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Modelling the Claims Process in the Presence of Covariates

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  • Renshaw, Arthur E.

Abstract

An overview of the potential of Generalized Linear Models as a means of modelling the salient features of the claims process in the presence of rating factors is presented. Specific attention is focused on the rich variety of modelling distributions which can be implemented in this context.

Suggested Citation

  • Renshaw, Arthur E., 1994. "Modelling the Claims Process in the Presence of Covariates," ASTIN Bulletin, Cambridge University Press, vol. 24(2), pages 265-285, November.
  • Handle: RePEc:cup:astinb:v:24:y:1994:i:02:p:265-285_00
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    Cited by:

    1. Sarabia, José María & Guillén, Montserrat, 2008. "Joint modelling of the total amount and the number of claims by conditionals," Insurance: Mathematics and Economics, Elsevier, vol. 43(3), pages 466-473, December.
    2. Yip, Karen C.H. & Yau, Kelvin K.W., 2005. "On modeling claim frequency data in general insurance with extra zeros," Insurance: Mathematics and Economics, Elsevier, vol. 36(2), pages 153-163, April.
    3. repec:mup:actaun:actaun_2016064020683 is not listed on IDEAS
    4. repec:prg:jnlpep:v:2017:y:2017:i:4:id:621:p:450-466 is not listed on IDEAS
    5. Natacha Brouhns & Montserrat Guillén & Michel Denuit & Jean Pinquet, 2003. "Bonus‐Malus Scales in Segmented Tariffs With Stochastic Migration Between Segments," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 70(4), pages 577-599, December.
    6. Garrido, J. & Genest, C. & Schulz, J., 2016. "Generalized linear models for dependent frequency and severity of insurance claims," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 205-215.
    7. Jiří Valecký, . "Calculation of Solvency Capital Requirements for Non-life Underwriting Risk Using Generalized Linear Models," Prague Economic Papers, University of Economics, Prague, vol. 0, pages 1-17.
    8. 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.

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