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Evaluation

Reserving

Level 2: General knowledge of the subject (6-9 Years)

C:MM:L3

C:FE:L3

S:DA:L2

S:LT:L2

T:AN:L1

CS-13 - Ensemble Distributional Forecasting for Insurance Loss Reserving

Wednesday, November 8, 2023
9:30 AM – 10:30 AM PST
Location: San Diego Ballroom (2nd Floor)
Loss reserving generally focuses on identifying a single model that can generate superior predictive performance. However, different loss reserving models specialise in capturing different aspects of loss data. In our work, we propose a systematic framework to objectively combine (i.e. ensemble) multiple stochastic loss reserving models such that the strengths offered by different models can be utilised effectively.

Learning Objectives:

  • Upon completion, participant will be able to understand why model combination is important for loss reserving purpose, and a general knowledge of the model combination framework proposed for the loss reserving purpose.
  • Upon completion, participant will be able to learn how to effectively implement the model combination framework by considering the special structure of aggregate loss reserving data.
  • Upon completion, participant will be able to learn how to effectively choose different ensembling strategies based on probabilistic forecasting evaluation metrics and statistical tests.