CN113449964A - Enterprise financial risk monitoring and early warning system and monitoring and early warning method - Google Patents
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Abstract
The invention relates to an enterprise financial risk monitoring and early warning system and a monitoring and early warning method, wherein the enterprise financial risk monitoring and early warning system comprises: the data acquisition module comprises a big data acquisition module, a credit investigation data acquisition module and a database; the index selection module is used for selecting indexes reflecting enterprise risks; the index selection module comprises a credit condition unit and a financial index change unit; the credit condition unit comprises a plurality of credit investigation indexes; the risk evaluation module comprises a risk judgment unit, an index score calculation unit and a risk evaluation unit; and the risk condition display module comprises a risk early warning display unit. Through the setting, the problem that financial risks of current key financing enterprises cannot be accurately monitored and monitoring efficiency is low, so that early risk warning cannot be performed in advance can be solved.
Description
Technical Field
The invention relates to the technical field of enterprise financial risk monitoring and early warning, in particular to an enterprise financial risk monitoring and early warning system and a monitoring and early warning method.
Background
Large enterprises as important attention targets of financial risks may cause that the financial risks of the enterprises are continuously increased and gathered due to deterioration of operation conditions, reduction of repayment capacity and financial performance of the enterprises, and even regional systematic financial risks are directly influenced in intense market competition.
Among them, the influence of the major financing enterprises such as the listed companies, the major financing enterprises and the large liability enterprises is particularly significant.
The traditional enterprise monitoring method depends on manpower to carry out troubleshooting, is backward in means, and cannot accurately position and early warn.
Therefore, how to improve the enterprise monitoring method and monitoring efficiency in the prior art to effectively monitor high-risk enterprises or key financing enterprises, grasp the dynamic risk change condition of the enterprises, early warn the emergent financial events in advance, and form an effective monitoring mechanism of early warning, in-process monitoring and after-process tracking so as to create a good financial industry environment is a problem to be solved urgently at present.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide an enterprise financial risk monitoring and early warning system and an enterprise financial risk monitoring and early warning method, wherein the enterprise financial risk monitoring and early warning system is used for solving the problems that financial risks of a large enterprise or a major financing enterprise cannot be accurately monitored at present and risk early warning cannot be performed in advance due to low monitoring efficiency.
In order to achieve one of the above objects, an embodiment of the present invention provides an enterprise financial risk monitoring and early warning system, including:
the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module comprises a big data acquisition module, a credit investigation data acquisition module and a database, and the big data acquisition module is used for acquiring data of an enterprise through big data technology, cleaning the data and inputting the cleaned data into the database; the credit investigation data acquisition module is used for inputting credit investigation data of an enterprise into the database through a credit investigation data interface;
the index selection module is used for selecting indexes reflecting enterprise risks; the index selection module comprises a credit condition unit and a financial index change unit; the credit condition unit comprises a plurality of credit investigation indexes;
the risk evaluation module comprises a risk judgment unit, an index score calculation unit and a risk evaluation unit; the risk judgment unit is used for judging whether the index is included in a risk early warning range according to the index change condition; the index calculation unit is used for calculating index scores of various indexes and comprehensive indexes which are included in the risk early warning range according to the configured index calculation rule; the risk evaluation unit is used for evaluating the risk degree of each unit in the index selection module and the comprehensive risk of the index selection module according to the index score;
and the risk condition display module comprises a risk early warning display unit and is used for displaying the risk early warning result of the enterprise.
As a further improvement of an embodiment of the present invention, the financial index changing unit includes a repayment ability unit, a profit ability unit, an operation ability unit, and a growth ability unit; the index selection module further comprises a capital background unit, an operation condition unit, a guarantee pledge risk unit and a co-purchase risk unit.
As a further improvement of an embodiment of the present invention, the repayment capability unit includes three indexes of a flowing rate, an asset liability rate and a debt scale, and the corresponding calculation formula is:
end-of-run (end-of-run) assets/(end-of-run liability;
rate of assets liability (end of term) total of liability/(end of term) total of assets;
the profitability unit comprises a sales profit rate index, and the calculation formula is as follows:
sales profit rate (end of term) total profit/(end of term) revenue;
the operational capability unit includes an inventory turnover rate indicator calculated by the formula:
stock turnover rate (end of term) business cost/[ 0.5 (initial balance of stock period + end of stock period balance) ];
the co-purchase risk unit comprises a reputation index, and the calculation formula is as follows:
reputation to net asset weight-reputation/owner rights.
