Scientific and technological enterprise credit risk early warning method, device, equipment and medium

Abstract

The invention particularly relates to a scientific and technological enterprise credit risk early warning method and device, equipment and a medium. According to the scientific and technological enterprise credit risk early warning method and device, the equipment and the medium, credit risk assessment information of different scientific and technological enterprises is collected in a self-defined mode, and risk index factors of scientific and technological enterprise credit risk early warning are determined through a service expert assessment system; carrying out multi-factor analysis, confirming key indexes of scientific and technological enterprise credit risk early warning, constructing a scientific and technological enterprise credit risk early warning risk model, building a scientific and technological enterprise credit risk early warning system, carrying out real-time risk scanning on the added scientific and technological enterprises, and when the enterprise risk indexes exceed a threshold range, carrying out early warning. And early warning display is carried out in an information highlighting or pop-up prompt mode. According to the scientific and technological enterprise credit risk early warning method, apparatus and device, and the medium, a real-time alarm function is realized, timeliness and accuracy of early warning are fully guaranteed in a credit risk monitoring process of scientific and technological enterprises, and differentiated demands of different financial institutions can be satisfied.

Description

Technical Field

[0001] The present invention relates to the technical field of financial risk management, and in particular to a method, device, equipment and medium for early warning of credit risk of a technology enterprise. Background Art

[0002] With the development of inclusive finance and Internet of Things technology, credit to technology companies, as an important part of inclusive finance, has been increasingly valued by financial institutions. Credit risk supervision is the core link for financial institutions to ensure the safety of funds, and its importance is self-evident. However, credit to technology companies has long faced challenges such as lack of effective collateral and information asymmetry, which has led to traditional risk supervision methods generally encountering problems such as rising operational risks and high labor costs, making it difficult to meet the actual needs of financial institutions.

[0003] On the one hand, the traditional credit risk assessment still remains at the stage of manual information entry or paper documents in terms of indicator selection, and the value of data is difficult to fully explore and utilize. At the same time, the traditional credit risk assessment model mostly relies on the "scoring card" method based on the rule engine, which has serious homogeneity and lacks sufficient objectivity in the assessment of customer credit, especially in the field of technology enterprise credit, which makes it difficult to meet the differentiated service needs of different financial institutions.

[0004] On the other hand, current financial institutions often face the problems of scarce data samples and uneven data quality in the credit business of technology companies. Insufficient data support makes it difficult to ensure the timeliness and accuracy of early warnings in risk monitoring during the loan process.

[0005] In order to solve the technical problems that the current credit monitoring process of science and technology enterprises relies on manual review, is difficult to monitor and is costly, the present invention proposes a credit risk warning method, device, equipment and medium for science and technology enterprises. Summary of the invention

[0006] In order to make up for the defects of the prior art, the present invention provides a simple and efficient technology enterprise credit risk early warning method, device, equipment and medium.

[0007] The present invention is achieved through the following technical solutions:

[0008] A technology enterprise credit risk early warning method, characterized in that it includes the following steps:

[0009] Step S1: collect credit risk assessment information of different technology companies through automatic system collection, business data interface docking and manual entry, and use the collected information as an assessment sample for credit warning of technology companies;

[0010] Step S2: obtaining key operating indicators and market indicators that affect the revenue of technology enterprises through the business expert evaluation system, and determining risk indicator factors for credit risk warning of technology enterprises;

[0011] Step S3: Conduct multi-factor analysis on the risk indicator factors evaluated and confirmed by the business experts to confirm the key indicators for credit risk warning of technology enterprises;

[0012] Step S4: Determine the risk rules for credit warning of technology enterprises based on the confirmed key indicators for credit risk warning of technology enterprises, and construct a credit warning risk model for technology enterprises;

[0013] Step S5: Build a credit risk warning system for technology enterprises based on the credit warning risk model for technology enterprises, conduct real-time risk scanning on added technology enterprises, and when the enterprise risk index exceeds the threshold range, display a warning by highlighting the information or popping up a prompt.

