increases, which means that the companies in the industry as a whole can extract more profit from each unit of revenue. This is usually because the companies in the industry perform better in cost control, product pricing, market positioning, etc., or the market demand increases, resulting in higher profit levels. When the average profit margin of the industry increases, The increase in the value indicates that the profitability of the enterprise has increased relatively, which means that the profit environment of the industry has become better, and the financial health of the enterprise in the industry may be further improved; secondly, the income change rate of the industry has decreased, which means that the income growth rate of the industry is relatively stable. Although the income growth has not increased significantly, the enterprise can still maintain a high profit margin through effective cost control and profit improvement. Therefore, the income growth of the industry has slowed down or is relatively stable, but in the context of a lower income change rate, the higher profit margin makes The increase in the value reflects that even in an environment with slower revenue growth, the company can still maintain a high level of profitability, thereby improving its financial health index.

[0102] It should be noted that building a corporate financial data prediction model and adopting a convolutional neural network structure can effectively process and learn complex nonlinear relationships in financial data, thereby improving the accuracy and robustness of financial health prediction. Through its multi-level structure, the convolutional neural network can extract deep features from the input feature vector, and is particularly suitable for processing multi-dimensional data with spatial or temporal characteristics. In this model, the input layer receives the corporate financial feature vector to ensure that the model can obtain comprehensive financial information; the hidden layer automatically captures the potential patterns and associations in the financial data by processing data layer by layer; the output layer generates the corporate financial health index, providing an accurate prediction of the company's financial health. Using the mean square error as the loss function can effectively measure the difference between the predicted value and the true value, and optimize the model parameters through the back propagation algorithm to gradually improve the model's prediction accuracy. This method continuously optimizes the model performance through multiple rounds of training and parameter updates, ensuring high prediction reliability and stability in practical applications.

[0103] Therefore, it is necessary to establish a financial security prediction model to obtain the revised value of the enterprise's financial security index. The method is based on:

[0104] A financial security prediction model is established, with the characteristic parameter data of the enterprise as input and the financial security index of the enterprise as output. The financial security prediction model adopts a neural network convolution structure, including an input layer, a hidden layer and an output layer. The input layer is responsible for receiving the processed characteristic parameter data; the hidden layer is used to process the characteristic parameter data. By applying multiple convolution kernels, the hidden layer can recognize complex characteristic patterns. By using the ReLu activation function, nonlinear relationships are introduced so that the model can fit complex characteristic relationships; an independent neuron is set in the output layer, which is responsible for converting the local and high-level feature representations extracted by the hidden layer into the final prediction results;

[0105] Obtain the financial characteristic parameter data of the enterprise in the historical years, and perform evaluation and calculation based on financial experts to obtain the financial security index. Take the financial characteristic parameter data of the enterprise in the history as input and the financial security index as label to train the financial security prediction model. In the training process, select the mean square error function as the loss function, calculate the loss function value according to the output result and the true label, and calculate the gradient through the back propagation algorithm, update the weight and bias of the neural network, and repeat the above operation until the model reaches the predetermined number of training rounds;

[0106] The financial adjustment factor and financial health index calculated are then used to correct the financial security index to obtain the revised value of the financial security index. The formula for calculating the revised value of the financial security index is:

[0107]

[0108] in, represents the financial health index, is the revised value of the financial security index, is the financial security index; in the above formula, the reason why the financial health index is used is and financial correction factors Financial security index The correction is made because if there is a year When the value is small, use and The value of When increasing, will increase moderately, which means that the company's annual revenue and profit will be better this year; When increasing, It will increase moderately, which means that the development environment of the enterprise is good and has good development prospects; and The bigger the better. Bigger means the following:

[0109] Profitability is enhanced. Enterprises can effectively improve core profit indicators such as gross profit margin and net profit, indicating that the profitability and market competitiveness of their core businesses are strong;

[0110] Proper cost control, higher Value means that the enterprise performs well in cost and expense management, can effectively control operating expenses, optimize financial structure, and avoid unnecessary expenses;

[0111] Financial risks are lower. As the financial security index improves, the company's debt repayment ability, such as the free cash flow ratio, is enhanced, which means that it can better cope with financial crises and external economic pressures and reduce financial risks;

[0112] Good capital operation, higher It usually indicates that the company's capital operation is more efficient, it can maintain good cash flow, and has strong reinvestment capacity to support long-term sustainable development;

[0113] Sound financial management, overall The larger and higher the ratio, the better. It indicates that the company has a sound financial structure, proper risk management, and is able to remain stable during economic fluctuations and generate better returns for shareholders and investors.

[0114] It should be noted that comparing the revised value of an enterprise's financial security index with the financial risk threshold can effectively determine the health status of the enterprise's financial data, thereby providing timely risk warnings and decision-making support to management. The judgment logic enables enterprises to distinguish whether there is potential financial risk based on whether the revised value of the financial security index exceeds the set financial risk threshold. When , it indicates that the financial data is in a healthy state and no adjustment is required; When the financial health index is adjusted to a level above the safe range, it means that the revised value of the financial health index has exceeded the safe range, indicating that there may be risks and measures need to be taken to monitor and adjust. Financial risk threshold The setting is based on the analysis of the company's industry characteristics, historical financial performance and future operating environment. It aims to help companies identify potential financial crises, ensure that effective measures are taken in a timely manner, avoid financial risks from having a significant impact on corporate operations, and ensure the long-term healthy development of the company.

