Tobacco financial data risk analysis system

Abstract

The invention relates to the technical field of tobacco finance, and discloses a tobacco finance data risk analysis system, which comprises an authority management module, a data source collection module, a data processing module, a data analysis module and a risk assessment module. According to the tobacco financial data risk analysis system, an authorizer can directly obtain tobacco financial data after key input and fingerprint identification success, and a third-party authorizer needs to send a success signal to a confirmation window after third-party key and third-party fingerprint information identification success; the financial data source can be obtained only after the user confirms authorization, the safety and privacy of the financial data are effectively guaranteed, only the authorized user can access the financial data, data leakage or malicious tampering is prevented, manual intervention can be reduced by automatically collecting and processing data, the working efficiency is improved, human errors are reduced, and the user experience is improved. An enterprise is helped to identify and evaluate potential risks in real time, so that preventive measures are taken, and risk influences are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of tobacco finance, and in particular to a tobacco finance data risk analysis system. Background Art

[0002] The tobacco financial data risk analysis system is a tool used to evaluate and manage the financial risks of tobacco industry enterprises. Its main goal is to help enterprises identify, analyze and respond to various risk factors that may affect financial health. The use of the tobacco financial data risk analysis system has changed the original financial working methods and the concepts of financial personnel, promoted the reform of financial organizational structure, and also put forward higher requirements on the quality and skills of financial personnel;

[0003] The system uses technical means such as data extraction, data cleaning, data analysis, model display, and intelligent early warning to achieve regular inspection and early warning of financial information standardization and financial risk focus indicators. This helps companies quickly and accurately understand their financial status and potential risks, and provides strong data support for decision-making;

[0004] However, in order to improve the effectiveness of the tobacco financial data risk analysis system, the system may not have a mechanism to update data in real time or at a high frequency, resulting in the analysis results being based on outdated data, affecting the accuracy of the forecast, failing to accurately identify and assess risks, and prone to false warnings or omissions. At the same time, when collecting and processing large amounts of financial data, the system needs to ensure the privacy and security of the data. Lax access control of the system may result in unauthorized users accessing sensitive data, thereby increasing risks. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the deficiencies in the prior art, the present invention provides a tobacco financial data risk analysis system, which has the function of limiting access to financial data to authorized users through data permission management, preventing data leakage or malicious tampering, thereby reducing the risk of data leakage. Automatic data collection and processing can reduce manual intervention, improve work efficiency and reduce human errors. At the same time, the collection of real-time data can help enterprises to instantly identify and evaluate potential risks, so as to take preventive measures and reduce the impact of risks. It solves the problems of lax access control of the system, resulting in unauthorized users accessing sensitive data, and the system has no mechanism for real-time or high-frequency data update, resulting in the analysis results being based on outdated data, resulting in erroneous warnings or underreporting.

[0007] (II) Technical solution

[0008] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a tobacco financial data risk analysis system, comprising a rights management module, a data source collection module, a data processing module, a data analysis module and a risk assessment module;

[0009] The authority management module includes a personal login unit, a non-personal login unit and a user identification unit, and the authority management module is connected to the data source collection module through a network;

[0010] The personal login unit is internally provided with a key input window, a fingerprint identification window and a confirmation window. The key input window is used to input a key for login, and the fingerprint identification window is used to identify the fingerprint information of the authorizer. The key input window and the fingerprint identification window form a personal login data group BRDL and send it to the user identification unit.

[0011] The non-personal login unit is internally provided with a third-party key input window and a third-party fingerprint identification window. The third-party key input window is used for the third-party to input a key for login. The third-party fingerprint identification window is used to collect fingerprint information of the third-party authorizer and send it to the confirmation window for confirmation. The third-party key input window and the third-party fingerprint identification window form a non-personal login data group FBRDL and send it to the user identification unit.

