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Micro-level parametric duration-frequency-severity modeling for outstanding claim payments

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  • Yanez, Juan Sebastian
  • Pigeon, Mathieu

Abstract

Unlike collective models, individual models have the advantage of keeping the attributes of each claim intact. We propose a three-component parametric individual model that uses this information in the form of explanatory variables. The first component predicts the delays between the occurrence, report, and closure of each claim using parametric survival models. For the second (frequency) and third (severity) components, we use generalized linear models and splice models. Moreover, the elapsed time between report and closure of claims is converted into an exposure variable in the count model. Finally, we discuss estimation procedures, make predictions, and compare the results with other models using a data set from a major Canadian insurance company.

Suggested Citation

  • Yanez, Juan Sebastian & Pigeon, Mathieu, 2021. "Micro-level parametric duration-frequency-severity modeling for outstanding claim payments," Insurance: Mathematics and Economics, Elsevier, vol. 98(C), pages 106-119.
    • Handle: RePEc:eee:insuma:v:98:y:2021:i:c:p:106-119
    DOI: 10.1016/j.insmatheco.2021.01.008
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    References listed on IDEAS

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    Cited by:

    1. Sebastian Calcetero-Vanegas & Andrei L. Badescu & X. Sheldon Lin, 2023. "Claim Reserving via Inverse Probability Weighting: A Micro-Level Chain-Ladder Method," Papers 2307.10808, arXiv.org, revised Jul 2023.
    2. Daniel J. Geiger & Akim Adekpedjou, 2022. "Analysis of IBNR Liabilities with Interevent Times Depending on Claim Counts," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 815-829, June.

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