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As the need for unemployment insurance swept the nation, benefits agencies across the country stepped in to provide aid to those in need. Alongside the uptick in volume, new legislation and inefficient legacy systems created a perfect storm for errors or fraud, meaning many benefits didn’t reach those who truly needed it.
To reduce improper payments and streamline the system, agencies need a way to analyze applications and identify potential errors. But this is no easy feat when more than 18 million Americans are collecting unemployment.
Modern AI solutions can offer an answer.
To help wade through and analyze applications, the Oklahoma Employment Security Commission tapped an AI-based solution from data analytics company SpringML. Making use of Google Cloud tools, the solution uses artificial intelligence and machine learning to uncover suspicious patterns, detect fraud and improve verification.
So, how did the OESC make use of AI and ML to improve benefit integrity? And how can your agency do the same? That’s exactly what we’ll be speaking about on this episode of AI: Gov Reimagined, a podcast from Google Cloud and GovExec’s Studio 2G. Joining our host James Hanson, group publisher for Federal and Technology Markets at GovExec is Denise Winkler, strategic business executive for Global Public Sector at Google Cloud; Arun Natarajan, director of Cloud & Platform Partners for SpringML; and Shelley Zumwalt, CEO and Executive Director at OESC.
Check out what they have to say by listening to the full episode below. Or download and subscribe on Apple Podcasts, Spotify or SoundCloud to take AI: Gov Reimagined with you on your favorite device.
This content was produced by Government Exec’s Studio 2G and made possible by our sponsor, Google Cloud. The editorial staff of GovExec was not involved in its preparation.
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