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Artificial Intelligence and Operational Risk Management: A Qualitative Analysis in the Moroccan Banking Sector
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Author(s): Hajar El Haji (Mohammed First University, Morocco)and Oumayma Aitmoussa (Mohammed First University, Morocco)
Copyright: 2026
Pages: 28
Source title:
Transparency in AI-Assisted Management Decisions
Source Author(s)/Editor(s): Abdelfattah Jamal (Cadi Ayyad University, Morocco), Karima Aissaoui (Mohammed First University, Morocco), Lhoussaine Alla (Sidi Mohamed Ben Abdellah University, Morocco), Bouchra Alj (Hassan II University, Morocco)and Badr Bentalha (Sidi Mohammed Ben Abdellah University, Morocco)
DOI: 10.4018/979-8-3373-1737-3.ch011
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Abstract
This paper explores the impact of artificial intelligence (AI) on operational risk management in the Moroccan banking sector through a qualitative case study conducted at Banque Populaire. The objective is to understand how AI, particularly in front-office operations, contributes to risk reduction, improved operational efficiency, and process automation. The results reveal a growing integration of AI, particularly through chatbots and automated services, helping to limit human error and reduce workload. However, challenges remain, related to both technical aspects (outages, cybersecurity, system interoperability) and human aspects (resistance to change, uneven adoption across customer segments). The study also highlights that the post-Covid context and accelerated digital transformation require banks to continually adapt their governance, information systems, and training practices. AI thus appears to be a major strategic lever for strengthening banks' operational resilience, provided it is accompanied by appropriate organizational preparation.
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