Author

Listed:

David Kuo Chuen Lee
(School of Business, Singapore University of Social Sciences, 463 Clementi Road, Singapore 599494, Singapore)
Chong Guan
(SUSS Academy, Singapore University of Social Sciences, Singapore 408601, Singapore)
Yinghui Yu
(School of Business, Singapore University of Social Sciences, 463 Clementi Road, Singapore 599494, Singapore)
Qinxu Ding
(School of Business, Singapore University of Social Sciences, 463 Clementi Road, Singapore 599494, Singapore)

Abstract

The integration of generative AI (GAI) into the financial sector has brought about significant advancements, offering new solutions for various financial tasks. This review paper provides a comprehensive examination of recent trends and developments at the intersection of GAI and finance. By utilizing an advanced topic modeling method, BERTopic, we systematically categorize and analyze existing research to uncover predominant themes and emerging areas of interest. Our findings reveal the transformative impact of finance-specific large language models (LLMs), the innovative use of generative adversarial networks (GANs) in synthetic financial data generation, and the pressing necessity of a new regulatory framework to govern the use of GAI in the finance sector. This paper aims to provide researchers and practitioners with a structured overview of the current landscape of GAI in finance, offering insights into both the opportunities and challenges presented by these advanced technologies.

Suggested Citation

David Kuo Chuen Lee & Chong Guan & Yinghui Yu & Qinxu Ding, 2024. "A Comprehensive Review of Generative AI in Finance," FinTech, MDPI, vol. 3(3), pages 1-19, September.

Handle: RePEc:gam:jfinte:v:3:y:2024:i:3:p:25-478:d:1481681

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References listed on IDEAS

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