Abstract
An IBNYR event is one that occurs randomly during some fixed exposure interval and incurs a random delay before it is reported. A previous paper developed a continuous-time model of the IBNYR process in which both the Poisson rate at which events occur and the parameters of the delay distribution are unknown random quantities; a full-distributional Bayesian method was then developed to predict the number of unreported events. Using a numerical example, the success of this approach was shown to depend upon whether or not the occurrence dates were available in addition to the reporting dates. This paper considers the more usual practical situation in which only discretized epoch information is available; this leads to a loss of predictive accuracy, which is investigated by considering various levels of quantization for the same numerical example.
Keywords: Incurred But Not Reported (IBNR) models; reporting delays; Bayesian estimation and prediction; Bayesian approximations; discrete-time models.
Volume
20:1
Page
93-112
Year
1990
Categories
Actuarial Applications and Methodologies
Reserving
Reserving Methods
Publications
ASTIN Bulletin