Abstract
Personal credit scoring has played an extremely important role in the credit risk management of commercial banks. Specially, application scoring provides an important basis for the approval of customers’ credit application for the first time. In this paper, firstly, the classification of the personal credit scoring is sorted out and the definition of application scoring is given; then T test method is used to do the indicators selection; further, the author establishes the static application scoring model based on the data mining methods of Logistic regression and MCLP. The results show that among the methods that used in the application scoring, the effect of MCLP is better and it's more suitable for commercial application and promotion.
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