【摘要】Based on a set of credit card sample of Chinese commercial bank,a systemically comparative study of various statistical credit scoring models was firstly made in China The comparative study indicated that every model has its own strength and weakness The strengths of linear discriminant analysis,linear program,and Logistic regression are that these models are explainable and their outputs can be a linear scorecard(so can be easily implemented) But these models have higher misclassification rate comparing with others Neural network and classification tree models have a higher predict accuracy,but may be‘over fitted’,and their outputs are hard to be explained