Audio-native detection is your first line of defense, using the raw audio to create several fraud likelihood scores.

You’ll have answers well before transcription, biometrics, or agent interaction ever comes into play and before funds are ever moved.

The fraud likelihood scores should then trigger one to three of the following:

• Out-of-band verification, such as email confirmation codes, a verified call back, or pushed approvals through a verified app.
• Dynamic-challenge response, such as “tell me the last 4 digits of the vendor we paid yesterday” or “tell me the last deposit we made in your account.”
• Device-binding identity that ties customers to a trusted device or cryptographic key.
• Transaction-level risk scoring that authenticates the action with signals such as whether or not it’s an unusual amount, a different beneficiary, or there’s a geo-location mismatch.

This layered approach helps to reduce your operational load, lower customer friction, and increase fraud-catch rates.

Ultimately, that is the goal of any fraud detection tool, but audio-native detection tools like Modulate’s Deepfake Detection API are the only systems getting companies close to complete protection.