An evolutionary strategy for multiobjective reinsurance optimization - A case study
Juan G. Villegas (Universidad de Antioquia, Colombia)
June 15, 2016 | 13h00-14h00 | Salle Von Neuman - Polytech Tours
In this work we tackle the reinsurance optimization problem (ROP) from the point of view of an insurance company. The ROP seeks to find a reinsurance program that optimizes two conflicting objectives: the maximization of the expected value of the profit of the company and the minimization of its value at risk (or other measure of risk).
To calculate these two objectives we built a probabilistic model of the portfolio of risks of the company. This model is embedded within an evolutionary strategy (ES) that approximates the efficient frontier of the ROP using a combination of four classical insurance structures: surplus, quota share, excess of lost and stop loss reinsurances.