Review
Version 1
This version is not peer-reviewed
A Comprehensive Review of Generative AI in Finance
Version 1
: Received: 25 July 2024 / Approved: 25 July 2024 / Online: 26 July 2024 (08:18:51 CEST)
How to cite: Lee, D. K. C.; Guan, C.; Yu, Y.; Ding, Q. A Comprehensive Review of Generative AI in Finance. Preprints 2024, 2024072109. https://doi.org/10.20944/preprints202407.2109.v1 Lee, D. K. C.; Guan, C.; Yu, Y.; Ding, Q. A Comprehensive Review of Generative AI in Finance. Preprints 2024, 2024072109. https://doi.org/10.20944/preprints202407.2109.v1
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.
Keywords
Generative AI; Large Language Models; Finance; Topic Modeling
Subject
Business, Economics and Management, Finance
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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