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A maximum likelihood approach for uncertain volumes in the additive reserving model

Published online by Cambridge University Press:  12 February 2025

Ulrich Riegel Open the ORCID record for Ulrich Riegel [Opens in a new window]
Ulrich Riegel*
Affiliation:
Munich Reinsurance Company, Munich 80802, Germany
*
Email: [email protected]
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Abstract

The additive reserving model assumes the existence of volume measures such that the corresponding expected loss ratios are identical for all accident years. While classical literature assumes these volumes are known, in practice, accurate volume measures are often unavailable. The issue of uncertain volume measures in the additive model was addressed in a generalization of the loss ratio method published in 2018. The derivation is rather complex and the method is computationally intensive, especially for large loss development triangles. This paper introduces an alternative approach that leverages the well-established EM algorithm, significantly reducing computational requirements.

Keywords

Loss ratio methodadditive modelvolume measuresreserving methodEM algorithmmean squared error of prediction
Type
Research Article
Information
ASTIN Bulletin: The Journal of the IAA , First View , pp. 1 - 26
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The International Actuarial Association

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