Basic Qualitative Methods

Qualitative risk assessment focuses on describing potential risks using expert judgment rather than numbers. Risks are evaluated based on their likelihood and severity in descriptive terms such as high, medium, or low, and often visualized with tools like risk matrices. This approach is useful for initial screening when there isn’t enough data to assign precise values or when speed and experience-based insights are important. (HSE Info Service)

In finance, qualitative methods help decision-makers quickly identify major threats and prioritize areas that may require deeper analysis before applying more complex models.

Semi-quantitative Methods

Semi-quantitative risk assessment combines the subjective insights of qualitative analysis with simple numerical scoring systems. Instead of just saying whether a risk is “high” or “low,” analysts assign scores or weights to likelihood and impact based on predefined scales, and then combine these scores to produce a risk rating. (Drata)

This approach provides more structure and consistency than purely descriptive methods, and can be especially helpful when partial data is available but a full statistical analysis isn’t practical. It offers a middle ground that improves objectivity without requiring complex models or extensive historical data.

Quantitative Methods

Quantitative risk assessment uses numerical data, statistics, and mathematical models to estimate risk in measurable terms. It assigns actual numbers to both the probability of a risk event occurring and the magnitude of its financial impact. (Metricstream)

In finance, quantitative methods include:

• Monte Carlo simulations
• Value at Risk (VaR)
• Conditional Value at Risk (CVaR)
• Expected Shortfall
• Probability distributions and loss models

Because these approaches rely on data and rigorous computation, they provide precise, measurable risk estimates, making them ideal for pricing, capital allocation, regulatory compliance, and portfolio optimization.