In this workshop you will develop a fully data driven strategy to incorporate factor information, continuous risk factors and geographical information in an insurance tariff. The approach combines tools from statistical learning (GAMs, GLMs) with machine learning tools (clustering, evolutionary trees).
The workshop is hands-on and gradually explains the concepts and tools via examples in R. You can run the examples on your own computer (with R, RStudio and some dedicated packages installed), or via an RStudio Cloud workspace that will be created by the teacher. In the latter case you only need a computer that can connect to the wifi at IABE.
Background reading is the paper "A data driven binning strategy for the construction of insurance tariff classes", by Henckaerts, Antonio, Clijsters and Verbelen in Scandinavian Actuarial Journal (2018).
More information and documentation is available on https://github.com/katrienantonio/PE-pricing-analytics. A dedicated GitHub page will become available in the week before the workshop.