Insurance Pricing with Proprietary Information

Information regarding the likelihood and severity of automobile accidents for individual insurance consumers enables insurance companies to price insurance policies. The more accurate and predictive the data, the more accurate and fair insurance prices are. Modern advances, such as telematics technology, allow insurers to improve the quality of their information. This improved information has an efficiency-enhancing effect on the personal automobile insurance market which makes both insurers and consumers better off. Thus, this research project will develop a mathematical model, in collaboration with AVIVA, a leading property and casualty insurance group in Canada and provider of home, automobile and business insurance, to aid insurers with improving the efficiency of insurance markets.

Jason Strauss
Faculty Supervisor: 
Dr. Norma Nielson