Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-02T22:03:37.010Z Has data issue: false hasContentIssue false
  • English
  • Français

Chain ladder and interactive modelling. (Claims reserving and GLIM)

Published online by Cambridge University Press:  20 April 2012

A. E. Renshaw
Get access Rights & Permissions [Opens in a new window]

Extract

The prediction of outstanding claims amounts in non-life insurance is, by its very nature, highly speculative. Partially because of this and partially because of the variety of features suggested by various researchers for possible inclusion in the structure of the underlying prediction model, the past two decades have seen a proliferation of methodologies for making such predictions. Specific details of these developments are contained in a comprehensive and highly detailed survey conducted by Taylor (1986) in which a taxonomy of methods is established. One feature common to all of these methods is the utilization of current and past records of claims amounts—invariably in the form of the familiar so-called runoff triangle or a variant thereof—to calibrate the proposed prediction model before use. Prudence dictates that diagnostic checks should then be made to establish whether or not the data are supportive of the structure imparted to the prediction model before use, a feature which apart from some notable exceptions including Zehnwirth (1985) and Taylor (1983), is not always emphasized in the literature.

Type
Research Article
Information
Journal of the Institute of Actuaries , Volume 116 , Issue 3 , December 1989 , pp. 559 - 587
Copyright
Copyright © Institute and Faculty of Actuaries 1989

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

(1) Aitchison, J. & Brown, J. A. C. (1969). The Log-Normal Distribution. Cambridge University Press.Google Scholar
(2) Dejong, P. & Zehnwirth, B. (1983). Claims Reserving, State-Space Models and the Kalman Filter. J.I.A. 110, 157.Google Scholar
(3) Green, P. J. (1988). Non-Diagonal Weight Matrices. GLIM Newsletter No. 16.Google Scholar
(4) Haberman, S. & Renshaw, A. E. (1988). Generalised Linear Models in Actuarial Work. Presented to a joint meeting of the Staple Inn Actuarial Society and the Royal Statistical Society, General Applications Section. February 1988.Google Scholar
(5) Hossack, I. B., Pollard, J. H. & Zehnwirth, B. (1983). Introductory Statistics with Applications in General Insurance. Cambridge University Press.Google Scholar
(6) Kremer, E. (1982). IBNR Claims and the Two-Way Model of ANOVA. Scandinavian Actuarial Journal.Google Scholar
(7) Taylor, G. C. (1979). Statistical Testing of a Non-Life Insurance Model. Proceedings Actuarial Sciences Institute, Act. Wetemschappen, Katholieke Univ. Leuven, Belgium.Google Scholar
(8) Taylor, G. C. (1983). An Invariance Principle for the Analysis of Non-Life Insurance Claims. J.I.A. 110, 205–242.Google Scholar
(9) Taylor, G. C. & Ashe, F. R. (1983). Second Moments of Estimates of Outstanding Claims. Journal of Econometrics 23, 37–61.Google Scholar
(10) Taylor, G. C. (1986). Claims Reserving in Non-Life Insurance. North-Holland.Google Scholar
(11) Taylor, G. C. (1988). Regression Models in Claims Analysis (II), Mercer, William M., Campbell, Cook, Knight, Sydney, Australia.Google Scholar
(12) Verrall, R. (1988). Bayes Linear Models and the Claims Run-Off Triangle. Actuarial Research Report No. 7. The City University, London.Google Scholar
(13) Verrall, R. (1989). Private communication.Google Scholar
(14) Zehnwirth, B. (1985). Interactive Claims Reserving Forecasting System. Benhar Nominees Pty Ltd, Turramurra, NSW, Australia.Google Scholar