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

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

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)79-93
Number of pages15
JournalInsurance: Mathematics and Economics
Volume94
DOIs
StatePublished - Sep 2020

Keywords

  • Automobile claims
  • Claim frequency modeling
  • Claim severity modeling
  • Clustering
  • CWM
  • GCWM
  • General insurance

ASJC Scopus subject areas

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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