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The Know Your Customer (KYC) process is a fundamental component of anti-money laundering regulations in jurisdictions around the world. However, with the rise of disruptive blockchain technology and increased global use of cryptocurrencies, criminals have been able to develop new money laundering methodologies that allow them to use digital assets to conduct transactions quickly and anonymously.
The emergent threats of the cryptocurrency landscape have prompted governments and regulators to increase their focus on digital assets: in 2019 the Financial Action Task Force (FATF) extended its KYC-focused Travel Rule to cryptocurrency service providers and, in September 2020, released advisory guidance to member-states on the red flag indicators of money laundering using digital assets. Financial penalties are also being issued: in October 2020, the Financial Crimes Enforcement Network (FINCEN) imposed a $60 million fine on the founder of the Helix and Coin Ninja Bitcoin mixing services for violating AML rules.
Given the risks and the potential for significant penalties, firms that deal with cryptocurrency or offer other types of digital asset services must adapt their KYC process to manage new challenges. In practice, this means integrating technological automation to handle vast amounts of AML data, react to emerging criminal typologies, and continue to deliver compliance.
In principle, the KYC compliance challenge associated with digital assets remains the same as fiat currencies: firms must be able to establish the identities of customers at onboarding, and then monitor and understand their customers’ financial behavior on an ongoing basis. In more detail, conventional KYC involves:
However, the speed with which digital asset transactions take place and the anonymity benefits they offer increase their AML risk and complicate the KYC process. Adding to the complexity of the AML challenge is a lack of understanding of the cryptocurrency space from authorities and financial institutions and the broad regulatory divergence between jurisdictions which allows criminals to exploit blindspots and disparities. FATF’s list of ‘red flag’ digital asset money laundering typologies revealed a range of specific risks including:
Customer experiences: Beyond addressing the specific risks of digital asset transactions, firms must also consider as a priority the experience of their customers during onboarding and when using their services. The more onerous the AML measures, the more likely it is that customers experience friction at onboarding and throughout the business relationship, and either turn to competitors or retreat from engaging in digital asset services.
To meet the challenge of digital asset AML/KYC compliance without negatively affecting the customer experience, firms must seek to deploy a technological solution. In practice, that means automating the collection and analysis of vast amounts of data from a range of global sources, while building enhanced speed and efficiency into AML measures to reduce administrative friction.
In data-driven digital asset environments, manual KYC is an inadequate response to the threat presented by money laundering typologies. By automating the KYC process, firms can address digital AML compliance risks and optimize customer experiences. Specific advantages of KYC automation include:
FATF member states require financial institutions to put risk-based AML programs in place which means they must deploy KYC measures proportionate to the risk that customers present. The typologies that characterize digital asset money laundering and other types of fintech crimes require firms to move away from the post-analysis of data and instead be proactive about AML, working to detect and prevent money laundering threats, and submit suspicious activity reports to the relevant authorities, quickly.
Accordingly, smart technology, and specifically artificial intelligence and machine learning, should be a crucial component of a pro-active AML program. Artificial intelligence and machine learning systems not only add speed and accuracy to conventional AML processes, but enable firms to harness the vast amount of unstructured electronic data they collect to enhance their KYC performance, reducing administrative noise and false positives, spotting suspicious divergences in customer behavior, and reacting to emerging criminal methodologies and new compliance requirements as quickly as possible.
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Originally published 06 January 2021, updated 19 March 2024
Disclaimer: This is for general information only. The information presented does not constitute legal advice. ComplyAdvantage accepts no responsibility for any information contained herein and disclaims and excludes any liability in respect of the contents or for action taken based on this information.
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