Impersonation Scams Surge 1400% as AI Fuels Crypto Fraud Now

One high‑profile case involved scammers impersonating Coinbase, resulting in nearly $16 million stolen from victims; the theft is the subject of an indictment by the Brooklyn District Attorney’s office, and the accused has pleaded not guilty. The report notes many schemes combine impersonation with other tactics such as pig‑butchering, social engineering and wallet‑focused fraud.

The study highlights growing use of artificial intelligence and specialized vendor tools, which have contributed to what the authors call an “industrialization of fraud.” The analysis found scams using AI were about 4.5 times more profitable and showed higher daily revenue and transaction volume. “These metrics suggest both higher operational efficiency and potentially broader victim reach,” the report says.

Chainalysis recommends increased prevention measures, including wider adoption of real‑time fraud and mule detection systems and more resources for cross‑border law enforcement coordination and support in low‑capacity jurisdictions. The authors caution there are no simple solutions, noting “There are no silver bullets to tackling such entrenched, industrial-scale scamming activity and to be effective, a multi-pronged response is required.”

A graphic accompanying the findings was shared by Chainalysis. Additional context is available in the editorial policy.