GIRO 2021
Members of the Machine Learning in Reserving Working Party’s (‘MLRWP’) will build on the working party’s presentation at the 2021 IFoA Spring Conference to further explore the application of selected machine learning (‘ML’) models to triangle data for reserving, focusing on:
- Validation and feature engineering options
- Relative performance of ML and traditional reserving methods for different claims characteristics
- Interpreting ML model results.
Prior knowledge of our Spring Conference presentation would be beneficial but not essential.
- Available for IFoA members at the VLE site