What the UK’s Fraud Strategy 2026 Means for Data‑Driven Fraud Prevention

Fraud prevention must move from reaction to disruption – using data to intervene earlier in the harm cycle.

According to the National Crime Agency, fraud is now the most common crime affecting both individuals and businesses in the UK, with an estimated 3.9 million incidents in the year ending September 2024. In response, the UK Government published its Fraud Strategy  on 9th March, setting out a renewed approach to tackling fraud at scale, across borders, and earlier in the harm cycle.

A central theme of the strategy is clear: fraud prevention must become proactive, data‑driven, and targeted. This marks a deliberate shift from reaction to disruption, underpinned by three core pillars:

• Disrupt - Stop fraud before it reaches victims.

• Safeguard - Reduce vulnerability by building resilience across the economy.

• Respond - Intervene earlier using intelligence and data.

The first two pillars signal a material change in how public sector bodies are expected to operate. Rather than focusing primarily on investigation after loss has occurred, the strategy sets a clear ambition to halt and prevent fraud in the first place. While rapid response is essential, the emphasis moves away from purely tactical “firefighting” towards deeper, sustained analysis of organised fraud networks, to enable coordinated, intelligence‑led action across government, law enforcement, regulators, and industry.

Data models at the heart of fraud prevention

For UK public sector organisations, one section of the new strategy is particularly significant. The Government confirms it will:

“Use advanced data models to identify fraud hotspots and deploy targeted interventions, especially to the most vulnerable.” 

This is an explicit endorsement of data driven intervention as a core operating principle, not a supporting capability. So, what does this mean in practice? 

• Moving beyond static rules and manual reviews, to automated, data‑driven assessment during onboarding that identifies fraudulent or suspicious entities early, while allowing legitimate organisations to progress more quickly.

• Prioritising resources where harm is most likely to occur.

• Allowing teams on the ground to act earlier, before fraud scales.

For departments and agencies, this places higher importance on high quality, and explainable signals that can be operationalised, governed, and shared.
 

Targeted intervention, not blanket controls

The strategy also places strong emphasis on proportionality. Targeted intervention is prioritised over blanket enforcement, particularly in procurement, grants, supplier onboarding, and business engagement, where excessive friction can slow delivery or exclude legitimate organisations.

By combining commercial risk data points with fraud intelligence and signals, public bodies can automate tiered decisioning: low‑risk entities can progress quickly, medium‑risk entities should be continuously monitored automatically, and high‑risk clusters should be escalated for further review by internal teams. This approach both reduces fraud and helps increase operational efficiency.
 

Collaboration and shared intelligence

Organised fraud risks – such as bid rigging, hidden connections, and criminal links - rarely sit in isolation. They are systemic, and emerge across networks, supply chains, and jurisdictions. The strategy reinforces the need for shared intelligence across now only government departments and agencies, but also between the public sector and wider industry. 

For this to be a success, this sharing should be underpinned by consistent, standardised signals and trusted data foundations that are interoperable.

Challenges in practice

The message from the new Fraud Strategy is unambiguous. Fraud prevention must happen earlier, using insight across the entire fraud landscape rather than on a case‑by‑case basis. 

The challenge has shifted from whether advanced data models should be used to how effectively they can be embedded into day‑to‑day operations. Having the data is one thing, but the ability to join the dots is often a challenge.
 

Using data to effectively disrupt fraud

Elevated risk often points to fraudulent activity emerging further along the chain. Dun & Bradstreet has experience when it comes to supporting the public sector in evaluating many different risk areas, and we can help departments and agencies to align to the new Fraud Strategy.

We provide signals and indicators that can help to pinpoint suspicious information and known fraudulent activity. These signals can be overlaid with other risk indicators across a supplier portfolio and continuously monitored to identify emerging risk, fraudulent activity, or entity changes, so hotspots can be addressed before fraud scales. By turning individual red flags into actionable risk hotspots, public bodies can intervene earlier, allocate resources more effectively, and disrupt fraud before it scales.

Furthermore, our data is standardised and anchored on our unique business identifier, the D-U-N-S number. This means it is already set up for cross-department sharing and interoperability with different technologies and systems.

The result is not simply better fraud outcomes, but a more efficient and resilient system overall.