Algorithmic Insurable Risk Portfolios

Companies and organizations face many risks such as damage to their buildings, liability resulting from management misbehavior, and threats external to the organization, such as cyber attacks. Firms have financial responsibility for these risks, meaning they “own” them, and so it is natural to consider them as a risk portfolio. Analogous to the familiar asset portfolio methods, this article shows how risk managers can use a data-driven approach, utilizing constrained optimization algorithms, to provide guidance on the amount of risk to retain or transfer. Using a case study, we are largely able to corroborate the work of expert risk brokers who make risk retention decisions using their extensive experience and knowledge of the worldwide insurance marketplace. Moreover, this optimal insurance framework supplements their work by emphasizing the risk versus return/cost trade-off and offering data visualization educational tools that help improve managers’ financial literacy.