The influence of gender and age in driving ability: an analysis of average and extreme behaviours

In 2012, the European Court of Justice introduced the ban on differentiating car insurance premiums for gender to avoid gender inequality. This paper deals with a gender analysis of driving ability by investigating the relationship between gender and the relative total claim amount in Motor Third Party Liability insurance, also considering the effect of age. Leveraging a two-part model based on parametric quantile regression, we want to investigate the average behaviour of drivers and their tail behaviour in order to highlight the importance of dispersion and the impact of largest claims. As a consequence, the purpose of our contribution is to study how gender and age can influence the entire probability distribution of the insurance claim with a particular focus on the quantiles with high probability levels, which are very important indicators to determine the effective riskiness of a driver. We apply our model to an Australian insurance dataset; our results suggest that men are in general riskier in terms of both average and tail behaviour.