CN105335891A - Enterprise debt paying risk assessment method - Google Patents

Abstract

The invention discloses an enterprise debt paying risk assessment method. Through comprehensively considering an enterprise debt paying credit threshold a, an enterprise reputation threshold b and an enterprise asset stability threshold c, enterprise credit can be precisely assessed; when a loan risk value w is calculated, a trend value lambda is introduced, and thus, the finally-acquired loan risk value w is more in line with the current enterprise condition, and a lender can make a more accurate judgment. Data for calculating the enterprise debt paying credit threshold a, the enterprise reputation threshold b and the enterprise asset stability threshold c are easy to acquire and hard to counterfeit, and risks brought by excessive dependence on low financial data authenticity when the enterprise financial data are used can be avoided.

Description

A kind of enterprise payment of debts methods of risk assessment

Technical field

The present invention relates to enterprise evaluation technical field, particularly relate to a kind of enterprise payment of debts methods of risk assessment.

Background technology

In China, a lot of Corporate finance is difficult, must by obtaining financing to pledging.Set up the To enterprises operational risk early-warning system groupware, be used for assisting financial institution to enterprise's credit decision-making and credit legal system, very necessary.The business risk assessment software of current widespread use, is all the basic data using the financial statement of enterprise as assessment, by these believable financial basic datas, is calculated the business circumstance of enterprise by wind control model.But a lot of enterprise especially medium-sized and small enterprises because of financial statement quality of information lower, the influence degree that Credit Risk Assessment of Enterprise is subject to business manager is high, and financial statement information credibility is lower, often has the situation that inside and outside account is inconsistent.Therefore traditional business risk forecast model is applied on medium-sized and small enterprises, certainly will have structural inclined mistake, cause predictive ability to reduce, and certainly will affect bank's credit according to survey, improves the credit risk of bank.

Summary of the invention

Based on the technical matters that background technology exists, the present invention proposes a kind of enterprise payment of debts methods of risk assessment.

A kind of enterprise payment of debts methods of risk assessment that the present invention proposes, comprises the following steps:

S1, setup times segmentation, obtain enterprise's payment of debts historical data of nearest multiple time slice, evaluates the enterprise payment of debts credit fragmentation value a in corresponding time slice according to the enterprise's payment of debts historical data in each time slice _n;

S2, according to multiple enterprise payment of debts credit fragmentation value a _ncalculate represent credit rating variation tendency move towards value λ, wherein, h ₀for the time span value of time slice, η is computational constant, and meets λ≤1;

S3, according to multiple enterprise payment of debts credit fragmentation value a _ncalculate enterprise's payment of debts credit threshold a in multiple time slice sum, $a=\underset{n=1}{\Σ}{a}_n/n;$

S4, obtain company-related information from internet, and relevant information is divided into positive information and negative report, then according to positive information and negative report occurrence number and the reliability weight occurring website, calculate corporate reputation threshold value b;

S5, the corporate financial information obtained on different time node, judge the total assets of the corresponding timing node of enterprise according to financial information, and according to the variation track of responsible official's total assets, assess enterprise assets degree of stability threshold value c;

S6, according to enterprise payment of debts credit threshold a, corporate reputation threshold value b and enterprise assets degree of stability threshold value c comprehensive descision business standing degree e;

S7, according to business standing degree e and move towards value λ calculate debt-credit value-at-risk w.

Preferably, step S1 is specially: count according to the enterprise's payment of debts historical data in each time slice and repay number of times A on schedule _n, exceed the time limit to repay number of times B _ndo not repay number of times C _nthree kinds, and three class data importings are preset the first computation model calculating acquisition enterprise payment of debts credit fragmentation value a _n; First computation model is:

A _n=K ₁a _n+ K ₂b _n+ K ₃c _n ², K ₁, K ₂and K ₃be scale-up factor, wherein, K ₁> 0, K ₃< 0, K ₃< K ₂< K ₁.

Preferably, in step S3, multiple time slice sum equals enterprise's establishment time or the incumbent responsible official of enterprise holds a post the time.

Preferably, in step S4, reputation threshold calculations model is:

wherein, n is the positive information quantity searched, δ _nbe that a positive information is reprinted number of times, β _nfor the reliability weight of website appears in described positive information first; M is the positive information quantity searched, α _mbe that a negative report is reprinted number of times, ε _mfor the reliability weight of website appears in described negative report first.

Preferably, step S5 is specially: obtain the corporate financial information on different time node, judges the total assets f of the corresponding timing node of enterprise according to financial information _n, and Real-time Obtaining assets mean value f _ave, enterprise assets degree of stability threshold value

Preferably, in step S6, the computing formula of business standing degree e is:

ω ₁, ω ₂and ω ₃be computational constant, and desirable positive count value.

Preferably, in step S7, the computing formula of debt-credit value-at-risk w is: ω=(1+ λ) × e.

