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Optimal Risk Transfer: A Numerical Optimisation Approach

Asimit, A.V., Gao, T., Hu, J. & Kim, E. (2018). Optimal Risk Transfer: A Numerical Optimisation Approach. North American Actuarial Journal, 22(3), pp. 341-364. doi: 10.1080/10920277.2017.1421472

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Capital efficiency and asset/liability management are part of the Enterprise Risk Management Process of any insurance/reinsurance conglomerate and serve as quantitative methods to fulfill the strategic planning within an insurance organisation. There has been a considerable amount of work in this ample research field, but invariably one of the last questions is whether or not, numerically, the method is practically implementable, which is our main interest. The numerical issues are dependent upon the traits of the optimisation problem and therefore, we plan to focus on the optimal reinsurance design, which has been a very dynamic topic in the last decade. The existing literature is focused on finding closed-form solutions that are usually possible when economic, solvency, etc constraints are not included in the model. Including these constraints, the optimal contract can only be found numerically. The efficiency of these methods is extremely good for some well-behaved convex problems, such as the Second-Order Conic Problems. Specific numerical solutions are provided in order to better explain the advantages of appropriate numerical optimisation methods chosen to solve various risk transfer problems. The stability issues are also investigated together with a case study performed for an insurance group that aims capital efficiency across the entire organisation.

Publication Type: Article
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in North American Actuarial Journal, available online:
Publisher Keywords: Linear Programming, Optimal Reinsurance/Risk Transfer, Risk Measure, Second-Order Conic Programming
Departments: Bayes Business School > Actuarial Science & Insurance
Text - Accepted Version
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