In recent years, my country's economic situation has been stable with changes. The overall situation is not optimistic. Coupled with the impact of the epidemic, credit risk (CR) events often occur in the financial market. Optimize the process of CR management and increase CR. Management capabilities and the establishment of a CR management system based on a standardized process are the top priorities for major banking financial institutions. Therefore, this paper studies the bank CR model based on artificial neural network (NN). This paper first briefly explains the impact mechanism of CR from the aspects of profitability and liquidity, then builds the BP NN model, and finally analyzes the BP model. The results show that the misjudgment rate of the BP model is 7.14%, and the judgment accuracy rate is 92.86%. The model is more accurate for CR judgment.

Zhaoyang Wu. A Bank Credit Risk Model Integrating Artificial Neural Network. International Journal of Neural Network (2021), Vol. 2, Issue 4: 17-23. https://doi.org/10.38007/NN.2021.020403.

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