[0012] The user identification unit performs login confirmation according to the user login data group BEDL and the non-user login data group FBRDL;

[0013] The data source collection module includes a cash flow data collection unit, a financial data collection unit and a profit data collection unit. The cash flow data collection unit is used to collect multiple real-time cash flow data XJLsj, and the collected multiple cash flow data XJLsj form a real-time cash flow data set. The financial data collection unit collects operating cost data, current total asset data, retained earnings data, profit before interest and tax, equity market value, current total liabilities and current total sales revenue according to market data and financial statements, and sends the collected data to the data analysis module. The profit data collection unit is used to collect multiple real-time profit data LRsj, and the collected multiple real-time profit data LRsj form a real-time profit data set. The data source collection module sends the real-time cash flow data set and the real-time profit data set to the data processing module;

[0014] The data processing module pre-processes the real-time cash flow data set and the real-time profit data set to obtain the cleaned cash flow characteristics XJLtz and profit characteristics LRtz, and the data analysis module sends these data to the risk assessment module through the network;

[0015] The data analysis module calculates the financial health feature CWJKtz based on the collected operating cost data, current total asset data, retained earnings data, profit before interest and tax, equity market value, current total liabilities and current total sales revenue, and the data analysis module sends the data to the risk assessment module through the network;

[0016] The risk assessment module is preset with a cash flow standard indicator XJzb, a profit standard indicator LRzb, a high-level financial health standard value CJbz, an intermediate financial health standard value ZJbz and a low-level financial health standard value DJbz. The risk assessment module compares the cleaned cash flow characteristic XJLtz with the cash flow standard indicator XJzb to determine whether the company has the repayment ability. The risk assessment module compares the cleaned profit characteristic LRtz with the profit standard indicator LRzb to determine whether the company is facing risks. The risk assessment module compares the financial health characteristic CWJKtz with the high-level financial health standard value CJbz, the intermediate financial health standard value ZJbz and the low-level financial health standard value DJbz to determine the current financial status.

[0017] Preferably, the expression of the personal login data group BRDL is:

[0018]

[0019] In the formula, BRMY1 represents the personal key, BRZW1 represents the personal fingerprint information, BRMY1=0 represents the personal key input is successful, BRZW1=0 represents the personal fingerprint information is successfully identified, and the user identification unit sends the personal identification success signal to the data source collection module to authorize login.

[0020] Preferably, the expression of the non-personal login data group FBRDL is:

[0021]

[0022] In the formula, DMY3 represents a third-party key, DZW3 represents third-party fingerprint information, DMY3=1 represents successful input of the third-party key, DZW3=1 represents successful identification of the third-party fingerprint information, and the user identification unit sends a third-party identification success signal to the confirmation window, which is then confirmed by the user and sent to the data source collection module for authorized login.

[0023] Preferably, the real-time cash flow data set expression is: to Real-time current assets, inventories and current liabilities obtained from corresponding financial statements, XJLxj z Represents the real-time current asset value, XJLsj cRepresents the real-time inventory value, XJLsj f Represents the real-time current liabilities value, XJLsj1 represents the first data collected in the data set, XJLsjN represents the last data collected in the data set, and N represents that there are N data in the data set;

[0024] The algorithm formula of the cleaned cash flow characteristic XJLtz is as follows:

[0025]

[0026] In the formula, (XJLsj1 z +XJLsj2 z +…+XJLsjN z ) represents the sum of all real-time current assets within the collection interval, (XJLsj1 c +XJLsj2 c +…+XJLsjN c ) represents the sum of all real-time inventories within the collection interval, XJLsj 1f +XJLsj2 f +…+XJLsjN f Represents the sum of all real-time current liabilities within the collection interval, (XJLsj1 z +XJLsj2 z +…+XJLsjN z )-(XJLsj1 c +XJLsj2 c +…+XJLsjN c ) represents the total value of quick assets. The cleaned cash flow characteristics XJLtz are calculated by dividing the total value of quick assets by the sum of all real-time current liabilities in the collection interval.

