Topic starter
11/06/2026 11:55 pm
TL;DR: As Vietnam’s State Bank of Vietnam Decision 2345 raises biometric assurance expectations for online transactions, MoMo is deploying Dynamic Liveness to strengthen remote identity verification against deepfakes and digital injection attacks according to iProov research. The core issue is not biometrics alone, but whether verification can still prove a real, present person when AI makes impersonation cheaper and more convincing.
Editorial analysis by NHI Mgmt Group, based on content published by iProov: “Leading Fintech Group MoMo Partners with iProov to Safeguard Vietnamese Against Digital Fraud”.
Key questions
Q: What breaks when biometric verification cannot prove liveness in financial services?
A: When verification only checks whether a face matches, it can accept deepfakes, replayed media, or injected signals as genuine users.
Q: Why do deepfakes make video-based identity verification so risky for remote operations?
A: Deepfakes undermine video verification because they can convincingly mimic a person’s face and voice, which makes social engineering easier to scale.
Q: How can teams tell whether their biometric assurance is too weak?
A: Warning signs include heavy reliance on a single check, no independent device or metadata validation, and a manual review process that assumes humans can reliably spot synthetic media.
Practitioner guidance
- Strengthen liveness at remote verification Test whether your biometric flow can reject replayed video, still images, synthetic faces, and injected capture streams before authentication succeeds.
- Map assurance to transaction risk Define which online transactions require stronger biometric assurance and document the threshold that distinguishes ordinary sign-in from high-risk approval.
- Review your media-injection exposure Check whether the capture path, device trust assumptions, and verification channel can be manipulated before the liveness decision is made.
Bottom line: AI-driven fraud is changing what biometric controls must prove, shifting the focus from matching identity traits to proving real-time presence.
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12/06/2026 8:50 am
Biometric liveness is becoming the control boundary for AI-era identity proofing: Traditional face matching assumes the biometric sample is an honest capture of a real person. That assumption weakens when deepfakes and injection attacks can fabricate the input itself. The governance question is no longer how accurate the matcher is, but whether the proofing step can establish liveness under adversarial conditions.
A few things that frame the scale:
- U.S. fraud losses are projected to reach $40 billion by 2027.
A question worth separating out:
Q: Should financial teams treat liveness as part of identity proofing or fraud prevention?
A: Both. Liveness sits at the point where identity proofing meets fraud resistance, because it decides whether the system is interacting with a real human or an artefact. In practice, that means identity and fraud teams should jointly define assurance thresholds, escalation paths, and controls for remote transactions.
👉 Read our full editorial: Biometric liveness for AI-driven fraud in financial services