Joint modelling of the total amount and the number of claims by conditionals

In the risk theory context, let us consider the classical collective model. The aim of this paper is to obtain a flexible bivariate joint distribution for modelling the couple ( S , N ) , where N is a count variable and S = X 1 + ⋯ + X N is the total claim amount. A generalization of the classical hierarchical model, where now we assume that the conditional distributions of S | N and N | S belong to some prescribed parametric families, is presented. A basic theorem of compatibility in conditional distributions of the type S given N and N given S is stated. Using a known theorem for exponential families and results from functional equations new models are obtained. We describe in detail the extension of two classical collective models, which now we call Poisson–Gamma and the Poisson–Binomial conditionals models. Other conditionals models are proposed, including the Poisson–Lognormal conditionals distribution, the Geometric-Gamma conditionals model and a model with inverse Gaussian conditionals. Further developments of collective risk modelling are given.