Topic starter
12/07/2026 12:15 pm
TL;DR: Deepfakes are making it easier to impersonate real people during digital onboarding, and Prove Identity says selfie-based checks and liveness detection are increasingly poor fits for that fraud pattern. The assumption that visual identity signals remain trustworthy at onboarding is collapsing, so verification has to shift to stronger possession and network signals.
Editorial analysis by NHI Mgmt Group, based on content published by Prove Identity: “Creating Deepfakes is Easy - And That’s a Huge Onboarding Problem”.
By the numbers:
- 66% of cybersecurity professionals reported encountering deepfake attacks within their organizations in a 2023 study cited by Prove Identity.
- 92% of finance security leaders expressed deep concern about the impact of deepfakes.
- Deepfake-related fraud cases surged 10 times globally between 2022 and 2023, according to Sumsub research cited by Prove Identity.
Key questions
Q: What breaks when remote onboarding still relies on document and selfie checks?
A: The control breaks when the verification path assumes visible evidence is enough to prove identity.
Q: Why do AI-generated fake IDs and deepfakes create such a sharp fraud risk in digital onboarding?
A: AI-generated documents and biometric spoofing reduce the quality gap that traditional verification once depended on.
Q: How can security teams tell whether onboarding verification is too easy to spoof?
A: Look for controls that accept visual evidence without requiring device-linked or network-linked corroboration, especially in high-risk journeys.
Practitioner guidance
- Replace visual-only proofing for high-risk onboarding Remove self-attested selfies and standalone liveness checks as decisive controls in flows where account opening or funds movement is high impact.
- Bind onboarding to device possession Use device-linked evidence, such as registered phone ownership and network signals, to anchor identity assurance before granting trust.
- Add step-up checks for risky claims Trigger stronger verification when onboarding details, behavioural signals, or transaction intent do not align with prior trust history or expected patterns.
Bottom line: Deepfake-enabled onboarding attacks exploit the gap between fast digital acquisition and the level of assurance needed to prevent impersonation.
Explore further
View Full Forum → | NHI Foundation Course → | Our Services → | Read the full analysis →
12/07/2026 12:29 pm
Visual trust has become an identity assumption, not an identity control: Selfie and video-based onboarding only work when the presentation layer remains a dependable proxy for personhood. Deepfakes break that proxy by manufacturing believable evidence on demand. The result is not just more fraud, but a collapse in the assumption that appearance can carry proofing decisions, which forces identity programmes to re-centre assurance on stronger signals.
A few things that frame the scale:
- Businesses report a 200% surge in attempted deepfake-aided wire fraud in Q1 2025 alone.
A question worth separating out:
Q: Should organisations move from selfie-based onboarding to phone-centric verification?
A: For higher-risk onboarding, yes, because phone-centric verification ties trust to device possession and stronger contextual signals rather than to a fabricated image. The right design is usually risk-based, where stronger evidence is required only when the exposure justifies it.
👉 Read our full editorial: Deepfakes are turning frictionless onboarding into an identity risk