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Quantifying Uncertainty
in Actuarial Models: An Introduction to Conformal
Prediction |
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12 June 2025, 10:00-13:00 CEST |
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As the actuarial landscape becomes increasingly
data-driven, traditional statistical methods are evolving, linking
point estimates with quantifiable uncertainty. Conformal Prediction
is a powerful framework used to evaluate the uncertainty of
predictions. It turns point predictions into prediction regions, in
this way, when you make a prediction, the output has probabilistic
guarantees that it covers the true outcome. In this web session, we
will explore the theoretical foundations of Conformal Prediction,
its assumptions, methodology, and advantages over traditional
approaches. Participants will see how this technique can be a
disruptive innovation in risk assessment, pricing, reserving, and
forecasting by integrating uncertainty directly into predictions.
The session is balanced between theory and hands-on activities,
offering real-world examples and code demonstrations in
classification, regression, time series, natural language
processing (NLP), and computer vision, all applied to challenges in
the actuarial field.
further
details |
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