[0014] In step S3, a regression model of the relationship between risk indicator factors and technology enterprise income is constructed, and the relationship strength coefficient between each risk indicator factor and technology enterprise income is confirmed by standardized regression coefficient method, and the key indicators of technology enterprise credit risk are determined by comparing the relationship strength coefficients; the implementation steps are as follows:

[0015] Step S301: For the target technology enterprise, a regression model of the relationship between the business operation risk index factor and the technology enterprise income is constructed, and the construction formula is as follows:

[0016] Y1=β0+β1X1+…+βnXn+e

[0017] Among them, Y1 is the enterprise revenue index, X1, X2, …, Xn are the business operation risk indicator factors of the credit risk warning of technology enterprises, e is the error term, β0 is the intercept term, and β1, β2, …, βn are all regression coefficients;

[0018] The collected credit risk assessment information of different technology companies is used as input sample data to evaluate the model parameters, and the relationship strength coefficients S1, S2, ..., Sn between the business operation risk indicator factors X1, X2, ..., Xn and the enterprise revenue index Y1 are determined by the standardized regression coefficient method;

[0019] Step S302: for the target technology enterprise, a regression model of the relationship between the market trend risk index factor and the technology enterprise income is constructed, and the construction formula is as follows:

[0020] Y2=β0+β1P1+β2P2+β3P3+e

[0021] Among them, Y2 is the market trend index, P1 is the industry growth rate, P2 is the change in market demand, P3 is the dynamics of competitors, e is the error term, β0 is the intercept term, and β1, β2 and β3 are all regression coefficients:

[0022] The collected credit risk assessment information of different technology companies is used as input sample data to evaluate the model parameters, and the relationship strength coefficients G1, G2 and G3 between the industry market trend risk indicator factors P1, P3 and P3 and the market trend index Y2 are determined by the standardized regression coefficient method;

[0023] Step S303: The larger the relationship strength coefficient is, the more important the corresponding risk indicator factor is; comparative analysis is performed on the calculated relationship strength coefficients to customize key indicators for determining the credit risk of technology enterprises.

[0024] In step S2, the risk indicator factors for the credit risk warning of technology enterprises include the business operation risk indicator factors and market trend risk indicator factors of technology enterprises;

[0025] The business operation risk indicator factors include the proportion of R&D investment, product replacement frequency and market share;

[0026] The market trend risk indicator factors include industry growth rate, market demand changes and competitor dynamics.

[0027] In step S301, the formula for constructing the regression model of the relationship between the business operation risk indicator factor and the income of the technology enterprise is as follows:

[0028] Y1=β0+β1X1+β2X2+β3X3+e

[0029] Among them, X1 is the proportion of R&D investment, X2 is the frequency of product updates and upgrades, and X3 is the market share.

[0030] In step S4, the risk intensity index is calculated to determine the credit risk warning model for technology enterprises. The formula is as follows:

[0031] The calculation formula of the technology enterprise credit risk correlation strength index RISK is as follows:

[0032] RISK=(RY1C1+RY2C2) / (C1+C2)

[0033] Among them, RY1 is the risk intensity index of the enterprise revenue index Y1, RY2 is the risk intensity index of the market trend index Y2, Q is the number of times the risk intensity index RY1 of the key business index Y1 exceeds the custom risk warning threshold, and L is the number of times the risk intensity index RY2 of the market trend index Y2 exceeds the custom risk warning threshold;

[0034] If the technology enterprise credit risk correlation strength indicator RISK exceeds the custom risk warning threshold, an early warning is triggered;

[0035] The calculation formula of the enterprise revenue index Y1 risk intensity index RY1 is as follows:

[0036] RY1=(QX1S1+QX2S2+…+QXnSn) / (Q1+Q2+…+Qn)

