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Predictors for compliance with anti-terrorist financing standards

Erik Joosten (Royal Air Force, Breda, The Netherlands)
Marion Bogers (Netherlands Defence Academy, Breda, The Netherlands)
Robert Beeres (Netherlands Defence Academy, Breda, The Netherlands)
Robert Bertrand (Netherlands Defence Academy, Breda, The Netherlands)

Journal of Money Laundering Control

ISSN: 1368-5201

Article publication date: 7 May 2019

235

Abstract

Purpose

The purpose of this paper is to identify and test predictors for countries to comply with the Financial Action Task Force’s (FATF) anti-money laundering and terrorist financing recommendations.

Design/methodology/approach

The authors conduct a quantitative study to explore which factors predict compliance of countries. They include the compliance scores of 196 countries.

Findings

The results of a forward stepwise regression analysis show that a country’s wealth, measured as gross domestic product (GDP) per capita, is the most important predictor for compliance. This result supports earlier academic work about predictors for compliance (Simmons, 1998; Giraldo and Trinkunas, 2007; Whitaker, 2010). The other factors identified suffering from terrorist attacks, relative financial market dominance, tourism sector and the degree of democracy do not explain additional variance in compliance.

Practical implications

This research sheds light on compliance as a concept. For policymakers, accountants, companies and governments, it is important to understand why compliance occurs and why not.

Originality/value

The empirical results indicate that, in contrast to common belief, countries that suffer more from terrorism are not more compliant. Moreover, the rate of democracy, a relative dominant financial market and a strong tourism sector do not stimulate compliance with anti-terrorist financing standards.

Keywords

Citation

Joosten, E., Bogers, M., Beeres, R. and Bertrand, R. (2019), "Predictors for compliance with anti-terrorist financing standards", Journal of Money Laundering Control, Vol. 22 No. 2, pp. 257-269. https://doi.org/10.1108/JMLC-02-2018-0011

Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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