Abstract
Specially in the case of scenarios under uncertainty, the efficient management of risk when matching assets and liabilities is a relevant issue for most insurance companies. This paper considers such a scenario, where different assets can be aggregated to better match a liability (or the other way around), and the goal is to find the asset-liability assignments that maximises the overall benefit over a time horizon. To solve this stochastic optimisation problem, a simulation-optimisation methodology is proposed. We use integer programming to generate efficient asset-to-liability assignments, and Monte-Carlo simulation is employed to estimate the risk of failing to pay due liabilities. The simulation results allow us to set a safety margin parameter for the integer program, which encourage the generation of solutions satisfying a minimum reliability threshold. A series of computational experiments contribute to illustrate the proposed methodology and its utility in practical risk management.
Highlights
Within the enormous variety of insurance types that we can find, long-term life insurance stands out for its complexity in terms of financial management
A feasible solution to the net present value asset-liability management (NPV-ALM) problem consists of a set of asset-liability assignments such that: (i) all liabilities are covered; and (ii) no individual assets or liabilities are part of more than one asset-liability assignment
We propose a matheuristic algorithm for solving the NPV-ALM problem
Summary
Within the enormous variety of insurance types that we can find, long-term life insurance stands out for its complexity in terms of financial management. It is a requirement that the insurer has a range of techniques that allow for matching its assets, as long-term income generators, with its liabilities. One of most popular solutions to this asset management problem is cash-flow matching (Iyengar and Ma 2009), whose main objective is to ensure the timely payment of the liabilities This approach minimises the number of contractual breaches. Bayliss et al (2020) considered a simplified ALM problem, based on the net present value (NPV) concept, in which only one-to-one asset-liability assignment were allowed. An integer program is solved recursively to generate feasible and efficient asset-liability assignments for a deterministic scenario (where we assume average values for each random variable in the model).
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