Interest in the use of machine learning (ML) in reserving has been increasing in recent years, though its use in practice is not yet widespread. ML methods must tick several boxes before actuaries will feel comfortable deploying them. These include model stability, interpretability, ease of use, and the ability to estimate reserve uncertainty.
This talk focuses on this last topic and considers:
This is an online presentation aimed at reserving actuaries with an interest in the use of ML or actuaries interested in uncertainty estimation. Full R code for the analysis will be available online in the form of a detailed worked example on some real-life data.
A recording of this webinar is available to view. Watch the webinar recording.
An actuary for over 20 years, Gráinne has extensive experience with the use of statistical and machine learning techniques in reserving, both through her work and as a member of the Machine Learning in Reserving Working Party. She has a particular interest in the estimation of reserve variability, and ways to practically use stochastic reserving methods in day-to-day work. She has delivered a number of presentations on these topics over the course of her career. She currently works with Optum Ireland.