by Katrien Antonio, Roel Henckaerts and Roel Verbelen.
Course materials for the Pricing analytics in R course in March 2021 in Leuven and Brussels.
📆 March, 2021
🕗 approx. 3h (in company) and 5h (for MSc students in
class)
📌 IA|BE in Brussels, Data science for non-life insurance
class at KU Leuven
You’ll work through the essential steps of the implementation in R of
the pricing framework proposed in 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). The methodology is illustrated with the same
data set as the one used by Henckaerts et al. (2018).
This paper develops a fully data driven strategy to incorporate continuous risk factors and geographical information in an insurance tariff. The framework nicely aligns flexibility with the practical requirements of an insurance company, the policyholder and the regulator. The approach combines tools from statistical learning (GAMs, GLMs) with machine learning (clustering, evolutionary trees).
The detailed schedule is subject to small changes.
| Description | Lecture material | R script | R solutions |
|---|---|---|---|
| Prologue, the R universe and preliminaries | sheets prologue | script | solutions |
| Data set | sheets data set | script | solutions |
| Spatial data and maps | sheets data set | script | solutions |
| Model building | sheets model building | script | solutions |
| From GAM to GLM | sheets from GAM to GLM | script | solutions |
You can access the lecture sheets 9 (in html) via pricing-analytics-sheets and in pdf via pricing-analytics-sheets-pdf.
An older documentation of the same workshop is here.
Please bring a laptop with a recent version of R and RStudio installed. Make sure you can connect your laptop to the internet (or download the course material one day before the start of the workshop). You will need:
- R (at least 3.5.2 https://cloud.r-project.org/bin/windows/base/ )
- RStudio ( https://www.rstudio.com/products/rstudio/download/#download )
You should install and load the packages that will be used throughout
the workshop. You can use the following instructions to install (if
necessary) and load the packages. These instructions are also available
in prework_installation_packages.R from the scripts folder.
packages <- c("tidyverse", "mgcv", "evtree", "classInt", "rgdal", "RColorBrewer", "grid", "gridExtra", "visreg", "sf", "tmap", "rgeos", "mapview", "leaflet")
suppressMessages(packages <- lapply(packages, FUN = function(x) {
if (!require(x, character.only = TRUE)) {
install.packages(x)
library(x, character.only = TRUE)
}
}))We provide a back-up plan in case your local installation of R (and the necessary packages) is not working properly. Please join our project on RStudio Cloud via the link posted on TOLEDO.
After creating an account for RStudio you will be able to work with the scripts and data sets in the cloud.
Katrien Antonio is professor in insurance data science at KU Leuven and associate professor at University of Amsterdam. She teaches courses on data science for insurance, life and non-life insurance mathematics and loss models. Research-wise Katrien puts focus on pricing, reserving and fraud analytics, as well as mortality dynamics.
You are now ready to load the data and build predictive models.