Generative AI in banking: empirical insights on integration, challenges and opportunities in a regulated industry
Abstract
Purpose
This study aims to fill critical research gaps by providing empirical evidence on the practical application of generative AI in the banking sector. It explores managerial preparedness, regulatory compliance and data privacy challenges in implementing this technology, offering insights into its operational effectiveness and potential in financial services.
Design/methodology/approach
The research employs a qualitative approach, conducting in-depth interviews with bank managers and industry experts. These interviews are analysed to identify key factors influencing the integration of generative AI in financial institutions.
Findings
The study identifies five critical factors – recognition, requirement, reliability, regulatory and responsiveness – that collectively impact the adoption and operational effectiveness of generative AI in banking. These factors highlight the challenges and opportunities of integrating this technology within the highly regulated financial industry.
Practical implications
The findings have significant theoretical and managerial implications. Theoretically, the research contributes to understanding AI integration in regulated industries, particularly financial services. Managerially, it provides a roadmap for financial institutions to adopt generative AI responsibly, balancing innovation with regulatory compliance and ethical considerations.
Originality/value
This study is among the first to provide empirical data on generative AI’s practical application in the banking sector, addressing the lack of real-world evidence and offering a comprehensive analysis of the factors influencing its successful implementation in a highly regulated environment.
Keywords
Acknowledgements
While preparing this work, the author(s) used Grammarly and ChatGPT to enhance the manuscript’s readability. These AI-assisted technologies improved grammar, style, and coherence. After using these tools, the author(s) carefully reviewed and edited the content as necessary, ensuring accuracy and clarity. The author(s) take full responsibility for the publication’s content.
Funding: The authors gratefully acknowledge the Deanship of Graduate Studies and Scientific Research at Taif University, Saudi Arabia for their generous funding support for this project.
Citation
Moharrak, M. and Mogaji, E. (2024), "Generative AI in banking: empirical insights on integration, challenges and opportunities in a regulated industry", International Journal of Bank Marketing, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJBM-08-2024-0490
Publisher
:Emerald Publishing Limited
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