[0027] Preferably, the risk assessment module compares the cleaned cash flow characteristic XJLtz with the cash flow standard indicator XJzb. If the cleaned cash flow characteristic XJLtz is higher than or equal to the cash flow standard indicator XJzb, it means that the company has the ability to repay. If the cleaned cash flow characteristic XJLtz is lower than the cash flow standard indicator XJzb, it means that the company faces repayment risk.

[0028] Preferably, the financial data collection unit numbers the collected operating cost data, current total asset data, retained earnings data, earnings before interest and taxes, equity market value, current total liabilities and current total sales revenue according to financial characteristics, and the collected operating cost data, current total asset data, retained earnings data, earnings before interest and taxes, equity market value, current total liabilities and current total sales revenue are numbered YY1, DZ2, LC3, XS4, GQ5, FZ6 and XSz7, respectively.

[0029] Preferably, the algorithm formula of the financial health feature CWJKtz is as follows:

[0030]

[0031] In the formula, Represents the liquidity and short-term debt repayment ability of tobacco companies. Represents the accumulated profitability of tobacco companies, Represents the profitability of tobacco company assets, Represents the debt capacity of shareholders. Represents the asset operation efficiency of tobacco companies, 0.2 means The weight of the ratio, 0.3 means for The weight of the ratio, 0.1 means for The weight of the ratio, 0.2 means for The weight of the ratio, 0.1 means for The weights of the ratios, 0.2, 0.3, 0.1, 0.2 and 0.1 are all fixed constants in the calculation formula of the financial health characteristics.

[0032] Preferably, the risk assessment module compares the financial health characteristic CWJKtz with the low-level financial health standard value DJbz. If the financial health characteristic CWJKtz is lower than the low-level financial health standard value DJbz, it means that the enterprise is facing bankruptcy. If the high-level financial health standard value CJbz≤financial health characteristic CWJKtz<low-level financial health standard value DJbz, it means that the enterprise is in financial risk. If the financial health characteristic CWJKtz is higher than the high-level financial health standard value CJbz, it means that the current financial situation is healthy.

[0033] Preferably, the profit data set expression is {LRsj1, LRsj2, ..., LRsj N}, LRsj1 represents the first collected data in the data set, LRsj N Represents the last data in the data set, and the subscripts 1 to N represent that there are N data collected in the data set;

[0034] The profit characteristic LRtz algorithm formula after cleaning is as follows:

[0035]

[0036] In the formula, i=2 in the table means that the calculation starts from the second profit data in the real-time profit data set, that is, LRsj2, and N means that the calculation ends at the last data in the value data set, that is, LRsj N End, (LRsj i -LRsj i-1) represents LRsj i The difference between the previous data, Represents the sum of the differences between all adjacent data points in the collection interval, In Represents the mean of all data points in the collection interval, Represents the difference between all data points and the mean value in the collection interval. Represents the square of the difference between all data points and the mean value in the collection interval, Represents the sum of the square differences of all data points in the collection interval. The sum of the square differences is divided by the total number of data points in the collection interval N to get the average square difference. The square root of the average square difference is taken to get the standard deviation. The profit feature LRtz after cleaning is calculated based on the sum of the differences between all adjacent data points in the collection interval divided by the standard deviation.

[0037] Preferably, the risk assessment module compares the cleaned profit characteristic LRtz with the profit standard indicator LRzb. If the cleaned profit characteristic LRtz is higher than the profit standard indicator LRzb, it means that the enterprise is facing financial difficulties.

[0038] Compared with the prior art, the present invention provides a tobacco financial data risk analysis system, which has the following beneficial effects:

[0039] 1. The present invention connects the data source collection module through the authority management module network. The authority management module includes a personal login unit and a non-personal login unit. The authorized person can directly obtain tobacco financial data after the key input and fingerprint recognition are successful, while the third-party authorizer needs to send its success signal to the confirmation window after the third-party key and third-party fingerprint information are successfully recognized. The financial data source can be obtained only after the authorization is confirmed by the person himself, which effectively guarantees the security and privacy of the financial data. Through data authority management, it can be restricted to only authorized users to access the financial data, prevent data leakage or malicious tampering, and thus reduce the risk of data leakage.

