Research Article
A Comprehensive Review of Vertical Applications in the Financial Sector Based on Large Language Models
@INPROCEEDINGS{10.4108/eai.12-1-2024.2347198, author={Yanlin Mao and Bo Chen and Weiqin Chen and Yuandan Deng and Juntao Zeng and Mengzhen Du}, title={A Comprehensive Review of Vertical Applications in the Financial Sector Based on Large Language Models}, proceedings={Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12--14, 2024, Ningbo, China}, publisher={EAI}, proceedings_a={BDEDM}, year={2024}, month={6}, keywords={large language models financial text analysis sentiment analysis risk management prediction customer service intelligent assistant}, doi={10.4108/eai.12-1-2024.2347198} }- Yanlin Mao
Bo Chen
Weiqin Chen
Yuandan Deng
Juntao Zeng
Mengzhen Du
Year: 2024
A Comprehensive Review of Vertical Applications in the Financial Sector Based on Large Language Models
BDEDM
EAI
DOI: 10.4108/eai.12-1-2024.2347198
Abstract
This paper investigates the vertical applications of Large Language Models (LLM) in the financial domain, with a focus on the widespread use and profound impact of large language models in the financial industry. It begins by introducing the developmental history of large language models, followed by an overview of mainstream large language models in the financial domain. Subsequently, it explores the applications of large language models in financial text analysis and sentiment analysis, risk management and prediction, as well as customer service and intelligent assistants. Finally, it analyzes the challenges and limitations faced by large language models in the financial sector, proposing potential directions for future technological improvements.
