70% of fraud happens after onboarding…

Most verification platforms aren’t built for that. Thomas Taraniuk, who leads partnerships at Sumsub, has spent the last decade watching the fraud landscape evolve and the gap between where platforms focus their defences versus where the actual risk lives grow wider.

The threat driving this gap right now is AI as an operational infrastructure for fraud. Thomas is direct about his view that bad actors have democratised fraud as a service. Deepfake tools are easily used to bypass liveness checks, bots target users through AI-personalised phishing, and there are other sophisticated attacks  go much further than the KYC flow.

Within the onboarding flow itself, Sumsub has built deepfake detection, 3D facial mapping, document forgery analysis, and deep pixel inspection. They can also spot patterns that human reviewers would likely miss, like repeated backgrounds, the same desktop setup across multiple submissions, camera injection attacks etc.

But the more important battle, as Thomas frames it, is what happens after onboarding. That’s where continuous monitoring comes in. Tracking thousands of fraud indicators across behaviour, device intelligence, IP analysis, and transaction activity, with AI surfacing signals that wouldn’t be visible to a human analyst working a case queue.

The question Thomas leaves us to think about is agentic payments and the new verification challenge it creates. AI agents acting on behalf of users, spending funds, potentially issuing their own cards. Did the user authorise this agent? Is the agent being used as a vector for coordinated attacks across multiple merchants or institutions? The answer, as he sees it, is the same principle applied at scale: AI versus AI, with continuous monitoring of agent behaviour, device clusters, and spend patterns as the defence layer.

Watch the full interview below.

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