Big data could tackle £2.8bn lost to benefit fraud

Business Intelligence

by Claire Vanner| 17 January 2014

Analytics offers potential for zero-tolerance approach.

Benefit fraud and claimant error overpayments cost taxpayers £2.8bn last year, according to government figures.

While this may seem a positive step as the government said the level of fraud and error in the benefits system was lower than three years ago, it is still a substantial loss that could easily have been prevented.

"The use of big data analytics gives public sector organisations power to gain insights into fraud, so it can enforce a zero tolerance approach," said Amanda Gardiner, public sector fraud expert at SAS UK.

"Fraudsters can be swiftly identified when the public sector treats its information as an asset, collecting it, valuing it, and analysing it in smarter, more efficient and effective ways to tackle this problem. Detection is further improved if the data and insights from data are shared across departments," she added.

"A lot more than data matching is required. A hybrid approach is needed - not just traditional analytics, but other techniques such social network analysis (understanding how various parties are connected) and detection of anomalous behaviour are required to build a more complete picture. While the drop in fraudulent benefits claims is to be welcomed, there is still a considerable level of fraud across the public sector that needs to be tackled," she said.

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