Financial decision support system based on machine learning driving

Abstract

The invention relates to the technical field of enterprise financial aid decision making, and discloses a financial decision support system based on machine learning driving. According to the financial decision support system driven by machine learning, various data of enterprise finance are collected, the data are combined to analyze risks of the data, financial risks are calculated according to the risks of the generated data, and the financial risks are judged according to the financial risks generated through calculation. According to the method and the device, the enterprise finance risk early-warning signal is generated, the generated finance risk early-warning signal is fed back to the enterprise finance staff through the display unit, and the enterprise finance staff judges the current finance risk of the enterprise according to the generated finance risk early-warning signal and makes a corresponding decision according to the numerical value in combination with the actual situation. Therefore, early warning can be quickly made in time according to the current financial state of the enterprise, financial staff are assisted to make corresponding decisions, and omission and decision deviation caused by manual analysis are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise financial decision support, and in particular to a financial decision support system driven by machine learning. Background Art

[0002] Corporate financial decision-making refers to a series of decision-making processes in which companies identify, evaluate and respond to uncertain factors that may affect their financial status and profit levels when conducting fund management, investment selection and strategic planning. This includes predicting and managing possible financial risks, such as market risk, credit risk, liquidity risk, etc., through financial analysis and risk control measures to ensure the financial health and long-term sustainable development of the company.

[0003] At present, corporate financial decisions are usually made through manual analysis and judgment by the company's finance and managers based on the company's current cash flow, accounts receivable, sales, sales volume, accounts payable and other data. However, some data will be missed during manual analysis. At the same time, it is impossible to quickly issue warnings based on the current financial status of the company, resulting in decision-making deviations. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides a financial decision support system driven by machine learning, which has the ability to collect various financial data of an enterprise, combine and analyze the risks of various data, calculate the financial risks based on the risks of various data generated, judge the size of the financial risks based on the calculated financial risks, generate corresponding financial risk warning signals, and feed back the generated financial risk warning signals to the enterprise's financial staff through a display unit. The enterprise's financial staff judge the current size of the enterprise's financial risks based on the generated financial risk warning signals, and make corresponding decisions based on this value and actual conditions. In this way, early warnings can be made in a timely manner based on the current financial status of the enterprise, and financial personnel can be assisted in making corresponding decisions, thereby avoiding omissions in manual analysis and decision-making deviations, thereby solving the above-mentioned problems.

[0006] (II) Technical solution

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a financial decision support system driven by machine learning, comprising an enterprise financial data collection unit, an enterprise financial data processing unit and a display unit;

[0008] The enterprise financial data collection unit is used to collect the enterprise's cash inflow data, cash outflow data, total sales data, total accounts receivable data, the total debt that the enterprise currently needs to repay, current sales volume and sales volume data of the previous cycle, and the enterprise financial data collection unit sends the collected data to the enterprise financial data processing unit connected thereto;

[0009] After the enterprise financial data processing unit receives the data sent by the enterprise financial data collection unit, the enterprise financial data processing unit calculates the net cash flow, current ratio and cash burn rate according to the cash inflow data and the cash outflow data, calculates the accounts receivable turnover rate according to the total sales data and the total accounts receivable data, calculates the cash flow coverage ratio according to the cash inflow data, the cash outflow data and the total amount of debts that the enterprise currently needs to repay, calculates the business growth rate according to the current sales volume and the sales volume data of the previous cycle, determines the size of the financial risk of the enterprise according to the calculated cash inflow amount, current ratio, cash burn rate, accounts receivable turnover rate, cash flow coverage ratio and business growth rate, and generates a corresponding financial risk warning signal, and the enterprise financial data processing unit sends the generated financial risk warning signal to the display unit;

[0010] The display unit is used to display the value of the financial risk warning signal to the staff.

[0011] Preferably, the cash inflow data is represented as Jx, the cash outflow data is represented as Cx, the total sales data is represented as XSz, the total accounts receivable data is represented as Ys, the total debt that the enterprise currently needs to repay is represented as CHZ, the current sales volume is represented as XS, and the sales volume data of the previous cycle is represented as qXS.

