Description

Do you feel lost in the random forests? Do you need some career boosting? Would you like to demystify magic words like cross-validation, bagging, shrinkage… or discover what is hidden behind wild acronyms like GAM, LASSO, GBM, etc. that you heard during meetings or at the coffee machine? Do you wonder whether GLMs should still be considered by actuaries, or better archived in a museum dedicated to the history of the actuarial discipline? If affirmative then you should consider attending this one-week intensive course about statistical learning techniques applied to insurance data analysis!

This course has been conceived by actuaries for actuaries, accounting for all the specificities of insurance data instead of simply re-using standard recipes borrowed from other fields. The sessions proceed step by step, recalling the fundamental statistical concepts at the heart of the modern learning techniques and the standard GLM approach, and then moving to GAMs, GBMs and tree-based methods like random forests. Their relative merits are illustrated by means of several case studies with insurance data.

The sessions aim to be interactive, alternating between methodological parts and case studies performed in front of the audience. Participants are invited to bring their own PC. Data sets and R code are made available through a supporting website. The installation of R packages prior to attendance remains at the participant’s responsibility.