Graeme Keith

In this article, Graeme Keith explores the deeper purpose of risk modeling—not as a mathematical exercise in prediction, but as a disciplined way of thinking. Drawing parallels from military planning to decision science, Keith examines why the act of modeling itself often yields greater value than the models it produces. Through reflections on clarity, logic, and the pursuit of usefulness over perfection, he argues that modeling is as much about understanding uncertainty as it is about managing it.

In his latest article, Graeme Keith explores the foundations of risk modeling in his latest piece, tracing its roots from ancient mathematics to modern decision-making. He argues that models should begin with real-world problems, not abstract equations, and makes the case for why risk modeling must remain intelligible to decision makers.

In this article, Graeme Keith dives into the limitations of traditional risk matrices and presents an alternative approach to risk management. By exploring the need for a model that better aligns with real-world decision-making, Keith highlights the shortcomings of compliance-driven exercises and offers a framework that allows businesses to better assess and prioritize risks across the enterprise.

In Graeme Keith's latest article, he explores the limitations of heat maps in risk assessment and why quantitative risk analysis is essential for effective Enterprise Risk Management (ERM). By using two hypothetical risk scenarios, Keith highlights the significant gaps in traditional risk matrices and advocates for a more rational, analytical approach to risk prioritization and aggregation. Through his analysis, he emphasizes the need for a deeper understanding of risk impacts, beyond surface-level assessments.

In today's risk landscape, regulatory-driven practices often fail to deliver meaningful value. Graeme Keith examines the challenges and opportunities presented by the dichotomy between Risk Management 1 (RM1) and Risk Management 2 (RM2). By exploring the unintended consequences of regulatory pressure on risk management systems, Keith presents a case for evolving traditional risk practices into a more strategic, decision-supportive approach.