Xiaokang Shi, Xiaoqun He

【Abstract】

Default rate of credit data is low due to conservative consumption habits in China. The data sets always have the characteristic of imbalance. The feature brings logistic regression model negative influence. Asymmetrical connection function is introduced to the credit rating and the link function of logistic regression model is replaced by the skew-logistic distribution. In addition, skewness parameter and regression coefficients are estimated by real data.The results show that the prediction of skew-logistic model is better than the ordinary logistic regression. In 10% default rate of data set, the skew-logistic model performance is better than the decision tree, neural network and support vector machine.

【Keywords】

credit scoring, asymmetrical connection function, skew-logistic regression