[0012] Preferably, the net cash flow calculation expression is:

[0013] Xj=Jx-Cx

[0014] In the formula, Xj represents the net cash flow, and Jx-Cx represents the difference between the cash inflow data and the cash outflow data.

[0015] Preferably, the current ratio calculation expression is as follows:

[0016]

[0017] In the formula, Xld is expressed as the current ratio, which is the ratio of net cash flow to cash outflow data.

[0018] Preferably, the cash burn rate calculation expression is as follows:

[0019]

[0020] In the formula, t represents the time span of this data collection cycle, Cx-Jx represents the difference between the cash outflow data and the cash inflow data, and Xjr represents the cash burn rate.

[0021] Preferably, the accounts receivable turnover rate calculation expression is as follows:

[0022]

[0023] In the formula, ZZl represents the accounts receivable turnover. Represents the ratio of total sales data to total accounts receivable data.

[0024] Preferably, the cash flow coverage ratio calculation expression is as follows:

[0025]

[0026] In the formula, XJF represents the cash flow coverage ratio, and Cx+CHZ represents the sum of the cash outflow data and the total amount of debt that the company currently needs to repay, that is, the total expenses that the company needs to spend in the current cycle. It is expressed as the ratio of cash inflow data to the total expenses that the company needs to pay in the current cycle, which is the cash flow coverage ratio.

[0027] Preferably, the business growth rate calculation expression is as follows:

[0028]

[0029] In the formula, YZl represents the business growth rate, and XS-qXS represents the difference between the current sales volume and the sales volume data of the previous cycle.

[0030] Preferably, the cash inflow financial risk judgment expression is:

[0031]

[0032] In the formula, Xjf represents the financial risk of cash inflow, 1 means that there is risk in cash inflow, and 0 means that there is no risk in cash inflow;

[0033] The current ratio financial risk judgment expression is:

[0034]

[0035] In the formula, Xldf represents the financial risk of the current ratio, 1 means that the current ratio is at risk, and 0 means that the current ratio is not at risk;

[0036] The cash burn rate financial risk judgment expression is:

[0037]

[0038] In the formula, Xjrf represents the financial risk of cash burn rate, 1 means that the cash burn rate is at risk, and 0 means that the cash burn rate is not at risk. The cash burn rate at risk means that the company is consuming cash;

[0039] The financial risk judgment expression of accounts receivable turnover rate is:

[0040]

[0041] In the formula, ZZlf represents the financial risk of accounts receivable turnover rate, 1 means that there is risk in accounts receivable turnover rate, and 0 means that there is no risk in accounts receivable turnover rate;

[0042] The cash flow coverage ratio financial risk judgment expression is:

[0043]

[0044] In the formula, XJFf represents the financial risk of the cash flow coverage ratio, 1 means that there is a risk in the cash flow coverage ratio, and 0 means that there is no risk in the cash flow coverage ratio;

[0045] The financial risk judgment expression of the business growth rate is:

[0046]

[0047] In the formula, YZlf represents the financial risk of the business growth rate, 1 means that there is a risk in the business growth rate, and 0 means that there is no risk in the business growth rate.

[0048] Preferably, the financial risk calculation expression is determined as follows:

[0049] CF=Xjf+Xldf+Xjrf+ZZlf+XJFf+YZlf

[0050] In the formula, CF represents financial risk;

[0051] When the financial risk CF>3, it means that the financial risk is high and a high financial risk warning signal is generated;

[0052] When 3<Financial Risk CF≤2, it means that the financial risk is medium and a medium financial risk warning signal is generated;

[0053] When 0<Financial Risk CF<2, it means that the financial risk is small and a low financial risk warning signal is generated.

