Glossary
Updated
Uses statistical and probabilistic methods (Monte Carlo simulations, value-at-risk calculations, Bayesian risk models) to assign numerical scores to identified risks (e.g., model drift, data breaches). Quantitative assessments allow direct comparison of disparate risks, support cost-benefit analyzes of controls, and feed into enterprise risk dashboards. Governance mandates consistent risk-scoring methodologies, transparent assumptions, and periodic re-estimation as data evolves.
Example
An insurer quantifies the risk of automated-underwriting errors by modeling the probability of misclassification (2%) and average claim cost ($10k), yielding an expected loss of $200 per policy. They compare this to control-implementation costs, deciding to invest in additional validation rather than manual reviews, optimizing risk mitigation spend.