Modeling Credit Risk For SMEs Based On Logistic Regression

With the rapid development of financial markets,the pressure of international regulatory increases.Competition among commercial banks is fierce,the management of credit risk should be more flexible and proactive.In contrast,although with the high administrative costs and thin profits,SMEs occupies most of the market share for commercial banks to develop business,which attracts more attention.However,due to asymmetric information and other reasons,less than 10% SMEs access to bank loans,which makes them vulnerable to outside risk.In order to ease the financing difficulties,we have to analyze the main reason for the bank credit crunch,and finding the right way to reduce the cost of bank loans,serving more SMEs,to achieve a win-win situation.This paper introduces the relevant literature of domestic and international credit risk assessment,including qualitative and quantitative analysis theory.And then describing the characteristics of SMEs and commercial banks,credit risk concepts and theories.After comparing the advantages and disadvantages of various types of model,we ultimately select the Logistic model for credit risk.We choose SMEs data of year 2015 and mainly select 17 annual financial indicators,constructing 0,1 dummy variables and Logistic regression model.At last,the result shows that the model provides universal equation of China's commercial bank credit risk assessment.