Author(s)

Hongjie Yue ¹

Affiliation(s)

¹ Kharkiv Institute, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China

Corresponding Author

Hongjie Yue

ABSTRACT

International bank failures occur frequently. In order to analyze and predict the causes of international bank failures, this paper uses the index data of Polish banks from 2017 to 2021 to establish a BP neural network prediction model. The optimal BP neural network prediction model with 50,000 training times, low time complexity and high model accuracy was determined.

KEYWORDS

BP neural network, bank failure, visualization

CITE THIS PAPER

Hongjie Yue, An international bank failure prediction model based on BP neural network. Financial Engineering and Risk Management (2022) Vol. 5: 47-54. DOI: http://dx.doi.org/10.23977/ferm.2022.050407.

REFERENCES

[1] Liu Lulu, Ning Xin. A Self-Learning BP Neural Network Assessment Algorithm for Credit Risk of Commercial Bank[J]. Wireless Communications and Mobile Computing, 222, 2022.
[2] Wang Xiaogang. Analysis of Bank Credit Risk Evaluation Model Based on BP Neural Network.[J]. Computational Intelligence and neuroscience, 2022,202, 2.
[3] Shan Zhirui. Credit Risk Assessment and Prediction Model of Commercial Banks[J]. Financial Engineering and Risk Management, 2021, 4 (4).
[4] Fariyanti. Iskandar, Malani Rheo, Suprapty Bedi. Total asset prediction of the large Indonesian bank using adaptive artificial neural network back-propagation[J]. International Journal of Engineering & Technology, 2018, 7 (2.2).
[5] Honglei Zhang, Wenshan Yuan, Hua Jiang. Performance Evaluation On Human Resource Management Of China'S Commercial Banks on Improved Bp Neural Networks [J]. International Journal of Advancements in Computing Technology, 2012, 4 (11).

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