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Data Science in Finance: Challenges and Opportunities.

Authors :
Zheng, Xianrong
Gildea, Elizabeth
Chai, Sheng
Zhang, Tongxiao
Wang, Shuxi
Source :
AI. Mar2024, Vol. 5 Issue 1, p55-71. 17p.
Publication Year :
2024

Abstract

Data science has become increasingly popular due to emerging technologies, including generative AI, big data, deep learning, etc. It can provide insights from data that are hard to determine from a human perspective. Data science in finance helps to provide more personal and safer experiences for customers and develop cutting-edge solutions for a company. This paper surveys the challenges and opportunities in applying data science to finance. It provides a state-of-the-art review of financial technologies, algorithmic trading, and fraud detection. Also, the paper identifies two research topics. One is how to use generative AI in algorithmic trading. The other is how to apply it to fraud detection. Last but not least, the paper discusses the challenges posed by generative AI, such as the ethical considerations, potential biases, and data security. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
26732688
Volume :
5
Issue :
1
Database :
Academic Search Index
Journal :
AI
Publication Type :
Academic Journal
Accession number :
176266238
Full Text :
https://doi.org/10.3390/ai5010004