Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/257909 
Authors: 
Year of Publication: 
2019
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 7 [Issue:] 3 [Article No.:] 71 [Publisher:] MDPI [Place:] Basel [Year:] 2019 [Pages:] 1-17
Publisher: 
MDPI, Basel
Abstract: 
In this study, we consider the problem of zero claims in a liability insurance portfolio and compare the predictability of three models. We use French motor third party liability (MTPL) insurance data, which has been used for a pricing game, and show that how the type of coverage and policyholders' willingness to subscribe to insurance pricing, based on telematics data, affects their driving behaviour and hence their claims. Using our validation set, we then predict the number of zero claims. Our results show that although a zero-inflated Poisson (ZIP) model performs better than a Poisson regression, it can even be outperformed by logistic regression.
Subjects: 
telematics
generalised linear modelling
validation
zero-inflated poisson model
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Creative Commons License: 
cc-by Logo
Document Type: 
Article
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