Data Risk: The Strategic Imperative for UK Banks in 2025

The Prudential Regulation Authority has made it clear that data governance is now critical for UK banks' competitiveness. As financial institutions pursue digital transformation, they're discovering these initiatives can only succeed with robust data quality and management across three key challenges: impaired risk management, blocked innovation, and the need for executive accountability.

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In recent guidance from the Prudential Regulation Authority (PRA), the message to UK banks could not be more clear: data is no longer just an operational asset but a systemic risk. The financial sector is under mounting pressure to bring greater discipline to how data is handled, managed, and governed across the enterprise.

For many banks, the growing complexity of digital transformation has exposed underlying weaknesses in data strategy. As firms embrace AI, cloud migration, and advanced analytics, they discover that these initiatives are only as effective as the quality of the data that underpins them. Innovation stalls, and regulatory compliance become harder to achieve without robust data governance.

At Digiata, we see a clear pattern emerging data risk is no longer a byproduct of weak controls—it's a central obstacle to competitiveness and compliance. Based on recent regulatory commentary and our experience working with leading financial institutions, three critical challenges must be addressed.

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1. Data Risk Is Impairing Risk Management

Inadequate data aggregation, poor lineage, and fragmented governance structures erode the effectiveness of risk and compliance functions. Stress testing, liquidity forecasting, and credit exposure modelling rely heavily on the ability to source accurate, timely, and complete data. Where this foundation is lacking, so too is the reliability of internal risk frameworks.

The PRA has reinforced that deficiencies in regulatory reporting are not just technical gaps—they represent fundamental risk governance failures. The collapse of Silicon Valley Bank, for example, served as a global reminder of what can go wrong when balance sheet decisions are made using flawed data.

Clearly, strong data aggregation capabilities are no longer a "nice to have"—they are central to managing risk in volatile markets, particularly as institutions increase their exposure to private credit and other less-regulated asset classes.

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2. Data Deficiencies Are Blocking Innovation

Banks that are slow to remediate their data environments are finding it difficult to capitalise on the promise of AI and machine learning. Most advanced models require not just volumes of data but precision and explainability—especially in regulated environments.

Recent studies of AI adoption in UK financial services indicate that "data quality" is now among the top concerns slowing enterprise-scale deployments. As regulators develop frameworks for model governance, banks will be expected to demonstrate confidence in their inputs just as much as their outputs.

Digiata works with clients to resolve this through better internal alignment and scalable data infrastructure. We believe AI success depends not only on algorithmic sophistication but on disciplined data ownership, controlled data pipelines, and precise regulatory alignment—starting from day one.

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3. Effective Remediation Requires Executive Accountability

Fixing data isn't a project—it's a transformation in itself. While many institutions have made tactical improvements, systemic change is harder. Legacy reporting practices, siloed systems, and spreadsheet-based workflows continue to undermine progress.

The Standard Chartered misreporting case, which led to a £46.5m PRA fine, illustrates the potential cost of underestimating data integrity. One spreadsheet error cascaded into a months-long regulatory breach. It's not enough to implement tools—banks need a culture of data accountability driven by leadership and embedded throughout operations.

For UK banks, aligning with BCBS 239 remains a critical benchmark. But compliance alone isn't the goal. Forward-looking firms use this moment to re-architect how data flows through their business, with an eye toward future scalability, auditability, and real-time insight.

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How we help

UK bank executives should treat data risk as both a compliance mandate and a strategic opportunity. The institutions that succeed will invest in long-term data strategies with measurable business outcomes.

This means:

• Re-evaluating current data programmes and transformation initiatives.

• Prioritising governance frameworks that extend across business and IT.

• Embedding data accountability at the executive level.

• Partnering with technology providers who understand the complexity of financial services and the regulatory context.

At Digiata, we help banks accelerate this journey—turning data into an asset that enables control, innovation, and resilience. Because in today's banking environment, the most significant risk isn't data—it's ignoring it.

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