[0040] 2. The present invention uses a data processing module to pre-process the real-time cash flow data set and the real-time profit data set, and cleans the cleaned cash flow characteristics XJLtz and profit characteristics LRtz. The data analysis module calculates the data collected by the financial data acquisition unit to generate financial health characteristics CWJKtz. The risk assessment module compares the cleaned cash flow characteristics XJLtz with the cash flow standard indicator XJzb to determine whether the enterprise has the repayment ability, and can promptly discover signs of insufficient repayment ability, provide a reliable basis for financial decision-making, and help enterprises formulate more scientific financial and operational strategies. The cleaned profit characteristic LRtz is compared with the profit standard indicator LRzb to clearly understand its own market position, which helps to promptly discover potential risks and take corresponding countermeasures to ensure the company's continued healthy development.

[0041] 3. The present invention collects the latest data in real time during data collection through the data source collection module, can make decisions quickly, reduce delays, and analyze based on the latest data to improve the accuracy of decisions and avoid decision-making errors caused by outdated data. Automatic collection and processing of data can reduce manual intervention, improve work efficiency and reduce human errors. At the same time, the collection of real-time data can help enterprises immediately identify and evaluate potential risks, so as to take preventive measures and reduce the impact of risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of the system flow of the present invention;

[0043] Figure 2 This is a flowchart of the permission management module;

[0044] Figure 3 This is a flow chart of the data source collection module. DETAILED DESCRIPTION

[0045] 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.

[0046] See also Figure 1 , a tobacco financial data risk analysis system, including a rights management module, a data source collection module, a data processing module, a data analysis module and a risk assessment module;

[0047] The authority management module includes a personal login unit, a non-personal login unit and a user identification unit. The authority management module is connected to the data source collection module through a network;

[0048] The personal login unit is internally provided with a key input window, a fingerprint identification window and a confirmation window. The key input window is used to input a key for login, and the fingerprint identification window is used to identify the fingerprint information of the authorized person. The key input window and the fingerprint identification window form a personal login data group BRDL and send it to the user identification unit.

[0049] The non-personal login unit is internally provided with a third-party key input window and a third-party fingerprint identification window. The third-party key input window is used for the third party to input the key for login. The third-party fingerprint identification window is used to collect the fingerprint information of the third-party authorizer and send it to the confirmation window for confirmation. The third-party key input window and the third-party fingerprint identification window form a non-personal login data group FBRDL and send it to the user identification unit.

[0050] The user identification unit performs login confirmation based on the user login data group BRDL and the non-user login data group FBRDL;

[0051] The expression of my login data group BRDL is:

[0052]

[0053] In the formula, BRMY1 represents the user's key, BRZW1 represents the user's fingerprint information, BRMY1=0 represents the user's key input is successful, BRZW1=0 represents the user's fingerprint information is successfully identified, and the user identification unit sends the user identification success signal to the data source collection module to authorize login;

[0054] The expression of the non-personal login data group FBRDL is:

[0055]

[0056] In the formula, DMY3 represents the third-party key, DZW3 represents the third-party fingerprint information, DMY3=1 represents the successful input of the third-party key, DZW3=1 represents the successful identification of the third-party fingerprint information, and the user identification unit sends the third-party identification success signal to the confirmation window, which is then confirmed by the user and sent to the data source collection module for authorized login.

[0057] The authorized person can directly obtain tobacco financial data after successfully entering the key and fingerprint identification, while the third-party authorizer needs to send its success signal to the confirmation window after the third-party key and third-party fingerprint information are successfully identified. Only after the authorization is confirmed by the person himself can the financial data source be obtained, which effectively protects the security and privacy of financial data. Through data permission management, it can limit access to financial data to only authorized users, prevent data leakage or malicious tampering, and thus reduce the risk of data leakage.

