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Insurance ratemaking using the Exponential-Lognormal regression model

Published online by Cambridge University Press:  26 June 2019

George Tzougas ,
Woo Hee Yik  and
Muhammad Waqar Mustaqeem
George Tzougas*
Affiliation:
Department of Statistics, London School of Economics and Political Science, Holborn, London WC2A 2AE, UK
Woo Hee Yik
Affiliation:
Department of Statistics, London School of Economics and Political Science, Holborn, London WC2A 2AE, UK
Muhammad Waqar Mustaqeem
Affiliation:
Department of Statistics, London School of Economics and Political Science, Holborn, London WC2A 2AE, UK
*
*Corresponding author. E-mail: [email protected]
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Abstract

This paper is concerned with presenting the Exponential-Lognormal (ELN) regression model as a competitive alternative to the Pareto, or Exponential-Inverse Gamma, regression model that has been used in a wide range of areas, including insurance ratemaking. This is the first time that the ELN regression model is used in a statistical or actuarial context. The main contribution of the study is that we illustrate how maximum likelihood estimation of the ELN regression model, which does not have a density in closed form, can be accomplished relatively easily via an Expectation-Maximisation type algorithm. A real data application based on motor insurance data is examined in order to emphasise the versatility of the proposed algorithm. Finally, assuming that the number of claims is distributed according to the classic Negative Binomial and Poisson-Inverse Gaussian regression models, both the a priori and a posteriori, or Bonus–Malus, premium rates resulting from the ELN regression model are calculated via the net premium principle and compared to those determined by the Pareto regression model that has been traditionally used for modelling claim sizes.

Keywords

Exponential-Lognormal regression modelEM AlgorithmMotor Third Party Liability Insuranceratemaking
Type
Paper
Information
Annals of Actuarial Science , Volume 14 , Issue 1 , March 2020 , pp. 42 - 71
Copyright
© Institute and Faculty of Actuaries 2019 

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