[0054] Compared with the prior art, the present invention provides a financial decision support system driven by machine learning, which has the following beneficial effects:

[0055] The present invention collects various financial data of an enterprise, combines and analyzes the risks of various data, calculates the financial risks based on the risks of various data, judges the size of the financial risks based on the calculated financial risks, generates corresponding financial risk warning signals, and feeds back the generated financial risk warning signals to the financial staff of the enterprise through a display unit. The financial staff of the enterprise judges the current financial risk size of the enterprise based on the generated financial risk warning signals, and makes corresponding decisions based on this value and actual conditions, thereby making early warnings in a timely manner based on the current financial status of the enterprise, and assisting financial personnel in making corresponding decisions, thereby avoiding omissions in manual analysis and decision-making deviations. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0057] 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.

[0058] See also Figure 1 , a financial decision support system based on machine learning drive, including an enterprise financial data collection unit, an enterprise financial data processing unit and a display unit;

[0059] The enterprise financial data collection unit is used to collect the enterprise's cash inflow data, cash outflow data, total sales data, total accounts receivable data, the total amount of debt that the enterprise currently needs to repay, the current sales volume and the sales volume data of the previous cycle, wherein the cash inflow data is represented by Jx, the cash outflow data is represented by Cx, the total sales data is represented by XSz, the total accounts receivable data is represented by Ys, the total amount of debt that the enterprise currently needs to repay is represented by CHZ, the current sales volume is represented by XS, and the sales volume data of the previous cycle is represented by qXS. The enterprise financial data collection unit sends the collected data to the enterprise financial data processing unit connected to it.

[0060] After the enterprise financial data processing unit receives the data that can be sent by the enterprise financial data collection unit, the enterprise financial data processing unit processes the received data, for example:

[0061] The enterprise financial data processing unit calculates the net cash flow, current ratio and cash burn rate based on the cash inflow data and cash outflow data;

[0062] The calculation expression of net cash flow is:

[0063] Xj=Jx-Cx

[0064] In the formula, Xj represents the net cash flow, and Jx-Cx represents the difference between the cash inflow data and the cash outflow data;

[0065] The current ratio calculation expression is as follows:

[0066]

[0067] In the formula, Xld is expressed as the current ratio, which is the ratio of net cash flow to cash outflow data;

[0068] The cash burn rate calculation expression is as follows:

[0069]

[0070] In the formula, t represents the time span of this data collection cycle, Cx-Jx represents the difference between the cash outflow data and the cash inflow data, and Xjr represents the cash burn rate.

[0071] The enterprise financial data processing unit calculates the accounts receivable turnover rate based on the total sales data and the total accounts receivable data. The calculation expression is as follows:

[0072]

[0073] In the formula, ZZl represents the accounts receivable turnover. Represents the ratio of total sales data to total accounts receivable data.

[0074] The enterprise financial data processing unit calculates the cash flow coverage ratio based on the cash inflow data, cash outflow data and the total amount of debt that the enterprise currently needs to repay; its calculation expression is as follows:

[0075]

[0076] In the formula, XJF represents the cash flow coverage ratio, and Cx+CHZ represents the sum of the cash outflow data and the total amount of debt that the company currently needs to repay, that is, the total expenses that the company needs to spend in the current cycle. It is expressed as the ratio of cash inflow data to the total expenses that the company needs to pay in the current cycle, which is the cash flow coverage ratio.

[0077] The enterprise financial data processing unit calculates the business growth rate based on the current sales volume and the sales volume data of the previous cycle. The calculation expression is as follows:

[0078]

[0079] In the formula, YZl represents the business growth rate, and XS-qXS represents the difference between the current sales volume and the sales volume data of the previous cycle.

[0080] The enterprise financial data processing unit determines the financial risk of the enterprise based on the calculated cash inflow, current ratio, cash burn rate, accounts receivable turnover rate, cash flow coverage ratio and business growth rate, and generates corresponding financial risk warning signals. The specific judgments are as follows:

[0081] The financial risk judgment expression of cash inflow is:

[0082]

[0083] In the formula, Xjf represents the financial risk of cash inflow, 1 means that there is risk in cash inflow, and 0 means that there is no risk in cash inflow;

[0084] The financial risk judgment expression of current ratio is:

[0085]

[0086] In the formula, Xldf represents the financial risk of the current ratio, 1 means that the current ratio is at risk, and 0 means that the current ratio is not at risk;

