Incorporating heterogeneity into the prediction of total claim amount

Authors : Aslıhan ŞENTÜRK ACAR, Uğur KARABEY, Dario GREGORİ

Pages : 1321-1334

View : 35 | Download : 13

Publication Date : 2018-10-16

Article Type : Research Paper

Abstract :This paper proposes an alternative predictor for the total claim amount  of individuals that can be used for any type of non-life insurance products in which individuals may have multiple claims within one policy period. The impact of heterogeneity on expected total claim amount is investigated focusing on marginal predictions. Generalized linear mixed  model insert ignore into journalissuearticles values(GLMM); is used for the amounts of loss per claim. Closedform expression of the predictor is derived using marginal mean under  GLMM and claim count distribution. Empirical studies are performed using a private health insurance data set of a Turkish insurance company. Proposed predictive model provides the lowest prediction errors among competing models according to the mean absolute error criterion. 
Keywords : Generalized linear mixed model, Aggregate loss, Marginal mean, Iinsurance pricing, Zero inflation, Iinsurance pricing