[0037] Among them, Q1, Q2, ..., Qn are the times that the relationship strength coefficients S1, S2, ..., Sn exceed the custom risk warning threshold, and Q is the average of Q1, Q2, ... and Qn;

[0038] The calculation formula of market trend indicator Y2 risk intensity indicator RY2 is as follows:

[0039] RY2=(LP1G1+LP2G2+LP3G3) / (L1+L2+L3)

[0040] Among them, L1, L2 and L3 are the times that the relationship strength coefficients G1, G2 and G3 exceed the custom risk warning threshold, and L is the average value of L1, L2 and L3.

[0041] A technology enterprise credit risk early warning device, comprising:

[0042] The data collection unit is responsible for collecting credit risk assessment information of different technology companies through automatic system collection, business data interface docking and manual entry, and using the collected information as an assessment sample for credit warning of technology companies;

[0043] The risk indicator factor determination unit is responsible for evaluating and determining the corresponding risk indicator factors for different business scenarios by industry experts;

[0044] The key indicator analysis unit is responsible for constructing a regression model of the relationship between risk indicator factors and the income of technology companies, confirming the relationship strength coefficient between each risk indicator factor and the income of technology companies through the standardized regression coefficient method, and determining the key indicators of credit risk of technology companies by comparing the relationship strength coefficients;

[0045] The enterprise credit early warning unit is responsible for constructing a credit early warning risk model for technology enterprises, and building a credit risk early warning system for technology enterprises based on the credit early warning risk model for technology enterprises. It conducts real-time risk scanning on added technology enterprises, and when the enterprise risk indicators exceed the threshold range, the early warning will be displayed by highlighting the information or popping up prompts.

[0046] A risk warning device for technology enterprises, the device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can implement the above method.

[0047] A computer program is stored on a readable storage medium, and the computer program implements the above method when executed by a processor.

[0048] The beneficial effects of the present invention are as follows: the technology enterprise credit risk early warning method, device, equipment and medium realize the real-time alarm function, fully guarantee the timeliness and accuracy of the early warning in the process of loan risk monitoring of technology enterprise credit, and can meet the differentiated needs of different financial institutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Attached Figure 1 This is a schematic diagram of the technology enterprise credit risk early warning method of the present invention. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention.

[0052] The embodiments of the present invention are part of the embodiments, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0053] The technology enterprise credit risk early warning method comprises the following steps:

[0054] Step S1: collect credit risk assessment information of different technology companies through automatic system collection, business data interface docking and manual entry, and use the collected information as an assessment sample for credit warning of technology companies;

[0055] Step S2: obtaining key operating indicators and market indicators that affect the revenue of technology enterprises through the business expert evaluation system, and determining risk indicator factors for credit risk warning of technology enterprises;

[0056] Step S3: Conduct multi-factor analysis on the risk indicator factors evaluated and confirmed by the business experts to confirm the key indicators for credit risk warning of technology enterprises;

[0057] Step S4: Determine the risk rules for credit warning of technology enterprises based on the confirmed key indicators for credit risk warning of technology enterprises, and construct a credit warning risk model for technology enterprises;

[0058] Step S5: Build a credit risk warning system for technology enterprises based on the credit warning risk model for technology enterprises, conduct real-time risk scanning on added technology enterprises, and when the enterprise risk index exceeds the threshold range, display a warning by highlighting the information or popping up a prompt.

