As states raced to distribute unemployment benefits during the COVID-19 pandemic, government watchdogs warned that state workforce agencies were facing challenges detecting and deterring fraud.
In a 2020 audit, the Department of Labor reported that 98% of respondents said their state faced challenges implementing the Pandemic Unemployment Assistance program, which allowed claimants to certify their own eligibility. Although 91% of unemployment administrators used a variety of tools to combat fraud, 53% still cited vulnerabilities, according to the audit.
In the two years since, the toll of likely fraud has crept past $57.3 billion. Although some states are struggling more than others to modernize their unemployment programs, partnerships with the federal government can help them implement new data- and evidence-based approaches to fighting fraud.
Ohio created an entirely new PUA system that has become a model. First, the state formed a public-private partnership to determine the needs of its Department of Job and Family Services. Officials then used the existing InnovateOhio Platform, a state-run data-integration hub, to curate and combine relevant information to evaluate claims as they came in. This approach has helped the state identify likely fraudulent claims so legitimate ones can be prioritized.
Data visualization and interpretation is only part of the challenge, however; the other part is that the new tools rely on updated information technology infrastructure. Although plans to modernize unemployment insurance systems have been around for years, the pandemic helped catalyze action in many states. Vermont, which relied on a 52-year-old mainframe for handling UI benefits, had been working to modernize its system since 2017. The pandemic created pressure to accomplish the goal immediately—and the state did. Having already laid much of the groundwork, officials created and implemented a new data-driven system in just 11 days.
The focus on data improvement extends to the federal level, too. The Labor Department began dispatching “tiger teams” to assess areas for improvement in state UI programs. The experts have already been to 18 states and recommended changes for translation, disability access, unblocking bottlenecks and improving data. States that adopt the proposed changes will be eligible for federal funding to implement them. Which states choose to do so remains to be seen.
Zaakary Barnes is a policy specialist in NCSL’s Employment, Labor and Retirement Program.