The government is failing to put data analytics in the most effective way to work to tackle fraud and error, according to a new report by the National Audit Office (NAO).
The cross-government report examines how well placed government is to seize the opportunity offered by old and new data analytics technologies to tackle the problem – which the NAO estimates cost the taxpayer between £55 billion and £81 billion in 2023-24.
The NAO said the use of data analytics can achieve significant returns on investment.
“Counter-fraud experts, within and outside of government, consistently told us that data analytics needed to be a key part of any plan to reduce fraud and error. They highlighted how data analytics can help ensure public bodies pay the right amount to the right suppliers, receive the right amount of tax revenue and only pay grants or benefits to eligible recipients,” it said.
But to date the savings have been “relatively modest compared to its overall potential and the value of taxpayer money lost to fraud and error.”
It goes on to say there “is a clear mismatch between the scale of the problem of fraud and error and the lack of concrete plans to implement better data analytics.”
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The NAO said the Public Sector Fraud Authority (PSFA) needed to help government work with departments and their arm’s-length bodies to innovate and generate significant fraud and error savings. But it cannot do this alone, it added.
The Government Digital Service (GDS) needs to make sure its work facilitates fraud and error analytics, “as this is such a significant component of its vision for achieving cost savings through digital government. Additionally, other functions need to acknowledge their responsibility to use and implement data analytics to help prevent waste.”
A good test case for AI
GDS believes government could save as much as £6 billion a year by using data analytics to help tackle fraud and waste. It based the figure on the savings the Department for Work & Pensions (DWP) has achieved in one example of data analytics and applied these savings to PSFA’s estimate of the level of fraud and error across all of government.
Some other parts of government also already use data analytics to save money by preventing fraud and error, or by recovering money lost to fraud and error. Alongside DWP, HM Revenue & Customs (HMRC) have been using data analytics to tackle fraud and error. But most tools used in government bodies are designed to detect fraud and error, rather than prevent incorrect transactions before they are paid, said the NAO.
The report went on to say that tackling fraud and error is a good test case for new technologies in data analytics such as AI.
It noted: “In theory, with good-quality linked data, these technologies can deliver more immediate returns on investment, tackling fraud and error without requiring the wider system or organisational reform that fuller digital transformation would require.”
