Passkeys prove possession of a cryptographic credential tied to a specific service, while voice biometrics infer identity from a characteristic that can be copied or synthesised. That makes passkeys materially stronger against impersonation. Voice checks may still help as a signal, but they should not carry sole authority for sensitive actions.
Why This Matters for Security Teams
Call center authentication is a high-friction, high-risk decision point because attackers target it for account takeover, payment diversion, and social engineering. Passkeys and voice biometrics can both improve the user experience, but they do not solve the same problem. Passkeys verify possession of a cryptographic credential bound to a service, while voice biometrics infer identity from speech patterns that can be replayed, altered, or synthesized. For security teams, that difference matters more than the convenience story.
Current guidance also matters because call centers often become a weak link in broader identity assurance. The Ultimate Guide to NHIs — What are Non-Human Identities shows that 97% of NHIs carry excessive privileges, which is a reminder that any weak authenticator can become a path to sensitive systems once identity is accepted. In practice, teams often discover the limits of voice checks only after a well-rehearsed impersonation or deepfake attempt has already reached a privileged workflow, rather than through intentional control testing.
How It Works in Practice
Passkeys are based on public-key cryptography and are designed to resist phishing because the private key stays on the user’s device and the credential is scoped to the relying service. In a call center context, that makes passkeys a stronger step-up mechanism for agent portals, customer self-service, and sensitive account changes. By contrast, voice biometrics are pattern-matching systems. They can reduce handle time and add an additional signal, but they are probabilistic, not decisive. The State of Non-Human Identity Security underscores how often organisations struggle to secure identity-related controls at scale, which is relevant here because poor identity design tends to be weakest where human review is still trusted to fill gaps.
In practice, security teams should treat passkeys as a primary authenticator and voice as a risk signal. A mature flow usually looks like this:
- Use passkeys or another strong possession factor for the initial login or caller-to-agent handoff.
- Use voice biometrics only to support fraud scoring, routing, or low-risk verification steps.
- Require step-up checks for payment changes, password resets, SIM swaps, and recovery actions.
- Bind policy to transaction risk, not just caller recognition, so the same voice cannot authorize every action.
- Log biometric decisions carefully and keep retention and consent aligned with privacy requirements.
Standards for biometrics are still evolving, but eIDAS 2.0 and the EU General Data Protection Regulation (GDPR) both reinforce that identity evidence and personal data handling must be proportionate, auditable, and purpose-limited. These controls tend to break down in outsourced call center environments because identity proofing, transcription, and escalation paths are split across vendors with inconsistent enforcement.
Common Variations and Edge Cases
Tighter authentication often increases call handling time and integration overhead, so organisations must balance fraud resistance against customer friction and accessibility needs. That tradeoff becomes more visible when customers do not have passkey-ready devices, when recovery journeys are poorly designed, or when the contact center serves older demographics or high-acuity support lines. Current guidance suggests voice biometrics can still be useful as a layered signal, but there is no universal standard that treats it as equivalent to cryptographic authentication.
There are also important edge cases. Voice can be degraded by illness, background noise, accents, accessibility aids, and telephony compression, which can create both false rejects and false accepts. Deepfakes and replay attacks make the risk model worse over time, not better. Passkeys are not a universal fix either: if a customer loses a device or the recovery process is weak, the security benefit can evaporate at the moment it is needed most. The practical answer is to use passkeys for decisive verification and reserve voice biometrics for augmentation, not authority. When call centers outsource verification across multiple platforms, governance gaps often appear at the handoff points, where the policy says one thing and the operator workflow does another.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10, OWASP Agentic AI Top 10 and CSA MAESTRO address the attack and risk surface, while NIST AI RMF and NIST Zero Trust (SP 800-207) set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-03 | Strong credential lifecycle matters when passkeys replace weaker factors. |
| OWASP Agentic AI Top 10 | A-07 | Risk-based runtime checks parallel how call flows should step up on sensitive actions. |
| CSA MAESTRO | GOV-2 | Call-center identity decisions need governed, auditable assurance levels. |
| NIST AI RMF | AI-supported voice scoring should be governed as a risk-based system. | |
| NIST Zero Trust (SP 800-207) | PR.AC | Passkeys fit zero-trust access decisions better than voice-only checks. |
Document voice-biometric risk, monitor errors, and limit use to supporting signals.
Related resources from NHI Mgmt Group
- What is the difference between role-based access and API key governance for NHI security?
- What is the difference between adaptive MFA and passkeys for account protection?
- What is the difference between SSO and Zero Trust for remote identity security?
- What is the difference between attack surface management and NHI governance?
