Stochastic simulation of optimal insurance policies to manage supply chain risk

Manufacturing firms, particularly those in the chemical industry, typically employ risk management principles to identify, analyze, and prioritize risks that have the potential to cause significant property damage and business interruption to operating assets. These risks, which may exceed the firm´s financial capacity post-loss, can be hedged using financial instruments in the insurance markets. Many firms design insurance programs to share the loss exposure; however characterization of the loss distributions and determination of the optimal coverage limits is more challenging. Few applied simulation models have been published in the open literature to address optimal insurance policies, despite the importance and value provided to shareholders. Consequently, corporate risk managers often rely on heuristics or past decisions to structure insurance programs during renewal periods. This simulation model considers the benefit of risk management given loss distributions specific to contract manufacturers and establishes a scientific approach for making optimal insurance policy decisions.