In general, Machine Learning (ML) is the study of algorithms that improve through experience. These algorithms or models can make systematic, repeatable, validated decisions based on historical data. ML has come a long way in recent years, which is reflected in the methods available for time series forecasting (they are also important for assessing parameters for different kinds of liability provisions).

Therefore, this type of analysis can help actuaries and members of pension fund boards of trustees to accurately assess different kinds of pension fund parameters for assets and liabilities and to prepare any kind of forecasts. Visualizing the evolution of pension fund parameters and forecasting them will help the board of trustees explain how to adjust them in the actuarial provision or what to expect in their future evolution.

For this workshop, several examples for analyzing and providing such assumptions will be prepared and explained. Many useful visualization techniques will be presented with practical examples (via Python).

Early-bird discount is available for bookings made by 18 September 2025.

Storytelling for Actuaries | 16/17 October 2025 in Lisbon

Addressing Class Imbalance in Machine Learning | 3 November 2025

FIDA for Actuaries: Challenge or Opportunity? | 21 November 2025

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