Modeling frequency and severity of claims with the zero-inflated generalized cluster-weighted models

Nikola Počuča, Petar Jevtić, Paul D. McNicholas and Tatjana Miljkovic

Insurance: Mathematics and Economics, 2020, vol. 94, issue C, 79-93

Abstract: To facilitate applications in general insurance, some extensions are proposed to cluster-weighted models (CWMs). First, we extend CWMs to have generalized cluster-weighted models (GCWMs) by allowing modeling of non-Gaussian distribution of the continuous covariates, as they frequently occur in insurance practice. Secondly, we introduce a zero-inflated extension of GCWM (ZI-GCWM) for modeling insurance claims data with excess zeros coming from heterogeneous sources. Additionally, we give two expectation–optimization (EM) algorithms for parameter estimation given in the proposed models. An appropriate simulation study shows that, for various settings and in contrast to the existing mixture-based approaches, both extended models perform well. Finally, a real data set based on French auto-mobile policies is used to illustrate the application of the proposed extensions.

Keywords: GCWM; CWM; Clustering; Automobile claims; General insurance; Claim severity modeling; Claim frequency modeling (search for similar items in EconPapers)
JEL-codes: C02 C40 C60 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:94:y:2020:i:c:p:79-93

DOI: 10.1016/j.insmatheco.2020.06.004

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