[0115] Therefore, it is necessary to compare the revised value of the financial security index output by the model with the financial risk threshold to determine the health status of the company's financial data. The logical formula is:

[0116]

[0117] in, Represents a logical value for judging the health status of an enterprise's financial data. When the revised value of the enterprise financial security index does not exceed the financial risk threshold, it indicates that there is no potential risk in the enterprise financial data at this time and it can be maintained; when When the revised value of the enterprise's financial security index exceeds the financial risk threshold, it indicates that the enterprise's financial data is at risk and needs to be monitored and adjusted; is the financial risk threshold.

[0118] See also Figure 2 The present invention also provides a system for constructing a forecast enterprise financial data model, the system being used to execute the above-mentioned method for constructing a forecast enterprise financial data model, comprising:

[0119] An enterprise financial characteristic data collection module, which is used to extract characteristic parameter data based on the enterprise financial data of the enterprise to be predicted in the previous quarter of the previous year, and the characteristic parameter data includes the enterprise's operating income, total expenditure, sales cost, total profit, net profit, total liabilities and free cash flow;

[0120] A feature data preprocessing module, which is used to preprocess the collected feature parameter data, and to generate the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise's finance by permutation and combination according to the preprocessed business income, total overhead expenditure, sales cost, total profit, net profit, total liabilities and free cash flow. The preprocessing includes data cleaning and normalization of the collected feature parameter data;

[0121] A financial health index generation module, the financial health index generation module is used to calculate the financial health index of the enterprise by using the generated cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance;

[0122] A financial correction factor generation module, which is used to obtain historical financial data of other companies in the industry to which the enterprise to be predicted belongs, so as to calculate the income change rate and average profit rate of the industry to which the enterprise to be predicted belongs, and to generate a financial correction factor for the industry to which the enterprise to be predicted belongs by combining the income change rate and the average profit rate;

[0123] Constructing a financial security prediction model module, the financial security prediction model construction module is used to establish a financial security prediction model, input the characteristic parameter data of the enterprise to be predicted into the financial security prediction model to obtain a financial security index, and use the calculated financial adjustment factor and financial health index to correct the financial security index to obtain a financial security index correction value;

[0124] The risk warning module is used to establish a financial risk threshold, compare the financial security index correction value with the financial risk threshold, and determine the health and safety status of the company's financial data.

[0125] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0126] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0127] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0128] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for constructing a model for predicting enterprise financial data, characterized in that: The specific steps include: Step 1: Extract characteristic parameter data based on the enterprise financial data of the previous quarter of the enterprise to be predicted, wherein the characteristic parameter data includes the enterprise's operating income, total expenditure, sales cost, total profit, net profit, total debt and free cash flow; Step 2: Preprocessing the collected characteristic parameter data, combining the preprocessed business income, total expenditure, sales cost, total profit, net profit, total liabilities and free cash flow of the enterprise, and generating the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance respectively, wherein the preprocessing includes data cleaning and normalization of the collected characteristic parameter data; Step 3: Calculate the financial health index of the enterprise using the generated cost input ratio, gross profit margin, profit conversion ratio and free cash flow ratio of the enterprise financials; Step 4: Obtain the historical financial data of other companies in the industry to which the enterprise to be predicted belongs, calculate the income change rate and average profit rate of the industry to which the enterprise to be predicted belongs, and generate the financial correction factor of the industry to which the enterprise to be predicted belongs by combining the income change rate and the average profit rate; Step 5: Establish a financial security prediction model, input the characteristic parameter data of the enterprise to be predicted into the financial security prediction model to obtain a financial security index, and use the calculated financial adjustment factor and financial health index to correct the financial security index to obtain a corrected value of the financial security index; Step 6: Establish a financial risk threshold, compare the revised value of the financial security index with the financial risk threshold, and determine the health and safety status of the company's financial data.

2. A method for constructing a forecasting enterprise financial data model according to claim 1, characterized in that: The collected characteristic parameter data is cleaned and normalized according to the following method: Data cleaning of characteristic parameter data includes detection and deletion of outliers and duplicate data, and processing of missing values. Specifically, it uses statistical methods to identify outliers and duplicate data in characteristic parameter data, deletes outliers and duplicate data in characteristic parameter data, and uses the mean, median or mode of characteristic parameter data to fill in missing values ​​in characteristic parameter data; The characteristic parameter data is normalized as minimum-maximum normalization, scaling the data to Within the range, all characteristic parameter data have the same scale, and the formula is: in, is the characteristic parameter data after normalization. is the original characteristic parameter data, is the minimum value of the same type of feature parameter data in the data set, It is the maximum value of the same type of feature parameter data in the data set.

