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

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...

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Autor principal:	Ahmad Ghandour
Formato:	article
Lenguaje:	EN
Publicado:	UIKTEN 2021
Materias:	artificial intelligence banking fintech opportunities challenges Education L Technology T
Acceso en línea:	https://doaj.org/article/a3b1144ba0c64f83abe2944e138e4cb2
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spelling	oai:doaj.org-article:a3b1144ba0c64f83abe2944e138e4cb22021-12-01T09:32:09ZOpportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review10.18421/TEM104-122217-83092217-8333https://doaj.org/article/a3b1144ba0c64f83abe2944e138e4cb22021-11-01T00:00:00Zhttps://www.temjournal.com/content/104/TEMJournalNovember2021_1581_1587.pdfhttps://doaj.org/toc/2217-8309https://doaj.org/toc/2217-8333The 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.Ahmad GhandourUIKTENarticleartificial intelligencebankingfintechopportunitieschallengesEducationLTechnologyTENTEM Journal, Vol 10, Iss 4, Pp 1581-1587 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial intelligence banking fintech opportunities challenges Education L Technology T
spellingShingle	artificial intelligence banking fintech opportunities challenges Education L Technology T Ahmad Ghandour Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review
description	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.
format	article
author	Ahmad Ghandour
author_facet	Ahmad Ghandour
author_sort	Ahmad Ghandour
title	Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review
title_short	Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review
title_full	Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review
title_fullStr	Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review
title_full_unstemmed	Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review
title_sort	opportunities and challenges of artificial intelligence in banking: systematic literature review
publisher	UIKTEN
publishDate	2021
url	https://doaj.org/article/a3b1144ba0c64f83abe2944e138e4cb2
work_keys_str_mv	AT ahmadghandour opportunitiesandchallengesofartificialintelligenceinbankingsystematicliteraturereview
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Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review

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