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.
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
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