Connecting the Data Dots for Better Fraud Defense

When I helped revitalize a fraud program for a state revenue department, I was surprised by what the data told us. Why, for instance, would identity theft fraud be concentrated in counties starting with an ”A” but improper deductions be concentrated more haphazardly? Why did the state suddenly get a surge of part-time residents? How come electronic tax filing was climbing in numbers faster than the population growth rate?

The answer to these questions made more sense when we started thinking of the fraudsters as businessmen. These were criminal business reactions to our budding fraud defenses. A preponderance of identity fraud occurred in counties starting with ”A” because the fraudsters don’t like to scroll all the way to ”Z” on our county drop down menus. Fraudsters found that filing as part-time residents is another way to maximize their profit and lower their risk by sending in more refund returns. And those higher electronic numbers? You can sit in Florida and do tax returns for lots of states with just one stolen identity.

Our math guys kept talking about correlations. A correlation can be described as an unexpected relationship. As we started thinking about how to commit fraud against our systems, the correlations became more logical. None of these relationships should have been unexpected. They are simply the ”bad guys” doing good business. Then we came to the conclusion that the fraud program for the Department of Revenue was not really able to encircle the problem. Identities are not stolen from states; they are just used against Revenue departments, as one example. Tax fraud is just another way to monetize identity theft, and it might be becoming more prevalent as fraudsters run into defenses elsewhere. This prompted some questions, like the following:

  • Are all state departments victims to the same identity-based attacks?
  • Are the mills where criminals are filling out multiple tax forms moving to Medicare fraud after tax season?
  • Are the people who take very improper deductions also cheating on their benefits requests?

Every department, agency, credit card company, and business has fraud departments. And we hold on tight to our fraud data to the great benefit of the criminals. There are indications that there are correlations between Medicare fraud mills and tax fraud mills, or that people who lie on one government form are more likely to also lie on another, or that identities fraudulently used against one state’s revenue department are vastly more likely to be used against other states.

Look at what the data can tell us. I would love to share my data with you, but that would make me a criminal.


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Matthew Donahue is an information technology consultant with roots in the telecommunications industry. He has headed change management initiatives with several federal and state government agencies. As the former commissioner of the Indiana Department of Revenue, he helped them save over $200 million and identify thousands of identity theft victims. He is currently advising a large client in raising fraud awareness and heightening protection against systems intrusion. He is also supporting the Internal Revenue Service Security Summit process. An Indiana native, he earned both his MBA and bachelor’s degree from Purdue University.