An Analytical Study of Generative AI in Finance: Evaluating Its  Applications in Risk Modeling, Algorithmic Trading, Fraud Detection,  and Ethical Challenges in Automated Decision-Making

Abhishek Chatrath

An Analytical Study of Generative AI in Finance: Evaluating Its Applications in Risk Modeling, Algorithmic Trading, Fraud Detection, and Ethical Challenges in Automated Decision-Making

Authors

Abhishek Chatrath

Keywords:

Generative AI, Financial Risk Modeling, Algorithmic Trading, Fraud Detection, Ethical AI, Automated Decision-Making, Machine Learning in Finance, GitHub.

Abstract

This study analytically evaluates the transformative role of generative artificialintelligence (GenAI) in financial services, focusing on its applications in risk modeling,algorithmic trading, fraud detection, and ethical implications in automated decision making. Employing a mixed-methods approach,

References

[1] Aldasoro, I., Doerr, S., & Frost, J. (2023). Mapping generative AI in central banking. BIS Quarterly Review. https://doi.org/10.2139/ssrn.4466312

[2] Sidharth Sharma (2023). Ai-driven anomaly detection for advanced threat detection.

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Published

2024-03-20

How to Cite

Abhishek Chatrath. (2024). An Analytical Study of Generative AI in Finance: Evaluating Its Applications in Risk Modeling, Algorithmic Trading, Fraud Detection, and Ethical Challenges in Automated Decision-Making. Journal of Computational Analysis and Applications (JoCAAA), 33(4), 1187–1203. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5744