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This study examines the growing impact of Artificial Intelligence (AI) and Machine Learning (ML) technologies in the banking sector, exploring how these innovations are transforming financial operations, improving efficiency, and reshaping customer interactions. Through a comprehensive bibliometric analysis of recent studies published in top academic journals, we identify key research trends, influential authors, and institutions driving this technological revolution. The results reveal an exponential rise in AI and ML-related research since 2020, reflecting the increasing adoption of these technologies within the financial industry. Key themes emerging from the literature include AI-driven risk management, fraud detection, customer behavior analysis, and operational optimization. Our study also highlights significant international collaboration networks, with major contributions from Asian, Middle Eastern, and European institutions. These collaborations are vital in advancing AI and ML applications in banking and fostering innovation on a global scale. Moreover, the research emphasizes the importance of ethical considerations, including data privacy and algorithmic transparency, in the development of AI and ML systems. Finally, we provide recommendations for policymakers to create regulatory frameworks that ensure responsible AI use in banking, promoting transparency and safeguarding consumer interests while encouraging continued innovation in the financial sector.

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Artificial Intelligence and Machine Learning in Banking Through a Bibliometric Lens

  • 会议论文

  • 发表日期：

    2026年

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  • Gherțescu Claudia,
  • Manta Alina Georgiana,
  • Bădîrcea Roxana Maria,
  • Olaru Mihail

摘要

This study examines the growing impact of Artificial Intelligence (AI) and Machine Learning (ML) technologies in the banking sector, exploring how these innovations are transforming financial operations, improving efficiency, and reshaping customer interactions. Through a comprehensive bibliometric analysis of recent studies published in top academic journals, we identify key research trends, influential authors, and institutions driving this technological revolution. The results reveal an exponential rise in AI and ML-related research since 2020, reflecting the increasing adoption of these technologies within the financial industry. Key themes emerging from the literature include AI-driven risk management, fraud detection, customer behavior analysis, and operational optimization. Our study also highlights significant international collaboration networks, with major contributions from Asian, Middle Eastern, and European institutions. These collaborations are vital in advancing AI and ML applications in banking and fostering innovation on a global scale. Moreover, the research emphasizes the importance of ethical considerations, including data privacy and algorithmic transparency, in the development of AI and ML systems. Finally, we provide recommendations for policymakers to create regulatory frameworks that ensure responsible AI use in banking, promoting transparency and safeguarding consumer interests while encouraging continued innovation in the financial sector.