Actuaries are exceptionally good at turning data into decisions. For decades, this has been our competitive advantage.
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.
