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Finding the Fraudulent Needle in the Haystack

So, exactly how would you go about finding a needle in a haystack? 1. Eliminate the haystack. Probably the fastest way to find the needle is to burn the haystack. Or dumping the hay into a pool of water and waiting for the needle to sink to the bottom would also work. If we were really talking about needles and haystacks, fine – but we’re not.

 · When it comes to detecting insider trading, it really is like finding a needle in a haystack with more than 15,000 different stocks, options and bonds trading every day across millions of transactions. Yet, Sam Draddy and the Insider Surveillance team in the Office of Fraud Detection and Market Intelligence manage to find those needles.

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Finding the evidentiary needle demonstrating fraud in the big data haystack By Samir Syed, Senior Manager, kpmg forensic services, KPMG in canada. nate silver may have been talking about politics and baseball, however forensic accountants using data analytics to look for signs of fraud would do well to pay attention to his credo.

Food fraud detectives count on scientific instruments to. Ghosh says. “Our emphasis is on finding the needle in the haystack.” Near-IR and time-of-flight mass spectrometry (TOF MS) are rapid.

 · So, fraud, for now, isn’t trending for the worse or the better. But, the change rate for the fraud index cited in the headline is about as informative as the national change in house prices. Just as real estate is local, so is mortgage fraud! The five riskiest states for mortgage fraud are Florida, Michigan, New Jersey, California, and New York.

And, while the data is there, it’s difficult to find the fraud indicators amidst the huge number of daily transactions. So, what can we do in the face of all this data? How do we find the needle in the haystack? We have to take it one step at a time.

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However, some of those needles are bent — they’re fraudulent. Data mining acts like a giant magnet that pulls the needles out of the haystack so the fraud examiner can sort them, find the fraud, and reduce overall waste and abuse. Of course, advances in computer technology and data-mining software have revolutionized fraud detection.

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