Revenue at Risk Calculator
The formula
What the revenue at risk tells you
Probability-weighted exposure across the pools that can realistically move: concentrated accounts and contracts renewing inside the planning window.
Calculation: Revenue at risk = Σ (exposure × probability) across risk pools. Enter your inputs and every substitution is shown below the result.
Reading the result
The number sizes the retention investment — a company with 18% of ARR at risk is buying different insurance than one at 6%.
Rules of thumb: Single-account exposure above 10% of ARR draws public-company disclosure treatment
Limitations and best practice
The classic error is double-counting: the largest accounts usually renew inside 12 months too. Run the pools as one matrix (account × renewal date), not two stacked numbers.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Where do the loss probabilities come from?
Is revenue at risk the same as expected loss?
Source & methodology
Risk-weighted exposure practice (concentration-risk conventions).
Revenue at Risk: what this tool answers
This page was written for one job: turning your own inputs into a defensible figure, with the working shown. Searchers land on a Revenue at Risk page for three reasons — to plan, to compare options, and to check that somebody else’s arithmetic is honest. This tool serves all three, and everything after the calculator explains the model instead of hiding it.
In plain terms, Revenue at Risk answers the question "Revenue at risk?". The measurement matters because it converts a situation that feels complicated — several inputs pulling in different directions — into a single number you can act on. Within Business & Entrepreneurship, Sales & Revenue is the context where this figure is quoted most often, and professionals treat it as a first-pass screen rather than a verdict.
There is a habit that separates people who get useful answers from Sales & Revenue numbers: they decide what question the figure answers before they compute it. Revenue at Risk answers “Revenue at risk?” — and nothing else, which is precisely why the result is trustworthy.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here revenue at risk = $605,504, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — ARR with renewals inside 12 months first, at ≈7.0 % of the headline for a ten-percent error either way in that input. Work down the page and by the end you could re-derive the result in a spreadsheet from memory.
Inside the Revenue at Risk calculation: formula and every input
The engine implements a single stated model: Revenue at risk = Σ (exposure × probability) across risk pools. There is no hidden coefficient and no login-gated precision — the formula printed is the formula executed, which is also what makes the result citable.
Top-10 account ARR ($) (example value 1,511,520) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
Annual loss probability of top 10 (%) (example value 12) is a quantity rather than a category — precision here is cheap and worth having. Enter it exactly as your document states it — quoted annual, monthly and effective rates are three different numbers.
ARR with renewals inside 12 months ($) (example value 2,356,233) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. If the period is partial, decide whether you mean elapsed or planned time and keep that meaning across every field.
Loss probability in renewals window (%) (example value 18) is a measured number in the unit named by the label; the formula does not convert for you. Enter it exactly as your document states it — quoted annual, monthly and effective rates are three different numbers.
Total ARR ($) (example value 17,375,000) is a plain measured quantity — the unit shown in the label is the unit the formula expects. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
A fully worked Revenue at Risk example
Rather than describe the calculation, here it is end to end — every substitution in order, starting from the inputs above. Starting figures: Top-10 account ARR ($), Annual loss probability of top 10 (%), ARR with renewals inside 12 months ($), Loss probability in renewals window (%). The computed revenue at risk comes out at $605,504, which the interpretation band labels “Risk pool is within a normal defensive-planning band”.
- Top-10 pool: $1,511,520 × 12% = $181,382
- Renewal pool: $2,356,233 × 18% = $424,122 → total $605,504
Risk from top accounts — $181,382. If your inputs change, this is usually the first companion figure to move.
Risk from renewal window — $424,122. This is the number experienced users quote when the headline alone would mislead.
Risk as share of total ARR — 3.5 %. This is the number experienced users quote when the headline alone would mislead.
Re-running with your own figures is instant; re-running by hand once is the best way to know the tool is telling you the truth.
How far Revenue at Risk can reasonably move
Read this table as the practical error bar on the headline figure. It answers the question people actually have after seeing a single number: how wrong could this be if the main input is off by ten or twenty percent?
| ARR with renewals inside 12 months setting | Revenue at risk |
|---|---|
| 80 % of the example value | $520,680 |
| 90 % of the example value | $563,092 |
| example inputs | $605,504 |
| 110 % of the example value | $647,917 |
| 120 % of the example value | $690,329 |
Across 5 settings of ARR with renewals inside 12 months, the result spans $520,680 to $690,329. A decision that only works at one row of this table is a decision waiting for an input to move. Reproduce it in the form above by editing ARR with renewals inside 12 months alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change Revenue at Risk the most
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the revenue at risk recomputed, so the ranking below is measured rather than asserted. It is the fastest honest answer to “what matters most in Revenue at Risk?” — and it is specific to these defaults, because sensitivity moves with the starting point.
