Revolut is piloting an in-store facial recognition checkout in London that allows enrolled customers to authenticate a payment with their face rather than a card or phone. The three-day Pay with Smile trial is running at selected Kiss the Hippo cafes through Revolut Register, the bank's point-of-sale system.

Revolut says the service verifies the customer against the selfie identity checks completed when the account was opened. Participation is opt-in through the Revolut app. The company is also using the pilot to promote 0 per cent processing fees for Pay with Smile transactions on Revolut Register. Its accompanying figures on merchant costs and payment outages are Revolut research and should be treated as vendor-reported benchmarks rather than industry-wide measures.

The more important question is what happens when biometric identity becomes a routine payment credential. Account-opening checks were designed to establish who a customer is. Reusing that identity signal at checkout can reduce friction, but it also joins payments, biometric templates, consent and transaction dispute processes in one chain. A short coffee-shop pilot will not answer the harder questions around false matches, accessibility, fallback authentication, revocation and redress. It does, however, make those questions operational rather than theoretical.

Agentic Exploits- Deterministic gates for a probabilistic problem
David Girvin, CEO and co-founder of Assury, joins Stewart Tinson to dig into what’s actually happening when agentic AI goes wrong, and why he thinks most of the industry is solving the wrong layer of the problem. David explains the difference between prompt-level exploits and execution-level ones, arguing that the real danger starts the moment an agent moves from generating text to calling tools: deleting databases, reading files, sending emails. He walks through real-world incidents, including a Mexican government breach chain that escalated from just over a thousand prompts to over five thousand AI-executed actions across multiple agencies before detection, and the UK AI Security Institute’s recent cyber evaluation, in which agents took unsanctioned action including fabricating identities to socially engineer a real GitHub maintainer. The conversation covers why David is sceptical of “guardrails” language and AI-governing-AI approaches, arguing that only deterministic, architectural controls can reliably constrain agent behaviour, alongside human review reserved for genuinely high-stakes actions rather than blanket approval fatigue. He breaks down credential starvation, session risk accumulation, and why classifier-based tools keep failing inconsistently on identical actions, pointing to a named frontier lab’s own zero trust paper as an example of the industry misjudging what actually works. Elsewhere, David discusses the exposed MCP server problem, the widening trust gap between small specialist security vendors and platform incumbents, and why he believes regulation, not product quality alone, is what finally drives enterprise security spend. He closes with the exploit that concerns him most for the year ahead: session-level, goal-directed deception with no attacker involved at all.
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