Mogens Bladt, University of Copenhagen, Denmark
A multi--state life--insurance model is naturally described in terms of the intensity matrix of the corresponding underlying, in general time--inhomogeneous, Markov process which describes the dynamics for the states of an insured person. Between and at transitions, payments and premiums are paid, which defines a payment process, and the technical reserve is then defined as the present value of all future payments of the contract. Classical methods for finding the reserve and higher order moments involve the solution of certain differential equations (Thiele and Hattendorff, respectively). In this paper we present an alternative matrix--oriented approach based on general reward considerations for Markov jump processes. The matrix--approach provides a general framework for effortlessly setting up general and even complex multi--state models, where moments of all orders are then expressed explicitly in terms of so--called product integrals (matrix--exponentials) of certain matrices. As Thiele and Hattendorff type of theorems can be retrieved immediately from the matrix--formulae, this methods also provides a quick and transparent approach to proving these classical results. Methods for obtaining distributions of the future payments and related properties (e.g. quantiles or survival functions) are presented from both a theoretical and practical point of view (via Laplace transforms and methods involving orthogonal polynomials).