How should security teams verify callers in contact center workflows without creating more friction for agents and customers?

Use phishing resistant authentication methods that fit the call flow, such as passkeys, push approval, OTP, or biometric recovery, and keep the verification step inside the agent workflow. The goal is to confirm identity before sensitive actions occur, while reducing handoffs and reauthentication loops that slow support teams and frustrate callers.

Why This Matters for Security Teams

Contact center verification is not just an authentication step. It is a control point that decides whether an agent can change account data, reset credentials, or release protected information. If the flow is too rigid, agents bypass it; if it is too loose, attackers exploit social engineering, account takeover, and scripted fraud. Current guidance suggests the safest pattern is to verify identity without moving the caller into a separate, high-friction channel.

That matters because support operations are already under pressure to reduce handle time while maintaining strong assurance. Security teams should design verification around the workflow the agent already uses, not around a separate security ceremony that forces customers to repeat themselves. This is especially important where high-risk actions are triggered after a successful call authentication event, since the same session can still be hijacked later through callback abuse, SIM swap, or deepfake-enabled impersonation. NHI Mgmt Group’s Ultimate Guide to NHIs notes that 80% of identity breaches involved compromised non-human identities such as service accounts and API keys, which is a useful reminder that verification failures often cascade beyond the human caller into downstream systems.

In practice, many security teams discover that the control failed only after a fraud case or an unauthorized reset has already been completed, rather than through intentional testing.

How It Works in Practice

The best contact center designs treat caller verification as a layered confidence check, not a single password-like event. A secure flow usually starts with a phishing-resistant primary factor where possible, then adds step-up checks only when the request is sensitive. That can include passkeys, push approval, OTP, or biometric recovery, but the key is that the method must fit the call path and not force an unnecessary handoff. For examples of how identity and tool access failures spread across modern workflows, see NHI Mgmt Group’s Meta AI Instagram Account Takeover analysis and the CoPhish OAuth Token Theft via Copilot Studio report.

Operationally, security teams should anchor the workflow in the agent desktop and call center platform, then use policy decisions at request time rather than broad static rules. That aligns with the direction of the NIST AI Risk Management Framework and the OWASP Agentic AI Top 10, both of which reinforce context-aware decisioning. In practice, that means:

• Authenticate the caller early, but only step up when the requested action warrants it.
• Use short-lived verification state tied to the live session, not reusable approval tokens.
• Require stronger assurance for password resets, payout changes, and address updates.
• Keep the verification result visible to the agent so they do not create a second, manual approval path.
• Log the evidence used for verification so fraud teams can review patterns later.

Where available, use workload-style identity and policy controls for the backend systems that process the call outcome, because the agent interface is only as strong as the privileges behind it. These controls tend to break down when legacy IVR, outsourced queues, and disconnected CRM systems force the caller to reprove identity in separate tools, because the assurance context is lost between handoffs.

Common Variations and Edge Cases

Tighter caller verification often increases handle time and customer friction, so organisations have to balance fraud reduction against abandonment risk. That tradeoff is real, especially in high-volume support, multilingual queues, and recovery scenarios where the customer no longer has access to their original device or email. Best practice is evolving, and there is no universal standard for this yet.

In lower-risk calls, a lightweight step-up may be enough, while high-risk workflows should use stronger evidence and tighter approval boundaries. For example, some teams allow OTP plus account history for routine inquiries, but require a passkey or verified callback for sensitive changes. The important design choice is to make the verification step proportional to the action, not to apply the same burden to every call. Guidance from CSA MAESTRO agentic AI threat modeling framework is useful here because it emphasizes contextual threat modeling rather than one-size-fits-all controls.

Another edge case is fallback recovery. If biometric or passkey verification fails, the recovery path should not become weaker than the primary path. Fraudsters routinely target the weakest escape hatch. That is why security teams should define escalation rules, agent override limits, and manual review thresholds before deployment. A practical benchmark from NHI Mgmt Group’s State of Non-Human Identity Security report is that only 1.5 out of 10 organisations are highly confident in securing NHIs, which reflects how often identity controls erode when process, tooling, and governance are not aligned.

Related resources from NHI Mgmt Group

• How should security teams authenticate callers without creating too much friction?
• How should security teams verify callers in service desk workflows without relying on security questions or employee IDs?
• How should security teams authenticate AI agents in enterprise environments?
• How should security teams govern AI agents without creating a manual review bottleneck?