Tackling fraud in government with data analytics
Government wants to hear the views of citizens, academia, and industry on how we can approach the challenges of using data and analytics to counter fraud in the public sector.
Documents
Details
Over the last few years the Cabinet Office has been exploring how data can improve counter fraud in government, working in collaboration with the private sector and academia. Now we would like to open-up this conversation further. This thought paper summarises the key challenges government faces when employing data analysis and data sharing to counter fraud, and asks you to share your own thoughts and the insights of your experience as we explore how to address them.
The Cabinet Office’s Counter Fraud Centre of Expertise has spent the last four years working closely with departments across government and across the United Kingdom to identify where and how they can share their data to identify and prevent fraud. This work has pioneered new approaches to counter fraud, and has been improved through cross-sector collaboration.
Government faces many challenges as we continue working to make more and better use of the data we hold. The National Audit Office has recently published a report on the challenges of sharing data in government and we continue to explore how we can move away from siloed ways of thinking and make sharing information more commonplace. Sharing this information, when secure and appropriate, will enable better decision making and improve the services we are able to deliver to the public.
We are asking you to read this paper and contribute your own experience and insight to a conversation asking how we can take on these challenges. Please help us to safeguard the public purse and ensure it is used to deliver the best public services to the citizens of the United Kingdom by engaging with us now.
Email your responses to us at fraud.data@cabinetoffice.gov.uk or send them to us at:
Counter Fraud Centre of Expertise
Cabinet Office
70 Whitehall
Westminster
London, SW1A 2AS