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Does autocalibration improve goodness of lift?

Author

Listed:
  • Ciatto, Nicolas

    (Université Libre de Bruxelles)

  • Verelst, Harrison

    (Université Libre de Bruxelles)

  • Trufin, Julien

    (Université Libre de Bruxelles)

  • Denuit, Michel

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

Abstract

Autocalibration is a desirable property since it ensures that the information contained in a candidate premium is used without any bias. It turns out to be intimately related to the method of marginal totals that predates modern risk classification methods. The present note aims to assess the impact of autocalibration on the goodness of lift. It is shown on a case study that autocalibration does not only restore global and local balances but also improve lift.

Suggested Citation

  • Ciatto, Nicolas & Verelst, Harrison & Trufin, Julien & Denuit, Michel, 2023. "Does autocalibration improve goodness of lift?," LIDAM Reprints ISBA 2023007, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2023007
    DOI: https://doi.org/10.1007/s13385-022-00330-4
    Note: In: European Actuarial Journal, 2023, vol. 13(1), p. 479-486
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    Cited by:

    1. Denuit, Michel & Huyghe, Julie & Trufin, Julien & Verdebout, Thomas, 2024. "Testing for auto-calibration with Lorenz and Concentration curves," Insurance: Mathematics and Economics, Elsevier, vol. 117(C), pages 130-139.

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