[0059] In step S3, a regression model of the relationship between risk indicator factors and technology enterprise income is constructed, and the relationship strength coefficient between each risk indicator factor and technology enterprise income is confirmed by standardized regression coefficient method, and the key indicators of technology enterprise credit risk are determined by comparing the relationship strength coefficients; the implementation steps are as follows:

[0060] Step S301: For the target technology enterprise, a regression model of the relationship between the business operation risk index factor and the technology enterprise income is constructed, and the construction formula is as follows:

[0061] Y1=β0+β1X1+…+βnXn+e

[0062] Among them, Y1 is the enterprise revenue index, X1, X2, …, Xn are the business operation risk indicator factors of the credit risk warning of technology enterprises, e is the error term, β0 is the intercept term, and β1, β2, …, βn are all regression coefficients;

[0063] The collected credit risk assessment information of different technology companies is used as input sample data to evaluate the model parameters, and the relationship strength coefficients S1, S2, ..., Sn between the business operation risk indicator factors X1, X2, ..., Xn and the enterprise revenue index Y1 are determined by the standardized regression coefficient method;

[0064] Step S302: for the target technology enterprise, a regression model of the relationship between the market trend risk index factor and the technology enterprise income is constructed, and the construction formula is as follows:

[0065] Y2=β0+β1P1+β2P2+β3P3+e

[0066] Among them, Y2 is the market trend index, P1 is the industry growth rate, P2 is the change in market demand, P3 is the dynamics of competitors, e is the error term, β0 is the intercept term, and β1, β2 and β3 are all regression coefficients:

[0067] The collected credit risk assessment information of different technology companies is used as input sample data to evaluate the model parameters, and the relationship strength coefficients G1, G2 and G3 between the industry market trend risk indicator factors P1, P3 and P3 and the market trend index Y2 are determined by the standardized regression coefficient method;

[0068] Step S303: The larger the relationship strength coefficient is, the more important the corresponding risk indicator factor is; comparative analysis is performed on the calculated relationship strength coefficients to customize key indicators for determining the credit risk of technology enterprises.

[0069] In step S2, the risk indicator factors for the credit risk warning of technology enterprises include the business operation risk indicator factors and market trend risk indicator factors of technology enterprises;

[0070] The business operation risk indicator factors include the proportion of R&D investment, product replacement frequency and market share;

[0071] The market trend risk indicator factors include industry growth rate, market demand changes and competitor dynamics.

[0072] In step S301, the formula for constructing the regression model of the relationship between the business operation risk indicator factor and the income of the technology enterprise is as follows:

[0073] Y1=β0+β1X1+β2X2+β3X3+e

[0074] Among them, X1 is the proportion of R&D investment, X2 is the frequency of product updates and upgrades, and X3 is the market share.

[0075] In step S4, the risk intensity index is calculated to determine the credit risk warning model for technology enterprises. The formula is as follows:

[0076] The calculation formula of the technology enterprise credit risk correlation strength index RISK is as follows:

[0077] RISK=(RY1C1+RY2C2) / (C1+C2)

[0078] Among them, RY1 is the risk intensity index of the enterprise revenue index Y1, RY2 is the risk intensity index of the market trend index Y2, Q is the number of times the risk intensity index RY1 of the key business index Y1 exceeds the custom risk warning threshold, and L is the number of times the risk intensity index RY2 of the market trend index Y2 exceeds the custom risk warning threshold;

[0079] If the technology enterprise credit risk correlation strength indicator RISK exceeds the custom risk warning threshold, an early warning is triggered;

[0080] The calculation formula of the enterprise revenue index Y1 risk intensity index RY1 is as follows:

[0081] RY1=(QX1S1+QX2S2+…+QXnSn) / (Q1+Q2+…+Qn)

[0082] Among them, Q1, Q2, ..., Qn are the times that the relationship strength coefficients S1, S2, ..., Sn exceed the custom risk warning threshold, and Q is the average of Q1, Q2, ... and Qn;

[0083] The calculation formula of market trend indicator Y2 risk intensity indicator RY2 is as follows:

[0084] RY2=(LP1G1+LP2G2+LP3G3) / (L1+L2+L3)

[0085] Among them, L1, L2 and L3 are the times that the relationship strength coefficients G1, G2 and G3 exceed the custom risk warning threshold, and L is the average value of L1, L2 and L3.

