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Strategic Business Leader · Identification, assessment and measurement of risk

Risk Measurement Techniques for ACCA SBL

Updated 11 October 2026 · Fact-checked

Risk measurement techniques put a size on uncertainty. Expected values weight outcomes by probability. Sensitivity analysis changes one variable at a time. Scenario analysis changes several together. Simulation runs many random trials. Value at risk estimates the loss not exceeded at a set confidence level over a set period.

Understand Risk Measurement Techniques

Risk is the chance that actual results differ from expected results. Before a board can decide how to respond, it must know how big the risk is. Measurement turns a vague worry into something you can compare and rank.

There are two broad groups. Qualitative methods use judgement, such as rating a risk high, medium or low. They are quick and work when data is thin. Quantitative methods use numbers, such as probabilities and money values. They are more precise, but only as good as the inputs.

The main quantitative tools differ in what they show. Expected value gives a single average outcome. Sensitivity analysis shows which one variable matters most. Scenario analysis shows what happens when several variables move together, for example in a recession. Simulation uses a computer to run thousands of random trials and shows the spread of outcomes. Value at risk (VaR) gives a single loss figure at a stated confidence level and time period.

Every tool has limits. Expected values hide the spread and may never actually occur. Sensitivity ignores links between variables. Scenarios depend on which ones you choose. Simulation and VaR rely on past data and assumed distributions, so they can fail in extreme events. In SBL you are marked on applying the right tool to the case and judging its limits, not on heavy calculation.

Key rules to remember

Expected value (EV)
EV = Σ (probability × outcome)
Probabilities must add up to 1. EV is a long-run average, not a likely single result.
Sensitivity (percentage change)
Sensitivity = (NPV or profit ÷ value of the variable) × 100%
This shows the percentage change in the variable that makes the result zero. The smaller the percentage, the more sensitive the project is to that variable.
Value at risk (normal distribution)
VaR = z × σ × √t (with the mean assumed to be zero)
σ is the standard deviation per period, t is the number of periods, and z is the confidence-level factor. For 95% one-tailed, z = 1.65. For 99% one-tailed, z = 2.33. Multiply by the position value if σ is a percentage.

How to solve Risk Measurement Techniques questions

Use this method for any question asking you to measure, compare or evaluate risk.

  1. 1Read the requirement. Decide whether it asks you to calculate, explain, or advise on a technique.
  2. 2Identify the risk and what is uncertain in the scenario, such as demand, cost, exchange rate or market price.
  3. 3Pick the technique that fits the data given. Probabilities suggest expected value. One key variable suggests sensitivity. Linked changes suggest scenarios. A tradeable portfolio suggests VaR.
  4. 4Do any calculation neatly and label every figure. Show the formula first.
  5. 5Interpret the result in the context of the business. Say what it means for the decision.
  6. 6State the limitations of the technique, such as reliance on estimates or ignoring links between variables.
  7. 7Conclude with a recommendation and, where relevant, a risk response.

Quickest way: Compare and contrast in four lines

When to use it: Use this when a question asks for the difference between two techniques, or which is more suitable.

  1. Say what the technique measures in one sentence.
  2. Say what it needs as input.
  3. Give one strength and one weakness.
  4. Link to the case: why it suits or does not suit this company.

Common mistakes in Risk Measurement Techniques

  • Treating expected value as the outcome that will happen.

    The result is a single neat number, so it looks like a forecast.

    Fix: State that EV is a weighted average over many repeats. Say the actual result may be very different, especially for one-off decisions.

  • Confusing sensitivity analysis with scenario analysis.

    Both test 'what if' changes.

    Fix: Sensitivity changes one variable at a time. Scenario analysis changes several variables together in a consistent story.

  • Quoting VaR without the confidence level and time period.

    Students remember it as 'the maximum loss'.

    Fix: Always write it as, for example, 'a 95% chance the loss will not exceed ₹X over one day'. VaR does not say how bad losses are beyond that point.

  • Only calculating and not advising.

    Numbers feel safer than judgement.

