SIUs are faced with unprecedented challenges that require a unique skill set complemented by the most current and innovative technologies. In a fireside chat at the NHCAA 2020 ATC, Tim McBride, AHFI, and Jessica Gay, AHFI, will address how AI prevents healthcare FWA and increases SIU efficiencies.

At the upcoming NHCAA 2020 Annual Training Conference, Tim McBride, the Director, Product Development, Cyber and Intelligence Solutions at Mastercard, will discuss techniques for special investigation units (SIUs) in healthcare fraud, waste and abuse (FWA). Tim puts things in context as the world grapples with a global pandemic.

While healthcare fraud in the U.S. was about $300 billion in 2019, experts are unsure what the unexpected costs will be after COVID-19. Tim thinks telehealth is particularly vulnerable as under the CARES Act many safeguards designed to protect the ecosystem have been eliminated or eased to reduce barriers to care, making it easier/safer for patients to receive medical attention during the pandemic. Meanwhile, service providers are continuing to defraud payers billions of dollars for durable medical appliances, coronavirus “cures,” bogus rehabilitation programs and more. The FBI website is a veritable ticker tape of fraudsters.

AI detects FWA in real time to enable prepay models in healthcare

Tim is a big fan of using AI models to reduce rules and create efficiencies. As he likes to point out, rules become dated very quickly as fraudsters evolve their schemes to stay ahead of detection. The AI model learns from the known patterns of FWA and leverages its learning capabilities to identify additional FWA beyond fixed concepts/algorithms/rules. As a result, AI can detect fraud both pre- and post-payment, potentially shifting away from the “pay-and-chase” paradigm.

AI tools continuously refine models for performance and accuracy, reduce maintenance, increase efficiencies, detect fraud in real time (before payments are made against bad claims) and identify previously unknown fraud schemes.

AI models reduce rules and create efficiencies

The presentation will touch on the rules-compared-to-AI-models debate that continues on in healthcare. Payers have traditionally stuck to using rules-based decisioning to identify FWA, but Tim plans to make the case for using AI models to reduce rules and create efficiencies, thereby generating revenue and operational efficiency. In his own career as an investigator, Tim says, “having AI would have given me back at least 30% more time to investigate fraud (instead of updating rules).”

AI Express, Mastercard’s AI platform, develops a working AI model that is trained on a company’s historical data within six to eight weeks, and continues to learn once in production.

Tim will also talk about recent case studies to illustrate how Mastercard’s AI detects and prevents healthcare FWA and reduces false positives by 10 to 20 times.

How Mastercard’s AI experience benefits your organization

Mastercard has become a respected leader in the world of developing AI solutions to detect fraud and anomalous activities. Mastercard has evolved into a technology company with roots in payment services. What started as a mission to protect its own customers has evolved into something much bigger.

Mastercard develops AI solutions that are uniquely coded to perform at scale for speed and reliability. In fact, 100,000 transactions are analyzed for fraud and processed every second of every day.  It also can use data from any source and in any format. Regardless of an organization’s claims data and format, the platform automatically refines and processes the data.

Best of all, it comes with Mastercard’s expertise in preventing fraud. At the end of the day, McBride reminds us, the AI model is built to find anomalies in data and flag them for investigation.

Visit Mastercard Healthcare Solution’s virtual booth at the NHCAA 2020 Annual Training Conference, November 17-19, to engage with one of our AI for FWA experts, book an appointment for a private consultation or view informative videos, infographics and e-books.