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Report: What 100 Healthcare Execs Had to Say About Using AI to Stop Fraud, Waste and Abuse

The average United States healthcare insurer has 22% of all claims flagged for fraud, waste and abuse (FWA) investigation, costing them roughly 12% of the revenue they generate annually. They are therefore wrestling with a dire need to streamline the claims process to boost their bottom lines.

Artificial intelligence (AI) can help streamline insurers’ claim processes, ultimately reducing the cost of FWA compliance — and insurers know it. Ninety-seven percent say that AI is an important tool, as it has the ability to adapt to changing behaviors exhibited in data claims, and 96% say it is important for having a high level of accuracy in detecting FWA. Still others see AI as critical for being easy to use and capable of scaling their current operations and reducing provider abrasion. Yet many insurers are either not using AI or are not properly equipped to handle their claims processes, as is.

AI In Focus: The Healthcare Technology Roadmap, a collaboration between PYMNTS and Brighterion, a Mastercard company, provides an overview of U.S. health insurers’ AI and machine learning (ML) investment outlooks. We surveyed 100 executives from healthcare insurance businesses across the nation to discover how they are using AI- and ML-enabled technologies to streamline their claims processes, detect and prevent fraud and enhance their payments operations.

PYMNTS’ research shows that many insurers not only understand the myriad benefits that AI can provide, but they are also taking active measures to expand their AI capabilities. Seventy-five percent of all U.S. insurers plan to invest in AI to improve their payment integrity within the next three years, in fact, with nearly 4% planning to do so within the next year.

AI is not the only technology in which insurers are investing, either. There are a wide variety of ML technologies that are also top priorities for businesses in the U.S. healthcare sector. Seventy percent of healthcare firms plan to invest in deep learning and neural networks in the next 12 months, for example, making it their most common investment area of all. There are also 19% that intend to invest in case-based reasoning and more than 9% who will invest in data mining in that time.

Investing in such technologies is only the first step in a much more complex story about the growing importance of AI and ML in the healthcare industry. AI In Focus: The Healthcare Technology Roadmap provides a close examination of where insurers’ AI and ML strategies are headed and the hurdles they must overcome to tap AI and ML’s full potential.

To learn more about how health insurers plan to incorporate AI and ML into their broader claims strategies, download the playbook.

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