Journal of Xi'an Jiaotong University

Study on Prediction Ability of Credit Scoring System Based on Neural Network Using Back Propagating Algorithm
Zhu Xiaoming，Cheng Jian，Liu Zhiguo,Zhong Jingfan
(Jinhe Center for Economic Research，Xi'an　Jiaotong　University，Xi'an 710049，China)

Abstract：A credit scoring system based on BP(back propagation) neural network model is presented in order to improve the accuracy and stability of the prediction. A new method for evaluating the accuracy and stability of the system is also presented. Combining with the features of credit scoring problems, a neural network model is established and the parameters are determined. Then the input variables are decided by a forward selecting method to train the model. The prediction ability of the proposed credit scoring system is valuated through introducing theory of ROC (receiver operating characteristics) curves, AUC(area under curve) value and information theory, and compared to the traditional logistic credit scoring system. Finally, the checking samples are created by means of bootstrap method to validate the stability of the system. The experiment results show that the credit scoring system based on BP neural network is more accurate and stable than the logistic credit scoring system, and averagely, the AUC value is increased by 0.036 7 and its standard error is decreased by 0.005.
Keywords：neural network; back propagating algorithm； credit scoring； area under curve value