The present invention is by considering enterprise payment of debts credit threshold a, corporate reputation threshold value b and enterprise assets degree of stability threshold value c, business standing degree can be assessed accurately, when calculating debt-credit value-at-risk w, introduce and move towards value λ, thus, make the final debt-credit value-at-risk w obtained more meet enterprise's present case, be conducive to lending side and make and judging more accurately.

The data being used for calculating enterprise payment of debts credit threshold a, corporate reputation threshold value b and enterprise assets degree of stability threshold value c in the present invention are all easily obtain, and not easily fake, avoid when utilizing enterprise's financial data owing to depending on the low risk brought of financial data validity unduly.

Accompanying drawing explanation

Fig. 1 is a kind of enterprise payment of debts methods of risk assessment process flow diagram that the present invention proposes.

Embodiment

With reference to Fig. 1, a kind of enterprise payment of debts methods of risk assessment that the present invention proposes, comprises the following steps:

S1, setup times segmentation, obtain enterprise's payment of debts historical data of nearest multiple time slice, counts repay number of times A on schedule according to the enterprise's payment of debts historical data in each time slice _n, exceed the time limit to repay number of times B _ndo not repay number of times C _nthree kinds, and three class data importings are preset the first computation model calculating acquisition enterprise payment of debts credit fragmentation value a _n.First computation model is:

A _n=K ₁a _n+ K ₂b _n+ K ₃c _n ², K ₁, K ₂and K ₃be scale-up factor, wherein, K ₁> 0, K ₃< 0, K ₃< K ₂< K ₁, concrete desirable K ₁=10, K ₂=1, K ₃=-10.

Enterprise's payment of debts history not only reflects enterprise's fiscal solvency, also reflects the credit of enterprise's debt-credit payment of debts aspect.In present embodiment, enterprise's payment of debts history is assessed, avoid the one-sidedness of single assessment enterprise fiscal solvency, it also avoid independent evaluations enterprise fiscal solvency and the loaded down with trivial details of credit rating of paying a debt.

S2, according to multiple enterprise payment of debts credit fragmentation value a _ncalculate represent credit rating variation tendency move towards value λ, wherein, h ₀for the time span value of time slice, η is computational constant, and meets λ≤1.Particularly, η determines by drawing coordinate system, take time shaft as X-axis, with enterprise payment of debts credit fragmentation value a _nfor Y-axis, then, as (t, a _n-1) and (t+h ₀, a _n) line and X-axis angle when being 45 °,

S3, according to multiple enterprise payment of debts credit fragmentation value a _ncalculate enterprise's payment of debts credit threshold a in multiple time slice sum, in present embodiment, multiple time slice sum can equal enterprise's establishment time or the incumbent responsible official of enterprise holds a post the time, the former can embody the payment of debts credit threshold mean value of enterprise since setting up, and the latter can embody incumbent responsible official and to hold a post enterprise's payment of debts credit threshold mean value in the time.

S4, obtain company-related information from internet, and relevant information is divided into positive information and negative report, then according to positive information and negative report occurrence number and the reliability weight occurring website, calculate corporate reputation threshold value b.Reputation threshold calculations model is:

wherein, n is the positive information quantity searched, δ _nbe that a positive information is reprinted number of times, β _nfor the reliability weight of website appears in described positive information first; M is the positive information quantity searched, α _mbe that a negative report is reprinted number of times, ε _mfor the reliability weight of website appears in described negative report first.

In this step, capture data by internet, and evaluate according to the overall reputation of information to enterprise captured.The corporate reputation threshold value b obtained in this step can reflect the culture of enterprise to a certain extent.In present embodiment, fully take into account the speed of internet information circulation, thus only consider that the reliability weight of website appears in information first, namely decreases calculated amount and improves counting yield, again by improve the accuracy of assessment to the evaluation in source; And reprint number of times and directly represent the viewed number of times of information and received degree by masses.

S5, the corporate financial information obtained on different time node, judge the total assets of the corresponding timing node of enterprise according to financial information, and according to the variation track of responsible official's total assets, assess enterprise assets degree of stability threshold value c.

This step is specially: the total assets f judging the corresponding timing node of enterprise according to financial information _n, and Real-time Obtaining assets mean value f _ave, enterprise assets degree of stability threshold value

The assets of any enterprise are all real-time change, the Appreciation gist of enterprise assets degree of stability threshold value as enterprise's debt-credit risk is obtained in present embodiment, the financial data lower relative to validity, enterprise assets degree of stability threshold value is as a relative value, and its confidence level is higher.

S6, according to enterprise payment of debts credit threshold a, corporate reputation threshold value b and enterprise assets degree of stability threshold value c comprehensive descision business standing degree e, the computing formula of business standing degree e is:

ω ₁, ω ₂and ω ₃be computational constant, and desirable positive count value, such as, ω ₁, ω ₂and ω ₃can equal values 1.

