Edward W. (Jed) Frees is at the University of Wisconsin and ISO Innovative Analytics. Glenn Meyers is at ISO Innovative Analytics. A. David Cummings is at ISO Innovative Analytics. The authors can be contacted via e-mail: firstname.lastname@example.org, email@example.com, and DCummings@iso.com, respectively.
Insurance Ratemaking and a Gini Index
Article first published online: 14 MAR 2013
© The Journal of Risk and Insurance, 2013
Journal of Risk and Insurance
Volume 81, Issue 2, pages 335–366, June 2014
How to Cite
Frees, E. W., Meyers, G. and Cummings, A. D. (2014), Insurance Ratemaking and a Gini Index. Journal of Risk and Insurance, 81: 335–366. doi: 10.1111/j.1539-6975.2012.01507.x
- Issue published online: 16 MAY 2014
- Article first published online: 14 MAR 2013
Welfare economics uses Lorenz curves to display skewed income distributions and Gini indices to summarize the skewness. This article extends the Lorenz curve and Gini index by ordering insurance risks; the ordering variable is a risk-based score relative to price, known as a relativity. The new relativity-based measures can cope with adverse selection and quantify potential profit. Specifically, we show that the Gini index is proportional to a correlation between the relativity and an out-of-sample profit (price in excess of loss). A detailed example using homeowners insurance demonstrates the utility of these new measures.