open access publication

Article, 2022

Extension of as-if-Markov modeling to scaled payments

INSURANCE MATHEMATICS & ECONOMICS, ISSN 0167-6687, 0167-6687, Volume 107, Pages 288-306, 10.1016/j.insmatheco.2022.09.001

Contributors

Christiansen, Marcus C [1] Furrer, Christian 0000-0002-7600-4513 (Corresponding author) [2]

Affiliations

  1. [1] Carl Von Ossizetzky Univ Oldenburg, Inst Math, Oldenburg, Germany
  2. [NORA names: Germany; Europe, EU; OECD];
  3. [2] Univ Copenhagen, Dept Math Sci, Copenhagen, Denmark
  4. [NORA names: KU University of Copenhagen; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

In multi-state life insurance, as-if-Markov modeling has recently been suggested as an alternative to Markov modeling in case of deterministic sojourn and transition payments. Incidental policyholder behavior, on the other hand, gives rise to duration-dependent payments in the form of so-called scaled payments. The goal of this paper is to establish as-if-Markov modeling also for scaled payments. To this end, we employ change of measure techniques to transfer the added complexity from the payments to an auxiliary probabilistic model. Based hereon, we show how to compute the accumulated cash flow by solving a system of equations comparable to Kolmogorov's forward equations for Markov chains, but with the transition rates replaced by certain forward transition rates related to the auxiliary probabilistic model. Finally, we provide feasible landmark estimators for these auxiliary forward transition rates subject to entirely random right-censoring. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Keywords

Incidental policyholder behavior, Kolmogorov?s forward equations, Landmark estimators, Life insurance, Non-Markov models

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