Data-driven solutions will help tackle fraud and error in the welfare system

4 August 2016

Losses recorded by government due to fraud and error overpayments in the welfare system remain persistently high – totalling £4.6 billion in 2013-14 alone. The drain this has on public finances has been well documented, but fraud and error also causes harm to the most vulnerable in society: claimants were underpaid by £1.6 billion in 2013-14, creating additional hardship for those that can least afford it. This issue, and the question of what more we can do to tackle it, was the subject of a Reform roundtable sponsored by Liberata last month.

In recent years, policymakers have made headway on this issue. Total losses were cut from 2.1 per cent of the Department for Work and Pensions budget in 2010 to 1.8 per cent in 2016. And attendees discussed the potential for the use of data analytics and real-time information, underpinned by the rollout of Universal Credit, to open up new avenues for identifying fraud and error. The results of a 24 month pilot led by Liberata show they have good reason to be optimistic.

Undertaken in partnership with twelve local authorities, GB Group, and supported by funding from the Department for Communities and Local Government, the objective of the pilot was to identify fraud and error in Housing Benefit (HB) and Council Tax Reduction (CTR).

The solution that Liberata built to meet that objective has three key components: enriched data; enhanced analytics capability; and an experienced operational team. We began by collecting and cross-referencing information from a variety of Credit Referencing Agencies and new third party sources – both open and commercial – on a range of issues, such as identity and address, income, occupancy and property. This allowed us to undertake a far richer analysis than with previous models, spot mis-matches in eligibility and ensure our records were correct. We then deployed our manual process, led by a team with unrivalled experience, to investigate high risk cases and pinpoint those that were fraudulent or erroneous.

The results were impressive: across the cases that our system flagged as needing further investigation we achieved a success rate of 39 per cent on CTR adjustments and 44 per cent on HB overpayments. This represents a considerable improvement on current levels and secured a total saving of over £3 million across the twelve local authorities, making a really meaningful dent into their fraud and error targets. Underpayments were also identified and subsequently corrected in approximately 10 per cent of cases that were reviewed.

Yet the success of the pilot extended beyond a significant increase in success rates. It also gave us a clear and fresh insight into why fraud and error occurs in the first place. Incorrect information regarding income (48 per cent) and household circumstances (14 per cent) were the most common causes of fraud and error, with identity and address (40 per cent), income (17 per cent) and property (5 per cent) being the most effective data sources we used.

Liberata is doing further exciting work in this area, working with the Department for Work and Pensions to apply our solution across Jobseeker’s Allowance, Income Support and Pension Credit Payments. But if we are to achieve a real step change it will be crucial to take these findings, and those from other successful initiatives, and apply them right across Whitehall and local government – ensuring we take a collaborative and joined-up approach to tackling this billion pound question for the benefit of both taxpayers and vulnerable people.

Charlie Bruin, Chief Executive, Liberata



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