IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v30y2003i8p857-865.html
   My bibliography  Save this article

Modelling repeated insurance claim frequency data using the generalized linear mixed model

Author

Listed:
  • Kelvin Yau
  • Karen Yip
  • H. K. Yuen

Abstract

Most of the methods used to estimate claim frequency rates in general insurance have assumed that data are independent. However, it is not uncommon for information stored in the database of an insurance company to contain previous years' claim data from each policyholder. We consider the application of the generalized linear mixed model approach to the analysis of repeated insurance claim frequency data in which a conditionally fixed random effect vector is incorporated explicitly into the linear predictor to model the inherent correlation. A motor insurance data set is used as the basis for simulation to demonstrate the advantages of the method. Ignoring the underlying association for observations within the same policyholder results in an underestimation of the standard error of the parameter estimates and a remarkable reduction in the prediction accuracy. The method provides a viable alternative for incorporating repeated claim experience that enables the revision of rates in general insurance.

Suggested Citation

  • Kelvin Yau & Karen Yip & H. K. Yuen, 2003. "Modelling repeated insurance claim frequency data using the generalized linear mixed model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(8), pages 857-865.
  • Handle: RePEc:taf:japsta:v:30:y:2003:i:8:p:857-865
    DOI: 10.1080/0266476032000075949
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/0266476032000075949
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dionne, Georges & Vanasse, Charles, 1989. "A Generalization of Automobile Insurance Rating Models: The Negative Binomial Distribution with a Regression Component," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 19(02), pages 199-212, November.
    2. Renshaw, Arthur E., 1994. "Modelling the Claims Process in the Presence of Covariates," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 24(02), pages 265-285, November.
    3. K. K. W. Yau, 1999. "Estimation of surgeon effects in the analysis of post-operative colorectal cancer patients data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(2), pages 257-272.
    4. Stroinski, Krzysztof J. & Currie, Iain D., 1989. "Selection of variables for automobile insurance rating," Insurance: Mathematics and Economics, Elsevier, vol. 8(1), pages 35-46, March.
    5. Kelvin K. W. Yau & Anthony Y. C. Kuk, 2002. "Robust estimation in generalized linear mixed models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(1), pages 101-117.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. GÓMEZ GARCÍA, J.Mª & PELÁEZ FERMOSO, F.J. & y GARCÍA GONZÁLEZ, A., 2005. "Repercusiones del envejecimiento demográfico sobre el sistema público de pensiones en Castilla y León," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 23, pages 235-253, Abril.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:japsta:v:30:y:2003:i:8:p:857-865. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.