[0087] The cash burn rate financial risk judgment expression is:

[0088]

[0089] In the formula, Xjrf represents the financial risk of cash burn rate, 1 means that the cash burn rate is at risk, and 0 means that the cash burn rate is not at risk. The cash burn rate at risk means that the company is consuming cash;

[0090] The financial risk judgment expression of accounts receivable turnover rate is:

[0091]

[0092] In the formula, ZZlf represents the financial risk of accounts receivable turnover rate, 1 means that there is risk in accounts receivable turnover rate, and 0 means that there is no risk in accounts receivable turnover rate;

[0093] The financial risk judgment expression of cash flow coverage ratio is:

[0094]

[0095] In the formula, XJFf represents the financial risk of the cash flow coverage ratio, 1 means that there is a risk in the cash flow coverage ratio, and 0 means that there is no risk in the cash flow coverage ratio;

[0096] The financial risk judgment expression of business growth rate is:

[0097]

[0098] In the formula, YZlf represents the financial risk of the business growth rate, 1 means that there is a risk in the business growth rate, and 0 means that there is no risk in the business growth rate.

[0099] After the above determination is completed, the corresponding financial risk warning signal is generated, and the financial risk is calculated according to the above determination result. The specific expression is as follows:

[0100] CF=Xjf+Xldf+Xjrf+ZZlf+XJFf+YZlf

[0101] In the formula, CF represents financial risk.

[0102] There are three types of financial risks, which are specifically determined as follows:

[0103] When the financial risk CF>3, it means that the financial risk is high and a high financial risk warning signal is generated;

[0104] When 3<Financial Risk CF≤2, it means that the financial risk is medium and a medium financial risk warning signal is generated;

[0105] When 0<Financial Risk CF<2, it means that the financial risk is small and a low financial risk warning signal is generated.

[0106] After the financial risk warning signal is generated, the enterprise's financial data processing unit sends the generated financial risk warning signal to the display unit, and the display unit displays the value of the financial risk warning signal to the enterprise's financial staff. The enterprise's financial staff judges the current financial risk of the enterprise based on the value of the generated financial risk warning signal.

[0107] By collecting various financial data of the enterprise, combining and analyzing these data for risks, calculating the financial risks of the various data, and judging the size of the financial risks based on the calculated financial risks, and generating corresponding financial risk warning signals, the generated financial risk warning signals are fed back to the enterprise's financial staff through the display unit. The enterprise's financial staff judge the size of the enterprise's current financial risk based on the generated financial risk warning signals, and make corresponding decisions based on this value and actual conditions, so that early warnings can be made in a timely manner based on the current financial status of the enterprise, and financial personnel can be assisted in making corresponding decisions to avoid omissions in manual analysis and decision-making deviations.

[0108] 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 decision support system driven by machine learning, characterized by: It includes an enterprise financial data collection unit, an enterprise financial data processing unit and a display unit; The enterprise financial data collection unit is used to collect the enterprise's cash inflow data, cash outflow data, total sales data, total accounts receivable data, the total debt that the enterprise currently needs to repay, current sales volume and sales volume data of the previous cycle, and the enterprise financial data collection unit sends the collected data to the enterprise financial data processing unit connected thereto; After the enterprise financial data processing unit receives the data sent by the enterprise financial data collection unit, the enterprise financial data processing unit calculates the net cash flow, current ratio and cash burn rate according to the cash inflow data and the cash outflow data, calculates the accounts receivable turnover rate according to the total sales data and the total accounts receivable data, calculates the cash flow coverage ratio according to the cash inflow data, the cash outflow data and the total amount of debts that the enterprise currently needs to repay, calculates the business growth rate according to the current sales volume and the sales volume data of the previous cycle, determines the size of the financial risk of the enterprise according to the calculated cash inflow amount, current ratio, cash burn rate, accounts receivable turnover rate, cash flow coverage ratio and business growth rate, and generates a corresponding financial risk warning signal, and the enterprise financial data processing unit sends the generated financial risk warning signal to the display unit; The display unit is used to display the value of the financial risk warning signal to the staff.

