Topic starter
11/07/2026 8:45 pm
TL;DR: Deepfake fraud attempts rose more than 1,300% in 2024, while the Wall Street Journal reported over $200 million in deepfake scam losses in the first quarter of 2025, according to Oz Forensics and cited sources in its analysis. The identity lesson is that onboarding controls must prove presence, not just likeness, because fraud has industrialised.
Editorial analysis by NHI Mgmt Group, based on content published by Oz Forensics: “The Deepfake Surge: Why Liveness Detection is the Answer”.
Key questions
Q: What breaks when banks rely on face matching without liveness detection?
A: Face matching alone breaks when an attacker can inject a replayed, synthetic, or manipulated video stream into the app.
Q: Why do deepfakes and AI-enabled fraud create new pressure on KYC and AML programmes?
A: Deepfakes raise the chance that organisations will trust fabricated identities, manipulated documents, or impersonation during onboarding and support interactions.
Q: What are the signs that onboarding anti-spoofing controls are not working?
A: A weak control often shows up as repeatable success against the same capture flow, failed detection of replayed media, or fraud cases where a claimant passed facial verification but later proved false.
Practitioner guidance
- Strengthen proof-of-presence at the first capture Require liveness verification before any onboarding decision can bind a face to a customer record, account, or credential set.
- Test replay and synthetic-media failure modes Include replayed video, manipulated imagery, and 3D mask scenarios in onboarding assurance testing so the control is evaluated against the fraud patterns described in the article.
- Separate face match from authenticity checks Do not treat successful facial similarity as evidence of live capture; require a distinct control that verifies the image was captured in real time.
Bottom line: Deepfake fraud now targets the onboarding decision itself, where a live claimant can be mistaken for a legitimate customer or user.
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11/07/2026 9:14 pm
Liveness is becoming a front-door trust control, not a narrow biometric feature. The article shows that onboarding is where synthetic identity, replay attack, and impersonation risk now concentrate. When deepfakes can convincingly simulate presence, the real control question is whether the claimant was live at capture time. Practitioners should treat liveness as part of identity assurance, not as an optional user-experience layer.
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: How should businesses detect deepfake fraud in remote onboarding and authentication flows?
A: Businesses should combine liveness checks, AI-based anomaly detection, and step-up verification for high-risk actions. Deepfakes are designed to defeat human judgment, so controls must look for manipulated image artifacts, duplicate identities, and suspicious behavioral patterns. The most effective approach is layered: verify identity, validate session risk, and require stronger checks when confidence drops or the transaction is unusually sensitive.
👉 Read our full editorial: Deepfake fraud is forcing stronger liveness checks at onboarding