AML for Cryptocurrency: Combining Blockchain Analytics with Real-Time Transaction Monitoring

The current cryptocurrency AML (anti-money laundering) landscape is dominated by Blockchain Analytics Tools (BATs) like Chainalysis, Scorechain or Elliptic. Although their capabilities are undeniably impressive, they are not sufficient for comprehensive AML.
In this whitepaper, Deloitte proposes the combination of BATs with AML transaction monitoring solutions, which they believe will lead to more effective AML compliance for cryptocurrency firms.
Limitations in how crypto firms detect money laundering
Deloitte identifies three key limitations that cryptocurrency firms face in relying on BATs to detect money laundering:
- End-to-End Fiat & Crypto Monitoring: BATS often lack the ability to track the exchange of fiat money into cryptocurrency and vice versa – a critical aspect of money laundering schemes.
- Pattern Analysis: BATs usually cannot identify suspicious transactional or behavioral patterns beyond simplistic rule-based scenarios, which is a key regulatory requirement and a necessity for identifying money laundering.
- Indirect Risk Scoring: BATs often assign indirect risk scores, as only a limited number of blockchain addresses are directly connected to identified crimes. Indirectly scored addresses often leave analysts with too much room to decide whether to file a Suspicious Activity Report (SAR) or not.
These limitations result in:
- Low detection rates (and thus an increased risk of being misused for money laundering)
- Technical shortcomings in complying with money laundering laws and regulations
- Inefficiencies in alert clearing processes and high numbers of false positives. This causes operators to spend a considerable amount of time on hard-to-decide alerts – which are ultimately unproductive.
How can crypto firms combine BATs with AML Transaction Monitoring?
The constraints listed above require BATs to be complemented with AML transaction monitoring solutions. Together, a combination of BAT and crypto-ready AML transaction monitoring solutions can overcome the shortcomings.
- Combining Fiat and Crypto Transactions - for effective risk management, monitoring systems should link fiat and crypto transactions to display overall customer behavior, e.g., based on a customer or account ID. This is particularly important at crypto exchanges, which have data available about both types of transactions.
- Analysis of Complex Transaction Patterns - it is imperative to recognize known (yet unidentified) intricate money laundering behavioral patterns. Although modern BATs allow rule creation, they are mostly confined to simple and usually one-dimensional criteria, like amount thresholds. More complex rule sets or AI models – as seen in Hawk's platform – allow operators to uncover complex suspicious behaviors such as money muling, account passthrough, and other common money laundering techniques.
- Inclusion of Customer Risk Data - modern AML transaction monitoring solutions provide for a combined view of static Know-Your-Customer (KYC) data and dynamic transactional data. The connection between customer and transaction data is even more critical in cryptocurrency, due to the pseudonymity of blockchain transactions.
Read more in the full white paper
To learn more about how Hawk can enable cryptocurrency firms to improve their AML capabilities, contact us today.