Research & Reports

How AI and generative AI can impact improper payment & FWA detection

Written by Shift Technology | Mar 30, 2024 11:19:00 PM

It is estimated that fraud, waste, and abuse (FWA) is equivalent to 10% of total healthcare spending per year, or more than $400 billion annually in the US alone. That is a staggering figure which becomes even more mind boggling when we begin to think about it on a global scale. Yet, despite the impact FWA, improper payments, and other errors have on health plans, honest providers, and patients, it has remained difficult to overcome. Why is it so challenging for health payor organizations to spot, and stop, fraudulent behavior?

In this edition of Shift Insurance Perspectives we explore the world of FWA and improper payments, and the approaches health payors can take to mitigate the financial and operational impact of fraud on their organizations. 

We examine the importance of data, and why understanding “who’s who” in your provider network is critical to anti-FWA initiatives. We address how third-party and external data can be used more effectively in the fight against FWA. We illustrate how artificial intelligence (AI) can bolster both postpay and prepay detection efforts. And, we take a look at how emerging technologies such as generative AI are driving new fraud trends, and being used to stop them.

 

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