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Risk Classification for Claim Counts and Losses Using Regression Models for Location, Scale and Shape

Tzougas, G and Vrontos, S and Frangos, N (2015) 'Risk Classification for Claim Counts and Losses Using Regression Models for Location, Scale and Shape.' Variance, 9 (1). 140 - 157. ISSN 1940-6444

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Abstract

This paper presents and compares different risk classi?cation models for the frequency and severity of claims employing regression models for location, scale and shape. The differences between these models are analyzed through the mean and the variance of the annual number of claims and the costs of claims of the insureds, who belong to different risk classes and interesting results about claiming behaviour are obtained. Furthermore, the resulting a priori premiums rates are calculated via the expected value and standard deviation principles with independence between the claim frequency and severity components assumed.

Item Type: Article
Uncontrolled Keywords: Claim frequency; Claim severity; Regression Models for Location, Scale and Shape; A priori risk classification; Expected value premium calculation principle; Standard deviation premium calculation principle.
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Jim Jamieson
Date Deposited: 07 Apr 2016 12:34
Last Modified: 17 Aug 2017 17:27
URI: http://repository.essex.ac.uk/id/eprint/16428

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