Artificial Intelligence in Financial Risk Management: A Bibliometric Review

This study presents a bibliometric analysis of research studies on the integration of artificial intelligence (AI) within the financial risk management, analyzing a dataset of 791 publications indexed in Scopus from 1987 to 2025. The primary objective of this research is to systematically map the global distribution of academic au-thority by identifying the core contributors: the most prolific authors, leading institutional affiliations, and the top performing countries driving the academic agenda. Additionally, the study tracks the evolution of au-thors’ keywords to monitor shifting thematic trends over time. The results reveal a sharp increase in research output in 2024, while long-term citation impact remains concentrated in earlier works such as Barboza et al. (2017). Geographically, India and China dominate in publication amount, whereas the U.S. and the U.K. lead in citation influence. Co-authorship networks Indicate highly fragmented collaboration structures among au-thors and institutions, with localized regional clusters prevailing over integrated global partnerships. Themat-ic mapping shows strong integration of AI with risk assessment and diversification into diverse topics, includ-ing advanced analytics and sustainability. Despite limitation of reliance on a single database, this review pro-vides a comprehensive overview of the intellectual structure and research dynamics in the evolving field. The findings offer valuable insights for scholars and practitioners, guiding future research directions and support-ing the development of AI applications in financial risk management.

Bibliometric Analysis; Artificial Intelligence; Financial Risk Management; Prolific Authors; Geographic Dis-tribution.

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