The cornerstone of the modern approach to money laundering is to prevent illicit funds from entering the financial system. The rationale is understandable: if criminals won’t be able to use their money, they will have to eventually stop whatever they are doing and go get a 9 to 5 job.

However, after 20 years of ever tighter (and ever more expensive) AML regulations, the levels of organized crime, tax evasion, or drug use do not show any signs of decrease. At the same time, the basic right to privacy is being unceremoniously violated on an everyday basis, with each financial operation, no matter how tiny, being subject to extensive verifications and tons of paperwork. Check Part 1 of this story for details and numbers.

This prompts a question: should we reconsider our approach to the AML strategy?

Two years ago, a fintech author David G.W. Birch wrote an article for Forbes, reflecting on the main principle of AML – gatekeeping. The key thought could be resumed as “instead of trying to prevent criminals from getting into the system, we let them in and monitor what they are up to.”

Indeed, why do we erect expensive AML gates and force the bad guys to turn to hardly traceable cash or works of art, while we can simply let them in and follow the money to hunt them down? To do so, we can use both the existing reporting system within traditional finance and the on-chain analytics within the blockchain. However, while the former is more or less understandable, the latter is still a mystery for most people. What’s more, politicians and bankers regularly accuse crypto of being a tool for criminals, tax evaders, and all sorts of Satan worshipers, further exacerbating the misunderstanding.

To shed more light on this matter, we need to better understand how on-chain analytics works. It is not an obvious task though: blockchain analysis methods are often proprietary and analytics companies sharing them could risk losing their business edge. However, some of them, like Chainalysis, publish rather detailed documentation, while the Luxembourgish firm Scorechain agreed to share some details of their trade for this story. Combining this data can give us a good idea of the potential and limitations of on-chain analytics.

How does on-chain analytics work?

The blockchain is transparent and auditable by anyone. However, not everyone is capable of drawing meaningful conclusions from the myriads of datasets it is composed of. Gathering data, identifying the entities, and putting the conclusions into a readable format is the specialty of on-chain analytic firms.

It all starts with getting a copy of the ledger, i.e. synchronizing the internal software with the blockchains.

Then, a tedious stage of mapping begins. How can we know that this address belongs to an exchange, and this one – to a darknet marketplace? Analysts employ all their creativity and resourcefulness to try and de-pseudonymize the blockchain as much as they can. Any technique is good as long as it…

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