As a further improvement of an embodiment of the present invention, the credit status unit includes a credit assessment score index, and the credit assessment score index is credit assessment score information of a local credit assessment platform in suzhou.
As a further improvement of an embodiment of the present invention, the credit status unit further includes a negative internet public opinion indicator.
As a further improvement of an embodiment of the present invention, the risk assessment module further includes an early warning level assessment unit, configured to assess a corresponding early warning level of an important index according to a variation degree of the important index.
As a further improvement of an embodiment of the present invention, the index calculation unit includes a timing unit, and a timing interval of the timing unit is one quarter.
As a further improvement of an embodiment of the present invention, the risk early warning display unit includes a text expression unit and a graph unit, which are used to display the risk early warning result of the enterprise in combination with each other.
As a further improvement of an embodiment of the present invention, the risk condition display module further includes an enterprise summary display unit, configured to sort all enterprises according to risk level distribution.
An embodiment of the present invention further provides an enterprise financial risk monitoring and early warning method, based on the enterprise financial risk monitoring and early warning system described in any one of the above, the method includes:
the method comprises the steps of collecting enterprise data through a big data technology, cleaning the data and inputting the cleaned data into a database, and inputting credit investigation data of the enterprise into the database through a credit investigation data interface;
selecting indexes reflecting enterprise risks through a credit condition unit and a financial index change unit, wherein the credit condition unit comprises a plurality of credit investigation indexes;
judging whether the indexes are included in a risk early warning range according to the index change condition, calculating index scores of all the indexes included in the risk early warning range and comprehensive indexes, and evaluating the risk degree of each unit in an index selection module and the comprehensive risk of the index selection module according to the index scores;
and displaying the risk early warning result of the enterprise.
Compared with the prior art, the invention has the beneficial effects that:
in the enterprise financial risk monitoring and early warning system, a data acquisition module, an index selection module, a risk evaluation module and a risk condition display module are arranged to respectively acquire basic data, select risk indexes, evaluate risks and display risks, so that the early warning effect of risks is realized;
the data acquisition module comprises a big data acquisition module and a credit investigation data acquisition module, public data are acquired through a big data technology, data summarization is realized by combining credit investigation data, the accuracy and reliability of the data are guaranteed, index risks can be judged and evaluated through indexes such as financial data and credit investigation data, and therefore the accuracy and reliability of risk evaluation are improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments or the description of the prior art will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a block diagram of an enterprise financial risk monitoring and warning system according to an embodiment of the present invention;
FIG. 2 is a block diagram of a data acquisition module according to an embodiment of the present invention;
FIG. 3 is a table diagram of an index selection module according to an embodiment of the invention;
fig. 4 is a flowchart illustrating an enterprise financial risk monitoring and early warning method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following detailed description of the invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in fig. 1 to fig. 3, an embodiment of the present invention provides an enterprise financial risk monitoring and early warning system, including:
the data acquisition module comprises a big data acquisition module, a credit investigation data acquisition module and a database, wherein the big data acquisition module is used for acquiring data of an enterprise through big data technology, cleaning the data and inputting the cleaned data into the database; the credit investigation data acquisition module is used for inputting credit investigation data of an enterprise into a database through a credit investigation data interface;
the index selection module is used for selecting indexes reflecting enterprise risks; the index selection module comprises a credit condition unit and a financial index change unit; the credit condition unit comprises a plurality of credit investigation indexes;
the risk evaluation module comprises a risk judgment unit, an index score calculation unit and a risk evaluation unit; the risk judgment unit is used for judging whether the index is included in the risk early warning range according to the index change condition; the index calculation unit is used for calculating various indexes and index scores of comprehensive indexes which are included in the risk early warning range according to the configured index calculation rule; the risk evaluation unit is used for evaluating the risk degree of each unit in the index selection module and the comprehensive risk of the index selection module according to the index score;
and the risk condition display module comprises a risk early warning display unit and is used for displaying the risk early warning result of the enterprise.
Specifically, in the enterprise financial risk monitoring and early warning system, a data acquisition module, an index selection module, a risk assessment module and a risk condition display module are arranged to respectively acquire basic data, select risk indexes, assess risks and display risks, so that the early warning function of risks is realized;
the data acquisition module comprises a big data acquisition module and a credit investigation data acquisition module, public data are acquired through a big data technology, data summarization is realized by combining credit investigation data, the accuracy and reliability of the data are guaranteed, index risks can be judged and evaluated through indexes such as financial data and credit investigation data, and therefore the accuracy and reliability of risk evaluation are improved.
