Fraud has evolved into a complex, multi-dimensional threat that transcends traditional boundaries. It is a problem that knows no organisational, sectoral or geographic silos.
Criminals collaborate, innovate and exploit gaps across industries and borders to stay ahead of detection. Yet, the organisations tasked with combating financial crime often remain fragmented, operating within isolated silos that hinder effective response.
Fraudsters do not distinguish between public and private sector boundaries, so our efforts to combat fraud must follow suit. Private sector organisations often possess specialised technology, cutting-edge AI and rich data sets derived from real-world commercial transactions.
When combined with government-held data, such as social services, tax records and law enforcement intelligence, the potential for uncovering fraud patterns multiplies exponentially.
Despite this potential, collaboration between public bodies and private companies remains limited, often confined within tightly controlled frameworks and programmes. Regulatory and governance concerns, though valid, frequently serve as convenient barriers to wider cooperation.
GDPR, for example, explicitly allows the use of personal data for fraud prevention, yet compliance teams frequently cite it as a reason not to share information. This cautious interpretation, while understandable, is too restrictive and prevents timely, impactful intervention.
The evolving regulatory landscape
Many organisations remain hesitant to share data due to perceived regulatory risks. However, the UK’s data protection framework is one of the most enabling globally, with clear provisions that support data sharing for fraud prevention and law enforcement purposes.
The issue lies less with the regulations themselves and more with operationalising data sharing in ways that respect privacy while unlocking value. It is essential to move beyond blanket fears of non-compliance and focus on creating trusted environments and protocols.
These include anonymisation techniques, strict access controls and shared governance models that allow data to flow securely without compromising individual rights. Educating compliance teams and decision-makers about these safeguards is vital to overcoming reluctance.
Imperfect data should not delay action
Another common stumbling block is the quest for perfect data. Fraud prevention teams often delay collaboration or model development, waiting for datasets to be complete, clean or comprehensive. This pursuit of perfection, however, can be paralysing.
In reality, perfect data does not exist, and waiting for it risks allowing fraudsters more time to exploit vulnerabilities. Synthetic data offers a promising solution by enabling organisations to develop and test models using realistic but artificial datasets. This approach mitigates privacy concerns while improving model accuracy and robustness.
Similarly, sharing high-level thematic trends, risk indicators or aggregated insights can yield actionable intelligence without exposing sensitive personal information. Taking a pragmatic stance – starting with ‘good enough’ data and iterating as data quality improves – is essential to maintaining momentum in fraud prevention.
Changing the culture
Data sharing is as much a cultural challenge as it is a technical one. Overcoming ingrained risk aversion requires leadership commitment and ongoing education about the tangible benefits of collaboration. Demonstrating what is at stake if data remains siloed – whether increased fraud losses, wasted resources or diminished public trust – helps galvanise action.
Moreover, the public and private sectors need to cultivate a shared sense of purpose and mutual trust. Government agencies must appreciate the innovation and agility private companies bring, while businesses should recognise the strategic value of government-held data. Building this collaborative mindset creates fertile ground for pilots, partnerships and scalable data-sharing initiatives.
Public attitudes toward data use are also shifting. While privacy remains a concern, there is growing awareness – and acceptance – that data is widely used to personalise experiences, enhance services and protect against crime. Consumers increasingly expect organisations to leverage data responsibly to prevent fraud and secure their financial well-being.
A call to action
This evolving public trust must be harnessed by communicating transparently about how data is shared and protected within organisations. Highlighting the collective benefits of data-driven fraud prevention can help maintain public confidence and foster greater cooperation.
Ultimately, the fight against fraud requires a united front. Public and private sectors must break down silos and embrace collaboration as the cornerstone of modern fraud prevention. This means balancing regulatory compliance with innovation, leveraging synthetic data and advanced analytics, and fostering a culture that values shared insights.
With the right frameworks, education and leadership, we can transform data sharing from a cautious afterthought into a proactive strategy that anticipates and disrupts fraud before it happens. Fraudsters don’t operate in silos – so our response to fraud shouldn’t either.
Caroline Payne is a solutions director at SAS
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