Modeling Credit Risk Factors of the Small and Medium-Sized Enterprises’ Default Behaviors
|關鍵字:||中小企業;邏輯斯迴歸;決策樹;逾期放款;財務危機;信用風險;Small and Medium-Sized Enterprises;Logistic Regression;Decision Tree;Overdue Loan;Financial Crisis;Credit Risk|
Financial intermediaries such as banks play an important role to keep the flow of funds moving in financial systems, and therefore their performance not only affect their existence and development, but also affect the benefit of customers and the national financial stability. If banks fail to control the quality of credit loan carefully, it may result in non-performing loans. Without a doubt, it makes the bank shareholders and customers expose to great risk of loss. When banks review the credit loan of the small and medium-sized enterprises, they often face the problems of distorted financial statements, insufficient financial strength of shareholders, dishonesty business owners and so on. For the soundness of credit loans, it is important for banks to use effective and objective ways to make the best decisions in order to avoid the occurrence of overdue loans. Three hundred scredit-loan cases of small and medium-sized enterprises from 2010 to 2011 were collected from one specific commercial bank in Taiwan. One hundred and thirteen companies were breach of loan cases, and one hundred and eighty-seven companies were not. We measured not only financial ratio indicators, indicators of corporate governance and credit conditions, but also indicators of the owners’ individual and credit conditions. Thirty-five indicators in three dimensions were included in the analysis of three risk assessment models: binary logistic regression model, decision tree, and two stage combined. The results showed that decision tree has higher differentiability among the credit risk factors, and its correct prediction rate is 96%. Thirteen influential indicators were identified in this study. The results of this study may offer a new perspective and valuable references for financial intermediaries’ credit risk management for loans of SMEs.