Enhancing Capital Adequacy in Banks Using AI and Machine Learning: A Predictive  Approach to Risk Management and Regulatory Compliance

Sukumar Reddy Beereddy, Kiran Kumar K

Enhancing Capital Adequacy in Banks Using AI and Machine Learning: A Predictive Approach to Risk Management and Regulatory Compliance

Authors

Sukumar Reddy Beereddy, Kiran Kumar K

Keywords:

Capital Adequacy, Artificial Intelligence (AI), Machine Learning (ML), Basel III, Risk Assessment, XGBoost, Explainable AI (XAI).

Abstract

This paper examines the application of Artificial Intelligence and Machine Learning inestimating capital adequacy at banks, thereby addressing the limitations of traditional riskassessment methods, which primarily rely on conventional models and data. ThroughXGBoost, LSTM, RC, and RL, the research demonstrates

References

Nwankwo, S. N. P. (2019). Effect of capital adequacy on commercial bank’s financial performance in Nigeria, 2010-2017. European journal of accounting, finance and investment, 5(4), 1-21.

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Published

2022-12-28

How to Cite

Sukumar Reddy Beereddy, Kiran Kumar K. (2022). Enhancing Capital Adequacy in Banks Using AI and Machine Learning: A Predictive Approach to Risk Management and Regulatory Compliance. Journal of Computational Analysis and Applications (JoCAAA), 30(2), 549–573. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2906