In the age of DarkNetMarkets proliferation, combatting money laundering has become even more complicated. Constantly evolving technologies add a new layer of difficulty to already intricated schemes of hiding the cryptocurrency’s origin. Considering the latest development of cryptocurrency- and blockchain-related use cases, this study aims to scrutinize Italian and Russian antimoney laundering regulations to understand their preparedness for a new era of laundering possibilities.
One of the most recommended ways to buy and sell cryptocurrencies for illegal drug trade on DarkNet was discovered using machine learning, i.e. natural language processing and topic modeling. This study compares how current Italian and Russian laws address this technique.
Despite differences in cryptocurrency regulation, both the Italian Republic and the Russian Federation fall behind on preventing cryptolaundering.
The main contributions of this paper: consideration of noncustodial wallet projects and nonfungible token platforms through the lens of money laundering opportunities, comparison of Italian and Russian antimoney laundering regulations related to cryptocurrency, empirical analysis of the preferred method of trading/exchanging cryptocurrency for DarkNet illegal trade using machine learning techniques and the assessment of how Italian and Russian regulations address these money laundering methods.