[0086] The technology enterprise credit risk early warning device includes:

[0087] The data collection unit is responsible for collecting credit risk assessment information of different technology companies through automatic system collection, business data interface docking and manual entry, and using the collected information as an assessment sample for credit warning of technology companies;

[0088] The risk indicator factor determination unit is responsible for evaluating and determining the corresponding risk indicator factors for different business scenarios by industry experts;

[0089] The key indicator analysis unit is responsible for constructing a regression model of the relationship between risk indicator factors and the income of technology companies, confirming the relationship strength coefficient between each risk indicator factor and the income of technology companies through the standardized regression coefficient method, and determining the key indicators of credit risk of technology companies by comparing the relationship strength coefficients;

[0090] The enterprise credit early warning unit is responsible for constructing a credit early warning risk model for technology enterprises, and building a credit risk early warning system for technology enterprises based on the credit early warning risk model for technology enterprises. It conducts real-time risk scanning on added technology enterprises, and when the enterprise risk indicators exceed the threshold range, the early warning will be displayed by highlighting the information or popping up prompts.

[0091] The technology enterprise risk warning device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can implement the above method.

[0092] The readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0093] The embodiment described above is only one specific implementation of the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A technology enterprise credit risk early warning method, characterized by: The following steps are involved: Step S1: collect credit risk assessment information of different technology companies through automatic system collection, business data interface docking and manual entry, and use the collected information as an assessment sample for credit warning of technology companies; Step S2: obtaining key operating indicators and market indicators that affect the revenue of technology enterprises through the business expert evaluation system, and determining risk indicator factors for credit risk warning of technology enterprises; Step S3: Conduct multi-factor analysis on the risk indicator factors evaluated and confirmed by the business experts to confirm the key indicators for credit risk warning of technology enterprises; Step S4: Determine the risk rules for credit warning of technology enterprises based on the confirmed key indicators for credit risk warning of technology enterprises, and construct a credit warning risk model for technology enterprises; Step S5: Build a credit risk warning system for technology enterprises based on the credit warning risk model for technology enterprises, conduct real-time risk scanning on added technology enterprises, and when the enterprise risk index exceeds the threshold range, display a warning by highlighting the information or popping up a prompt.

2. The technology enterprise credit risk early warning method according to claim 1 is characterized by: In step S2, the risk indicator factors for the credit risk warning of technology enterprises include the business operation risk indicator factors and market trend risk indicator factors of technology enterprises; The business operation risk indicator factors include the proportion of R&D investment, product replacement frequency and market share; The market trend risk indicator factors include industry growth rate, market demand changes and competitor dynamics.

3. The technology enterprise credit risk early warning method according to claim 1 is characterized by: In step S3, a regression model of the relationship between risk indicator factors and technology enterprise income is constructed, and the relationship strength coefficient between each risk indicator factor and technology enterprise income is confirmed by standardized regression coefficient method, and the key indicators of technology enterprise credit risk are determined by comparing the relationship strength coefficients; the implementation steps are as follows: Step S301: For the target technology enterprise, a regression model of the relationship between the business operation risk index factor and the technology enterprise income is constructed, and the construction formula is as follows: Y1=β0+β1X1+…+βnXn+e Among them, Y1 is the enterprise revenue index, X1, X2, ..., Xn are the business operation risk indicator factors of the credit risk warning of technology enterprises, e is the error term, β0 is the intercept term, and β1, β2, ..., βn are all regression coefficients; The collected credit risk assessment information of different technology companies is used as input sample data to evaluate the model parameters, and the relationship strength coefficients S1, S2, ..., Sn between the business operation risk indicator factors X1, X2, ..., Xn and the enterprise revenue index Y1 are determined by the standardized regression coefficient method; Step S302: for the target technology enterprise, a regression model of the relationship between the market trend risk index factor and the technology enterprise income is constructed, and the construction formula is as follows: Y2=β0+β1P1+β2P2+β3P3+e Among them, Y2 is the market trend index, P1 is the industry growth rate, P2 is the change in market demand, P3 is the dynamics of competitors, e is the error term, β0 is the intercept term, and β1, β2 and β3 are all regression coefficients: The collected credit risk assessment information of different technology companies is used as input sample data to evaluate the model parameters, and the relationship strength coefficients G1, G2 and G3 between the industry market trend risk indicator factors P1, P3 and P3 and the market trend index Y2 are determined by the standardized regression coefficient method; Step S303: The larger the relationship strength coefficient is, the more important the corresponding risk indicator factor is; comparative analysis is performed on the calculated relationship strength coefficients to customize key indicators for determining the credit risk of technology enterprises.

