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The comparative analysis of regulations in the Italian Republic and the Russian Federation against cryptolaundering techniques

The comparative analysis of regulations in the Italian Republic and the Russian Federation... 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.Design/methodology/approachOne 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.FindingsDespite differences in cryptocurrency regulation, both the Italian Republic and the Russian Federation fall behind on preventing cryptolaundering.Originality/valueThe 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Money Laundering Control Emerald Publishing

The comparative analysis of regulations in the Italian Republic and the Russian Federation against cryptolaundering techniques

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References (55)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1368-5201
eISSN
1368-5201
DOI
10.1108/jmlc-01-2022-0016
Publisher site
See Article on Publisher Site

Abstract

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.Design/methodology/approachOne 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.FindingsDespite differences in cryptocurrency regulation, both the Italian Republic and the Russian Federation fall behind on preventing cryptolaundering.Originality/valueThe 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.

Journal

Journal of Money Laundering Control – Emerald Publishing

Published: May 30, 2023

Keywords: Money laundering; Cryptocurrency; DarkNetMarkets; Drugs; Machine learning

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