The United States Department of Justice has arrested two Chinese nationals implicated in a $73 million money laundering operation. According to a May 17 announcement, the suspects funneled illicit funds through multiple U.S. financial institutions and subsequently converted the money into the stablecoin USDT.
The accused, Daren Li, a dual citizen of China and St. Kitts and Nevis, and his associate, Yicheng Zhang, a Chinese national residing in Temple City, California, orchestrated a sophisticated money laundering network. This network laundered millions of dollars obtained through “pig butchering” crypto scams, a fraudulent scheme where perpetrators gain the trust of victims and persuade them to invest large sums in fake ventures before absconding with the funds.
Li and Zhang allegedly directed their accomplices to open multiple U.S. bank accounts under the names of various shell companies. Victims were instructed to transfer millions into these accounts, which were meticulously monitored by the duo. Once the funds were deposited, they were moved to different domestic and international bank accounts.
Regulatory authorities identified several suspicious accounts at Deltec Bank in The Bahamas, with at least one operated under Li’s financial guidance. These funds were converted into USDT, a stablecoin that has become increasingly popular among scammers.
The DOJ revealed that a cryptocurrency wallet involved in the scheme received over $341 million in virtual assets. Li was apprehended at Atlanta’s airport in Georgia on April 12, and Zhang was arrested in Los Angeles on May 16. Both face six counts of international money laundering and conspiracy to launder money. If convicted, they could face up to 20 years in prison for each count.
Pig butchering scams have reportedly swindled victims out of over $75 billion worldwide. In response to rising complaints, the Brooklyn District Attorney’s Office recently dismantled a similar operation, and in 2023, the DOJ froze $9 million in USDT stolen from 70 victims through these scams.
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