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Main Authors: Woodman, George, Andrist, Ruben S., Häner, Thomas, Steiger, Damian S., Schuetz, Martin J. A., Katzgraber, Helmut G., Detyniecki, Marcin
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2504.16530
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author Woodman, George
Andrist, Ruben S.
Häner, Thomas
Steiger, Damian S.
Schuetz, Martin J. A.
Katzgraber, Helmut G.
Detyniecki, Marcin
author_facet Woodman, George
Andrist, Ruben S.
Häner, Thomas
Steiger, Damian S.
Schuetz, Martin J. A.
Katzgraber, Helmut G.
Detyniecki, Marcin
contents We propose and implement modern computational methods to enhance catastrophe excess-of-loss reinsurance contracts in practice. The underlying optimization problem involves attachment points, limits, and reinstatement clauses, and the objective is to maximize the expected profit while considering risk measures and regulatory constraints. We study the problem formulation, paving the way for practitioners, for two very different approaches: A local search optimizer using simulated annealing, which handles realistic constraints, and a branch & bound approach exploring the potential of a future speedup via quantum branch & bound. On the one hand, local search effectively generates contract structures within several constraints, proving useful for complex treaties that have multiple local optima. On the other hand, although our branch & bound formulation only confirms that solving the full problem with a future quantum computer would require a stronger, less expensive bound and substantial hardware improvements, we believe that the designed application-specific bound is sufficiently strong to serve as a basis for further works. Concisely, we provide insurance practitioners with a robust numerical framework for contract optimization that handles realistic constraints today, as well as an outlook and initial steps towards an approach which could leverage quantum computers in the future.
format Preprint
id arxiv_https___arxiv_org_abs_2504_16530
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Modern Computational Methods in Reinsurance Optimization: From Simulated Annealing to Quantum Branch & Bound
Woodman, George
Andrist, Ruben S.
Häner, Thomas
Steiger, Damian S.
Schuetz, Martin J. A.
Katzgraber, Helmut G.
Detyniecki, Marcin
Optimization and Control
Computational Finance
Quantum Physics
We propose and implement modern computational methods to enhance catastrophe excess-of-loss reinsurance contracts in practice. The underlying optimization problem involves attachment points, limits, and reinstatement clauses, and the objective is to maximize the expected profit while considering risk measures and regulatory constraints. We study the problem formulation, paving the way for practitioners, for two very different approaches: A local search optimizer using simulated annealing, which handles realistic constraints, and a branch & bound approach exploring the potential of a future speedup via quantum branch & bound. On the one hand, local search effectively generates contract structures within several constraints, proving useful for complex treaties that have multiple local optima. On the other hand, although our branch & bound formulation only confirms that solving the full problem with a future quantum computer would require a stronger, less expensive bound and substantial hardware improvements, we believe that the designed application-specific bound is sufficiently strong to serve as a basis for further works. Concisely, we provide insurance practitioners with a robust numerical framework for contract optimization that handles realistic constraints today, as well as an outlook and initial steps towards an approach which could leverage quantum computers in the future.
title Modern Computational Methods in Reinsurance Optimization: From Simulated Annealing to Quantum Branch & Bound
topic Optimization and Control
Computational Finance
Quantum Physics
url https://arxiv.org/abs/2504.16530