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A credit evaluation method for loan users based on fuzzy logistic regression

A logistic regression and credit evaluation technology, applied in data processing applications, finance, instruments, etc., can solve the problem that logistic regression cannot quantitatively use credit evaluation results for qualitative credit indicators, and achieve the effect of accurate judgment standards

Active Publication Date: 2022-07-29
NANJING UNIV OF POSTS & TELECOMM
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  • Description
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  • Application Information

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Problems solved by technology

[0005] The present invention mainly solves the problem that existing Logistic regression cannot quantitatively use qualitative credit indicators and the problem of absolutization of credit evaluation results, and proposes a method based on fuzzy Logistic regression, using a 5-point Likert scale to evaluate the score of each credit indicator , use the triangular fuzzy number in the fuzzy set theory to fuzzify the credit index score, and aim at the fuzzy model, propose to use the fuzzy least squares estimation method to estimate the coefficients corresponding to each credit index of the regression equation, and finally for each The predicted fuzzy results are normalized to provide accurate judgments for predicting credit status

Method used

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  • A credit evaluation method for loan users based on fuzzy logistic regression
  • A credit evaluation method for loan users based on fuzzy logistic regression
  • A credit evaluation method for loan users based on fuzzy logistic regression

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Experimental program
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Embodiment 1

[0060] Step 1: According to the collected loan user data, here only 12 indicators that affect user credit are extracted and evaluated as a reference. The names of each indicator are shown in Table 1:

[0061] Table 1 User Index Table

[0062]

[0063]

[0064] Evaluate each indicator using a 5-point Likert scale for selected credit indicators The specific score is: use a set of statements to express the quality of each indicator. Each set of statements has {"very poor", "poor", "moderate", "good", "very good"}, respectively Denoted as {1,2,3,4,5};

[0065] Step 2: Let the fuzzy number on the universe R be M, if the membership function of M is u M Make R→[0,1], expressed as the following formula:

[0066]

[0067] where, u M (x) is the triangular fuzzy function; where M is represented as (s, m, u), s and u represent the fuzzy infimum and supremum, respectively; m is the median value of the membership degree of M is 1, when When x=m, x completely belongs to M; the...

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Abstract

The invention discloses a credit evaluation method for loan users based on fuzzy Logistic regression. The invention includes the selection of credit index, the scoring of the credit index by the 5-point Likert scale, the fuzzification of the credit index, the fuzzification of the loan default result, the construction of a new fuzzy Logistic regression model, the calculation of the model coefficients based on the fuzzy least square method, Predict the user's credit status and other steps. The present invention uses a 5-point Likert scale to quantify the qualitative credit index; the fuzzy number can reflect the inherent uncertainty in the evaluation problem, so it is proposed to use the triangular fuzzy number to fuzzify it, avoiding the qualitative index and scope. The absoluteness of the quantification of indicators, so that some more important qualitative indicators can be better used. And on the basis of Logistic regression, a new fuzzy Logistic regression model is proposed to evaluate the possibility of prediction results, so as to provide accurate judgment criteria for credit evaluation.

Description

technical field [0001] The invention relates to the field of computer application, in particular to a credit evaluation method for loan users based on fuzzy Logistic regression. Background technique [0002] Under the situation that the unsecured pure credit loan is on the rise, all commercial banks take the loan business as the focus of development. However, the non-performing loan ratio of commercial banks is at a high level every year, so that commercial banks have more and more stringent requirements for loans, making it difficult for loan users to take out loans. The main reason hindering the development of credit business is that commercial banks have a low level of loan risk management and lack effective user credit assessment methods. Every one percentage point increase in the accuracy of the credit evaluation model can bring tens of thousands of profits to commercial banks. Therefore, it is of great practical value to study the credit evaluation of loan users. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q40/02
CPCG06Q40/03
Inventor 韩京宇万杨兰
Owner NANJING UNIV OF POSTS & TELECOMM
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