Risk management and performance in the age of disruptive technologies: the case of Moroccan customs

Authors

  • Hicham ATTAOUI Faculty of Law, Economics and Social Sciences of Souissi, Mohamed V University, Rabat, Morocco

Keywords:

Risk Management, Customs, Performance, Digital Transformation, Disruptive Technologies.

Abstract

Risk analysis and management is undoubtedly the primary tool available to customs administrations today for balancing effective oversight with the smooth flow of trade and, thereby, achieving performance objectives. While the advent of digital technology has enabled significant advances in this regard, the emergence of so-called disruptive technologies, such as predictive analytics and artificial intelligence for example, has opened the door to other possibilities that are both new and extraordinary.

That said, while numerous studies have analyzed the effect of the digital transition on performance in general, the impact of digital-based risk management in particular remains largely unexplored.
Based on this observation, the objective of this article is to analyze the effect of risk management on performance within the context of the digital transition in Morocco’s public sector.

From a methodological standpoint, this is a confirmatory case study conducted within the framework of a mixed methods approach and based on semi-structured (qualitative) interviews, a documentary analysis (quantitative) based on a selective literature review, and direct observation. Indeed, following the IMRAD model and drawing on official sources in this field (WCO, WTO, UNCTAD, ISO, ADII, etc.) as well as articles related to customs risk management, particularly in the Moroccan context, this article seeks to confirm the positive impact of such risk management on certain key indicators of customs performance, specifically, processing time and revenue, while highlighting the prospects for the evolution, or even transformation, of customs control in particular and, by extension, public policy in general.

JEL Classification : H83, H26, O33.

Paper type : Empirical Research.

Published

2026-08-20