    Fix: Add a sentence on what the result means for the board and what action follows. This earns application and professional skills marks.

  • Ignoring limitations of the technique.

    Students assume a quantitative method is automatically reliable.

    Fix: Name at least one limit: subjective probabilities, past data not repeating, or ignoring links between variables.

Worked examples

Example 1

A company is considering a project with three possible annual profits depending on demand: low demand ₹20,00,000 (probability 0.3), medium demand ₹50,00,000 (probability 0.5) and high demand ₹80,00,000 (probability 0.2). Calculate the expected profit and comment on its usefulness.

Show the solution
  1. Check the probabilities: 0.3 + 0.5 + 0.2 = 1.0.
  2. Low demand: 0.3 × ₹20,00,000 = ₹6,00,000.
  3. Medium demand: 0.5 × ₹50,00,000 = ₹25,00,000.
  4. High demand: 0.2 × ₹80,00,000 = ₹16,00,000.
  5. Add them: ₹6,00,000 + ₹25,00,000 + ₹16,00,000 = ₹47,00,000.
  6. Comment: no single scenario gives ₹47,00,000, so the figure is only an average. It also hides the spread, as profit could be anywhere from ₹20,00,000 to ₹80,00,000. The probabilities are estimates and may be biased.

Answer: Expected annual profit is ₹47,00,000. It helps compare projects, but it hides the spread of outcomes and relies on estimated probabilities.

Example 2

A project has a present value of future cash inflows of ₹1,25,00,000 and an initial outlay of ₹1,00,00,000. The NPV is therefore ₹25,00,000. Calculate the sensitivity of the NPV to the inflows, then explain how scenario analysis differs.

Show the solution
  1. NPV = ₹1,25,00,000 − ₹1,00,00,000 = ₹25,00,000.
  2. Sensitivity to inflows = NPV ÷ PV of inflows = ₹25,00,000 ÷ ₹1,25,00,000 = 20%.
  3. Interpretation: the present value of inflows can fall by 20% before NPV reaches zero.
  4. Sensitivity to the outlay = ₹25,00,000 ÷ ₹1,00,00,000 = 25%. The project is more sensitive to inflows, since 20% is smaller than 25%.
  5. Difference: sensitivity changes one variable while holding others constant. Scenario analysis changes several together, for example lower sales, higher costs and a weaker currency in a recession, and shows the combined effect on NPV.

Answer: NPV can fall to zero if inflows drop by 20%, or if the outlay rises by 25%. Inflows are the more critical variable. Scenario analysis tests combined changes, not one at a time.

Exam tips

  • Link every technique to the case. Name the actual uncertain variable in the scenario rather than giving a textbook definition.
  • When asked to compare techniques, give both a strength and a weakness for each. A one-sided answer loses marks.
  • Always state the limitations. Examiners reward judgement on how reliable the measure is.
  • End with advice. Say what the board should do given the measured risk, as this supports professional skills marks.

Practice questions from Identification, assessment and measurement of risk

Risk Measurement Techniques in other exams

The same ground in other exams, if you are preparing for more than one or want another angle on it.

Risk Measurement Techniques: frequently asked questions

What is the difference between sensitivity analysis and scenario analysis?

Sensitivity analysis changes one variable at a time to see how much it affects the result. Scenario analysis changes several variables together to model a coherent situation, such as a downturn. Scenarios capture links between variables, which sensitivity ignores.

What does value at risk tell you?

VaR gives a loss figure that should not be exceeded at a stated confidence level over a stated period. For example, a 95% one-day VaR of ₹10,00,000 means a 95% chance of losing no more than that in a day. It says nothing about how large the loss could be in the remaining 5%.

Do I need to calculate VaR in SBL?

SBL is mainly about explaining and applying concepts to a case, so detailed calculations are less likely than discussion. Be ready to explain what VaR is, what it needs, and its limits. Know the simple formula in case a calculation is asked.

Why is simulation useful?

Simulation runs a large number of trials with random values for uncertain variables. It shows the whole range and likelihood of outcomes, not just one average. It needs good data and assumptions, and it can be costly and complex.