[0058] The data source collection module includes a cash flow data collection unit, a financial data collection unit and a profit data collection unit. The cash flow data collection unit is used to collect multiple real-time cash flow data XJLsj, and the collected multiple cash flow data XJLsj form a real-time cash flow data set. The financial data collection unit collects operating cost data, current total asset data, retained earnings data, profit before interest and tax, equity market value, current total liabilities and current total sales revenue according to market data and financial statements, and sends the collected data to the data analysis module. The profit data collection unit is used to collect multiple real-time profit data LRsj, and the collected multiple real-time profit data LRsj form a real-time profit data set. The data source collection module sends the real-time cash flow data set and the real-time profit data set to the data processing module;

[0059] The data processing module preprocesses the real-time cash flow data set and the real-time profit data set to obtain the cleaned cash flow characteristics XJLtz and profit characteristics LRtz. The data analysis module sends these data to the risk assessment module through the network;

[0060] The data analysis module calculates the financial health characteristics CWJKtz based on the collected operating cost data, current total asset data, retained earnings data, earnings before interest and taxes, equity market value, current total liabilities and current total sales revenue. The data analysis module sends the data to the risk assessment module through the network;

[0061] The real-time cash flow data set expression is to Real-time current assets, inventories and current liabilities obtained from corresponding financial statements, XJLsj z Represents the real-time current asset value, XJLsj c Represents the real-time inventory value, XJLsj f Represents the real-time current liabilities value, XJLsj1 represents the first data collected in the data set, XJLsjN represents the last data collected in the data set, and N represents that there are N data in the data set;

[0062] The profit data set expression is {LRsj1, LRsj2, …, LRsj N}, LRsj1 represents the first collected data in the data set, LRsj N Represents the last data in the data set, and the subscripts 1 to N represent that there are N data collected in the data set;

[0063] The financial data collection unit numbers the collected operating cost data, current total asset data, retained earnings data, profit before interest and tax, equity market value, current total liabilities and current total sales revenue according to the financial characteristics, and numbers the collected operating cost data, current total asset data, retained earnings data, profit before interest and tax, equity market value, current total liabilities and current total sales revenue as YY1, DZ2, LC3, XS4, GQ5, FZ6 and XSz7 respectively;

[0064] The cleaned cash flow characteristic XJLtz algorithm formula is as follows:

[0065]

[0066] In the formula, (XJLsj1 z +XJLsj2 z +…+XJLsjN z ) represents the sum of all real-time current assets within the collection interval, (XJLsj1 c +XJLsj2 c +…+XJLsjN c ) represents the sum of all real-time inventories within the collection interval, XJLsj 1f +XJLsj2 f +…+XJLsjN f Represents the sum of all real-time current liabilities within the collection interval, (XJLsj1 z +XJLsj2 z +…+XJLsjN z )-(XJLsj1 c +XJLsj2 c +…+XJLsjN c ) represents the total value of quick assets. The cleaned cash flow characteristic XJLtz is calculated by dividing the total value of quick assets by the sum of all real-time current liabilities in the collection interval;

[0067] The algorithm formula of the financial health feature CWJKtz is as follows:

[0068]

[0069] In the formula, Represents the liquidity and short-term debt repayment ability of tobacco companies. Represents the accumulated profitability of tobacco companies, Represents the profitability of tobacco company assets, Represents the debt capacity of shareholders. Represents the asset operation efficiency of tobacco companies, 0.2 means The weight of the ratio, 0.3 means for The weight of the ratio, 0.1 means for The weight of the ratio, 0.2 means for The weight of the ratio, 0.1 means for The weights of the ratios, 0.2, 0.3, 0.1, 0.2, and 0.1, are all fixed constants in the formula for calculating the financial health characteristics;

[0070] The profit characteristic LRtz algorithm formula after cleaning is as follows:

[0071]

[0072] In the formula, i=2 in the table means that the calculation starts from the second profit data in the real-time profit data set, that is, LRsj2, and N means that the calculation ends at the last data in the value data set, that is, LRsj N End, (LRsj i -LRsj i-1 ) represents LRsj i The difference between the previous data, Represents the sum of the differences between all adjacent data points in the collection interval, In Represents the mean of all data points in the collection interval, Represents the difference between all data points and the mean value in the collection interval. Represents the square of the difference between all data points and the mean value in the collection interval, Represents the sum of the square differences of all data points in the collection interval. The sum of the square differences is divided by the total number of data points in the collection interval N to get the average square difference. The square root of the average square difference is taken to get the standard deviation. The profit feature LRtz after cleaning is calculated based on the sum of the differences between all adjacent data points in the collection interval divided by the standard deviation.