In actual operation, the enterprise financial risk monitoring and early warning system is mainly used for risk monitoring and early warning of key financing enterprises, and comprehensively analyzes listed enterprises on the basis of public enterprise basic information, transaction data, major events, financial data and index data and by combining data resources such as enterprise credit investigation scoring information and enterprise loan detail information of credit investigation institutions of all places.
In addition, multi-dimensional evaluation such as financial risk, judicial risk, pledge risk, public opinion risk and the like is established, and the monitoring of listed enterprises is complete in information provision, early in risk discovery and wide in monitoring dimension, so that various organizations are effectively assisted to make decisions.
In the data acquisition module, the big data is acquired, cleaned and put in a warehouse, and meanwhile, the credit investigation scoring interface is accessed, and data is summarized and combined.
The technical framework mainly comprises three layers, namely a data access layer, a service implementation layer and a presentation layer.
Further, the financial index change unit comprises a repayment capacity unit, a profit capacity unit, an operation capacity unit and a growth capacity unit; the index selection module further comprises a capital background unit, an operation condition unit, a guarantee pledge risk unit and a co-purchase risk unit.
Further, the credit status unit further includes a negative internet public opinion index.
As shown in fig. 3, in actual operation, the index selection module selects nine dimensional indexes, and reflects enterprise risks from multiple aspects such as capital background, financial status, business status, and credit status.
Wherein, the capital background unit comprises two indexes of registered capital alteration and enterprise property; the growth capacity unit comprises indexes such as sales income, business profit and the like; the operation condition unit comprises indexes such as electricity consumption, tax payment sum, customs export amount and the like; the guarantee pledge risk unit comprises indexes such as the stockholder pledge rate of a listed company and the like; the credit status unit also comprises indexes that the loan is classified as 'bad' or 'concern', administrative penalty, negative network public opinion, environmental assessment result, complaint condition and the like.
Further, the repayment capability unit comprises three indexes of a flowing rate, an asset liability rate and a debt scale, and the corresponding calculation formula is as follows:
end-of-run (end-of-run) assets/(end-of-run liability;
rate of assets liability (end of term) total of liability/(end of term) total of assets;
the profitability unit comprises a sales profit rate index, and the calculation formula is as follows:
sales profit rate (end of term) total profit/(end of term) revenue;
the operational capability unit includes an inventory turnover rate indicator calculated by the formula:
stock turnover rate (end of term) business cost/[ 0.5 (initial balance of stock period + end of stock period balance) ];
the co-purchase risk unit comprises a reputation index, and the calculation formula is as follows:
reputation to net asset weight-reputation/owner rights.
In actual operation, indexes such as flow rate, asset liability rate, sales profit rate, inventory turnover rate and reputation are important indexes in the index selection module and can be calculated through a set specific calculation formula.
Further, the credit condition unit comprises credit assessment scoring indexes, and the credit assessment scoring indexes are credit assessment scoring information of a local credit assessment platform in Suzhou.
It should be noted that, in the embodiment of the present invention, the credit investigation score is based on the credit investigation score of the suzhou local credit investigation platform, and when other scenes are used, the parameters may be adjusted according to actual situations.
Further, the risk assessment module further comprises an early warning level assessment unit for assessing the corresponding early warning level of the important index according to the variation degree of the important index.
In actual operation, whether the risk early warning range is included can be judged by comparing the change degree of the monitoring index and the previous period with the calculation result of the index.
Wherein, part of important indexes are graded to make parameters according to the variation degree and whether the early warning value is reached, for example, when the reduction range exceeds 10%, the early warning degree is two levels; when the descending amplitude exceeds 30%, the early warning degree is one level. For different indexes, the judgment standards of the early warning degree of the first-level and the second-level are slightly different.
Further, the index calculation unit includes a timing unit, and a timing time interval of the timing unit is one quarter.
Then, various indexes and summarized comprehensive index scores can be calculated according to the configured index calculation rules.
The index calculation rule adopts a Delphi method and an AHP analytic hierarchy process, and is updated once every quarter.
And then, correspondingly evaluating the risk degree and the comprehensive risk of the nine modules according to the index scores.
Furthermore, the risk early warning display unit comprises a character expression unit and a chart unit, and is used for displaying the risk early warning result of the enterprise by combining with each other.