3. A method for constructing a forecasting enterprise financial data model according to claim 1, characterized in that: The formulas for generating the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance are as follows: The expense-to-income ratio is used to measure a company's cost management and expense control, the gross profit margin is used to measure a company's core profitability, the profit conversion rate is used to measure a company's conversion efficiency from gross profit to net profit, and the free cash flow ratio is used to measure a company's debt-paying ability and financial risk.

4. A method for constructing a forecasting enterprise financial data model according to claim 1, characterized in that: The method for calculating the financial health index of an enterprise is based on: Define the cost-to-income ratio, gross profit margin, profit conversion rate and free cash flow ratio of corporate finance as letters respectively. , , , , the comprehensive calculation of the enterprise's financial health index is based on the formula: in, Represents the financial health index of the enterprise. , , , They represent the expense-to-income ratio, gross profit margin, profit conversion rate and free cash flow ratio of a company's finances respectively.

5. A method for constructing a forecasting enterprise financial data model according to claim 1, characterized in that: Combining the income change rate and the average profit margin, the financial correction factor of the industry to which the enterprise to be predicted belongs is generated based on the following method: Get the industry The operating income of other companies in the previous year and the previous year is calculated by comparing the absolute value of the difference between the operating income of the previous year and the previous year to the ratio of the previous year, and the average value is taken as the income change rate. The formula is: in, represents the rate of change of industry revenue, , Other companies The annual operating income of the company last year and the year before last, Indicates the index of other companies in the same industry. , The number of other companies in the industry; Get the industry The net profit and operating income of other companies last year are calculated and their ratio is taken as the average profit rate. The formula is: in, represents the average profit margin of the industry, For other companies The company’s net profit last year; The financial correction factor is calculated based on the rate of change of collected revenue and the average profit margin of the industry, based on the formula: in, Represents the financial correction factor.

6. A method for constructing a forecasting enterprise financial data model according to claim 1, characterized in that: A financial security prediction model is established to obtain the revised value of the enterprise's financial security index, based on the following method: A financial security prediction model is established, with the characteristic parameter data of the enterprise as input and the financial security index of the enterprise as output. The financial security prediction model adopts a neural network convolution structure, including an input layer, a hidden layer and an output layer. The input layer is responsible for receiving the processed characteristic parameter data; the hidden layer is used to process the characteristic parameter data. By applying multiple convolution kernels, the hidden layer can recognize complex characteristic patterns. By using the ReLu activation function, nonlinear relationships are introduced so that the model can fit complex characteristic relationships. An independent neuron is set in the output layer, which is responsible for converting the local and high-level feature representations extracted by the hidden layer into the final prediction results; The financial adjustment factor and financial health index calculated are then used to correct the financial security index to obtain the revised value of the financial security index. The formula for calculating the revised value of the financial security index is: in, represents the financial health index, is the revised value of the financial security index, The financial security index.

7. A method for constructing a forecasting enterprise financial data model according to claim 6, characterized in that: Compare the revised value of the financial security index output by the model with the financial risk threshold to determine the health status of the company's financial data. The logical formula is: in, Represents a logical value for judging the health status of an enterprise's financial data. When the revised value of the enterprise financial security index does not exceed the financial risk threshold, it indicates that there is no potential risk in the enterprise financial data at this time and it can be maintained; when When the revised value of the enterprise's financial security index exceeds the financial risk threshold, it indicates that the enterprise's financial data is at risk and needs to be monitored and adjusted; is the financial risk threshold.

8. A system for building a model for predicting corporate financial data, characterized in that: The construction system is used to execute a method for constructing a forecast enterprise financial data model according to any one of claims 1 to 7, comprising: An enterprise financial characteristic data collection module, which is used to extract characteristic parameter data based on the enterprise financial data of the enterprise to be predicted in the previous quarter of the previous year, and the characteristic parameter data includes the enterprise's operating income, total expenditure, sales cost, total profit, net profit, total liabilities and free cash flow; A feature data preprocessing module, which is used to preprocess the collected feature parameter data, and to generate the cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise's finance by permutation and combination according to the preprocessed business income, total overhead expenditure, sales cost, total profit, net profit, total liabilities and free cash flow. The preprocessing includes data cleaning and normalization of the collected feature parameter data; A financial health index generation module, the financial health index generation module is used to calculate the financial health index of the enterprise by using the generated cost input ratio, gross profit margin, profit conversion rate and free cash flow ratio of the enterprise finance; A financial correction factor generation module, which is used to obtain historical financial data of other companies in the industry to which the enterprise to be predicted belongs, so as to calculate the income change rate and average profit rate of the industry to which the enterprise to be predicted belongs, and to generate a financial correction factor for the industry to which the enterprise to be predicted belongs by combining the income change rate and the average profit rate; Constructing a financial security prediction model module, the financial security prediction model construction module is used to establish a financial security prediction model, input the characteristic parameter data of the enterprise to be predicted into the financial security prediction model to obtain a financial security index, and use the calculated financial adjustment factor and financial health index to correct the financial security index to obtain a financial security index correction value; The risk warning module is used to establish a financial risk threshold, compare the financial security index correction value with the financial risk threshold, and determine the health and safety status of the company's financial data.

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