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DPTree and DPForest: tree-based methods fulfilling demographic parity

Author

Listed:
  • Simon, Pierre-Alexandre

    (Université Libre de Bruxelles)

  • Denuit, Michel

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

  • Trufin, Julien

    (Université Libre de Bruxelles)

Abstract

Tree-based methods are widely used in insurance pricing due to their simple and accurate splitting rules. However, there is no guarantee that the resulting premiums avoid indirect discrimination when features recorded in the database are correlated with the protected variable under consideration. This paper shows that splitting rules in regression trees and random forests can be adapted in order to avoid indirect discrimination related to a binary protected variable like gender. The new procedure is illustrated on motor third-party liability insurance claim data.

Suggested Citation

  • Simon, Pierre-Alexandre & Denuit, Michel & Trufin, Julien, 2026. "DPTree and DPForest: tree-based methods fulfilling demographic parity," LIDAM Reprints ISBA 2026009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2026009
    DOI: https://doi.org/10.1017/S1748499525100092
    Note: In: Annals of Actuarial Science, 2026, vol. 20(1), p. 96-114
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