Financial Crime World

The Use of Cryptocurrencies in Transnational Money Laundering Schemes

Introduction

A recent analysis of 12 cases of transnational cryptocurrency money laundering (ML) has shed light on the patterns and trends in the use of cryptocurrencies, including Bitcoin and alt-coins, as well as the role of currency exchanges in ML schemes. This article summarizes the key findings from this study.

Key Findings

Prevalence of Cryptocurrencies

  • Bitcoin is the most prevalent form of cryptocurrency: 9 out of 12 cases used Bitcoin to transfer illicit funds.
  • Diverse “alt-coins” are used frequently: Alt-coins were used 14 times across 12 cases, suggesting that they are a popular choice for ML due to their obscurity and lower regulatory scrutiny.

Role of Currency Exchanges

  • Currency exchanges are key components of ML schemes: In all 12 cases, cryptocurrency was used in the placement stage, layering stage or both, highlighting the importance of currency exchanges in facilitating ML.
  • Layering is a common technique: Cryptocurrency allows for easy movement of funds across borders and can be exchanged into other cryptocurrencies or fiat currencies, making it an ideal tool for layering illicit funds.

Functionality of Cryptocurrencies

  • Limited functionality of cryptocurrency: Only 3 out of 12 cases used only cryptocurrency in their ML scheme, while three quarters used a mix of cryptocurrency and fiat currency.

Support for Hypotheses

The analysis supports the following hypotheses:

H1: Use of Cryptocurrency is Common in Placement and Layering Stages

  • Cryptocurrency is useful for both stages due to its anonymity and ease of transfer across borders.

H2: Limited Functionality of Cryptocurrency

  • The inaccessibility of cryptocurrency in everyday life makes it less likely to be used as a method to return illicit funds to the criminal for legitimate use.

Conclusion

The study highlights the interconnectedness between legal and illicit economies, with ill-gotten cryptocurrency being accepted by legitimate exchanges and banks, real investments and businesses being stolen from, and fraudulent exchanges being operated in the same manner as their legitimate counterparts. Overall, the analysis provides insights into the use of cryptocurrencies in ML schemes and underscores the importance of understanding both licit and illicit markets to comprehend the industry as a whole.