Abstract:With the rapid growth of personal credit business, personal credit risk assessment is an urgent problem to be
solved, and the personal credit rating classification problem is put under examination. Through the establishment of personal credit risk evaluation index system, using discriminant analysis method to construct a grading model for the samples, thus the discriminant score is obtained; then the neural network method is used to predict the scores for the samples, and the scores due are collected and such scores were to put into an descending order so an orderly sample is acquired. Finally, the optimal seg- mentation of the orderly sample is done so as to realize rating of personal credit. The model, to a certain extent, helps borrow- ers spot the high quality customers, thereby to reduce credit risk.