How big data is foiling fraud

By Danny Palmer
27 Dec 2013 View Comments

The terms “big data” and “analytics” are often thrown around by large organisations, particularly with an emphasis on how analysis of customer behaviour can lead to a better experience for consumers.

However, analysing big data can lead to much more than just a discount voucher for a tin of beans, with governments increasingly turning to analytics in the fight against fraud, for example. 

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A recent report by analytics provider SAS argued the government could retrieve much of the £20bn it loses through such activities as tax evasion and benefit fraud by properly harnessing big data.

“Wherever analytics is brought to bear, you either find what you would have found already much quicker, or you find things that would not otherwise have been detectable by a human,” Simon Dennis, central government director at SAS, told Computing. “A computer can look at big data and find something that looks interesting, or a pattern that a human couldn’t see.”

Dennis said SAS has beening working with HM Revenue & Customs (HMRC) since 2005, and has helped it to recoup billions in that time, partially by using analytics to detect behaviour patterns.

According to Dennis, the technology is capable of spotting such things as an official accepting bribes before issuing permits. “What an analytical system can do is spot that someone’s behaviour when issuing some permits was different than others,” Dennis explained.

“By observing that person the computer would say ‘this looks odd, don’t know why but once in a blue moon operative 7 does something different, so let’s look at what he’s doing’. When you then put them under observation you find they’re ringing people saying ‘I’m your permit officer, give me £1,000 or I’m going to refuse it’.”

HMRC expects to recoup £7bn by using technology to detect corruption like that described above.
It’s not just the UK that’s exploiting the power of analytics to combat fraud. SAS has worked with the Belgian government in preventing the theft of VAT by networks of conspirators estimated to be worth €1bn a year.

Authorities in the US are also seeing the benefits of analytics in the fight against fraud. Agencies including New York City Human Resources Administration, Georgia Department of Revenue and Florida Department of Children and Families all use LexisNexis’ HPCC Systems big data platform.

All three have been able to use analytics to detect and eliminate cases of fraud involving the use of bogus details or addresses.

“The New York City Human Resources Administration uses LexisNexis to both verify eligibility for benefits, and to identify and prevent fraud. Our agency needs to be sure people applying for benefits are who they say they are and they live where they say they live,” explained NYC Human Resources Administration deputy commissioner Saratu Grace Ghartey.

The agency uses algorithms to detect false claims, something that wouldn’t be possible without the use of LexisNexis.

“We also need to ensure that they haven’t misrepresented their incomes or assets. We use LexisNexis’ extensive databases to proactively data mine: we have created algorithms that identify fraud profiles and we routinely match our clients against ‘wealth indicators’ such as business affiliations, luxury car ownership,” she said.

“Using data this way allows us to better focus on our efforts to save New York City and taxpayers money, and provide help to those who really need it,” Ghartey added.

While significant savings have already been made by a number of governments through using analytics to counter fraud, there are many who have yet to even experiment with such techniques. But according to SAS’s Dennis, it represents an opportunity for better outcomes and even a change in culture.

“The real value in using analytics that civil servants have to make is actually look at the data and have the analytics tell you what the answer is rather than predisposing it. That’s quite the leap to actually be led by the analytics rather than try to use them to improve the speed of what you always did,” he said.


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