Institutions have begun to take crypto seriously and have entered the space in numerous ways. As noted in a previous analysis, this has resulted in banks and fintechs looking at custody products and services for their clients.
However, as custodians of clients’ assets, banks must also ensure they are clean assets and stay compliant.
This is where on-chain analytics solutions have a huge role to play in understanding patterns in transactions to identify money laundering and other spurious activities within the cryptocurrency and digital assets space. According to a report by Chainalysis, over $14 billion of illicit transactions took place in 2021.
Therefore, it is critical to build the foundational infrastructure around Anti-Money Laundering (AML) to support the growing institutional appetite for digital assets. Before getting into various types of money laundering patterns that exist in crypto, let us understand what an on-chain analytics solution is.
What are on-chain analytics?
All transactions on public blockchains are visible to anyone. Analytics tools query these blockchains to help us understand trends in transactions. Platforms like Glassnode, Nansen and Dune analytics offer ways for retail audiences to see the flow of money in the ecosystem.
Using on-chain analytics, it is possible to see the net flow of Bitcoin (BTC) into crypto exchanges from private wallets. This typically happens when someone chooses to sell their Bitcoin on an exchange. The net outflow of BTC from exchanges, on the other hand, represents someone wanting to hold on to their Bitcoin. Both actions have implications on the price of the asset.
However, at an institutional level, on-chain analytics can help with identifying spurious transactions. Firms like Chainalysis, Elliptic and Coinmetric are critical for banks to build digital assets capabilities that are foundational as this asset class grows in significance.
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Banks already have mechanisms in place to check for money laundering and terrorist financing activities. Therefore, any digital assets-related AML solution must ensure alignment with a bank’s existing AML controls.
What are money laundering patterns?
There are patterns that banks must keep an eye on to spot money laundering and other illicit activities. Referred to as “typologies” in traditional AML frameworks, not all of them are unique to the digital assets industry. However, on-chain analytics solutions can proactively track them.
Layering
Layering involves converting one crypto into another or moving assets from one chain to another. It makes AML efforts incredibly harder if there are multiple small-sized transactions that are generally beyond the monitoring radars.
Layering can also involve blending crypto assets across different exchanges and sources, making it harder to trace back to the original source of the assets.
Money mules
A money mule is someone who receives crypto assets from a third party and sends it over to another party. Alternatively, they could withdraw assets as fiat cash and hand it over to someone else and receive a commission for this.
Money mules are typically used when criminal syndicates want to be anonymous yet keep their money flowing through the system.
Dusting
Dusting involves creating many small transactions across several wallets that trigger AML monitoring systems. These small transactions would clog the pipeline of AML support teams whose workload increases and make them overlook the illicit transaction that really needed their attention.
Wallet laundering
Wallets used by crypto users make it hard to trace owners. As a result, a money launderer could just hand over the custody (private keys) of their wallet with assets in it to another party. In turn, they would receive payment in crypto on another wallet, thereby making the two transactions seem completely unrelated.
Darknet transactions and mixers
The darknet is an overlay network on the internet that is accessible through special software and configurations. It has earned a reputation for hosting anonymous illicit activities like drugs and arms sales.
Many platforms have flagged crypto addresses from darknet users and marketplaces and do accept assets that are sent therefrom.
However, some illicit actors have taken to crypto mixing services like Tornado Cash to hide the providence of their crypto.
Tornado Cash scrambles crypto transactions in an attempt to anonymize assets that have entered the platform, hiding their point of origin. It has become so associated with perceived criminality that the United States Treasury’s Office of Foreign Assets Control sanctioned the platform in August, and many trading platforms will not touch coins that came from a mixing service.
How are banks addressing this issue?
The money laundering methods described above are not exhaustive. A recent report from Elliptic covers over 41 typologies (patterns) observed within the digital assets space.
So, given the myriad ways that illicit actors attempt to use digital assets for money laundering, how can banks react?
Robust Know Your Customer (KYC) standards are a good starting point when onboarding digital assets customers. However, proactive screening and transaction monitoring should be in place through on-chain analytics solutions.
These solutions can automate AML and sanction checks, identify address clusters associated with illicit activities, map the flow of digital assets across addresses to perform forensic analysis and monitor how assets are moved through activities related to dark-web markets, smart contract frauds, oracle hacks, cross-chain bridge hacks and more.
Furthermore, banks and fintech firms have ramped up their digital assets AML capabilities through partnerships with on-chain analytics firms, as the below graphic shows.
Even though Barclays began its journey with Chainalysis in 2015, this space really has taken off only in the last 18 months. Be it investments or partnerships, it is highly critical that before offering custody services, banks must put AML controls in place to ensure they are handling clean assets.
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More institutional capital has flown into the digital assets space in the last two years. At the same time, more innovative models have emerged in cross-chain bridges, decentralized finance, nonfungible tokens and transaction mixers.
In order to protect assets while innovating at breakneck speed, AML and transaction monitoring controls must be in place. That is essential to keep attracting more institutional capital into digital assets.