Emerging Trends and Bibliometric Analysis of AI Applications in Financial Services

Abstract

The aim of this study is to analyze research themes, leading authors, and global collaboration networks in AI research within the financial services industry from 2019 to 2024 using bibliometric tools such as VOSviewer. Utilizing data from 226 Scopus-indexed publications, we identified five main research clusters: credit evaluation, fraud detection, investment management, personal banking services, and regulatory compliance. The number of publications increased from nine in 2019 to fifty-two in 2024, reflecting growing global collaboration across thirty-two countries in eight distinct groups. IEEE Access and the International Journal of Bank Marketing emerged as the top journals, with h-indices of 7 and 6, respectively. Co-citation analysis highlights evolving patterns in AI-based risk assessment and automated decision-making systems. The findings demonstrate the rapid integration of AI in financial services, driven in part by the COVID-19 pandemic, providing valuable insights for academics, practitioners, and policymakers. This study lays the groundwork for further exploration of AI’s regulatory, transdisciplinary, and ethical dimensions in financial services.