Assessing the impact of FinTech on bank efficiency: insights from the MENA region

Purpose The main goal of this paper is to investigate the impact of FinTech adoption on the cost and profit efficiency of Middle East and North Africa (MENA) banks, taking advantage of the region’s recent regulatory reforms, financial modernization policies, and digital inclusion initiatives that provide a timely and relevant context for the study. Design/methodology/approach Using a panel dataset of 116 banks across 12 MENA countries from 2014 to 2023, the study employs a one-step Stochastic Frontier Analysis (SFA) to jointly estimate efficiency scores and their determinants, allowing for a robust assessment of how digital innovations influence operational performance. Findings The findings show that banks adopting digital payment technologies and mobile transactions achieve higher cost and profit efficiency. Positive effects are also associated with online purchasing, while CARD and ATM usage are linked with increased operational costs and lower profit efficiency. The analysis further reveals that FinTech adoption's benefits are most pronounced in banks leveraging mobile-based solutions, underscoring the importance of targeted digital strategies to enhance banking performance in the MENA region. Research limitations/implications The findings offer practical guidance for policymakers and banking executives by emphasizing the need for supportive regulatory frameworks, investment in digital infrastructure and strategic prioritization of FinTech channels that maximize efficiency. The study also provides insights into balancing innovation adoption with cost and operational management. Originality/value This study adds to the literature in three key ways: first, by providing comprehensive empirical support on the impact of various FinTech innovations on bank efficiency in the MENA region; second, by integrating multiple digital channels to identify their distinct effects on cost and profit efficiency; and third, by employing a robust single-step stochastic frontier approach that jointly estimates efficiency scores and their determinants, offering deeper insights.