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A robust random coefficient regression representation of the chain-ladder method

Published online by Cambridge University Press:  09 June 2021

Ioannis Badounas ,
Apostolos Bozikas  and
Georgios Pitselis
Ioannis Badounas
Affiliation:
Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece
Apostolos Bozikas
Affiliation:
Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece
Georgios Pitselis*
Affiliation:
Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece Department of Mathematics and Statistics, Concordia University, Montreal, Canada
*
*Corresponding author. E-mail: [email protected]
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Abstract

It is well known that the presence of outliers can mis-estimate (underestimate or overestimate) the overall reserve in the chain-ladder method, when we consider a linear regression model, based on the assumption that the coefficients are fixed and identical from one observation to another. By relaxing the usual regression assumptions and applying a regression with randomly varying coefficients, we have a similar phenomenon, i.e., mis-estimation of the overall reserves. The lack of robustness of loss reserving regression with random coefficients on incremental payment estimators leads to the development of this paper, aiming to apply robust statistical procedures to the loss reserving estimation when regression coefficients are random. Numerical results of the proposed method are illustrated and compared with the results that were obtained by linear regression with fixed coefficients.

Keywords

Loss reservingrandom coefficient regression modelsrobust estimationchain-ladder methodG22
Type
Original Research Paper
Information
Annals of Actuarial Science , Volume 16 , Issue 1 , March 2022 , pp. 151 - 182
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Institute and Faculty of Actuaries

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