Modeling frequency distribution above a priority in presence of IBNR
Abstract
In reinsurance, Poisson and Negative binomial distributions are employed for modeling frequency. However, the incomplete data regarding reported incurred claims above a priority level presents challenges in estimation. This paper focuses on frequency estimation using Schnieper's framework for claim numbering. We demonstrate that Schnieper's model is consistent with a Poisson distribution for the total number of claims above a priority at each year of development, providing a robust basis for parameter estimation. Additionally, we explain how to build an alternative assumption based on a Negative binomial distribution, which yields similar results. The study includes a bootstrap procedure to manage uncertainty in parameter estimation and a case study comparing assumptions and evaluating the impact of the bootstrap approach.
Cite
@article{arxiv.2405.02871,
title = {Modeling frequency distribution above a priority in presence of IBNR},
author = {Nicolas Baradel},
journal= {arXiv preprint arXiv:2405.02871},
year = {2024}
}