Furthermore, the risk condition display module further comprises an enterprise summary display unit, which is used for sequencing all enterprises according to the risk level distribution.
Finally, in a risk condition display module, a risk early warning result is displayed by combining the character expression and the chart.
Wherein, the enterprises can be ranked according to the risk level distribution: and displaying the enterprises according to the grades (general, concern and important) of the enterprises in the monitoring list in descending order of the risk grade.
As shown in fig. 4, a specific embodiment of the present invention further provides an enterprise financial risk monitoring and early warning method, based on the above enterprise financial risk monitoring and early warning system, the method includes:
the method comprises the steps of collecting enterprise data through a big data technology, cleaning the data and inputting the cleaned data into a database, and inputting credit investigation data of the enterprise into the database through a credit investigation data interface;
selecting indexes reflecting enterprise risks through a credit condition unit and a financial index change unit, wherein the credit condition unit comprises a plurality of credit investigation indexes;
judging whether the indexes are included in a risk early warning range according to the index change condition, calculating the index scores of all the indexes included in the risk early warning range and the comprehensive indexes, and evaluating the risk degree of each unit in the index selection module and the comprehensive risk of the index selection module according to the index scores;
and displaying the risk early warning result of the enterprise.
In summary, the enterprise financial risk monitoring and early warning system and the monitoring and early warning method provided by the invention are used for risk monitoring and early warning of important financing enterprises such as listed companies, important financing enterprises and large liability enterprises, monitoring high-risk enterprises by means of a big data technology, collecting data from aspects such as financial credit, production and management, network public opinion and economic status, mastering the dynamic change situation of the risk of the enterprises, and early warning of large credit risk or sudden financial events, thereby forming an effective monitoring mechanism of early warning, in-process monitoring and post tracking, and facilitating the construction of a good financial industry environment.
It should be understood that although the present description refers to embodiments, not every embodiment contains only a single technical solution, and such description is for clarity only, and those skilled in the art should make the description as a whole, and the technical solutions in the embodiments can also be combined appropriately to form other embodiments understood by those skilled in the art.
The above-listed detailed description is only a specific description of a possible embodiment of the present invention and is not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention are included in the scope of the present invention.
Claims (10)
1. An enterprise financial risk monitoring and early warning system, comprising:
the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module comprises a big data acquisition module, a credit investigation data acquisition module and a database, and the big data acquisition module is used for acquiring data of an enterprise through big data technology, cleaning the data and inputting the cleaned data into the database; the credit investigation data acquisition module is used for inputting credit investigation data of an enterprise into the database through a credit investigation data interface;
the index selection module is used for selecting indexes reflecting enterprise risks; the index selection module comprises a credit condition unit and a financial index change unit; the credit condition unit comprises a plurality of credit investigation indexes;
the risk evaluation module comprises a risk judgment unit, an index score calculation unit and a risk evaluation unit; the risk judgment unit is used for judging whether the index is included in a risk early warning range according to the index change condition; the index calculation unit is used for calculating index scores of various indexes and comprehensive indexes which are included in the risk early warning range according to the configured index calculation rule; the risk evaluation unit is used for evaluating the risk degree of each unit in the index selection module and the comprehensive risk of the index selection module according to the index score;
and the risk condition display module comprises a risk early warning display unit and is used for displaying the risk early warning result of the enterprise.
2. The enterprise financial risk monitoring and early warning system of claim 1, wherein the financial index change unit comprises a repayment capacity unit, a profit capacity unit, an operation capacity unit and a growth capacity unit; the index selection module further comprises a capital background unit, an operation condition unit, a guarantee pledge risk unit and a co-purchase risk unit.
3. The enterprise financial risk monitoring and early warning system of claim 2,
the debt paying capacity unit comprises three indexes of a flow rate, an asset liability rate and a debt scale, and the corresponding calculation formula is as follows:
end-of-run (end-of-run) assets/(end-of-run liability;
rate of assets liability (end of term) total of liability/(end of term) total of assets;
the profitability unit comprises a sales profit rate index, and the calculation formula is as follows:
sales profit rate (end of term) total profit/(end of term) revenue;
the operational capability unit includes an inventory turnover rate indicator calculated by the formula:
stock turnover rate (end of term) business cost/[ 0.5 (initial balance of stock period + end of stock period balance) ];
the co-purchase risk unit comprises a reputation index, and the calculation formula is as follows:
reputation to net asset weight-reputation/owner rights.
