A Multivariate
Bayesian Claim Count Development Model With Closed Form Posterior
and Predictive Distributions, January 2005 Abstract: This paper presents a rich, yet tractable,
multivariate Bayesian model of claim count development. The model
combines two conjugate families: the gamma-Poisson distribution for
ultimate claim counts and the Dirichlet-multinomial distribution for
emergence. We compute closed form expressions for all distributions
of actuarial interest, including the posterior distribution of parameters
and the predictive multivariate distribution of future counts given
observed counts to date and for each of these distributions give a
closed form expression for the moments. A new feature of the model
is its explicit sensitivity to ultimate claim count variability and
the uncertainty surrounding claim count emergence. Depending on the
value of these parameters, the posterior mean can equal the BF or
chain-ladder reserve. Thus the model provides a continuum of models
interpolating between these common methods. We give an example to
illustrate use of the model.