By considering enterprise payment of debts credit threshold a, corporate reputation threshold value b and enterprise assets degree of stability threshold value c, business standing degree can be assessed accurately, thus reduce the risk to enterprise's debt-credit.In addition, the data being used for calculating enterprise payment of debts credit threshold a, corporate reputation threshold value b and enterprise assets degree of stability threshold value c in present embodiment are all easily obtain, and not easily fake, avoid when utilizing enterprise's financial data owing to depending on the low risk brought of financial data validity unduly.

S7, according to business standing degree e and move towards value λ calculate debt-credit value-at-risk w.The computing formula of debt-credit value-at-risk w is: ω=(1+ λ) × e.

In this step, when calculating debt-credit value-at-risk w, introducing and moving towards value λ, thus, make the final debt-credit value-at-risk w obtained more meet enterprise's present case, be conducive to lending side and make and judging more accurately.

The above; be only the present invention's preferably embodiment; but protection scope of the present invention is not limited thereto; anyly be familiar with those skilled in the art in the technical scope that the present invention discloses; be equal to according to technical scheme of the present invention and inventive concept thereof and replace or change, all should be encompassed within protection scope of the present invention.

Claims (7)

1. enterprise's payment of debts methods of risk assessment, is characterized in that, comprise the following steps:

S1, setup times segmentation, obtain enterprise's payment of debts historical data of nearest multiple time slice, evaluates the enterprise payment of debts credit fragmentation value a in corresponding time slice according to the enterprise's payment of debts historical data in each time slice _n;

S2, according to multiple enterprise payment of debts credit fragmentation value a _ncalculate represent credit rating variation tendency move towards value λ, wherein, h ₀for the time span value of time slice, η is computational constant, and meets λ≤1;

S3, according to multiple enterprise payment of debts credit fragmentation value a _ncalculate enterprise's payment of debts credit threshold a in multiple time slice sum, $a=\underset{n=1}{\&Sigma;}{a}_n/n;$

S4, obtain company-related information from internet, and relevant information is divided into positive information and negative report, then according to positive information and negative report occurrence number and the reliability weight occurring website, calculate corporate reputation threshold value b;

S5, the corporate financial information obtained on different time node, judge the total assets of the corresponding timing node of enterprise according to financial information, and according to the variation track of responsible official's total assets, assess enterprise assets degree of stability threshold value c;

S6, according to enterprise payment of debts credit threshold a, corporate reputation threshold value b and enterprise assets degree of stability threshold value c comprehensive descision business standing degree e;

S7, according to business standing degree e and move towards value λ calculate debt-credit value-at-risk w.

2. enterprise as claimed in claim 1 payment of debts methods of risk assessment, it is characterized in that, step S1 is specially: count according to the enterprise's payment of debts historical data in each time slice and repay number of times A on schedule _n, exceed the time limit to repay number of times B _ndo not repay number of times C _nthree kinds, and three class data importings are preset the first computation model calculating acquisition enterprise payment of debts credit fragmentation value a _n; First computation model is:

A _n=K ₁a _n+ K ₂b _n+ K ₃c _n ², K ₁, K ₂and K ₃be scale-up factor, wherein, K ₁> 0, K ₃< 0, K ₃< K ₂< K ₁.

3. enterprise as claimed in claim 1 or 2 payment of debts methods of risk assessment, is characterized in that, in step S3, multiple time slice sum equals enterprise's establishment time or the incumbent responsible official of enterprise holds a post the time.

4. enterprise as claimed in claim 1 payment of debts methods of risk assessment, it is characterized in that, in step S4, reputation threshold calculations model is:

wherein, n is the positive information quantity searched, δ _nbe that a positive information is reprinted number of times, β _nfor the reliability weight of website appears in described positive information first; M is the positive information quantity searched, α _mbe that a negative report is reprinted number of times, ε _mfor the reliability weight of website appears in described negative report first.

5. enterprise as claimed in claim 1 payment of debts methods of risk assessment, it is characterized in that, step S5 is specially: obtain the corporate financial information on different time node, judges the total assets f of the corresponding timing node of enterprise according to financial information _n, and Real-time Obtaining assets mean value f _ave, enterprise assets degree of stability threshold value $c=\underset{n=1}{\&Sigma;}\frac{f_n-f_{ave}}{f_{ave}}.$

6. enterprise as claimed in claim 1 payment of debts methods of risk assessment, it is characterized in that, in step S6, the computing formula of business standing degree e is:

ω ₁, ω ₂and ω ₃be computational constant, and desirable positive count value.

7. the enterprise's payment of debts methods of risk assessment as described in any one of claim 1 to 6, is characterized in that, in step S7, the computing formula of debt-credit value-at-risk w is: ω=(1+ λ) × e.