THE INTERSECTION OF INFORMATION TECHNOLOGY, FINANCIAL SERVICES, AND RISK MANAGEMENT, INCLUDING AI AND ML INNOVATIONS
Keywords:
Artificial Intelligence (AI), Machine Learning (ML), Risk Management, Credit Risk, Investment Strategies, Financial Services, Automation, Predictive Modeling, Ethical IssuesAbstract
The adoption of Artificial Intelligence (AI) and Machine Learning (ML) has significantly transformed risk management practices in financial services. This paper examines the impact of AI and ML on enhancing risk management through more precise credit risk evaluations, automated fraud detection, and advanced investment strategies. By analyzing case studies from JPMorgan Chase, ZestFinance, and Betterment, the study illustrates how these technologies improve accuracy, efficiency, and decision-making in financial operations. However, challenges such as data integrity, algorithmic transparency, and ethical concerns must be addressed. The paper concludes with insights into future developments and the need for effective strategies to overcome these challenges and fully capitalize on the benefits of AI and ML in managing financial risk.
References
Arner, D. W., Barberis, J., & Buckley, R. P. (2016). The evolution of fintech: A new post-crisis paradigm? Georgetown Journal of International Law, 47(4), 1271-1319.
Narayanan, A., Bonneau, J., Felten, E., Miller, A., & Washington, J. (2016). Bitcoin and cryptocurrency technologies: A
comprehensive introduction. Princeton University Press.
Philippon, T. (2016). The fintech opportunity. NBER Working Paper No. 22444.
Basel Committee on Banking Supervision. (2011). Basel III: A global regulatory framework for more resilient banks and banking systems. Bank for International Settlements.
COSO. (2017). Enterprise risk management—Integrating with strategy and performance. Committee of Sponsoring Organizations of the Treadway Commission.
Jorion, P. (2018). Financial risk manager handbook. Wiley.
Gustafsson, M., Harrington, M., & Kim, M. (2020). The rise of artificial intelligence in finance. Journal of Financial Transformation, 51, 53-60.
He, H., Wu, D., & Wu, L. (2019). Deep learning for financial forecasting. Journal of Financial Data Science, 1(1), 34-47.
Kumar, S., Garg, R., & Gupta, S. (2020). Applications of artificial intelligence in financial services. International Journal of Financial Studies, 8(2), 35.
Buchak, G., Piskorski, T., Seru, A., & Vickery, J. (2018). Fintech, regulatory arbitrage, and the rise of shadow banks. Journal of Financial Economics, 130(3), 453-483.
Chen, X., Wu, J., & Xu, B. (2018). Artificial intelligence in finance: A review. Financial Innovation, 4(1), 1-13.
Choudhury, P., Bandyopadhyay, S., & Mitra, S. (2019). Machine learning and its applications in financial risk management. Journal of Risk and Financial Management, 12(1), 28.
JPMorgan Chase. (2021). Leveraging AI for risk management: A case study. JPMorgan Chase & Co.
Ngai, E. W. T., Xiu, L., & Chau, D. C. K. (2019). Application of data mining techniques in financial fraud detection: A review. Decision Support Systems, 41(3), 727-739.
Palantir Technologies. (2020). AI and analytics for risk management. Palantir Technologies.