- Nudge ARR with renewals inside 12 months by ±10 % and Revenue at Risk lands between $563,092 and $647,917 (sensitivity ≈7.0 %)
- Nudge Loss probability in renewals window by ±10 % and Revenue at Risk lands between $563,092 and $647,917 (sensitivity ≈7.0 %)
- Nudge Top-10 account ARR by ±10 % and Revenue at Risk lands between $587,366 and $623,643 (sensitivity ≈3.0 %)
- Nudge Annual loss probability of top 10 by ±10 % and Revenue at Risk lands between $587,366 and $623,643 (sensitivity ≈3.0 %)
ARR with renewals inside 12 months is the dominant lever here: ten percent either way moves the result by about 7.0 %, from $563,092 to $647,917. Measure that input from a document rather than from memory, and Loss probability in renewals window is effectively tied with it (≈7.0 % for the same nudge), so verify the pair together. The rest of the inputs earn only a rounding-error of attention, and that asymmetry is the practical payoff of measuring rather than asserting.
What a Revenue at Risk of $605,504 means in practice
The value above only becomes useful the moment you know what it is being measured against. The verdict attached to the default calculation — “Risk pool is within a normal defensive-planning band” — is one band on a ladder your own figure may sit somewhere else on. Before treating the band as fact, note its width: ten percent either way on ARR with renewals inside 12 months already spans $563,092 to $647,917. The practical reading rules: read the band as a starting hypothesis, then test it: change the two dominant inputs by ten percent and see whether the verdict survives. Verdicts that survive stress are the ones worth acting on.
Related measures answer related questions, and the distinctions matter: Revenue at Risk is the quantity, Revenue at risk is this tool’s reading of it, and the decision that follows belongs to neither of them separately.
The errors that quietly break a Revenue at Risk figure
The classic error is double-counting: the largest accounts usually renew inside 12 months too. Run the pools as one matrix (account × renewal date), not two stacked numbers. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Stopping at the first plausible answer. If the result surprises you, the productive question is which input would have to be wrong for the surprise to disappear — then go check that input.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: ARR with renewals inside 12 months first, everything else second.
The subtlest error is answering the wrong question precisely. Confirm that revenue at risk is actually the quantity your decision needs — the arithmetic is flawless either way, which is what makes the mistake invisible.
Before you trust your Revenue at Risk: a short checklist
- Record the date and the inputs alongside the number so future-you knows what was assumed.
- State, in one sentence, which convention each rate, unit or period in the form is using.
- Re-verify ARR with renewals inside 12 months against a source document — ten percent of error there moves the headline by ≈7.0 %.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Confirm the answer against one independent method or published benchmark for Revenue at Risk.
A routine for decision-grade Revenue at Risk
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — start from evidence. The inputs behind Revenue at Risk are top-10 account arr ($), annual loss probability of top 10 (%), arr with renewals inside 12 months ($), loss probability in renewals window (%), total arr ($). Write them down with their source next to each one; if you cannot name where a figure came from, that is the input most likely to be wrong. The test of a good estimate is not that it feels right but that it changes what you do.
Step 2 — compute the version you would not be embarrassed by. If a stranger audited your inputs, which set would you hand over? Enter that set, read the result, and treat everything else as upside. Note the assumption you are least sure about; that is where the real risk lives.
Step 3 — measure what deserves measuring. The ranked levers above tell you where a careful figure pays off. Everything else can stay approximate, which is a licence to stop hunting for data you do not need. If a result feels obviously right, that is the moment to check the inputs hardest.
Step 4 — compute a corridor, not a point. Three runs — worst, likely, best — turn Revenue at Risk from a snapshot into a range. Plan against the pessimistic end and treat the optimistic end as the upside story. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
Step 5 — save the story with the figure. A number without its inputs and its date is unusable within a quarter. Record $605,504, the assumptions behind it, and today’s date; your future self will be auditing a stranger’s arithmetic. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
Who actually uses Revenue at Risk — and when
Most Sales & Revenue disagreements are arithmetic disagreements in disguise. When Revenue at risk of $605,504 sits on the table with its working shown, the conversation stops being about who sounds more confident and starts being about which input is wrong. When two sources disagree, it is almost never the arithmetic that differs.
Professionals in Sales & Revenue use this style of calculation as a screening filter before spending real money or effort: a quick Revenue at Risk check eliminates weak options in minutes, and the survivors earn the deeper, slower analysis. Note the assumption you are least sure about; that is where the real risk lives.
Nothing here is stored or transmitted, so the habit of checking is free: open the page, re-enter current figures, compare with the number you saved last time. A calculation you cannot explain to somebody else is a calculation you cannot defend.
