Crypto fraud surged to $11.4B in 2025, driven by AI scams and investment schemes, with elderly victims hardest hit.
Crimes involving crypto reached a new peak in 2025, with losses climbing to record levels across the United States. Data from the Federal Bureau of Investigation paints a clear picture of growing financial damage tied to digital assets. Older Americans faced the heaviest burden, while investment scams continued to dominate activity. Rising use of artificial intelligence and crypto ATMs also shaped the threat environment.
Seniors Lose $4.4B to Crypto Scams in 2025, FBI Data Shows
Figures from the Internet Crime Complaint Center show $11.366 billion in crypto-linked losses during 2025. That accounts for more than half of the $20.9 billion recorded across all internet crimes. Complaint volume reached 181,565 cases, marking a 21% increase from the previous year. Average losses per victim stood at $62,604, reflecting the scale of individual exposure.
Broader cybercrime activity also expanded. IC3 logged more than one million complaints for the first time in its history. Total losses rose 26% year-over-year, up from $16.6 billion in 2024. Growth across categories signals a widening attack surface, driven by digital adoption and evolving scam tactics.
Older Americans again accounted for the largest share of crypto-related losses. Individuals aged 60 and above filed 44,555 complaints and reported $4.4 billion in losses. That figure represents a sharp increase from the $2.84 billion recorded in 2024.
Across all cybercrime types, seniors lost $7.8 billion, with many cases involving high-value transfers. More than 12,000 victims in this age group reported losses exceeding $100,000 each.
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Investment scams remained the primary driver of losses. Fraudsters collected $7.2 billion across more than 61,000 complaints. Organized groups, particularly in Southeast Asia, continue to run large-scale operations.
Many rely on forced labor in scam compounds across Cambodia, Laos, and Myanmar. Law enforcement efforts have begun disrupting these networks, with authorities freezing or seizing over $580 million in digital assets linked to organized crime.
Key structural trends within crypto-related fraud include:
- Investment scams accounted for the largest losses, totaling $7.2 billion across tens of thousands of cases.
- Recovery scams added $1.4 billion, targeting victims a second time under false promises of fund retrieval.
- Crypto ATM-related fraud rose sharply, reaching $389 million in losses, with strong growth in complaint volume.
- AI-linked scams emerged as a major factor, contributing to $893 million in reported losses.
Recovery scams gained traction as criminals reused victim data. Fraudsters posed as law firms, officials, or even IC3 representatives. These schemes often targeted individuals who had already suffered losses, compounding financial damage.
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IC3 recorded 13,460 complaints tied to these machines, totaling $389 million in losses. Older users accounted for a large share, reporting losses of over $257 million. Increased regulatory scrutiny followed, with several states reviewing or restricting kiosk operations.
Artificial intelligence introduced a new layer of complexity. IC3 tracked over 22,000 AI-related complaints, with losses approaching $893 million. A significant share overlapped with crypto investment scams, suggesting AI tools are being used to impersonate advisors or automate fraudulent outreach. Many victims remain unaware of AI involvement, pointing to underreported exposure.
Efforts to limit damage showed some success. The IC3 Recovery Asset Team initiated nearly 4,000 interventions, targeting over $1.1 billion in attempted theft. Authorities managed to freeze $679 million, achieving a recovery rate of about 58%. Another initiative, known as Operation Level Up, contacted thousands of potential victims and prevented an estimated $225.9 million in losses.
Geographic data reveals an uneven distribution of losses. California led with $2.099 billion, followed by Texas, Florida, and New York. Oregon ranked fifth despite lower complaint numbers, suggesting higher average losses per victim.
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