Abstract
At present, financial analysis is still the main method to evaluate the risk of corporate credit customers. However, the design and modification of financial analysis model in credit practice are mostly based on the statistical data and experience of a certain section, which is not scientific and verifiable. In this paper, we try to apply the genetic algorithm model in the field of artificial intelligence to establish a set of solutions for the continuous iterative optimization of financial model parameters, and preliminarily verify its effectiveness, and discuss its possible shortcomings and development direction.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yin, K., Liu, X.: Research on credit rating model based on commercial banks. Econ. Manage. Rev. 22 (2006)
Zhou, Z.: Recognition Model of Financial Statement Authenticity of Listed Companies Based on Support Vector Machine. Jilin University, Changchun (2007)
Liang, Y.: Application of BP neural network in bank loan classification. China Finan. Comput. News 7, 59–62 (2005)
Zhou, Z., Cao, C.: Neural Network and its Application. Tsinghua University Press, Beijing (2004)
Acknowledgements
Optimization of Financial Rating Model for Bank Credit Customers Based on Artificial Intelligence Algorithm by the Provincial Basic Business Fee Project of Harbin Institute of Finance(2018-KYYWF-E007).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Lin, L. (2021). Optimization of Bank Credit Customer Financial Rating Model Based on Artificial Intelligence Algorithm. In: Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Advances in Intelligent Systems and Computing, vol 1398. Springer, Cham. https://doi.org/10.1007/978-3-030-79200-8_105
Download citation
DOI: https://doi.org/10.1007/978-3-030-79200-8_105
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-79199-5
Online ISBN: 978-3-030-79200-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)