People in line at unemployment office

Michigan turns to analytics to stop fraud, waste and abuse

Michigan officials are looking to fight fraud, waste and abuse in the state’s unemployment insurance and food stamp programs, with the goal of spotting fraud across all executive branch departments and programs.

Unemployment insurance, mandated by federal law and administered by state governments, provides a temporary safety net for workers who lose their jobs. However, in 2012, $10.3 billion in improper unemployment insurance payments were made across the country, according to Labor Department figures listed on the website.

Michigan officials, looking to curtail fraud and get assistance to the people who really need it, have selected SAS Analytics to power Michigan’s Enterprise Fraud Detection System, state officials said.  Michigan's Department of Technology, Management and Budget chose the SAS Fraud Framework for Government to detect where fraud occurs, as well as to uncover improper claims before they are paid, in an effort to avoid costly and high-risk collections, they said.

The EFDS initially will integrate and analyze data from the Michigan Unemployment Insurance Agency and the state's Departments of Human Services and Community Health. Additional data sources will be added over time.

Spotting fraud, waste and abuse has become a major concern for states, especially in an era of limited budgets and resources. For example, Georgia is using the LexisNexis Tax Refund Investigative Solution to spot identity fraud. The LexisNexis solution uses identity verification and authentication tools to detect and prevent potentially fraudulent tax returns.

Analytics software require a whole new way of thinking about how to measure data to make the right decisions, industry experts say. For example, in the case of waste, fraud and abuse, organizations need to examine the factors that caused the fraud to occur instead of just measuring the fraud.

About the Author

Rutrell Yasin is is a freelance technology writer for GCN.


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