Research Article
Empowering financial futures: Large language models in the modern financial landscape
@ARTICLE{10.4108/airo.6117, author={Xinwei Cao and Shuai Li and Vasilios Katsikis and Ameer Tamoor Khan and Hailing He and Zhengping Liu and Lieping Zhang and Chen Peng}, title={Empowering financial futures: Large language models in the modern financial landscape}, journal={EAI Endorsed Transactions on AI and Robotics}, volume={3}, number={1}, publisher={EAI}, journal_a={AIRO}, year={2024}, month={7}, keywords={Large language models, Financial sector, Customer support, Fraud detection}, doi={10.4108/airo.6117} }- Xinwei Cao
Shuai Li
Vasilios Katsikis
Ameer Tamoor Khan
Hailing He
Zhengping Liu
Lieping Zhang
Chen Peng
Year: 2024
Empowering financial futures: Large language models in the modern financial landscape
AIRO
EAI
DOI: 10.4108/airo.6117
Abstract
In this paper, we delve into the transformative influence of Large Language Models (LLMs) in the financial sector. Through meticulous exploration, we uncover the multifaceted applications of LLMs, ranging from elevating customer support and fortifying fraud detection to reshaping market analysis and prediction. LLMs, with their unparalleled ability to process extensive textual data, bring forth innovative solutions and insights. However, we also address critical challenges such as user trust and ethical considerations, emphasizing the need for responsible integration. Collaborative efforts between industry stakeholders and researchers are essential prerequisites for making a pivotal stride towards a future where LLMs redefine financial practices, with efficiency, accuracy, and ethical precision shaping the industry’s evolution.
Copyright © 2024 Xinwei Cao et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
