Multiple Attribute Decision Making (MADM) in Proportional-Stop-Loss Reinsurance

Wang Jiexuan

Abstract

This dissertation addresses the issue of optimal reinsurance contract, modeling the decision making process from both parties, which is most often negotiated through reinsurance broking rms. The study acknowledges existing literatures and methodologies addressing reinsurance decision problem, and proposes a decision ow to model the reinsurance design and selection process. In contrast to vast existing literature on pure proportional reinsurance or pure stop-loss reinsurance, the study adopts a modi ed reinsurance design with a combination of proportional and stop-loss reinsurance ("Proportional-Stop-loss"). In terms of methodology, the most signi cant contribution is that the study explores the possibility of incorporating Multiple Attribute Decision Making (MADM) to better represent the reinsurance negotiations. The Multi-Objective Decision Making (MODM) is applied in designing alternatives. Then MADM is applied to aid insurance companies in choosing the most appropriate reinsurance contract. To illustrates the feasibility of intelligent decision supporting system in reinsurance market, the study includes a numerical case study using simulation software @Risk in modelling risk and claim, and programming in MATLAB to implement MADM. By comparing and contrasting with optimality model under single criteria, the study demonstrates that MADM could better resemble and support comprehensive reinsurance decisions.