Mapping Research Clusters of Artificial Intelligence for Financial Services Using Topic Modelling: A Machine Learning Insight

Artificial Intelligence (AI) improves decision-making and streamlines processes in the financial services industry. This study aims to explore the adoption of artificial intelligence in financial services over the last two decades. This research conducts a comprehensive analysis using bibliometric techniques and structural topic modelling on a dataset of 378 articles collected from the Scopus database, covering the span of two decades from 2002 to 2022. The primary focus of this study revolves around the domain of AI in financial services. It seeks to scrutinise publication trends, identify prominent sources, and uncover thematic clusters within this field. Remarkably, "The AI Book: The Artificial Intelligence Handbook for Investors, Entrepreneurs, and Fintech Visionaries" emerges as the leading source, contributing 5% of the total articles. The results obtained through structural topic modelling reveal the presence of five distinct thematic clusters, including topics such as financial services and customer management, AI and regulations, technology adoption in financial services, AI-driven risk management, and fraud detection in financial services. Future research trends in this field are anticipated to emphasise transparency, regulatory compliance, personalised customer experiences, proactive fraud prevention, ethical considerations, and the integration of quantum computing with AI for addressing complex challenges, ultimately reshaping the financial services industry landscape. These findings hold significant implications for many stakeholders, encompassing academics, practitioners, regulators, and policymakers.