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Two Scammers Arrested in $73 Million "Pig Butchering" Scheme
Key Takeaways
- US authorities arrest two individuals for a $73 million crypto laundering scheme;
- The funds were laundered through "pig butchering" scams, involving building victims' trust, persuading them to invest, and disappearing with the money;
- The two each face up to 140 years in prison if convicted.
Two individuals, Daren Li and Yicheng Zhang, have been arrested for allegedly orchestrating a massive scheme of laundering over $73 million.
The US Department of Justice (DOJ) announced their arrests on May 17, with Li being apprehended at Atlanta airport on April 12 and Zhang detained in Los Angeles on May 16.
An indictment unsealed in a California court outlines their roles in a transnational network that laundered millions from "pig butchering" scams.
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"Pig butchering" scams involve fraudsters building victims' trust, persuading them to invest substantial amounts, and then vanishing with the funds.
The defendants allegedly directed co-conspirators to set up US bank accounts under the names of shell companies. Victims were deceived into transferring millions into these accounts, which were then used to launder the illicit proceeds.
The DOJ detailed:
The fraud scheme involved more than $73 million laundered through US financial institutions to bank accounts in The Bahamas, and converted to the virtual asset USDT, or Tether. A cryptocurrency wallet involved in the scheme received more than $341 million in virtual assets.
Li and Zhang face charges of conspiring to launder money and six counts of international money laundering. If convicted, they could each face up to 20 years in prison per count, potentially totaling 140 years.
The arrests of the duo represent a major step in fighting crypto-related crime and demonstrate the authorities' commitment to cracking down on such illegal activities.
Another recent crypto theft involved a former employee of Pump.fun, a memecoin creation platform, who stole around $1.9 million in Solana (SOL) from the platform.