Credit Risk Assessment In Small And Medium-sized Enterprises Based On Logit Model

In recent years, the fast-developing national economy and SMEs have become leadingforces for our socialist economy development. SMEs are playing an important role ontechnical innovation, alleviation of employment pressure and other aspects. We have tofocus our attention on SMEs development in order to create a fast, harmonious and stabledevelopment in national economy. Credit risk is one of the main risks faced by creditbusiness in commercial banks. SMEs are small sized, having fewer assets, low anti-riskability, poor management experience and nonstandard decision making.The information asymmetries between commercial banks and SMEs lead to high creditrisk for enterprises. Banking credit crunch makes it difficult for SMEs to raise capital andput their development in a difficult position. Therefore, the key problem in long-term andstable development of SMEs is to find out the suitable credit risk assessment way in Chinaby using statistical calculation methods to create credit risk assessment model which isappropriate to SMEs features. The model will analyze the relevant financial data andnon-financial data to measure the possibility of SMEs credit risk.The paper introduced SMEs financing conditions and analyzed the banking creditcrunch in the view of SMEs features and financial bank credit risk. Logit model finally waschosen as the researched risk assessment model after several common credit riskassessment models were compared and the SMEs features were taken into fullconsideration. And five items were adopted for analysis from financial targets inenterprises. This paper analyzed the influence of business classification on SMEs.Fifty-two enterprises were classified into priority and discretion projects equally accordingto national industrial policy. Annual financial targets from2009to2011were employedand75%of the asset-liability ratio was put as a critical value to construct virtual valueswith SPSS to analyze the targets of co-linearity and Logit regression. The researchindicates the Logit regression model in credit risk assessment of SMEs is effective. Afterthe business classification, the assessments and predict of priority projects are prior todiscretion projects.