4. The technology enterprise credit risk early warning method according to claim 3 is characterized by: In step S301, the formula for constructing the regression model of the relationship between the business operation risk indicator factor and the income of the technology enterprise is as follows: Y1=β0+β1X1+β2X2+β3X3+e Among them, X1 is the proportion of R&D investment, X2 is the frequency of product updates and upgrades, and X3 is the market share.

5. The technology enterprise credit risk early warning method according to claim 3 is characterized by: In step S4, the risk intensity index is calculated to determine the credit risk warning model for technology enterprises. The formula is as follows: The calculation formula of the technology enterprise credit risk correlation strength index RISK is as follows: RISK=(RY1C1+RY2C2) / (C1+C2) Among them, RY1 is the risk intensity index of the enterprise revenue index Y1, RY2 is the risk intensity index of the market trend index Y2, Q is the number of times the risk intensity index RY1 of the key business index Y1 exceeds the custom risk warning threshold, and L is the number of times the risk intensity index RY2 of the market trend index Y2 exceeds the custom risk warning threshold; If the technology enterprise credit risk correlation strength indicator RISK exceeds the custom risk warning threshold, an early warning is triggered; The calculation formula of the enterprise revenue index Y1 risk intensity index RY1 is as follows: RY1=(QX1S1+QX2S2+…+QXnSn) / (Q1+Q2+…+Qn) Among them, Q1, Q2, ..., Qn are the times that the relationship strength coefficients S1, S2, ..., Sn exceed the custom risk warning threshold, and Q is the average of Q1, Q2, ... and Qn; The calculation formula of market trend indicator Y2 risk intensity indicator RY2 is as follows: RY2=(LP1G1+LP2G2+LP3G3) / (L1+L2+L3) Among them, L1, L2 and L3 are the times that the relationship strength coefficients G1, G2 and G3 exceed the custom risk warning threshold, and L is the average value of L1, L2 and L3.

6. A technology enterprise credit risk early warning device, characterized by: include: The data collection unit is responsible for collecting credit risk assessment information of different technology companies through automatic system collection, business data interface docking and manual entry, and using the collected information as an assessment sample for credit warning of technology companies; The risk indicator factor determination unit is responsible for evaluating and determining the corresponding risk indicator factors for different business scenarios by industry experts; The key indicator analysis unit is responsible for constructing a regression model of the relationship between risk indicator factors and the income of technology companies, confirming the relationship strength coefficient between each risk indicator factor and the income of technology companies through the standardized regression coefficient method, and determining the key indicators of credit risk of technology companies by comparing the relationship strength coefficients; The enterprise credit early warning unit is responsible for constructing a credit early warning risk model for technology enterprises, and building a credit risk early warning system for technology enterprises based on the credit early warning risk model for technology enterprises. It conducts real-time risk scanning on added technology enterprises, and when the enterprise risk indicators exceed the threshold range, the early warning will be displayed by highlighting the information or popping up prompts.

7. A risk early warning device for a technology enterprise, comprising: at least one processor; And, a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to implement the above method.

8. A computer program is stored on a readable storage medium, and when the computer program is executed by a processor, the above method is implemented.

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