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The Optimization of Reinsurance by the Maximization of Technical Benefits and Minimization of Probability of Ruin Using Genetic Algorithms

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The ruin theory is a crucial tool for the insurance company and it is a very important factor in choosing an optimal reinsurance. However this single optimization criterion does not usually lead to a rational decision to choose an optimal reinsurance plan. In this paper, we propose an approach for optimizing a reinsurance strategy which is based on maximizing technical benefit of the insurer and the minimization of the probability of ruin simultaneously and dynamically using genetic algorithms. This approach uses a database that contains the forms of reinsurance and pricing methods. This work is a decision support tool for insurance companies.
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Optimization; Insurance; Reinsurance; Technical Benefit; Pricing Method; Form Reinsurance Ruin Probability; Genetic Algorithms

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