Cleaning mafia cash: an empirical analysis of the money laundering behaviour of 2800 Italian criminals

Despite an extensive anti-money laundering (AML) legislation worldwide and an increasing media attention, fostered by journalistic leaks such as Panama Papers or FinCEN Files, empirical knowledge on how criminals launder their illicit proceeds is still scarce, and limited to a couple of empirical studies in few countries. All these existing works have shown that money laundering (ML) strategies are often less sophisticated than they are depicted in the political and media debate. To contribute to the empirical knowledge of ML behaviour, and test this suggestion, the present study carries out an analysis of the ML activities related to 2818 Italian offenders included in the money laundering section of the LexisNexis’ WorldCompliance database. Through a quantitative content analysis of textual information related to each offender’s profile, it highlights the countries in which ML was conducted, the methods (or ‘typologies’, in FATF terms) employed, the modi operandi, the assets seized, the business sectors involved and the characteristics of the ML offenders. The results confirm that criminals, for laundering their money, tend to prefer Italy or jurisdictions which are close (geographically and culturally) to Italy; that they do not employ sophisticated ML strategies, and that they rarely employ more than one method at the same time. Tangible assets (first of all real estate and registered vehicles) are more frequent than financial assets. Finally, differences exist between the laundering by mafia-related ML offenders and non-mafia ones. The paper provides empirical ground to progress in the knowledge of how ML offenders behave, and supports the idea that criminals, when cleansing their proceeds, do not act as firms or households, but may be driven by other constraints and utility functions.