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BRIEF RESEARCH REPORT article

Front. Artif. Intell.
Sec. AI in Finance
Volume 7 - 2024 | doi: 10.3389/frai.2024.1440051
This article is part of the Research Topic Applications of AI and Machine Learning in Finance and Economics View all 3 articles

Adoption of Artificial Intelligence and Machine Learning in Banking Systems: A Qualitative Survey of Board of Directors

Provisionally accepted
  • Jeddah University, Jeddah, Saudi Arabia

The final, formatted version of the article will be published soon.

    The aim of the paper is twofold. First to examine the role of the board of directors in facilitating the adoption of AI and ML in Saudi Arabian banking sector. Second, to explore the effectiveness of artificial intelligence and machine learning in protection of Saudi Arabian banking sector from cyberattacks. A qualitative research approach was applied using in-depth interviews with 17 board of directors from prominent Saudi Arabian banks. The present study highlights both the opportunities and challenges of integrating artificial intelligence and machine learning advanced technologies in this highly regulated industry. Findings reveal that advanced artificial intelligence and machine learning technologies offer substantial benefits, particularly in areas like threat detection, fraud prevention, and process automation, enabling banks to meet regulatory standards and mitigate cyber threats efficiently. However, the research also identifies significant barriers, including limited technological infrastructure, a lack of cohesive artificial intelligence strategies, and ethical concerns around data privacy and algorithmic bias. Interviewees emphasized the board of directors' critical role in providing strategic direction, securing resources, and fostering partnerships with artificial intelligence technology providers. The study further highlights the importance of aligning artificial intelligence and machine learning initiatives with national development goals, such as Saudi Vision 2030, to ensure sustained growth and competitiveness. The findings from the present study offer valuable implications for policymakers in banking in navigating the complexities of artificial intelligence and machine learning adoption in financial services, particularly in emerging markets.

    Keywords: Artificial Intelligence1, Machine Learning2, stakeholder theory3, board of directors4, Banking Sector5, Saudi Arabia6

    Received: 28 May 2024; Accepted: 11 Nov 2024.

    Copyright: © 2024 Eskandarany. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Abdullah Eskandarany, Jeddah University, Jeddah, Saudi Arabia

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.