Incorporating Model Error into the Actuary’s Estimate of Uncertainty

Abstract

Current approaches to measuring uncertainty in an unpaid claim estimate often focus on parameter risk and process risk but do not account for model risk. This paper introduces simulation-based approaches to incorporating model error into an actuary’s estimate of uncertainty. The first approach, called Weighted Sampling, aims to incorporate model error into the uncertainty of a single prediction. The next two approaches, called Rank Tying and Model Tying, aim to incorporate model error in the uncertainty associated with aggregating across multiple predictions. Examples are shown throughout the paper and issues to consider when applying these approaches are also discussed.

Volume
Summer
Page
1-44
Year
2015
Keywords
Model uncertainty, model risk, model error, parameter risk, process risk, model variance, parameter variance, process variance, mean squared error, unpaid claim estimate, uncertainty, reserve variability, bias, simulation, scaling, weighted sampling, rank
Categories
Financial and Statistical Methods
Aggregation Methods
Simulation
Actuarial Applications and Methodologies
Reserving
Uncertainty and Ranges
Actuarial Applications and Methodologies
Dynamic Risk Modeling
Publications
Casualty Actuarial Society E-Forum
Authors
David J Otto
James Mackay
Formerly on syllabus
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