Topic starter
14/09/2026 10:09 am
TL;DR: AI-assisted fraud sessions on its platform rose from 2% in Q1 2023 to 32% in early 2026, while the cost of producing a convincing deepfake fell to US$1 and 18 seconds, making older detection economics inadequate according to Incode. The shift matters because identity verification now has to defeat synthetic media, bot behaviour, and device tampering at the same time, not one control failure in isolation.
Editorial analysis by NHI Mgmt Group, based on content published by Incode: “Incode Deepsight wins the 2026 Award for Best AI-Driven Innovation in the Datos Impact Awards in Fraud & AML”.
Key questions
Q: What breaks when deepfake detection is not paired with device and behavioural checks?
A: A single media detector can be bypassed when the attacker changes the capture path, automates the session, or injects manipulated content from a virtual device.
Q: Why do AI-driven fraud tactics create new pressure on traditional identity verification?
A: AI lowers the cost of fraud by making synthetic identities, deepfakes, and automated account takeover faster and more convincing.
Q: How should security teams respond when synthetic identities pass verification checks?
A: They should treat the pass event as the start of a governance review, not proof of legitimacy.
Practitioner guidance
- Harden capture integrity controls Block emulators, virtual cameras, and tampered capture paths before biometric or document evidence is accepted into the verification decision.
- Add behavioural telemetry to proofing Correlate interaction timing, session patterns, and automation indicators with media checks so bot-like activity cannot ride through a clean-looking selfie or document image.
- Test against multimodal fraud scenarios Run adversarial testing that combines synthetic faces, altered documents, and device spoofing so each control layer is measured against the others.
Bottom line: Deepfake fraud is no longer limited to fake faces, because attackers can combine synthetic media, automation, and device tampering in the same verification flow.
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14/09/2026 10:10 am
Deepfake fraud has become an identity governance problem, not just a fraud problem. Once synthetic media can be produced cheaply and quickly, the control question shifts from spotting one fake face to governing an end-to-end verification session. That means identity teams have to treat capture integrity, behavioural telemetry, and media authenticity as a single assurance chain. The practitioner conclusion is that traditional verification stacks are now missing the actual attack surface.
A few things that frame the scale:
- U.S. fraud losses are projected to reach $40 billion by 2027.
A question worth separating out:
Q: Should organisations treat deepfake fraud as a fraud team issue or an identity governance issue?
A: Both, but the governance owner needs to be identity because the control failure happens at verification time. Fraud teams can tune detection, yet identity leaders must define the assurance threshold, the escalation path, and the evidence required before trust is granted.
👉 Read our full editorial: AI deepfake fraud is outpacing identity verification controls