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Industries · Financial Services

Voice fraud defence for banks, fintechs and treasury operations.

Voice cloning takes one minute of audio. The result: helpdesk impersonation, CFO fraud, password-reset abuse and synthetic-identity onboarding at carrier-grade scale. DeepBlocker is the only voice deepfake detector with a published model card that holds up on real phone lines.

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The threat picture

Voice is now the primary channel for high-value financial fraud.

  • £1.17B stolen from UK victims to authorised push-payment and impersonation fraud (UK Finance, 2025).
  • $16.6B in reported losses to cybercrime, with vishing and impersonation accounting for the fastest-growing categories (FBI IC3, 2024).
  • 60% of firms experienced at least one deepfake-driven incident in the last twelve months (Thales, 2026).
  • Voice authentication is "fully defeated", per Sam Altman addressing the US Federal Reserve in 2024. Most banks still rely on it.
What we defend

The three voice-attack surfaces inside a financial institution.

Helpdesk and customer-service lines

Account takeover via password resets, address changes, and SIM-swap requests. DeepBlocker intercepts the call, verifies the speaker, and pushes high-risk requests to verified processes — never approves a sensitive change by phone.

Real-Time Protection · per-line
Treasury, payments and CFO fraud

Spoofed CEO/CFO calls instructing wire transfers or vendor changes. DeepBlocker terminates synthetic-voice calls before they reach the human, and routes the audit trail to your fraud team.

Real-Time Protection · executive lines
Onboarding and identity verification

Synthetic-voice fraud during phone-based KYC and re-verification. DeepBlocker Detect plugs into your existing fraud-decisioning stack as a hosted API — same telephony-tuned model that powers Real-Time Protection.

DeepBlocker Detect · API
The detection-grade you can audit

Reproducible, telephony-tuned, model-card-grade.

93.6%
AI callers caught on real phone calls, up from 86.2%
3.2%
AI callers that slip through, down from 8.5%
3.5%
Real callers wrongly flagged, unchanged
0.986
ROC AUC on real calls, up from 0.963

Measured on 207 real phone calls, both models scored on the same calls the way production scores them. We publish methodology and per-source breakdown — including known limitations — in the model card. Onecom-grade due-diligence is reproducible from the open base model.

Regulatory alignment

Built for FCA, DORA, NIS2, and GDPR obligations.

  • FCA Consumer Duty: evidence of meaningful steps to prevent foreseeable harm — every blocked deepfake call has a complete audit trail.
  • DORA (EU 2554/2022): ICT third-party risk management and operational resilience. DeepBlocker contracts include sub-processor disclosure and exit-plan support.
  • NIS2: incident reporting hooks into existing SOC tooling. Per-call disposition logs are exportable to Splunk / Sentinel / Elastic.
  • GDPR: per-tenant retention, encryption, and access controls; data-residency options on request.
The Enterprise Assessment

A 2–4 week board-ready output, before you commit.

  • Risk-scored map of every voice-triggered workflow inside the bank.
  • Simulated vishing exercises against your contact-centre and treasury teams, with transcripts.
  • Quick-wins list: changes you can make this quarter without a procurement cycle.
  • Structural roadmap: where Real-Time Protection or Detect sit in your existing stack.

Ready to brief your fraud team?

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