The questions that come up most about Revenue at Risk
What affects Revenue at Risk the most?
The short answer: ARR with renewals inside 12 months. The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the revenue at risk recalculated — ARR with renewals inside 12 months moved it furthest, by roughly 7.0 % ($563,092 to $647,917).
Do loss probability in renewals window and arr with renewals inside 12 months matter equally?
On these inputs, yes: the two measured within a rounding error of each other — ≈7.0 % and ≈7.0 % of the revenue at risk per ten-percent change. Treat them as one pair to verify together rather than ranking them.
What is a typical Revenue at Risk?
On the worked example above Revenue at Risk comes out at $605,504. Treat that as one point on a distribution rather than a norm: the bands, the companion outputs and the sensitivity ranking tell you how wide the plausible range really is.
How do I calculate Revenue at Risk by hand?
Use the stated model — Revenue at risk = Σ (exposure × probability) across risk pools — and substitute in the order the tool prints (it starts from Top-10 pool: $1,511,520 × 12% = $181,382). On the example inputs the hand route lands on $605,504, exactly what the calculator shows. A spreadsheet reproduces it in two or three cells; doing it once by hand is what makes the automated answer trustworthy.
What happens to Revenue at Risk if arr with renewals inside 12 months changes by 10 %?
Try it in the form above and the printed substitution will follow you; the pre-computed answer for the defaults is $563,092 to $647,917 across the ten-percent probe, i.e. ≈7.0 % sensitivity on the revenue at risk.
Is the Revenue at Risk result of $605,504 good or bad?
Good and bad are comparisons, so the honest test is three questions: where does your own Revenue at Risk sit against the $605,504 reference above, how far would a plausible input error move it (≈7.0 % per ten percent on ARR with renewals inside 12 months), and what does the alternative option compute to?
Should I use Revenue at Risk before launching?
Yes — a Revenue at Risk run on honest inputs before spending is the cheapest consulting an entrepreneur can buy. Re-run at every pricing change; the number moves more often than founders expect.
Can Revenue at Risk be negative or empty?
Yes, and that is informative rather than broken: a negative Revenue at Risk usually means the inputs encode an outflow or a shortfall, and the verdict band above labels exactly that situation instead of hiding it.
Where do the loss probabilities come from?
Historic cohort churn by risk tier — health score band, contract age, champion presence. Absent data, start with judgement rates and calibrate every renewal cycle.
Is revenue at risk the same as expected loss?
It is gross exposure × probability, before mitigation — the planning figure for what defense spend can be justified, not a forecast of what will actually churn.
Does this Revenue at Risk tool store my numbers?
No. The entire calculation runs in your browser session; nothing entered above is transmitted or saved, which is the correct behaviour for sensitive Business & Entrepreneurship figures and the reason you can re-run this page as often as you like.
The vocabulary of Revenue at Risk
- Risk from top accounts
- $181,382 on the example inputs — a companion figure printed beside the headline of Revenue at Risk so that no result is read in isolation.
- Risk from renewal window
- $424,122 for the Revenue at Risk worked case; it sits next to the main result because it carries context the headline leaves out.
- Risk as share of total ARR
- 3.5 % on the example inputs — a companion figure printed beside the headline of Revenue at Risk so that no result is read in isolation.
- Revenue at risk
- The primary output of this tool: $605,504 for the default inputs, computed exactly from Revenue at risk = Σ (exposure × probability) across risk pools.
- Worked example
- Every substitution in order, from the example inputs to $605,504 — the audit trail for the headline figure.
- Verdict band
- A named zone on the range of plausible results; the example inputs land in “Risk pool is within a normal defensive-planning band”, and your inputs may not.
- Sensitivity (±10 %)
- How far the Revenue at Risk moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Method, sources and what this tool cannot tell you
The model is published arithmetic implemented exactly as written: Revenue at risk = Σ (exposure × probability) across risk pools. Source of record: Risk-weighted exposure practice (concentration-risk conventions). Specialist software layers extra coefficients on top of the same algebra; none are hidden here, and that transparency is what makes a disagreement traceable to a specific input instead of a black box.
This page is an estimation aid, not professional advice. The design rule is simple: two people entering identical figures must get identical answers. What that buys you is reproducibility — two people, two browsers, the same arithmetic, and a printed trail from inputs to result that either of them can audit.
Next steps after the calculation
Save the number together with its inputs and today’s date; a Revenue at Risk figure without context is unusable the moment an input changes.
The audience here is people who need one trustworthy number before their next decision. Everything you need to defend the result — formula, substitution, sensitivity, source — is printed above, so the only remaining variable is the honesty of your inputs.