To fight fraud, follow the data

Federal program managers are being urged to use data analytics and information sharing to sniff out fraud, abuse and improper payments.

abstract image of money

As federal program managers look to take a more active role in preventing fraud and abuse, data analytics offers a unique opportunity.  According to the Government Accountability Office's Framework for Managing Fraud Risks in Federal Programs, “federal managers have the ultimate responsibility in overseeing how hundreds of billions of dollars are spent annually.” The  framework encourages program managers to actively use analytics as a key tool in securing their finances. The Fraud Reduction and Data Analytics Act, which has been law for over a year, seeks to codify the standards laid out by the framework.

There are several techniques managers can use to spot and prevent fraud, according to panelists at ACT-IAC's July 20 Fraud and Abuse Forum. Data matching, predictive analytics and risk assessments can be a boon for agencies in uncovering fraud or improper payments and preventing future fraud as well as in running cost-benefit analyses to determine the best tech investments.

Linda Miller, now a director at Grant Thornton, led the development of the framework while she was assistant director for GAO’s Forensic Audits and Investigative Services team. At the July 20 event, she encouraged "agencies to think about fraud from a risk-based perspective,” and to proactively use risk assessment.

“You don’t know how much fraud you have,” Miller observed, “because you’re likely not catching most of it.”

The solution, she said, is “to figure out how much fraud you have,” through a “fraud risk assessment at the front end that’s thorough and comprehensive.” Risk assessment is also critical in making the right tech investments for future fraud prevention, she added. 

A January GAO report noted that governmentwide improper payments climbed to $144 billion in fiscal year 2016. The distinction between improper payments and fraud is an important one, as administrative errors can dramatically affect those numbers. Data matching can help identify potential instances of intentional fraud. 

Deloitte's Dave Mader said at the event that when he was controller at the Office of Management and Budget, he helped create different categories for agencies “to start to deconstruct their improper payments so that we could better understand which of those payments was out-and-out fraud.” This was part of an effort, he said, along with the Fraud Reduction and Data Analytics Act, to help agencies “better understand their data” and “better understand that there are different treatments that would be required, based on that analysis.”

The Fraud Reduction and Data Analytics Act also established a working group where agency CFOs meet quarterly to share best practices in fraud prevention. Johanna Ayers, the managing director for GAO's Forensic Audits and Investigative Service team, told FCW she was optimistic about that group's impact. “People are really eager to talk and to learn,” she said.

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