On a Strategy to Develop Robust and Simple Tariffs from Motor Vehicle Insurance Data
Author: Christmann, Andreas
Source: Acta Mathematicae Applicatae Sinica, Volume 21, Number 2, May 2005 , pp. 193-208(16)
Abstract:The goals of this paper are twofold: we describe common features in data sets from motor vehicle insurance companies and we investigate a general strategy which exploits the knowledge of such features. The results of the strategy are a basis to develop insurance tariffs. We use a nonparametric approach based on a combination of kernel logistic regression and ε-support vector regression which both have good robustness properties. The strategy is applied to a data set from motor vehicle insurance companies.
Document Type: Research article
Publication date: 2005-05-01