An individual risk model for premium calculation based on quantile: a comparison between Generalized Linear Models and Quantile Regression
This paper deals with the use of quantile regression and generelized linear models for a premium calculation based on quantiles. A premium principle is a functional that assigns a usually loaded premium to any distribution of claims. The loaded premium is generally greater than the expected value of the loss and the difference is considered to be a risk margin or a safety loading. The failure of a right charge of individual risk rate exposes the insurer to adverse selection, and consequently, to deteriorating financial results.