[0073] The risk assessment module is preset with cash flow standard indicator XJzb, profit standard indicator LRzb, senior financial health standard value CJbz, intermediate financial health standard value ZJbz and low financial health standard value DJbz. The risk assessment module compares the cash flow characteristics XJLtz after cleaning with the cash flow standard indicator XJzb to determine whether the company has the ability to repay. The risk assessment module compares the profit characteristics LRtz after cleaning with the profit standard indicator LRzb to determine whether the company is facing risks. The risk assessment module compares the financial health characteristics CWJKtz with the senior financial health standard value CJbz, the intermediate financial health standard value ZJbz and the low financial health standard value DJbz, and determines the current financial status;

[0074] If the cash flow characteristic XJLtz after cleaning is higher than or equal to the cash flow standard indicator XJzb, it means that the company has the ability to repay. If the cash flow characteristic XJLtz after cleaning is lower than the cash flow standard indicator XJzb, it means that the company faces repayment risk.

[0075] If the financial health characteristic CWJKtz is lower than the low-level financial health standard value DJbz, it means that the enterprise is facing bankruptcy. If the high-level financial health standard value CJbz ≤ financial health characteristic CWJKtz < low-level financial health standard value DJbz, it means that the enterprise has financial risks. If the financial health characteristic CWJKtz is higher than the high-level financial health standard value CJbz, it means that the current financial situation is healthy.

[0076] If the profit characteristic LRtz after cleaning is higher than the profit standard indicator LRzb, it means that the company is facing financial difficulties.

[0077] The data processing module pre-processes the real-time cash flow data set and the real-time profit data set, and cleans and obtains the cleaned cash flow characteristics XJLtz and profit characteristics LRtz. The data analysis module calculates the data collected by the financial data acquisition unit to generate the financial health characteristics CWJKtz. The risk assessment module compares the cleaned cash flow characteristics XJLtz with the cash flow standard indicator XJzb to determine whether the company has the repayment ability. It can promptly discover signs of insufficient repayment ability, provide a reliable basis for financial decision-making, and help companies formulate more scientific financial and operational strategies. The cleaned profit characteristics LRtz are compared with the profit standard indicator LRzb to clearly understand their own market position, which helps to promptly discover potential risks and take corresponding countermeasures to ensure the company's continued healthy development.

[0078] The data source collection module collects the latest data in real time during data collection, which can make decisions quickly and reduce delays. Analysis based on the latest data can improve the accuracy of decisions and avoid decision-making errors caused by outdated data. Automatic collection and processing of data can reduce manual intervention, improve work efficiency and reduce human errors. At the same time, the collection of real-time data can help enterprises immediately identify and evaluate potential risks, so as to take preventive measures and reduce the impact of risks.

