Combating Deepfakes in Live Video Onboarding with AI

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Deepfakes generated through advanced AI techniques, including face swaps, voice mimicry, and manipulated video responses, are increasingly threatening live video onboarding by enabling fraudsters to impersonate legitimate users and bypass KYC checks. The material argues that effective defenses require AI-powered passive liveness detection, which assesses cues such as eye movement, skin texture, blood flow, and lighting anomalies, alongside active liveness prompts that test spontaneous user actions. It recommends a layered verification process combining liveness checks with identity-document authentication, 1:1 biometric face matching, AML screening, and phone or email verification to reduce fraud and support compliance. Didit is presented as an AI-native, modular identity platform offering these capabilities through APIs and a no-code console, with an iBeta-certified liveness product and a free core KYC tier under a pay-per-successful-check model.

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