4. The enterprise financial risk monitoring and early warning system of claim 1, wherein the credit status unit comprises credit assessment scoring indexes, and the credit assessment scoring indexes are credit assessment scoring information of a local credit assessment platform in Suzhou.
5. The enterprise financial risk monitoring and warning system of claim 4, wherein the credit status unit further comprises a negative cyber public opinion indicator.
6. The enterprise financial risk monitoring and early warning system of claim 1, wherein the risk assessment module further comprises an early warning level assessment unit for assessing the corresponding early warning level of the important index according to the variation degree of the important index.
7. The enterprise financial risk monitoring and early warning system of claim 1, wherein the index calculation unit comprises a timing unit, and the timing unit is timed to have a time interval of one quarter.
8. The enterprise financial risk monitoring and early warning system of claim 1, wherein the risk early warning display unit comprises a text expression unit and a graph unit, and is used for displaying the risk early warning result of the enterprise by combining with each other.
9. The enterprise financial risk monitoring and early warning system of claim 1, wherein the risk status display module further comprises an enterprise summary display unit for ranking all enterprises according to risk level distribution.
10. An enterprise financial risk monitoring and early warning method based on the enterprise financial risk monitoring and early warning system of any one of claims 1-9, the method comprising:
the method comprises the steps of collecting enterprise data through a big data technology, cleaning the data and inputting the cleaned data into a database, and inputting credit investigation data of the enterprise into the database through a credit investigation data interface;
selecting indexes reflecting enterprise risks through a credit condition unit and a financial index change unit, wherein the credit condition unit comprises a plurality of credit investigation indexes;
judging whether the indexes are included in a risk early warning range according to the index change condition, calculating index scores of all the indexes included in the risk early warning range and comprehensive indexes, and evaluating the risk degree of each unit in an index selection module and the comprehensive risk of the index selection module according to the index scores;
and displaying the risk early warning result of the enterprise.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114022273A (en) * | 2021-11-26 | 2022-02-08 | 江苏华博实业集团有限公司 | Financial risk management system and method for financing supply chain |
| CN114119251A (en) * | 2022-01-26 | 2022-03-01 | 未来地图(深圳)智能科技有限公司 | System and method for predicting financial risk trend based on intelligent AI |
| CN114997588A (en) * | 2022-05-05 | 2022-09-02 | 深圳市星火电子工程公司 | Financial enterprise risk identification early warning method and system |
| CN116720731A (en) * | 2023-05-25 | 2023-09-08 | 北京龙软科技股份有限公司 | Coal mine financial all-factor risk prevention and control early warning method and early warning system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108932577A (en) * | 2018-04-25 | 2018-12-04 | 广州广电研究院有限公司 | A kind of assessment of business risk and early warning system |
| CN109658235A (en) * | 2019-01-08 | 2019-04-19 | 河南长澜信息科技有限公司 | A kind of financial risks assessment system based on big data |
| CN112465648A (en) * | 2020-10-21 | 2021-03-09 | 湖南天设信息科技有限公司 | Risk data evaluation method and device, computer equipment and storage medium |
-
2021
- 2021-05-28 CN CN202110590665.2A patent/CN113449964A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108932577A (en) * | 2018-04-25 | 2018-12-04 | 广州广电研究院有限公司 | A kind of assessment of business risk and early warning system |
| CN109658235A (en) * | 2019-01-08 | 2019-04-19 | 河南长澜信息科技有限公司 | A kind of financial risks assessment system based on big data |
| CN112465648A (en) * | 2020-10-21 | 2021-03-09 | 湖南天设信息科技有限公司 | Risk data evaluation method and device, computer equipment and storage medium |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114022273A (en) * | 2021-11-26 | 2022-02-08 | 江苏华博实业集团有限公司 | Financial risk management system and method for financing supply chain |
| CN114119251A (en) * | 2022-01-26 | 2022-03-01 | 未来地图(深圳)智能科技有限公司 | System and method for predicting financial risk trend based on intelligent AI |
| CN114997588A (en) * | 2022-05-05 | 2022-09-02 | 深圳市星火电子工程公司 | Financial enterprise risk identification early warning method and system |
| CN116720731A (en) * | 2023-05-25 | 2023-09-08 | 北京龙软科技股份有限公司 | Coal mine financial all-factor risk prevention and control early warning method and early warning system |
| CN116720731B (en) * | 2023-05-25 | 2023-12-01 | 北京龙软科技股份有限公司 | Coal mine financial all-factor risk prevention and control early warning method and early warning system |
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