Credit Risk Assessment and Prediction Model of Commercial Banks
DOI: 10.23977/ferm.2021.040404 | Downloads: 24 | Views: 942
Author(s)
Shan Zhirui 1
Affiliation(s)
1 ICBC Credit Suisse Asset Management Co., Ltd., Beijing, China
Corresponding Author
Shan ZhiruiABSTRACT
Aiming at the risk assessment and prediction of commercial bank credit management, BP neural network and GRNN model are established respectively to fit and forecast the non-performing loan rate of commercial bank. The results show that GRNN neural network has high fitting accuracy but low prediction accuracy, while BP neural network has low fitting accuracy but high prediction accuracy.
KEYWORDS
BP neural network, Grnn, Net flow, Early warningCITE THIS PAPER
Shan Zhirui. Credit Risk Assessment and Prediction Model of Commercial Banks. Financial Engineering and Risk Management (2021) 4: 33-37. DOI: http://dx.doi.org/10.23977/ferm.2021.040404.
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