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Adoption of artificial intelligence in banking services: an empirical analysis

Author

Listed:
  • Mahfuzur Rahman
  • Teoh Hui Ming
  • Tarannum Azim Baigh
  • Moniruzzaman Sarker

Abstract

Purpose - This study aims to understand the importance and challenges of adopting artificial intelligence (AI) in the banking industry in Malaysia and examine the factors that are important in investigating consumers' intention to adopt AI in banking services. Design/methodology/approach - The qualitative research was carried out using in-depth interviews from officials in the baking industry to understand the importance and challenges of adopting AI in the banking industry. In the quantitative study, a total of 302 completed questionnaires were received from Malaysian banking customers. The data were analysed using the SmartPLS 3.0 software to identify the important predictors of their intention to adopt AI. Findings - The qualitative results reveal that AI is an essential tool for fraud detection and risk prevention. The absence of regulatory requirements, data privacy and security, and lack of relevant skills and IT infrastructure are significant challenges of AI adoption. The quantitative results indicate that attitude towards AI, perceived usefulness, perceived risk, perceived trust, and subjective norms significantly influence intention to adopt AI in banking services while perceived ease of use and awareness do not. The results also show that attitude towards AI significantly mediates the relationship between perceived usefulness and intention to adopt AI in banking services. Practical implications - Financial technology (FinTech) is regarded as a critical determinant of strategic planning in the banking industry. While AI provides various disruptive opportunities in the FinTech space in terms of data collection, analysis, safeguarding and streamlining processes, it also poses a sea of threats to incumbent banks. This study provides vital insights for the policymakers of the banking industry to address the challenges of adopting AI in banking. It also provides the important predictors of the bank customers' intention to adopt AI in banking services. Policymakers can devise their strategies to enhance AI adoption considering the facts. Originality/value - This study is amongst the pioneer in exploring the importance and potential challenges in implementing AI technology in banking services and identifying the essential factors influencing the intention to adopt AI in Malaysia's banking services.

Suggested Citation

  • Mahfuzur Rahman & Teoh Hui Ming & Tarannum Azim Baigh & Moniruzzaman Sarker, 2021. "Adoption of artificial intelligence in banking services: an empirical analysis," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 18(10), pages 4270-4300, December.
  • Handle: RePEc:eme:ijoemp:ijoem-06-2020-0724
    DOI: 10.1108/IJOEM-06-2020-0724
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    Citations

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    Cited by:

    1. Simona-Vasilica Oprea & Adela Bâra, 2024. "Exploring excitement counterbalanced by concerns towards AI technology using a descriptive-prescriptive data processing method," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-24, December.
    2. Pandey, Dharen Kumar & Hassan, M.Kabir & Kumari, Vineeta & Zaied, Younes Ben & Rai, Varun Kumar, 2024. "Mapping the landscape of FinTech in banking and finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 67(PA).

    More about this item

    Keywords

    Artificial intelligence; Bank customers; Intention to adopt; PLS-SEM; Malaysia; G20; G21; L86; 033;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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