Predictive Analytics Case Study: Syed Mehmud, ASA, FCA, MAAA
Syed Mehmud has always had a disruptive mindset.
That's how he refers to his natural tendency to observe, question and look for ways to make improvements on things by making them more efficient and intuitive.
Mehmud did not study actuarial science in school. He earned a degree in mathematics and physics while taking courses like Asian history and skeptical thinking. In retrospect, he said, his exposure to a liberal arts education allowed him to view problems with a multifaceted perspective.
As a result, Mehmud has been able to understand his audience and tailor the products he designs accordingly.
It was in 2003 that Mehmud saw a rising tide of data that would soon reach a crest of "too much information and not enough insight." He identified a need to radically revamp actuarial tools to deal with the onslaught. That's when he decided to make actuarial science his life's work.
If actuaries continue to develop new techniques, they can start thinking about solutions to questions they haven't even asked yet, Mehmud said. They also can fill a vacuum in the healthcare industry.
In 2009, Mehmud joined Wakely Consulting Group, where he manages a team supporting healthcare-related projects for Medicare, Medicaid and commercial insurers involving risk adjustment tools and methodologies.
When the Affordable Care Act (ACA) passed in 2010, Mehmud's disruptive mindset went to work. Faced with the ACA, new health plans could not adequately predict the financial impact of healthcare exchange offerings. With Ross Winkelman, FSA as the overall project lead, Mehmud led the technical aspects of a risk adjustment project that was on a scale not seen before in the commercial space.
"It wasn't that hard to convince them the need was there," he said. "We obviously had the idea early enough. Once we had critical mass, everyone wanted to join."
The Wakely team created a model to simulate patients' Health and Human Services (HHS) risk scores and convened more than 60 major insurance carriers from more than 30 states to run the model quarterly, helping payers and providers manage their risk and maintain profitability in an unfamiliar environment.
Actuaries thrive in the realm of the uncertain, Mehmud said. It's one of the many reasons they are able to solve healthcare industry problems that have never been seen before.
"Actuaries have created predictive models for a long time. The only thing that's changed is the volume of data and the tools to deal with it," Mehmud said. "We've always been in this space."
Despite initially resisting new predictive analytics techniques, Mehmud said actuaries are now more receptive to understanding how a new process, method or tool allows them to perform their functions better.
Mehmud's next major project is "either insane or awesome; probably both."
He plans to take the standardized data saved on healthcare servers and apply sophisticated predictive modeling techniques to understand what factors drive financial performance. Mehmud's team developed a computational algorithm that will allow healthcare plans to determine what makes the biggest difference - whether it is benefit richness, certain diagnoses, geography or being on the healthcare exchange.
"This is a dynamic field," Mehmud said. "It doesn't matter how many years of experience you have, there will always be new things to learn the next year."