What are the odds of suffering financial loss or reputation harm from deepfake fraud?
Evidence quality 4.5/5
Eight-dimension review score against the quality rubric . Each dimension scored 1–5.
- D1 Source grounding
- 3/5
- D2 Source authority
- 5/5
- D3 Arithmetic
- 5/5
- D4 Uncertainty
- 5/5
- D5 Scope
- 4/5
- D6 Prose
- 5/5
- D7 Perception honesty
- 4/5
- D8 Caveat completeness
- 5/5
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The FBI’s 2025 Internet Crime Report marks the first time the agency has broken out AI-enabled fraud as a distinct category, recording 22,364 complaints and nearly $893 million in reported losses. Voice cloning, deepfake video, and AI-generated documents featured across investment scams, family-emergency impersonations, romance fraud, and — in a newer pattern — employment interview fraud where candidates or employers use real-time face-swaps. Older adults bore a disproportionate share: $352 million of the $893 million total. These are reported figures only; the FBI acknowledges that IC3 complaints capture a fraction of actual victimisation, and independent estimates of underreporting run from 5x to 10x.
The growth trajectory is what distinguishes deepfake fraud from established cybercrime categories. Sumsub, an identity verification platform processing millions of checks globally, reports that deepfakes rose from 7% of all detected fraud attempts in 2024 to 11% in 2026 — a near-doubling in two years. The underlying technology is on a steep cost-performance curve: voice cloning that required several minutes of sample audio in 2023 now works reliably with a three-second clip, and real-time face-swap tools run on consumer-grade hardware. The barrier to entry for would-be fraudsters is falling faster than defensive tooling can adapt, which is why the FBI’s first-year tracking already produced a nine-figure loss number.
No reliable lifetime probability is offered here because the threat is too new and too fast- moving for a stable base rate. The 22,364 complaints in 2025 represent a category that literally did not exist in IC3 reporting the year before. Extrapolating a per-person lifetime figure from one year of partial data, during a period of exponential capability growth, would produce a number that is both precise and wrong. What the data does support is a directional claim: deepfake fraud is already a material financial risk for ordinary individuals, not just corporations or public figures, and the public perception has not caught up. The entry is tagged underrated accordingly.
Related tidbits
No reliable per-person rate exists for deepfake identity fraud. The signal is strong and growing, but the denominator is unclear and tracking only began recently, so any single probability would be premature. The threat is real; the number is not yet measurable.
Claim ledger
Every number below is what each source reported, with the verbatim quote we relied on and how we arrived at our figure. Click any link to verify directly.
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[1] Federal Bureau of Investigation — Cryptocurrency and AI Scams Bilk Americans of Billions
Cryptocurrency and AI Scams Bilk Americans of Billions- Statistic
22,364 AI-related complaints in 2025 with losses of nearly $893 million; voice cloning and deepfake videos used in investment schemes and family-emergency impersonations- Excerpt
“"For the first time in its nearly 25-year history, the IC3 report features a section on artificial intelligence, which accounts for 22,364 complaints, costing Americans nearly $893 million." ”
- Source data from
- 2026-04-23
- Accessed
- 2026-04-24 · archived copy
- Calculation
- The 2025 IC3 Annual Report is the first to break out AI-enabled fraud as a distinct category. The $893 million figure covers complaints where AI tools — including voice cloning, deepfake video, and AI-generated documents — were identified as enabling the fraud. Older adults accounted for $352 million of those losses. The FBI notes that actual losses are likely far higher because IC3 captures only a fraction of incidents (the FTC estimates IC3 complaint rates at roughly 10-15% of actual victimisation). Even with a conservative 5-10x underreporting multiplier, the annualised figure would be $4.5-9 billion — but the per-person probability remains impossible to pin down because (a) the denominator is unclear (US adults? global internet users?), (b) the technology is improving faster than annual reporting can track, and (c) 2025 is the first year with any dedicated tracking. This is why the entry uses no_reliable_estimate.
