1. What is Loss Expectancy?

Loss Expectancy is a risk assessment metric that calculates the expected monetary loss from a potential risk event. It combines the probability of an event occurring with the financial impact if it does occur.

2. How Does the Calculator Work?

The calculator uses the Loss Expectancy formula:

Where:

• \( Probability \) — Likelihood of the event occurring (0-1)
• \( Impact \) — Financial consequence if the event occurs (USD)

Explanation: This formula provides a quantitative estimate of potential losses, helping organizations prioritize risk mitigation efforts.

3. Importance of Loss Expectancy Calculation

Details: Calculating loss expectancy is crucial for effective risk management, insurance planning, resource allocation, and making informed decisions about risk mitigation strategies.

4. Using the Calculator

Tips: Enter probability as a decimal between 0 and 1 (e.g., 0.25 for 25% chance) and impact in US dollars. Both values must be valid non-negative numbers.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between single loss expectancy and annual loss expectancy?
A: Single Loss Expectancy (SLE) calculates loss from a single occurrence, while Annual Loss Expectancy (ALE) multiplies SLE by the estimated annual frequency of occurrence.

Q2: How accurate are loss expectancy calculations?
A: Accuracy depends on the quality of probability and impact estimates. These are often based on historical data, expert opinion, or statistical modeling.

Q3: What types of risks can this calculate?
A: This approach can be applied to various risks including cybersecurity incidents, natural disasters, equipment failure, or any event with quantifiable financial impact.

Q4: How should probability be estimated?
A: Probability can be estimated from historical data, industry benchmarks, expert judgment, or predictive models depending on the specific risk.

Q5: What are the limitations of loss expectancy calculations?
A: Limitations include uncertainty in probability estimates, difficulty quantifying intangible impacts, and the potential for unexpected correlation between risks.