Authors : Kun Chi; Stephanie Ness; Tayyab Muhammad; Mohan Raja Pulicharla

Volume/Issue : Volume 9 - 2024, Issue 2 - February

Google Scholar : http://tinyurl.com/m3ux989h

Scribd : http://tinyurl.com/2kkuhhyk

DOI : https://doi.org/10.5281/zenodo.10707503

Abstract : The integration of Artificial Intelligence (AI) in finance has received an increasing amount of attention in the industry over the past few years, extending from back- office trade automation to the more innovative robo- advisors in the front office. This paper presents a thorough review of the diverse landscape of AI in finance, covering both traditional financial operations and the new and exciting domain of FinTech. Unlike prior reviews that have been confined to very specific paradigms within AI methodologies, this review attempts to present a much more holistic approach to AI in Data Science (AiDS) in finance, encompassing the last several decades of AiDS research. The research categorizes, classifies, and carefully weighs the complete evolution of AiDS in finance. The research also points out the directions of the research, encompassing old and new challenges in finance. The research also critically compares the classical and the current AI in finance paradigms. In addition to its capabilities, the article details AI applications across wide- ranging financial sectors, including market prediction, fraud detection, algorithmic trading, and consumer behavior analysis.