Celebration of Scholars
Predictive Power of Prescription Data as an Indicator for Insurance Risk
Name:
Zoe Hobbs
Major: Economics
Hometown: Canton, OH
Faculty Sponsor: Haley Yaple
Other Sponsors:
Type of research: Course project
Funding: PIC Mathematics (Preparing for Industrial Careers)
Name:
Mario Del Real
Major: Computer Science
Hometown: Kenosha, WI
Faculty Sponsor: Haley Yaple
Other Sponsors:
Type of research: Course project
Funding: PIC Mathematics (Preparing for Industrial Careers)
Name:
Benjamin Levicki
Major: Mathematics
Hometown: Cary, IL
Faculty Sponsor: Haley Yaple
Other Sponsors:
Type of research: Course project
Funding: PIC Mathematics (Preparing for Industrial Careers)
Name:
Trevor Wills
Major: Mathematics
Hometown: Yorkville, IL
Faculty Sponsor: Haley Yaple
Other Sponsors:
Type of research: Course project
Funding: PIC Mathematics (Preparing for Industrial Careers)
Abstract
We are a part of a research class in mathematics affiliated with PIC Math (Preparing for Industrial Careers). In this class we are focused on developing a solution to real-world problems posed by a local company. Milliman IntelliScript, our partnering company, provides insurance firms with an enhanced model to better assess their own clients’ risks. In order to convince the firms that IntelliScript’s Model will outperform their own predictions, we are taking a new approach towards developing better visualizations of IntelliScript’s models. By converting the calculated loss ratios from a percentage to a dollar value and quantifying a value for the client’s reduction of risk observed when using IntelliScript’s model, we are providing the insurance firms with a clearer view of the impact of outliers. We are utilizing these new values to create a marketing tool. Using these two methods, we are able to clearly provide the clients of IntelliScript with an unambiguous view of where the Curv model wins over their own model.
Submit date: March 19, 2019, 8:48 a.m.