Optimal Reinsurance: A Ruin-Related Uncertain Programming Approach

TL;DR

This paper develops a novel approach using Liu's uncertainty theory to optimize reinsurance strategies by assessing and maximizing the uncertain measure of ruin, providing a practical computational method for insurance risk management.

Contribution

It introduces a new uncertain programming model for reinsurance optimization based on ruin probability, with a simplified computational method and a generalized, more practical framework.

Findings

A new uncertain measure of ruin for insurance companies.

A simple computational method for ruin probability.

A generalized reinsurance model for practical applications.

Abstract

We investigate the role of reinsurance in maximizing the wealth of an insurance company. We use Liu's uncertainty theory (B. Liu, 2007) for the problem modeling and follow-up computations. The uncertainty measure of ruin for the insurance company is considered as the optimization criterion. Since calculating the ruin index is very difficult, we introduce a simple computational method to identify the uncertain measure of ruin for an insurance company. Finally, a generalized model is presented, granting the model be more practical.