Balancing homogenous risk groups with credible dataset sizes when selecting a reserving segmentation has long been a challenge for reserving teams.
This session presents a practical framework to help general insurance actuaries evaluate career decisions across roles, countries, and levels of seniority.
The session will focus on our framework for identifying and assessing climate-related liability risks with some live examples.
The Machine Learning in Reserving Working Party will present some of our latest thinking based on our neural network (NN) framework.
This session will provide a holistic overview of recent loss development trends across US property and casualty lines of business, with a particular focus on how post-2017 structural shifts have affected the usability of recent data for actuarial analysis.
