Risk Quantification converts qualitative risk assessments into monetary values, probabilities, or other metrics enabling objective comparison, aggregation, and decision making. Techniques include actuarial analysis, Monte Carlo simulation, Value at Risk calculations, and loss distribution modeling. For example, quantifying cyber risk might estimate annual loss expectancy by multiplying breach likelihood by average incident cost based on historical data. Quantification supports cost-benefit analysis of controls, capital allocation, insurance purchasing decisions, and risk-adjusted performance measurement. Challenges include data scarcity for low-frequency events, model uncertainty, and false precision that obscures subjective assumptions. Effective practice combines quantitative analysis with qualitative judgment and sensitivity testing.