An International Benchmarking of Tunisian Banks in Terms of Risk Management Using Data Envelopment Analysis (DEA) with Undesirable Variables

Anis Ezzeddine () and Said Gattoufi
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Anis Ezzeddine: Universite´ de Tunis, Institut Supe´Rieur de Gestion de Tunis, Laboratoire SMART LR11ES03
Said Gattoufi: Universite´ de Tunis, Institut Supe´Rieur de Gestion de Tunis, Laboratoire SMART LR11ES03

A chapter in Advanced Data Analytics, Machine Learning and AI in Business, 2026, pp 530-548 from Springer

Abstract: Abstract This paper aims to root business analytics in operations research by providing epistemological analysis about the inception of this new discipline. It suggests that this capstone discipline is the result of a paradigm shift. The paper suggests a formal methodology to conduct business analytics study. The suggested methodology, Intelligent Data Enabled Analytics (IDEA), is exemplified through the international benchmarking of Tunisian banks in terms of risk management efficiency using Data Envelopment Analysis with undesirable variables. The results show the superiority of Tunisian private banks in terms of risk management efficiency over their public counterparts. Moreover, the results indicate that European banks, particularly German, have higher level of efficiency in handling banking risks, by reference to he four risk management ration suggested in Basel III standards.

Keywords: Paradigm shift; banking risk management; DEA; efficiency; Bench-mark; Tunisia (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-032-23493-3_32

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DOI: 10.1007/978-3-032-23493-3_32

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