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Most Britons can’t tell a deepfake from reality, despite knowing what they are

The report finds that UK adults are more familiar with deepfakes than those in any other country surveyed, yet their ability to detect them is barely better than a coin flip.

London – May 21, 2026 – A new report from Veriff, the global AI-native identity platform, reveals a striking paradox at the heart of Britain’s relationship with deepfakes. Veriff Deepfakes Report 2026 UK, produced in partnership with Kantar, surveyed 1,000 UK adults as part of a broader 3,000-person study spanning the United Kingdom, United States, and Brazil.

The headline finding is uncomfortable: knowing what a deepfake is does not mean you can spot one.

Awareness without accuracy

The UK leads all surveyed markets in familiarity with the term “deepfake” – 74% of British adults say they know what one is, compared to 67% in Brazil and 63% in the US. Younger Britons are more aware than older ones, consistent with the pattern seen in Brazil but not the US.

Yet this awareness advantage does not translate into better detection. In other markets, respondents who knew the term performed slightly better at identifying manipulated content. In the UK, that link breaks down entirely. Britons with conceptual knowledge of deepfakes were no more accurate at spotting them than those without.

The detection scores confirm it. British respondents averaged just 0.07 on a scale of -1 to 1, where 0 represents random guessing, identical to the US and only marginally behind Brazil’s 0.08. In practical terms, that score is indistinguishable from a coin flip.

The detection gap in numbers

The distribution of UK respondents’ scores tells a clear story:

  • 13% scored in the lowest possible range
  • 19% performed worse than chance
  • 15% scored at chance level
  • 37% performed slightly above chance
  • Only 16% achieved the highest scores

That means 53% of UK adults scored above chance and 32% scored below it.

Video content proved the hardest to judge. In a direct side-by-side comparison of a real and a fake female video, 70% of respondents misidentified the deepfake as genuine footage, the worst result across all visual formats in the study. The male video pair was closer, with respondents nearly evenly split (52% correct).

AI-generated images of women and faceswap visuals were also highly deceptive, while results varied more for male subjects.

High awareness, low verification

One of the most striking UK-specific findings is the gap between knowing about the threat and taking action. 22% of UK respondents say they do not try to verify suspicious content they see online, the highest non-verification rate of any market surveyed, compared to just 8% in Brazil.

At the same time, 44% of UK adults describe themselves as confident in their ability to spot deepfakes. While confidence does generally correlate with slightly higher accuracy in the UK, a significant share of self-described confident detectors still perform at or below chance level.

“Our research reveals what may be the most dangerous dynamic in the deepfake era: overconfidence,” said Ira Bondar-Mucci, Fraud Platform Lead at Veriff. “When people believe they can’t be fooled, they stop looking for the signs – and that’s precisely when they’re most vulnerable, whether to a synthetic identity used in financial fraud or a fabricated video designed to manipulate trust.”

quote

Our research reveals what may be the most dangerous dynamic in the deepfake era: overconfidence.

Ira Bondar-Mucci Fraud Platform Lead Veriff

The high-risk segment

Across all three markets, roughly 7% of respondents fall into a “high-risk” category: people who perform poorly at detection, are highly confident they would catch a fake, and rarely or never verify suspicious content. In the UK and Brazil, this group is somewhat less common among older respondents, unlike the US, where older adults are just as likely to fall into it. University-educated respondents are less likely to be in the high-risk category across all markets.

Concern is high, trust in platforms is low

UK respondents are deeply concerned about the real-world consequences of deepfakes, regardless of age or education:

  • Personal fraud and impersonation: 81% are rather or extremely concerned (compared to 79% in the US and 87% in Brazil)
  • Spreading political misinformation: 75% are rather or extremely concerned (vs. 77% in the US and 81% in Brazil)
  • Eroding general trust online: 78% are rather or extremely concerned (vs. 75% in the US and 82% in Brazil)

Unlike Americans, Britons are deeply sceptical that social media platforms can accurately identify and label AI-generated content – a view they share with Brazilian respondents. This creates a distinct challenge: great concern, low platform trust, yet a significant share of the population is not actively verifying what they see.

“When 81% of Britons say they’re concerned about deepfake-driven personal fraud, that’s not a hypothetical fear – it reflects a threat that’s already materialising,” said Bondar-Mucci. “That gap between perceived and actual protection is exactly where fraud thrives. For companies, the answer isn’t to reassure customers: it’s to earn that trust through action. It means deploying AI-driven biometric authentication that can verify a real person in real time, detect synthetic media at the point of interaction, and do so without relying on the customer to spot the fake themselves. The deepfake arms race is an AI problem that requires an AI solution. The companies that build this partnership between human oversight and automated verification today will be the ones that earn and keep their customers’ trust tomorrow.”

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The gap between perceived and actual protection is exactly where fraud thrives.

Ira Bondar-Mucci Fraud Platform Lead Veriff

Can you tell real from fake?

Take Veriff’s Deepfakes Quiz to test your own detection accuracy.

Methodology

The survey was conducted by Kantar in February 2026 using an online access panel. The study included 3,000 respondents aged 18–64, 1,000 each in the United Kingdom, United States, and Brazil, with nationally representative quotas applied for age, gender, and region. Participants assessed 16 visuals (8 real, 8 AI-generated or manipulated), including fully AI-generated images, AI-generated videos, and faceswap content. All visuals were shown in randomised order. Detection accuracy was calculated using a scoring index benchmarked against a defined chance-level baseline.

About Veriff

Veriff is a global AI-native identity platform that helps organizations build trust online. Leading companies across financial services, marketplaces, mobility, gig economy, and other digital sectors rely on Veriff’s technology to stay compliant, prevent fraud, protect users, and scale globally.

Veriff’s trust infrastructure supports the full customer journey, from verification to ongoing authentication and fraud prevention, with the least friction for honest people. Built for global scale, Veriff helps businesses expand across borders without the complexity of managing identity verification, compliance, and fraud in multiple markets – creating a single source of truth for trusted identities.

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