Gary Ellison, VP Head of Data & AI, Valtech
Financial institutions have poured hundreds of billions into digital transformation over the past decade. Cloud migrations, AI initiatives and modernisation programmes now sit at the centre of boardroom strategy. Yet despite this, disruptions keep coming. Outages that lock thousands of people out of their own money, block payments and cards, and often land the bank on the front page by lunchtime.
The cause may vary. A software update may fail, a system dependency may break, or a third-party service may drop out. But when major incidents continue to occur across the industry, it’s worth asking whether organisations are focusing too heavily on symptoms rather than the root cause.
Too often, outages are treated as isolated technology failures. In reality, most are symptoms of structural issues: unclear data ownership, weak governance, and legacy systems never designed for the complexity they now face.
Looking beyond the incident
When outages make headlines, attention naturally turns to customer impact, regulatory scrutiny and compensation costs. These are important considerations, but they don’t explain why similar incidents persist across the industry.
In many organisations, critical data remains fragmented across legacy systems, business units and functional teams. Information is duplicated, ownership is unclear, and dependencies are poorly understood. As technology estates grow more complex, with new platforms layered on ageing ones, even a small change can trigger unintended consequences elsewhere.
When something goes wrong, recovery is often slowed not by the technical fix itself but by the effort it takes to work out what changed, where responsibility lies and which systems are affected. The longer those questions go unanswered, the longer customers stay locked out.
Legacy infrastructure, a failed upgrade, a cloud dependency or a third-party outage are all real and rarely the same one twice. But the trigger only explains a single incident. What explains the pattern, why one glitch cascades across the estate while another is contained within minutes, is whether anyone owns the underlying data. It’s less a question of investment than of accountability.
Data readiness is becoming a competitive differentiator
The stakes grow higher as financial institutions accelerate their adoption of AI and advanced analytics.
Across the industry, many organisations have successfully launched pilot programmes and demonstrated promising use cases. The greater challenge is scaling those initiatives across the enterprise and embedding them in day-to-day operations.
Ambition is never the limiting factor. The real obstacle is often the quality, accessibility and ownership of the underlying data. AI systems depend on trusted, well-governed data to deliver reliable outcomes. When information is fragmented across multiple platforms or managed inconsistently across teams, projects become harder to scale, and value becomes more difficult to realise.
This is where competitive advantage is increasingly won or lost. Organisations that establish strong data foundations can move from experimentation to execution more quickly, while those operating in fragmented data environments risk seeing promising initiatives stall before delivering meaningful business value.
At a time when fintech challengers and digitally native competitors continue to raise customer expectations, the ability to translate data into action has become a critical differentiator.
Why operating models matter
Technology alone cannot solve these challenges.
Many financial institutions still rely on highly centralised decision-making structures, in which major technology and data investments require multiple layers of approval before action can be taken. While oversight remains essential in a heavily regulated industry, excessive bureaucracy can slow progress and limit responsiveness.
The organisations making the greatest strides are adopting a different approach. They are assigning clear ownership of data domains, establishing accountability closer to the teams responsible for delivery, and embedding governance into processes from the outset rather than applying it only when needed.
This creates greater clarity in decision-making and helps organisations respond more effectively when issues arise. Teams spend less time determining ownership and more time resolving problems.
The clearest illustration is the digital-native challengers, like Monzo and Starling. Built cloud-first, without decades of systems layered one on top of another, many began with exactly what established institutions are now trying to retrofit: clear data ownership and product-led teams empowered to act. That is a large part of why they can release changes quickly and contain problems before they cascade across the estate.
From resilience to advantage
The most mature organisations no longer view data governance solely as a risk-management exercise. Instead, they see it as an enabler of growth, innovation and customer value.
Where data is trusted and ownership is clearly defined, institutions are better placed to deliver capabilities such as real-time fraud detection, intelligent payment support, personalised customer journeys and proactive service interventions.
These tangible outcomes improve the customer experience, strengthen loyalty and create opportunities for differentiation in an increasingly competitive market. At the same time, strong governance helps organisations reduce complexity, accelerate delivery and improve their ability to recover from operational incidents.
Building for the next phase of banking
Banking outages may grab headlines, but they raise a bigger question: whether an organisation’s operating model is equipped to meet the demands of modern financial services.
As investment in AI and transformation accelerates, success will depend equally on replacing outdated systems and strengthening the foundations behind them. Clear data ownership, strong governance and accountability are becoming essential for both resilience and innovation.
The real lesson from today’s outages isn’t about what went wrong. It’s about what’s needed to move forward. In an industry increasingly defined by data and AI, the banks that can combine innovation with accountability will set the pace for the next decade.