A micro-level claim count model with overdispersion and reporting delays
AuthorAvanzi, B; Wong, B; Yang, X
Source TitleInsurance: Mathematics and Economics
University of Melbourne Author/sAvanzi, Benjamin
Document TypeJournal Article
CitationsAvanzi, B., Wong, B. & Yang, X. (2016). A micro-level claim count model with overdispersion and reporting delays. Insurance: Mathematics and Economics, 71, pp.1-14. https://doi.org/10.1016/j.insmatheco.2016.07.002.
Access StatusOpen Access
The accurate estimation of outstanding liabilities of an insurance company is an essential task. This is to meet regulatory requirements, but also to achieve efficient internal capital management. Over the recent years, there has been increasing interest in the utilisation of insurance data at a more granular level, and to model claims using stochastic processes. So far, this so-called ‘micro-level reserving’ approach has mainly focused on the Poisson process. In this paper, we propose and apply a Cox process approach to model the arrival process and reporting pattern of insurance claims. This allows for over-dispersion and serial dependency in claim counts, which are typical features in real data. We explicitly consider risk exposure and reporting delays, and show how to use our model to predict the numbers of Incurred-But-Not-Reported (IBNR) claims. The model is calibrated and illustrated using real data from the AUSI data set.
- Click on "Export Reference in RIS Format" and choose "open with... Endnote".
- Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References