[0079] 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 tobacco financial data risk analysis system, characterized by: It includes permission management module, data source collection module, data processing module, data analysis module and risk assessment module; The authority management module includes a personal login unit, a non-personal login unit and a user identification unit, and the authority management module is connected to the data source collection module through a network; The personal login unit is internally provided with a key input window, a fingerprint identification window and a confirmation window. The key input window is used to input a key for login, and the fingerprint identification window is used to identify the fingerprint information of the authorizer. The key input window and the fingerprint identification window form a personal login data group BRDL and send it to the user identification unit. The non-personal login unit is internally provided with a third-party key input window and a third-party fingerprint identification window. The third-party key input window is used for the third-party to input a key for login. The third-party fingerprint identification window is used to collect fingerprint information of the third-party authorizer and send it to the confirmation window for confirmation. The third-party key input window and the third-party fingerprint identification window form a non-personal login data group FBRDL and send it to the user identification unit. The user identification unit performs login confirmation according to the user login data group BRDL and the non-user login data group FBRDL; The data source collection module includes a cash flow data collection unit, a financial data collection unit and a profit data collection unit. The cash flow data collection unit is used to collect multiple real-time cash flow data XJLsj, and the collected multiple cash flow data XJLsj form a real-time cash flow data set. The financial data collection unit collects operating cost data, current total asset data, retained earnings data, profit before interest and tax, equity market value, current total liabilities and current total sales revenue according to market data and financial statements, and sends the collected data to the data analysis module. The profit data collection unit is used to collect multiple real-time profit data LRsj, and the collected multiple real-time profit data LRsj form a real-time profit data set. The data source collection module sends the real-time cash flow data set and the real-time profit data set to the data processing module; The data processing module pre-processes the real-time cash flow data set and the real-time profit data set to obtain the cleaned cash flow characteristics XJLtz and profit characteristics LRtz, and the data analysis module sends these data to the risk assessment module through the network; The data analysis module calculates the financial health feature CWJKtz based on the collected operating cost data, current total asset data, retained earnings data, profit before interest and tax, equity market value, current total liabilities and current total sales revenue, and the data analysis module sends the data to the risk assessment module through the network; The risk assessment module is preset with a cash flow standard indicator XJzb, a profit standard indicator LRzb, a high-level financial health standard value CJbz, an intermediate financial health standard value ZJbz and a low-level financial health standard value DJbz. The risk assessment module compares the cleaned cash flow characteristic XJLtz with the cash flow standard indicator XJzb to determine whether the company has the repayment ability. The risk assessment module compares the cleaned profit characteristic LRtz with the profit standard indicator LRzb to determine whether the company is facing risks. The risk assessment module compares the financial health characteristic CWJKtz with the high-level financial health standard value CJbz, the intermediate financial health standard value ZJbz and the low-level financial health standard value DJbz to determine the current financial status.

2. A tobacco financial data risk analysis system according to claim 1, characterized in that: The expression of the personal login data group BRDL is: In the formula, BRMY1 represents the personal key, BRZW1 represents the personal fingerprint information, BRMY1=0 represents the personal key input is successful, BRZW1=0 represents the personal fingerprint information is successfully identified, and the user identification unit sends the personal identification success signal to the data source collection module to authorize login.

3. A tobacco financial data risk analysis system according to claim 2, characterized in that: The expression of the non-personal login data group FBRDL is: In the formula, DMY3 represents a third-party key, DZW3 represents third-party fingerprint information, DMY3=1 represents successful input of the third-party key, DZW3=1 represents successful identification of the third-party fingerprint information, and the user identification unit sends a third-party identification success signal to the confirmation window, which is then confirmed by the user and sent to the data source collection module for authorized login.

4. A tobacco financial data risk analysis system according to claim 3, characterized in that: The real-time cash flow data set expression is: to Real-time current assets, inventories and current liabilities obtained from corresponding financial statements, XJLsj z Represents the real-time current asset value, XJLsj c Represents the real-time inventory value, XJLsj f Represents the real-time current liabilities value, XJLsj1 represents the first data collected in the data set, XJLsjN represents the last data collected in the data set, and N represents that there are N data in the data set; The algorithm formula of the cleaned cash flow characteristic XJLtz is as follows: In the formula, (XJLsj1 z +XJLsj2 z +…+XJLsjN z ) represents the sum of all real-time current assets within the collection interval, (XJLsj1 c +XJLsj2 c +…+XJLsjN c ) represents the sum of all real-time inventories within the collection interval, XJLsj 1f +XJLsj2 f +…+XJLsjN f Represents the sum of all real-time current liabilities within the collection interval, (XJLsj1 z +XJLsj2 z +…+XJLsjN z )-(XJLsj1 c +XJLsj2 c +…+XJLsjN c ) represents the total value of quick assets. The cleaned cash flow characteristics XJLtz are calculated by dividing the total value of quick assets by the sum of all real-time current liabilities in the collection interval.

