Cryptocurrencies: an unconventional challenge to the AML/CFT regulators?

Abstract

Purpose – The purpose of the article is to look closely at the phenomenon of the cryptocurrencies such as and bitcoin to identify their potential vulnerabilities to money laundering and financing of terrorism. It also explores their specific characteristics relevant to ML/FT risks. Design/methodology/approach – Using digicash and bitcoin protocols as primary cases for centralized and decentralized cryptocurrencies we analyse their characteristics against cash and cashless payments. We also draw on “bundle of attributes” that may define their attractiveness for common public or criminals. Findings – Our research shows that characteristics of the cryptocurrencies are unlikely to make them popular among the consumers, as demand for anonymity seems to be overrated. Cryptocurrencies can also be classified as payment instrument rather than private currencies; therefore their embededdness in the financial system minimizes the ML/FT risks. Research limitations/implications – Some decentralized cryptocurrencies operate within informal communities. Therefore, relations within these communities are constantly evolving and need to be monitored further. Practical implications – The paper provides an insight into the mechanics and classification of cryptocurrencies as payment instruments. Place of cryptocurrencies within the broader payment ecosystem defines their potential vulnerabilities to being abused by the criminals. Originality/value – The paper fills the gap in research on cryptocurrencies as payment instruments rather than private currencies and also provides an overview of their relevance for the Anti-money laundering and combating financing of terrorism (AML/CFT) regime.

The impact on people’s holding intention of bitcoin by their perceived risk and value

“…(4) Legal and policy risk (PR t, 4 ): Government would impose regulations or policies putting Bitcoin under surveillance since the money laundering and terrorism financing can have possible involvement in the transaction and speculation, and its uncontrolled supply or exchange. As suggested by Harwick, the primary practical barrier of Bitcoin is its purchasing power volatility that originates from a rigid money stock with extensive volatility in demand (Gandal, Hamrick, Moore, & Oberman, 2018;Vovchenko et al, 2017;Chuen, 2015;Yermack, 2015;Dostov & Hust, 2014; U. S. Department of the Treasury and Financial Crimes Enforcement Network, 2013; European Central Bank, 2012).…”

“…A number of scholars, as Chuen (2015), Dostov and Hust (2014), Polasik, Piotrowska, Wisniewski, Kotkowski, and Lightfoot (2015), Sauer (2016), Vovchenko et al (2017), Wang and Vergne (2017), considered the mechanics and classification of Bitcoin as the electronic currency or payment instruments. Particularly, Harwick (2016) termed Bitcoin not just as a medium of indirect exchange, but also as the supplanter of the existing regime of fiat currencies because of its portability, durability, divisibility, security, liquidity, salability, and stability of the value.…”

Analysis of Cryptocurrencies Price Development

“…Dostov and Shust (2014) dealt with the anonymity of transactions made using Bitcoin and issues raised by this anonymity for the application of the rules of Anti-money laundering and combating financing of terrorism.…”

Open and Big Data Management and Innovation

“…Descôteaux [50] holds the opinion that for the future development of Bitcoin, an appropriate legal and regulatory framework is extremely important in order to overcome the existing risks and threats slowing down the adoption of cryptocurrency. The literature also discusses the drawbacks and disadvantages of Bitcoin, such as the possibility of money laundering [51][52][53][54], trade in various illegal goods [55,56], potential financing of terrorism [51,57], Bitcoin loss or theft [21,58], and tax evasion or enormous volatility [27,43,59]. These aspects were also mentioned by our interview partners.…”

“…Taking in consideration that actor has an interest and a business model to use the data, the last type of dimensions is technology. The scientific and practical literature[7,51] identified six types of technology that can be used: (i) Computer programming languages, (ii) Data Visualization, (iii) Geography Coding and Mapping, (iv) Networking Analysis, (v) Business Intelligence and (vi) Data Mining.…”