Juan Sebastian Yanez, PhD.

Doctorat en mathématiques
UQAM

2023/06

Direction de recherche:

  • Mathieu Pigeon, professeur au Département de mathématiques de l’Université du Québec à Montréal

Thèse de doctorat:

Yanez, Juan Sebastian (2023), « Modélisation granulaire des réserves en assurances incendie, accidents et risques divers avec une structure en composantes hiérarchiques », Dir.: Mathieu Pigeon, Thèse de doctorat. Montréal (Québec, Canada), Université du Québec à Montréal, Doctorat en mathématiques.

Publications

  • J.S.Yanez, J.-P. Boucher & M.Pigeon (2023), Modeling Payment Frequency for Loss Reserves Based on Various Dynamic Claims Scores, North American Actuarial Journal, 1-22

    By modelling reserves with micro-level models, individual claims information is better preserved and can be more easily handled in the fitting process. Some of the claim information is available immediately at the report date and remains known until the closure of the claim. However, other useful information changes unpredictably as claims develop, for example, the previously observed number of payments. In this paper, we seek to model payment counts in a discrete manner based on past information both in terms of claim characteristics and previous payment counts. We use a dynamic score that weighs the risk of the claim based on previous claim behaviour and that gets updated at the end of each discrete interval. In this paper’s model we will also distinguish between the different types of payments. We evaluate our model by fitting it into a data set from a major Canadian insurance company. We will also discuss estimation procedures, make predictions, and compare the results with other models.

  • J.S.Yanez & M.Pigeon (2021), Micro-level Parametric Duration-Frequency-Severity Modeling for Outstanding Claim Payments, Insurance: Mathematics and Economics, 98, 106-119.

    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.

Présentations scientifiques

  • Dependence In Claim Processing Time: A Frailty Analysis Perspective, Congrès annuel de la Société statistique du Canada, Ottawa, Canada (QC), 16 juillet 2023.
  • Parametric Outstanding Claim Payment Count Modelling Through A Dynamic Claim Score, Perspectives on Actuarial Risks in Talks of Young Researchers, Valence, Espagne, 29 janvier 2023.
  • Parametric Outstanding Claim Payment Count Modelling Through A Dynamic Claim Score, Workshop on Risk Management and Insurance Research, Barcelone, Espagne, 20 octobre 2022.
  • Parametric Outstanding Claim Payment Count Modelling Through A Dynamic Claim Score, Actuarial Research Conference (ARC), University of Illinois, Urbana-Champaign, USA (IL), 3 août 2022.
  • Parametric Outstanding Claim Payment Count Modelling Through A Dynamic Claim Score, Congrès annuel de la Société statistique du Canada, Virtuel, 30 mai 2022.
  • Impact Of Individual Explanatory Variables In Loss Reserving, Actuarial Research Conference (ARC), Indianapolis, USA (IN), 14 août 2019.

Implications

Présentations locales

  • Parametric Outstanding Claim Payment Count Modelling Through A Dynamic Claim Score, Show and Share (Co-operators), UQAM, Montréal, Canada (QC), 28 janvier 2023.
  • Un survol de la recherche actuarielle sur les modèles de réserve granulaire, Séminaire de la Chaire Co-operators en analyse des risques actuariels, UQAM, Montréal, Canada (QC), 26 octobre 2022.
  • Duration-Frequency-Severity Parametric Modeling For Micro-Level Loss Reserves, Sommet des sciences et de l’analyse 2021 de Co-operators, Virtuel, 1er juin 2021.

Enseignement