Advanced Machine Learning Deployed to Mine Insights
Two large, regional Blue Cross / Blue Shield organizations urgently needed to learn about new members who came in through the Affordable Care Act (i.e. ACA or "Obamacare") - what were their likely future care needs, their payment resources or shortcomings?
Organization 1 - saw themselves already losing millions and called on an ACA provision that allowed them to sue the federal government for repayment of losses.
Organization 2 - tried a different approach- remediation, ie., identifying high-risk customers and negotiating agreements to reduce likely losses.
The big question was how to identify those customers? How could they manage the flood of data pouring in with new applications? - the answer..Machine Learning
The answer was in developing an artificial intelligence model that incorporated machine learning. We developed a highly advanced solution that leveraged machine learning for each Blue organization.
In insight 1: We were able to identify those few among the masses that were new applicants and had a higher potential profitability. To do so we:
- Determined who were and would be active consumers of provider services.
- Who brought high net value to the the client, as defined by dollars paid in premiums minus the predicted cost of providing services.
In insight 2: Among the millions of new applicants eligible for health care, the model identified those whose cases promised the most immediate positive results and put them at the head of the queue.
Impact for Client
The specific financial impact is subject to a non-disclosure agreement, but the client has been able to profitably remain in the market delivering health insurance options for nearly a decade. Additionally, provisions in the ACA allowed for firms to take legal action against the government if the provider sought to be released from the obligation to provide services. A long protracted lawsuit would have been extremely expensive and tie-up important company resources. Being able to deliver a better solution for the market without resorting to litigation saved millions in legal fees while adding a new revenue channel.