Welsh auditor unearths £4.4m of fraud and overpayments

20 Jul 16
Around £4.4m of fraud and overpayments have been identified in Wales through the latest National Fraud Initiative, it has been announced.

In a report released today, the auditor general for Wales outlined the findings of the latest biannual counter-fraud exercise, covering the period 2014-15.

The initiative has uncovered and prevented fraud and overpayments worth £2.14m in Council Tax Single Person Discount and £1.6m in Housing Benefit.

The National Fraud Initiative matches data across organisations and systems with the aim of helping public bodies identify and eliminate fraudulent or erroneous claims and transactions. Since it was created in 1996, the NFI has identified around £30m in fraud and overpayments, and £1.39bn across the UK.

As the independent statutory external auditor for most of the Welsh public sector, the auditor general is responsible for the annual audit of the majority of public money spent in Wales.

The latest exercise saw forty-two Welsh public sector bodies participate, including local authorities, police and fire authorities, and NHS bodies. Also, the Welsh government, Cardiff University, Welsh education inspectorate Estyn, and the Wales Audit Office participated in the NFI on a voluntary basis.

In a statement, the auditor general highlighted the fact that Welsh public bodies are facing their “biggest challenge for a generation” and that they needed therefore to reduce waste and inefficiencies to reduce the impact on front line services. 

Auditor general for Wales, Huw Vaughan Thomas, said: “Fraud impacts on the level of funding available for front line services, so fighting fraud must remain a key element in ensuring that limited public funds are used effectively.”

“The National Fraud Initiative is a highly effective tool which continues to play a vital role in the fight against fraud,” he added.

“I am continuing to implement a strategy for widening participation and usage of the NFI in Wales and encourage further potential data matches that could help in the prevention and detection of fraud.”

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