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[2] Sumsub — Fraud Trends 2026: AI Scams, Deepfakes, and Emerging Threats
Fraud Trends 2026: AI Scams, Deepfakes, and Emerging Threats- Statistic
Deepfakes accounted for 7% of all fraud attempts globally in 2024, rising to 11% in 2026; a 4x increase in deepfake detections from 2023 to 2024- Excerpt
“"In 2026, AI scams are everywhere, with deepfakes now accounting for 11% of global fraudulent activity." ”
- Source data from
- 2026-01-15
- Accessed
- 2026-04-24 · archived copy
- Calculation
- Sumsub is an identity verification platform that processes millions of verification checks globally and publishes an annual fraud report based on its operational data. The 7% → 11% trajectory from 2024 to 2026 is directionally consistent with the FBI's first-time inclusion of an AI section in its 2025 report. The 4x year-over-year increase in deepfake detections (2023 to 2024) reflects both improved detection tooling and genuine growth in deepfake usage. The Sumsub data covers identity verification contexts (onboarding, KYC) rather than all fraud, so it likely understates the share of deepfakes in social-engineering scams (romance fraud, family-emergency calls) where no verification check is attempted. The rapid growth rate is precisely what makes a stable lifetime probability estimate unreliable — any number computed from 2025 data would be stale before publication.
- Independence
- Sumsub's fraud detection data is independently collected from its own verification platform, distinct from FBI IC3 complaint-based reporting. The two datasets measure different things (attempted identity fraud at verification vs reported financial losses) and corroborate each other directionally.
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[3] Deloitte Center for Financial Services — Generative AI is expected to magnify the risk of deepfakes and other fraud in banking
Generative AI is expected to magnify the risk of deepfakes and other fraud in bankingSee all 2 Likelier entries citing this source →
- Statistic
Deloitte's 2024 projection: gen-AI-enabled fraud losses in the US could reach $40 billion by 2027, up from $12.3 billion in 2023 — a 32% compound annual growth rate- Excerpt
“"gen AI could enable fraud losses to reach US$40 billion in the United States by 2027, from US$12.3 billion in 2023, a compound annual growth rate of 32%." ”
- Source data from
- 2024-05-29
- Accessed
- 2026-06-14 · archived copy
- Calculation
- Deloitte's Center for Financial Services built this projection by assigning generative-risk scores to 26 IC3 complaint categories and modelling forward growth; the conservative variant lands nearer $22 billion. It is a forward-looking industry projection, not an observed base rate, and it does not yield a per-person lifetime probability — it forecasts an aggregate US dollar loss. It is included here to bound the trajectory and corroborate the FBI's first-year nine-figure AI-fraud loss: an independent analyst forecasts roughly 3.25x growth ($12.3B to $40B) over four years, consistent with the steep curve that makes any stable per-person estimate premature. This reinforces, rather than resolves, the no_reliable_estimate flag.
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[4] SecureWorld — FBI: AI-Enabled Fraud Topped $893M in 2025 — Real Toll Likely Far Higher
FBI: AI-Enabled Fraud Topped $893M in 2025 — Real Toll Likely Far Higher- Statistic
FBI acknowledges actual AI fraud losses likely far exceed $893M due to chronic underreporting; voice deepfakes used in job interview fraud cost victims $13 million in 2025- Excerpt
“"The FBI documented widespread use of voice spoofing and video deepfakes during online job interviews in 2025, with victims reporting losses of approximately $13 million." ”
- Source data from
- 2026-04-24
- Accessed
- 2026-04-24 · archived copy
- Calculation
- SecureWorld's analysis of the 2025 IC3 report highlights the underreporting problem that prevents reliable probability estimation. The $13 million job-interview-deepfake figure is a narrow subcategory illustrating how deepfake fraud extends beyond the stereotypical wire-transfer scam into employment, romance, and investment contexts. The article notes that the FBI itself considers reported figures a significant undercount. This corroborates the decision to use no_reliable_estimate: the signal is strong (deepfake fraud is large and growing), but the noise in the denominator (who is exposed? how often?) makes a per-person probability unreliable.