Comparative performance analysis between Grandient Boosting models and GLMs for non-life pricing

Abstract

In our study case of a French insurance motor portfolio, we found that Gradient Boosting models have a stronger predictive performance and a higher pricing ability to adjust the premiums to both high risk and low risk profiles. And finally, we conclude that these models can be used to support and improve GLMs and their pricing results as Machine Learning continues to settle in the actuarial modeling paradigm.