Abstract
Credit assessment of corporation borrower is the main means to control credit risk and asset risk management for commercial bank. The parameters of Logistic default model for the listed company's credit risk assessment are represented the state space form, Then the parameters are estimated by Kalman filter. The results show that the Kalman filter model can be obtained optimum results compared with Logistic regression model and the BP network model. Conclusions of this study enrich credit risk assessment system and strengthen risk management of chinese commercial banks.
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