Beyond blacklists: alternative approaches to rating countries at high risk of money laundering

The paper addresses the issue of how the risk of money laundering (ML) at country level can be measured. A number of official blacklists and grey lists exist, issued by national and international organisations such as FATF, European Commission or US INCSR, which rank countries according to their (presumed) ML vulnerabilities and regulatory weaknesses. But these lists may be biased by geo-political influence, and are not supported by empirical evidence. This paper suggests a new approach for operationalising and assessing the risk that a country may attract illicit proceeds. It develops a composite indicator of ML risk, which builds on the inputs from previous criminological literature. It then validates the indicator against observed evidence by employing a unique dataset of 2818 individuals involved in ML cases. The analysis shows a strong correlation between the new indicator and empirical evidence of ML, but a null (and sometimes negative) correlation with official AML blacklists. The work advances the current understanding of ML determinants, and empirically demonstrates the importance of proximity, opacity and security in driving illicit proceeds. It proposes that a unique, and universally valid, measure of high-risk countries is not appropriate for explaining a relational phenomenon like money laundering. It also provides empirical ground that may help to revise the current AML blacklisting process, and minimise its unintended consequences such as de-risking.