MQP 2018 – On-Leveling Commercial Auto Policies via Extension of Exposures for Ratemaking Preparation


The goal of our project was to assist our sponsor in making its commercial auto insurance more profitable and better positioned for the future, through the completion of three tasks. The first was to improve the accuracy of their SQL rerater code, so it can more accurately adjust old policy premiums to current rates. Second, we researched and recommended potential variable additions to the rating algorithm. Our last task was to research autonomous vehicles and recommend possible ways to insure cars with these capabilities. Final deliverables included detailed descriptions and solutions to the rerater’s errors, recommendations for new rating variables, and research on the future of autonomous cars.