The proportion of benefit expenditure overpaid remains too high, a new report from the National Audit Office (NAO) has found – though the figures for 2024-25 suggest that overpayment levels are now reducing due to the DWP’s recent interventions.

The estimated proportion of benefit expenditure overpaid fell from 3.6% (£9.7 billion) in 2023-24 to 3.3% (£9.5 billion) in 2024-25, while the estimated Universal Credit overpayment rate dropped significantly from 12.4% in 2023-24 to 9.7% in 2024-25.

The government has given the DWP £6.7 billion of dedicated funding for fraud and error activity over the nine years from 2020-21 to 2028-29, which it says will enable the department to increase the scale and impact of its approach.

Since April 2022, the DWP has mainly used the funding to scale up its programme of Targeted Case Review of Universal Credit claims, increase its counter-fraud staff and expand its use of data analytics to tackle fraud and error.

It says its new strategy incorporates a greater focus on prevention alongside its ongoing detection activity.

The NAO’s report finds that stopping overpayments before they occur is the best way to secure value for money in this area.

As part of its efforts to reduce fraud and error, the DWP is working to expand its innovative use of data analytics. For instance, since May 2022, DWP has used a machine learning model to flag potentially fraudulent claims for Universal Credit advances, saving an estimated £4.4 million.

However, concerns have been raised by the Public Accounts Committee about the potential impact of machine learning on vulnerable claimants.

In July 2025, the DWP published, for the first time, detailed information on its fairness analysis, which showed that older claimants (in age groups 45 to 54 and above) and non-UK nationals were being over-referred for review, with these groups being more likely to be asked to find and provide additional evidence for their claim.

In terms of performance, the DWP found the machine learning model to be around three times more effective at identifying fraud risk than a randomised control group sample.

As such, the department concluded that it remains reasonable and proportionate to continue operating the Universal Credit advances model as a fraud prevention control, but it would continue to seek to improve its effectiveness.

The DWP also successfully scaled up its Targeted Case Review (TCR) programme to detect and correct fraud and error in existing Universal Credit claims, with around 6,000 staff (in-house and outsourced) carrying out reviews by March 2025.

A total of 1.15 million claims have been reviewed, generating estimated total savings of £581 million from TCR, by March 2025.

This exceeded the DWP’s savings expectation by 11% although it did not meet its expectation for the proportion of reviewed cases found to be incorrect.

The total that the DWP expects to save from TCR has increased significantly over time – from an initial target of £2 billion in savings by 2026-27, to £13.6 billion by March 2030.

The NAO recommends that the DWP should finalise its approach to implementing its fraud and error strategy and should progress its ambition to reduce the overpayment rate to the pre-pandemic level.

Beyond this, DWP should focus on getting the overpayment rate down to a level that represents a cost-effective control environment.

The report also recommends that the DWP should build on its existing use of data analytics to explore how these emerging technologies may help to detect and prevent fraud and error.

Gareth Davies, head of the NAO, said: “The Department for Work and Pensions has made real progress in tackling the levels of benefit overpayments due to fraud and error, but there is still a way to go. With the increase in funding and the greater focus on prevention, the next few years will be key to its success in addressing this long-standing issue.

“The government should carefully consider the challenges and the recommendations outlined in today’s report if it is to build on its progress so far.”