Based on the data of listed companies in China. In this paper, we establish a number of credit risk default probability measurement models by factor scores, multiple typical discriminant, Bayesian discriminant, Logit regression and neural network, and compare the effectiveness of each model. It is found that the neural network model can accurately reflect the credit risk default in the sample, which is the optimal credit risk default probability measurement model in the above model.

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