Reaction and overreaction: The unemployment insurance disaster
Connecting state and local government leaders
Analytics technology can pore through thousands of unemployment claims filed across many different accounts, reducing fraud and adding speed and confidence to the payment process.
Criminals follow money, and the impacts of the COVID pandemic led them straight to unemployment insurance (UI) programs.
Coming off historically low unemployment rates and staffing, UI agencies were hit with a double whammy of a massive explosion in claims and changes to the system by the CARES Act. How did they respond? By shoveling money out the door with both hands. What was the result? Billions -- most likely, tens of billions -- of dollars, in fraud went to organized criminal networks.
I’ve testified in states across the country and at the federal level about the scourge of UI fraud. Most recently I was in Pennsylvania, where the state’s Department of Labor and Industry was overwhelmed by claims and, despite herculean efforts, is receiving thousands of calls per day from citizens in need. Lawmakers were concerned about threats to its Pandemic Unemployment Assistance Program -- and they are right to be concerned: UI fraud is rampant.
Some examples are stark. My home state of Washington was hit badly by Scattered Canary, a fraud operation conducted by a ring out of Nigeria. Losses quickly grew from $1 million to $300 million to $576 million. At the peak, the state admitted over 56% of all money going out the door was lost to fraud. The same ring hit numerous states, including Massachusetts, Wyoming, Oklahoma, Rhode Island and Florida.
Florida hackers who hijacked computers using malware tried to file $500 million in claims in Maryland. A state contractor hired to process claims for Michigan’s UI agency stole $2 million.
But that’s the tip of the iceberg. The Identity Theft Resource Center has seen 28 times the number of UI fraud cases reported year-to-date in 2020, compared to 2019. The Secret Service reports that UI fraud is now the bulk of its work.
Overreaction hurts people in need
In response to the waves of fraud, states clamped down in the most manual way possible. Agency employees, contractors and in some cases the National Guard were called up to manually process documents. State after state saw backlogs in claims -- tens of thousands in some cases, and more than 1 million in California.
Real people with legitimate claims haven’t received a single UI payment after waiting for two or three months. Or they received assistance for just one or two weeks, then were shut down and caught in an administrative nightmare. For those whose identities were stolen to file claims, it could be even worse as they fight that damaging impact and try to reclaim payments made to criminals.
Legislatures all over the country are making inquiries to find out exactly what happened, and how to set matters straight.
The balancing act
It’s time to think differently. Let’s stop funding identity thieves and bring together multiple datasets within each state to help validate identities and ensure that claims are paid to real Americans who are hurting.
One of the best approaches that could be quickly implemented is to run all the existing claims through analytics software to not only detect fraud and stop future payments, but see who looks like a real person and approve payment immediately.
What does that look like in the data? Here are a couple of examples taken from real-world experience:
- One person laid off from a restaurant in Massachusetts might bank at a small out-of-state bank in Indiana. But if 20 people from that restaurant are all at that same small bank, it’s a huge warning light for identity theft.
- An independent hairdresser shut down during the pandemic can file for Pandemic Unemployment Assistance. The UI agency doesn’t have much information on that person, as they were exempt from previous withholding. But they will have a business license from the state, a cosmetology license and state tax filings. If none of those exist, it’s identity theft.
Even for citizens with legitimate needs, payment speed is inhibited by fears that people will get money they “don’t deserve.” The risks of overpayments of a few hundred dollars that can be collected once people go back to work is small compared to an explosion of fraud.
UI agencies need people to staff the inundated phone lines and to process payments. However, analytics technology can be used as a force multiplier, poring through thousands of claims filed across many different accounts, providing a thorough view of risk, reducing fraud and adding speed and confidence to the payment process.
It’s time to stop rewarding criminals. It’s time to help Americans in need. Let’s get off the seesaw.