5. A tobacco financial data risk analysis system according to claim 4, characterized in that: The risk assessment module compares the cleaned cash flow characteristic XJLtz with the cash flow standard indicator XJzb. If the cleaned cash flow characteristic XJLtz is higher than or equal to the cash flow standard indicator XJzb, it means that the company has the ability to repay. If the cleaned cash flow characteristic XJLtz is lower than the cash flow standard indicator XJzb, it means that the company faces repayment risk.

6. A tobacco financial data risk analysis system according to claim 5, characterized in that: The financial data collection unit numbers the collected operating cost data, current total asset data, retained earnings data, earnings before interest and taxes, equity market value, current total liabilities and current total sales revenue according to financial characteristics. The collected operating cost data, current total asset data, retained earnings data, earnings before interest and taxes, equity market value, current total liabilities and current total sales revenue are numbered YY1, DZ2, LC3, XS4, GQ5, FZ6 and XSz7, respectively.

7. A tobacco financial data risk analysis system according to claim 6, characterized in that: The algorithm formula of the financial health feature CWJKtz is as follows: In the formula, Represents the liquidity and short-term debt repayment ability of tobacco companies. Represents the accumulated profitability of tobacco companies, Represents the profitability of tobacco company assets, Represents the debt capacity of shareholders. Represents the asset operation efficiency of tobacco companies, 0.2 means The weight of the ratio, 0.3 means for The weight of the ratio, 0.1 means for The weight of the ratio, 0.2 means for The weight of the ratio, 0.1 means for The weights of the ratios, 0.2, 0.3, 0.1, 0.2 and 0.1 are all fixed constants in the calculation formula of the financial health characteristics.

8. A tobacco financial data risk analysis system according to claim 7, characterized in that: The risk assessment module compares the financial health feature CWJKtz with the low-level financial health standard value DJbz. If the financial health feature CWJKtz is lower than the low-level financial health standard value DJbz, it means that the enterprise is facing bankruptcy. If the high-level financial health standard value CJbz≤financial health feature CWJKtz<low-level financial health standard value DJbz, it means that the enterprise is in financial risk. If the financial health feature CWJKtz is higher than the high-level financial health standard value CJbz, it means that the current financial situation is healthy.

9. A tobacco financial data risk analysis system according to claim 8, characterized in that: The profit data set expression is {LRsj1, LRsj2, ..., LRsj N }, LRsj1 represents the first collected data in the data set, LRsj N Represents the last data in the data set, and the subscripts 1 to N represent that there are N data collected in the data set; The profit characteristic LRtz algorithm formula after cleaning is as follows: In the formula, i=2 in the table means that the calculation starts from the second profit data in the real-time profit data set, that is, LRsj2, and N means that the calculation ends at the last data in the value data set, that is, LRsj N End, (LRsj i -LRsj i-1 ) represents LRsj i The difference between the previous data, Represents the sum of the differences between all adjacent data points in the collection interval, In Represents the mean of all data points in the collection interval, Represents the difference between all data points and the mean value in the collection interval. Represents the square of the difference between all data points and the mean value in the collection interval, Represents the sum of the square differences of all data points in the collection interval. The sum of the square differences is divided by the total number of data points in the collection interval N to get the average square difference. The square root of the average square difference is taken to get the standard deviation. The profit feature LRtz after cleaning is calculated based on the sum of the differences between all adjacent data points in the collection interval divided by the standard deviation.

10. A tobacco financial data risk analysis system according to claim 9, characterized in that: The risk assessment module compares the cleaned profit characteristic LRtz with the profit standard indicator LRzb. If the cleaned profit characteristic LRtz is higher than the profit standard indicator LRzb, it means that the enterprise is facing financial difficulties.

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