Mapping hawala risks around the world: the use of a composite indicator

ABSTRACT

The aim of this study is to map the landscape of risk faced by each country with respect to the presence and prosperity of informal fund transfer (IFT) systems. This study constructed a composite indicator to assess IFT risks of the 121 countries. The IFT risk that this study intended to gauge is not crime risk(s) that IFT systems cause but risk that IFT systems operate and prosper in given countries. The IFT risk indicator was developed with eleven variables extracted from public domain datasets regarding migration, access to formal financial institutions, AML/CFT measures, and societal attitudes towards informality. Routine activity theory was used to derive the factors associated with IFT risk. This study found that the level of IFT risk is associated with their levels of economic development. The main advantage of the IFT risk indicator is that it can gauge ‘nuanced’ differences in IFT risks among countries.

KEYWORDS:

• Informal fund transfer system
• hawala
• remittance
• composite indicator
• routine activity theory

Acknowledgments

We thank the four anonymous reviewers whose comments and suggestions helped improve and clarify this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Former U.S. Treasury secretary Larry Summers in his Financial Times article pointed out three events that gave major shocks to the global system in the 21 century: the 2001 terror attacks, the 2008 financial crisis, and the COVID-19 crisis.

2. Crypto assets are used as a remittance vehicle not only by remitters themselves but also by IFT brokers (Metzger et al., 2019).

3. IFT systems overtly operate in some countries, such as China, Somalia, and the U.A.E (Passas & Maimbo, 2008; Varese et al., 2019).

4. Financial Action Task Force (FATF) provides the definition of risk – a function of threat, vulnerabilities, and consequences – for the purposes of assessing national money laundering and terrorist financing risk (FATF, 2013b). This study did not adopt the FATF’s definition of risk as it is somewhat narrow given that it focuses on money laundering and terrorist financing risk. Nevertheless, among the eleven variables analysed with respect to IFT risk in this study, most of them relate to vulnerabilities to IFT risk. The variables regarding ‘migrants’ can be construed as ‘threat’ that leads to IFT activities.

5. With respect to the legitimacy of IFT systems, many studies on IFT systems discern legitimate use from illegitimate use of IFT systems. This study, however, did not seek to distinguish between them as it is nearly impossible to capture whether IFT brokers stick to ‘clean’ remittances and separate criminal proceeds from the funds that they take from their customers (El-Qorchi et al., 2003; Passas, 2005a).

6. Given that IFT systems emerged in ancient times to avoid the inconvenience and risk incurred from physically transporting money between merchants from different regions of MENA and South Asia, their then primary customers of IFT systems were merchants engaging in long distance trade (Schaeffer, 2008). Most of the current users are migrants, even though some merchants still use IFT systems to transfer payments abroad (FATF, 2013c). Many studies (Razavy, 2005; Thompson, 2008) show that migrants from MENA and South Asia are more familiar with IFT systems because of the historical and cultural context.

7. IFT systems may pose a threat to the governments as well as formal remittance systems. As IFT systems are illegal businesses in most countries, the governments of each country may miss out on taxes on remittances and the illegal businesses (El-Qorchi,). Some IFT systems may help tax evasion of traders who undervalue their imported goods by transferring payments for imported goods to exporters without traces. However, the damage to the government coffers caused by IFT systems may not be significant. Even remittances via formal remittance systems are not normally taxed in receiving countries. Many professionals express concern over some sending countries’ attempts to tax outward remittances (Ratha et al., 2017). IFT systems are normally small businesses that are exempted from taxation. Traders’ tax evasion via IFT systems tends to be addressed in light of AML efforts.

8. Although more recent datasets for migration, financial inclusion, and attitude towards informality were available, this study had to use the datasets of 2013 or 2014. When the data analysis for this study was conducted in 2018, the FATF’s fourth round mutual evaluations which started in 2014 were still ongoing. This study thus analysed 135 countries’ mutual evaluation reports of the third round which ended in 2014.

9. In the coding process, this study assigned 4 to ‘compliant’, 3 to ‘largely compliant’, 2 to ‘partially compliant’, 1 to ‘non-complaint’, and 0 to ‘not applicable’.

10. The 121 countries were not randomly selected samples but the study population per se. This study did not conduct a significance test given that ‘significance tests presuppose that the units being studied are sampled randomly from the populations to which they belong’ (Cowger, 1984, p. 365). Although some studies have conducted significance tests with populations (Leahey, 2006), this study holds the view that ‘significance tests are not only inappropriate when applied to a total population but are unnecessary since the probable relation of a sample and a population is defined as unity when they are the same’ (Berk et al., 1995; Cowger, 1984, p. 366).

11. Figure 2

12. Squared component loadings used as weights are produced by dividing squared component loadings by the variances of the original data explained by each principal component (OECD and JRC, 2008). For instance, 0.023 = (0.340 ^ 2) / 5.135, which is the proportion of the variance of the first principal component explained by the variable percentage of possession of a debit card.

13. PCA weighted IFT risk indicator = 0.210 z_emigrant + 0.279 z_immigrant + 0.020 z_account + 0.023 z_debit + 0.118 z_atm + 0.294 z_MVTSrecommedation + 0.400 z_overallrecommendation + 0.036 z_propertyrights + 0.037 z_IPR + 0.035 z_policing + 0.026 z_auditing.

14. In order to examine the impacts of individual variables on a composite indicator, the robustness of the indicator is assessed in a way of excluding each variable one by one. This study assessed the robustness of the IFT risk indicator by excluding not only individual variables but also each group of variables (e.g. variables regarding financial inclusion) from the IFT risk assessment models (R_equal ≥ 0.963 and R_pca ≥ 0.706).

15. The IFT risk rankings according to different weighting and aggregation methods are graphed in Annexe 2.

16. Table 7.

17. The U.A.E. is known as a hawala settlement hub (Ballard, 2005; Malit et al., 2005; accordingly ranked 49 by the PCA weighted indicator). Nevertheless, the U.A.E. was assessed as having a relatively low IFT risk level (i.e. ranked 91 by the equal weighted indicator). This counter intuitive assessment outcome seems to result from the underestimation of the U.A.E.’s level of informality and an (relative) overweight on it in the equal weighted indicator. The U.A.E.’s business friendly environments seem to have a positive impact on the assessment of its level of informality (Gatti et al., 2014; Loayza et al., 2005).

18. The two of the five datasets used to construct this indicator – the financial inclusion dataset of the IMF and the AML/CFT dataset of the FATF and its associates – unfortunately did not include data of some developing countries, including Somalia. This may imply that such countries do not have competence to collect and share financial inclusion data with international organisations and do not have instruments regarding AML/CFT; as a result, they may have high IFT risks.

Additional information

Notes on contributors

Chang Ryung Han

Chang Ryung Han is Director of Investigation Division I, Seoul Main Customs, Korea Customs Service, Republic of Korea. His research interests include illicit trade, illegal markets, and informal economies.

Bastiaan Leeuw

Bastiaan Leeuw is a policy advisor and researcher at the Department of Safety of the City of The Hague, The Netherlands. In this advisory role, he specialises in crime prevention and the application thereof in an urban and local setting, including the approaches to tackling organised crime and corruption.

Hans Nelen

Hans Nelen is Professor of Criminology, Faculty of Law, Maastricht University, The Netherlands. He has conducted research on a variety of criminological subjects, including police, drugs, corruption, fraud, organized crime, corporate and occupational crime.