The Financial Conduct Authority published its latest review of AI use in financial services this week, identifying examples of good practice alongside areas requiring improvement. The regulator highlighted the importance of defining customer needs before building products, maintaining effective human oversight of AI systems, and ensuring operational resilience. Sophie Njagi, chief executive of UK-regulated Electronic Money Institution EQWIRE, has used the findings to call on fintech businesses to place those principles at the core of product development.
Njagi’s central argument is that commercial enthusiasm for AI is creating a gap between what looks impressive in a product demonstration and what actually serves customers at scale. “Products can look impressive in a demonstration but struggle when customers start using them at scale,” she said. “The test is whether they solve a meaningful problem, make the customer’s experience simpler and have the operations behind them to deliver reliably.”
What the FCA found
The regulator’s review did not name firms but outlined a pattern: financial services businesses are deploying AI tools with insufficient clarity about the customer problem being addressed, and with oversight frameworks that have not kept pace with the capabilities being introduced. Operational resilience, a concept the FCA and Prudential Regulation Authority have embedded in formal rules for several years, featured prominently as an area where AI deployments are lagging.
The findings carry weight in a regulatory environment that is moving quickly. The FCA has signalled a pro-innovation stance on AI but has been equally clear that the Consumer Duty, which came into full force in 2023, requires firms to demonstrate good outcomes for retail customers. That creates a compliance obligation, not merely a design preference, to understand what customers need before committing engineering resource to building.
Five principles for durable product development
Njagi sets out five principles that she argues produce technology products built to last. These cover prioritising genuinely important customer problems over fashionable technology trends; investing in operational foundations rather than surface-layer design; managing complexity internally so customers experience simplicity; building teams with genuine ownership of outcomes; and maintaining the strategic flexibility to change direction as regulation, technology and customer behaviour shift.
The principles are not novel, but the FCA context gives them a compliance dimension that pure product advice lacks. For fintech founders and product leaders, the regulator’s findings amount to a signal that AI roadmaps will receive scrutiny on customer-outcome grounds, not only on technical-risk grounds.
Market context
The FCA review lands in a period of intense AI adoption across retail banking, payments and lending. Established banks and challenger firms alike are integrating large-language-model tooling into customer-facing and back-office processes. The risk the regulator appears most concerned about is the adoption of AI capabilities that are genuinely impressive in controlled conditions but whose performance, edge-case handling and failure modes are not well understood by the firms deploying them.
For smaller fintechs and EMIs operating under tighter capital and compliance resource constraints, the operational resilience requirement is particularly pointed. Building the oversight infrastructure that regulators expect around AI systems adds cost that must be justified by the customer outcome delivered. Njagi’s framing, from the perspective of a CEO running a regulated EMI, is that the discipline required by regulation and the discipline required by good product development are effectively the same thing.
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