Financial implications of artificial Neural Networks in automobile insurance underwriting

Abstract

In the insurance business, two things are considered when analysing losses: frequency of loss and severity of loss. Previous research investigated the use of artificial Neural Networks (NNs) to develop models as aids to the insurance underwriter when determining acceptability and price on insurance policies. This paper is a preliminary investigation into the financial impact of NN models as tools in underwriting of private passenger automobile insurance policies. Results indicate that an artificial NN underwriting model outperformed a linear model and a logistic model. Further research and investigation is warranted in this area.