Gate News message, April 28 — Kyle Holder, a 73-year-old from New York, lost her entire $300,000 retirement savings to an AI-driven crypto investment scam that began in December 2024. After responding to an unsolicited WhatsApp message advertising a crypto investment course, she was connected with someone claiming to be a single mother named “Niamh” and a customer service representative. Using a classic “pig butchering” fraud tactic, the scammers helped Holder set up crypto wallets and initially showed fake gains to build trust. Over two months, she transferred $300,000 across 14 different wallets before discovering the fraud. The IRS Criminal Investigation New York Field Office traced those 14 addresses to five wallets funneling approximately $5 million stolen from multiple victims. Investigators believe the criminals used AI tools available on the dark web to scrape personal information and identify vulnerable targets.
The FBI’s Internet Crime Complaint Center received 453,000 cyber-related fraud complaints in 2025, with total losses reaching $21 billion. Cryptocurrency-related fraud was the costliest category, accounting for $11 billion in losses across 181,565 complaints. The FBI identified 22,364 complaints tied to AI tools, resulting in combined losses of $893 million. In a separate case sentenced on April 23, federal court in the Northern Mariana Islands sentenced Sze Man Yu Inos to 71 months in prison for a bitcoin wire fraud scheme targeting older women in Saipan, Guam, Washington, and California, with $769,355 in ordered restitution.
The New York City Department of Consumer and Worker Protection warns that common indicators of AI-driven scams include unsolicited contact, messages creating urgency, and demands for secrecy. The Federal Trade Commission emphasizes that any business requesting cryptocurrency payments is not legitimate, and guaranteed investment returns in crypto are a major red flag. Victims can report fraud through the FBI’s IC3 portal or the FTC’s Report Fraud website; early reporting improves chances of tracing stolen funds and identifying perpetrators.
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