A Vast New Data Set Could Supercharge the AI Hunt for Crypto Money Laundering

One task where AI tools have proven to be particularly superhuman is analyzing vast troves of data to find patterns that humans can't see, or automating and accelerating the discovery of those we can. That makes Bitcoin's blockchain, a public record of nearly a billion transactions between pseudonymous addresses, the perfect sort of puzzle for AI to solve. Now, a new study--along with a vast, newly released trove of crypto crime training data--may be about to trigger a leap forward in automated tools' ability to suss out illicit money flows across the Bitcoin economy. On Wednesday, researchers from cryptocurrency tracing firm Elliptic, MIT, and IBM published a paper that lays out a new approach to finding money laundering on Bitcoin's blockchain. Rather than try to identify cryptocurrency wallets or clusters of addresses associated with criminal entities such as dark-web black markets, thieves, or scammers, the researchers collected patterns of bitcoin transactions that led from one of those known bad actors to a cryptocurrency exchange where dirty crypto might be cashed out.