Voice fraud detection for banks and call centers.

The voice is now the weakest link

A convincing clone needs only seconds of sample audio, and the scripts are consistent. In executive-impersonation (CEO) fraud, an attacker mimics a leader and instructs a finance team member to move money, a pattern covered in CEO fraud, as in the 2024 Hong Kong case where a worker was deceived into transferring about 25 million US dollars (reported by CNN). In vishing and family-emergency scams, the same technique targets call-center agents and relatives. The US Federal Trade Commission has warned that scammers now use AI to enhance these schemes, and losses are logged by the FBI's IC3.

The common thread is urgency plus a trusted-sounding voice used to bypass normal controls. Detection is the second line of defense behind process (dual approval, callbacks): once a recording exists, you can prove whether the voice was synthetic.

From flagged recording to filed verdict

The detector reads the acoustic signature of the audio, so it works on cloned and stock voices. It fits a review workflow, not a live switchboard.

How do banks stop AI voice fraud in their call centers?

No single tool stops it. Banks that hold up well combine process rules that do not trust the voice with detection on the recordings they already keep. The scale is real: the FBI IC3 2025 report counted 22,364 complaints involving AI in 2025, with about 893 million dollars lost, and named voice cloning in business email compromise and family emergency scams. Imposter scams across every channel cost people 3.5 billion dollars that year (FTC, June 2026).

1. Never act on the voice alone. A payment change, a new beneficiary or an account recovery requested by phone gets a callback to a number already on file, and large transfers need a second approver.
2. Treat passcode requests as an attack. No legitimate caller asks a customer to read out a one-time code (FTC). Agents should end the call and flag it.
3. Harden the help desk. Password and MFA resets by phone are a known pretext; CISA and the FBI describe Scattered Spider using it (CISA AA23-320A). Require identity checks that a cloned voice cannot pass.
4. Screen the recordings you keep. Send flagged or high-risk calls and voicemails to the detector through the API. Each one comes back with a verdict, an AI score and per-segment scores, so a reviewer starts with the calls most likely to be synthetic.
5. Keep the result with the case. Save the verdict and its share link with the fraud file, so a dispute or a referral shows what was checked and when.

Is there real-time voice fraud detection?

Not from us, and you should be wary of claims that any detector can make a reliable call mid-conversation on a compressed phone line. The detector analyzes recordings after the fact. It does not tap, monitor or block live calls. What works in practice is to record calls as you already do for quality and compliance, screen the ones that match a risk pattern (a payment change, a reset, an urgent transfer) through the API, and hold the action until the callback or second approval is done.

Where does synthetic voice detection fit next to your other controls?

Each control answers a different question. Only detection looks at whether the recorded voice itself was machine-generated.

Screening at volume, or need a contract and invoicing? Contact sales. Pricing for the API is on the pricing page.

Detection, not authentication

We detect whether a voice is machine-generated. That is different from voice biometrics, which verifies a known enrolled speaker as a login factor. The two are complementary: biometrics answers "is this the right person," and we answer "is this a real human voice at all," which is exactly the gap synthetic-voice attacks exploit. Use the detector as an anti-spoofing and post-incident check alongside your existing controls.

We analyze recordings after the fact. We do not tap, monitor, or block live calls. For programmatic checks, see the API; for how the underlying detection works, see how to detect AI voices. Related reading: spotting AI voice scams and the dangers of AI voices.

Frequently asked questions