Glossary term
Audio Deepfake Detection
Definition
Audio deepfake detection is the analysis of speech audio to identify signs of synthetic generation or voice conversion. Unlike speaker verification, which asks "is this the enrolled person?", audio deepfake detection asks "was this audio produced by a machine?" — examining spectral, prosodic, and phase artifacts characteristic of text-to-speech and voice-cloning models.
Why it matters for financial institutions
Call centers are the soft target of banking fraud: a convincing cloned voice plus breached personal data defeats knowledge-based authentication and can defeat voice biometrics, because the clone is engineered to match the enrolled voiceprint. Detecting the synthesis itself, rather than the speaker identity, is the control that still works when the clone is good.
How FalsiFind addresses it
FalsiFind streams call audio through detection models tuned to current speech-synthesis architectures and returns a first risk signal in about 700 milliseconds. Scores update continuously through the call, so escalation can happen mid-conversation instead of in post-call review.