Leveraging AI for Financial Risk Analytics

Authors

  • Dr. Soo-Yeon Oh Professor of Computer Science, Yonsei University, South Korea Author

Keywords:

Leveraging AI, Financial Risk Analytics

Abstract

Financial services are intensely marked by uncertainty. In such a scenario, the ability of financial entities to manage risk becomes crucial. This is where financial risk analytics come into the picture. Financial risk analytics is the critical product of financial engineering. It refers to the use of techniques to control financial risk, such as forecasting techniques, the use of derivatives, and other hedging techniques. Simply put, risk analytics refers to the process of examining the condition of various parts in the organization, an individual, or even a country, and exploring the background of financial troubles. Numerous complex decisions in financial institutions, like which business lines, borrowers, or entities to invest in or lend to, how much to invest or lend, etc., could potentially be the subject of financial risk analytics. In practice, institutions use some form of "rule of thumb" to guide these decisions, and the ability to replicate accurate forecasts is the ultimate consequence of using financial risk analytics.

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Published

30-10-2024

How to Cite

[1]
D. S.-Y. Oh, “Leveraging AI for Financial Risk Analytics”, Distrib Learn Broad Appl Sci Res, vol. 10, pp. 455–472, Oct. 2024, Accessed: Nov. 14, 2024. [Online]. Available: https://dlabi.org/index.php/journal/article/view/182

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