Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/56729 
Year of Publication: 
2010
Series/Report no.: 
SFB 649 Discussion Paper No. 2010-048
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Abstract: 
This paper is intended as a guide to building insurance risk (loss) models. A typical model for insurance risk, the so-called collective risk model, treats the aggregate loss as having a compound distribution with two main components: one characterizing the arrival of claims and another describing the severity (or size) of loss resulting from the occurrence of a claim. In this paper we first present efficient simulation algorithms for several classes of claim arrival processes. Then we review a collection of loss distributions and present methods that can be used to assess the goodness-of-fit of the claim size distribution. The collective risk model is often used in health insurance and in general insurance, whenever the main risk components are the number of insurance claims and the amount of the claims. It can also be used for modeling other non-insurance product risks, such as credit and operational risk.
Subjects: 
insurance risk model
loss distribution
claim arrival process
Poisson process
renewal process
random variable generation
goodness-of-fit testing
JEL: 
C15
C46
C63
G22
G32
Document Type: 
Working Paper

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