Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-23T18:13:38.925Z Has data issue: false hasContentIssue false

An Integrated System for Estimating the Risk Premium of Individual Car Models in Motor Insurance*

Published online by Cambridge University Press:  29 August 2014

Malcolm Campbell*
Affiliation:
Skandia International, Stockholm
*
Skandia International, Box 7693, S-103 95 Stockholm, Sweden.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The estimation of risk premium for individual car models is discussed. Cluster analysis is used to identify groups of car models with similar technical attributes. Credibility theory is used to combine estimates of risk premium from individual car model claim statistics, group claim statistics, and a technical assessment carried out by car experts. The procedure is applied to a small set of car models.

Type
Workshop
Copyright
Copyright © International Actuarial Association 1986

Footnotes

*

A previous version of this paper was presented to the Astin Colloquium at Biarritz, France.

References

Bühlmann, H. and Straub, E. (1970) Glaubwürdigkeit für Schadensätze. Mitteilungen der Vereinigung Schweizerischer Versicherungsmatematiker 70 (1), 111133.Google Scholar
Dubey, A. and Gisler, A. (1981) On parameter estimators in credibility. Mitteilungen der Vereinigung Schweizerischer Versicherungsmatematiker 81 (1), 187212.Google Scholar
van Eeghen, J., Greup, E. K. and Nüssen, J. A. (1983) Surveys of Actuarial Studies, No 2, Rate Making. Nationale-Nederlanden N.V., Rotterdam.Google Scholar
Hartigan, J. A. (1975) Clustering Algorithms. John Wiley & Sons, New York.Google Scholar
Sundt, B. (1983) Finite Credibility Formulae in Evolutionary Models. Scandinavian Actuarial Journal 106116.CrossRefGoogle Scholar
Velleman, P. F. and Hoaglin, D. C. (1981) Applications, Basics and Computing of Exploratory Data Analysis. Duxbury Press, Boston, Massachusetts.Google Scholar