Vol.10, No.4, November 2021.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                          eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review


Ahmad Ghandour


© 2021 Ahmad Ghandour, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 10, Issue 4, Pages 1581-1587, ISSN 2217-8309, DOI: 10.18421/TEM104-12, November 2021.


Received: 09 June 2021.

Revised:  19 September 2021.
Accepted: 25 September 2021.
Published: 26 November2021.




The primary aim of this systematic literature review (SLR) was to identify, assess and synthesize the extant evidence about the opportunities and challenges concerning the use of Artificial Intelligence (AI) in the banking sector. From the SLR, it is evident that AI has several opportunities for the sector. There are many fin-tech start-ups that offer banking AI solutions, and banking regulators are fostering AI adoption through legislation and collaboration. Other opportunities include the following: personalized services, smart wallets, decision-making and problem-solving, customer satisfaction and loyalty, process automation (especially targeting repetitive tasks), transactional security and cybersecurity improvements, and promotion of digital financial inclusion. Nevertheless, the key banking industry stakeholders have to formulate appropriate strategies aimed at overcoming existing and prospect AI challenges. Among the AI challenges that should be prioritized we include the following: job loss and user acceptance concerns, privacy breaches, creativity and adaptability loss, restrictive implementation and operational requirements, digital divide, availability of vast quality data, AI-business strategy alignment, and loss of emotional “human touch”. However, existing studies are largely descriptive and based on secondary sources of data. This necessitates empirical studies to expand the existing body of knowledge regarding AI opportunities and challenges in the banking industry.


Keywords –Artificial Intelligence, Banking, Fintech, opportunities, challenges.



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