2. A financial decision support system based on machine learning drive according to claim 1, characterized in that: The cash inflow data is represented as Jx, the cash outflow data is represented as Cx, the total sales data is represented as XSz, the total accounts receivable data is represented as Ys, the total debt that the enterprise currently needs to repay is represented as CHZ, the current sales volume is represented as XS, and the sales volume data of the previous cycle is represented as qXS.

3. A financial decision support system based on machine learning drive according to claim 2, characterized in that: The net cash flow calculation expression is: Xj=Jx-Cx In the formula, Xj represents the net cash flow, and Jx-Cx represents the difference between the cash inflow data and the cash outflow data.

4. A financial decision support system based on machine learning drive according to claim 3, characterized in that: The current ratio calculation expression is as follows: In the formula, Xld is expressed as the current ratio, which is the ratio of net cash flow to cash outflow data.

5. A financial decision support system based on machine learning drive according to claim 4, characterized in that: The cash burn rate calculation expression is as follows: In the formula, t represents the time span of this data collection cycle, Cx-Jx represents the difference between the cash outflow data and the cash inflow data, and Xjr represents the cash burn rate.

6. A financial decision support system based on machine learning drive according to claim 5, characterized in that: The calculation expression of accounts receivable turnover rate is as follows: In the formula, ZZl represents the accounts receivable turnover. Represents the ratio of total sales data to total accounts receivable data.

7. A financial decision support system based on machine learning drive according to claim 6, characterized in that: The cash flow coverage ratio calculation expression is as follows: In the formula, XJF represents the cash flow coverage ratio, and Cx+CHZ represents the sum of the cash outflow data and the total amount of debt that the company currently needs to repay, that is, the total expenses that the company needs to spend in the current cycle. It is expressed as the ratio of cash inflow data to the total expenses that the company needs to pay in the current cycle, which is the cash flow coverage ratio.

8. A financial decision support system based on machine learning drive according to claim 7, characterized in that: The business growth rate calculation expression is as follows: In the formula, YZl represents the business growth rate, and XS-qXS represents the difference between the current sales volume and the sales volume data of the previous cycle.

9. A financial decision support system based on machine learning drive according to claim 8, characterized in that: The cash flow amount financial risk judgment expression is: In the formula, Xjf represents the financial risk of cash inflow, 1 means that there is risk in cash inflow, and 0 means that there is no risk in cash inflow; The current ratio financial risk judgment expression is: In the formula, Xldf represents the financial risk of the current ratio, 1 means that the current ratio is at risk, and 0 means that the current ratio is not at risk; The cash burn rate financial risk judgment expression is: In the formula, Xjrf represents the financial risk of cash burn rate, 1 means that the cash burn rate is at risk, and 0 means that the cash burn rate is not at risk. The cash burn rate at risk means that the company is consuming cash; The financial risk judgment expression of accounts receivable turnover rate is: In the formula, ZZlf represents the financial risk of accounts receivable turnover rate, 1 means that there is risk in accounts receivable turnover rate, and 0 means that there is no risk in accounts receivable turnover rate; The cash flow coverage ratio financial risk judgment expression is: In the formula, XJFf represents the financial risk of the cash flow coverage ratio, 1 means that there is a risk in the cash flow coverage ratio, and 0 means that there is no risk in the cash flow coverage ratio; The financial risk judgment expression of the business growth rate is: In the formula, YZlf represents the financial risk of the business growth rate, 1 means that there is a risk in the business growth rate, and 0 means that there is no risk in the business growth rate.

10. A financial decision support system based on machine learning drive according to claim 9, characterized in that: The calculation expression for determining the financial risk is as follows; CF=Xjf+Xldf+Xjrf+ZZlf+XJFf+YZlf In the formula, CF represents financial risk; When the financial risk CF>3, it means that the financial risk is high and a high financial risk warning signal is generated; When 3<Financial Risk CF≤2, it means that the financial risk is medium and a medium financial risk warning signal is generated; When 0<Financial Risk CF<2, it means that the financial risk is small and a low financial risk warning signal is generated.

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