Why Cybersecurity Needs Probability — Not Predictions

The article argues that cybersecurity decision-making should shift from headline-driven predictions to Bayesian probability-based risk models that combine insurance claims data, expert judgment, control maturity, and firmographic signals. It explains how probabilistic models better estimate the likelihood and range of losses from perils like breaches, fraud, and extortion, cites insurance trends showing increased claim frequency but fewer material losses, and recommends data-driven risk management, improved security controls, cyber insurance, and resisting fear-driven narratives to improve organizational cyber resilience.