Intelligent Risk Modeling and Decision Frameworks

Intelligence risk models provide the foundations for decision-making systems capable of predicting, sensing, and managing risk under uncertainty. The past twenty-five years have seen the rapid integration of machine learning into business processes; however, many of these applications are built in silos and independent of risk modeling across the enterprise. For organizations to fully leverage the vast troves of data at their disposal, the systems that govern intelligence risk must incorporate machine learning methods. This chapter introduces intelligent risk modeling and decision frameworks. Its central theme is that intelligent risk models must be constructed in a manner that aligns with broader decision processes and the organization’s overall risk appetite. The framework subsumes the field of decision-making under uncertainty via probabilistic reasoning and Bayesian decision theory.