According to a Wall Street Journal article, forensic accountants recently uncovered
a several hundred thousand dollar fraud committed by employees at a national
call center simply by “wielding mathematical weapons.” Using data analysis,
they were able to identify a number of fraudulent refunds that call center
employees were issuing. The find was critical to the company as it helped them discover where they were losing a lot of money.
Benford's Law |
The forensic accountants who detected the fraud at the
call center used a mathematical test known as Benford’s Law. Contrary to
popular belief that there should be an even distribution in the starting digits
of numbers, Benford’s Law says that “more numbers start with one than any other
digit, followed by those that begin with two, then three, and so on,” and that “ones
should account for 30% of leading digits, and each successive number should
represent a progressively smaller proportion, with nines coming last, at under
5%.” In the case of the call center, the forensic team noticed an exceptionally
large percentage of refund amounts where the starting digit was a four. It also
happened to be that employees could issue refunds to customers up to $50
without needing additional supervision. By using Benford’s Law and investigating
the transactions where the leading digit was a four, forensic accountants
discovered a small number of operators at the call center “who had issued
fraudulent refunds to themselves, friends and family totaling several hundred
thousand dollars.”
At first you might think that fraudsters could learn about
Benford’s Law and then make sure that their fraud doesn’t violate any of the
statistical properties that the law says should be present. However, Mark J.
Nigrini, accounting professor at West Virginia University, says that “while you
are doing your scheme, you don't know what the data look like. It's a little
tricky to beat Benford's.” With employee fraud costing companies throughout the
country around $300 billion each year, data analysis is becoming more and more
common among auditors and forensic teams, and it is becoming much more
difficult for people to commit a fraud in such a way that data analysis can’t
detect the fraud. As data analysis continues to improve, I think we will see
more and more frauds uncovered that in the past could be hidden from a human
but now can’t be concealed from the math.
See this link for
an article in The Journal of Accountancy
that Mark J. Nigrini wrote about Benford’s Law.
What do you think this type of mathematical analysis could tell investigators about the herbalife MLM? Do the SEC and FTC conduct these kinds of forensic audits?
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