Topic starter
06/11/2026 6:40 pm
TL;DR: Biometric spoofing is getting easier as deepfakes, masks and replayed media can defeat face or voice matching, according to Zumigo, so liveness detection now matters as a separate presence check. The governance issue is not biometrics alone, but whether verification proves a live person is present at the point of access.
Editorial analysis by NHI Mgmt Group, based on content published by Zumigo: “Active Liveness Detection and Verification Explained: How It Stops Biometric Fraud”.
Key questions
Q: How do I reduce biometric spoofing in remote onboarding?
A: Reduce biometric spoofing in remote onboarding by pairing document checks with passive or active liveness detection, device and session risk signals, and step-up verification when the confidence level is low.
Q: What happens when biometric authentication is deployed without liveness detection?
A: Without liveness detection, a biometric system can confuse a fake representation for a real person and authenticate the wrong user.
Q: What is the difference between passive, active, and enhanced liveness detection?
A: Passive liveness checks analyse a selfie for natural signs of life with little user effort.
Practitioner guidance
- Define liveness by transaction risk Use passive checks for low-risk flows and active or hybrid checks for onboarding, recovery, and high-value transactions where spoof resistance matters more.
- Separate match confidence from presence assurance Require the verification workflow to log biometric match outcomes separately from liveness outcomes so reviewers can see which control actually failed.
- Add contextual signals to every high-risk flow Combine device reputation, SIM intelligence, geolocation consistency, and behavioural signals with liveness before granting access or completing onboarding.
Bottom line: Biometric fraud becomes much easier when organisations confuse a successful face or voice match with proof that a live person is present.
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06/11/2026 6:41 pm
Presence, not resemblance, is the control boundary. Biometric systems can confirm similarity while still failing to prove that the claimant is a live human in the session. That creates a governance gap whenever organisations treat face or voice matching as a complete authentication decision. The practical conclusion is that verification design must separate identity match from liveness proof.
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: How should teams combine liveness checks with fraud signals?
A: Teams should combine liveness checks with fraud signals by treating liveness as one control inside a wider identity proofing flow. Correlate selfie capture quality, device reputation, IP and geolocation anomalies, behavioural risk, and document verification, then trigger manual review or step-up checks when signals conflict or the risk score crosses a defined threshold.
👉 Read our full editorial: Active liveness is now a core control against biometric fraud