Published online by Cambridge University Press: 09 August 2023
INTRODUCTION
The current approach to tackling money laundering assumes that:
• all money launderers are the same, in the sense that all money launderers are criminals, and all criminals are money launderers; and
• all countries are the same, in the sense that, because crime is destructive, and because ML damages established industries, all countries are incentivized to tackle crime and ML.
In practice, however, we see very different types of launderer, in the sense that the money launderers in Deutsche Bank and those in IS have very different functions, motivations, dependence, sunk costs and vulnerabilities. In the same vein, we see very different responses to ML at the national level, in the sense that, whereas Germany invests in tackling ML, the Seychelles once actively encouraged ML, and publicly invited criminals to invest their illgotten gains there with the promise of immunity from prosecution.
In this chapter, we enrich the overview of money launderers described in Chapter 1, first by introducing a new taxonomy of money launderers, which identifies vulnerabilities in the ML chain, and then by introducing a taxonomy of ML countries, which explains why some countries fight ML, whereas others ignore it. Both discussions help us to understand who runs the laundry, and, more importantly, both discussions show the limitations of the current regulatory approaches to tackling ML.
A TAXONOMY OF MONEY LAUNDERERS
Distinguishing between types of criminal
Money launderers are criminals. Therefore, the academic literature, as described in Chapter 1, tends to treat the “criminal” – who generates “criminal proceeds” – and the “launderer” – who converts the dirty dollars into clean ones – as one and the same individual. This, we suggest, is a gross oversimplifi cation, as there are a number of important types of launderer, each with their own vulnerabilities. So, who launders?
Standard criminals
Standard criminal launderers are rational, profit-motivated individuals who generate criminal proceeds, for example by running guns or by selling drugs, and then self-launder the illegal proceeds that they generate. Criminal launderers are the standard launderer described in the ML literature.
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