Loss Given Default Calculator
The formula
What the loss given default tells you
Severity, not probability: when the borrower fails, what fraction of exposure does not come back? Collateral, seniority and the length of the workout decide it — in that order.
Calculation: LGD = 1 − (recovery − costs) ÷ EAD. Enter your inputs and every substitution is shown below the result.
Reading the result
Secured senior LGDs run 10–30%; unsecured corporate 60–70% is the classic assumption; consumer credit-card regimes sit near 90–100% because there is nothing to repossess.
Rules of thumb: Basel gives LGD floors by asset class; banks use downturn LGDs, not average LGDs, in stress work
Limitations and best practice
Recovery timing matters — a 70% recovery spread over four years is far worse than 60% next quarter. Discount recoveries or model the loss with the funding cost of the delay.
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
Why is unsecured bank lending so high in LGD?
Is LGD the same as a defaulted bond's haircut?
Source & methodology
Altman, Brand & Satterfield (2005) "LRRA"; Basel II Annex 7 LGD floors.
Loss Given Default: what this tool answers
This page was written for one job: turning your own inputs into a defensible figure, with the working shown. There are plenty of pages about Loss Given Default; almost none of them show the working. This one does: the formula, every input, a fully computed example, and a sensitivity analysis calculated live from this engine’s own defaults.
Every investing metric in Investing & Markets is a bet about the future priced in today’s language. Loss Given Default translates that bet: LGD = 1 − (recovery − costs) ÷ EAD. The translation is mechanical and reliable; the judgement is deciding whether the inputs you feed it are honest forecasts or wishful numbers.
The number itself is the easy part. What takes judgement is knowing which inputs are facts in your situation and which are guesses wearing a decimal point — a distinction this page makes explicit for every field above.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here loss given default = 28.6%, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Recovered value first, at ≈28.6 % 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.
The Loss Given Default formula, explained
Here is the complete model this tool runs — LGD = 1 − (recovery − costs) ÷ EAD — with each input explained below. If a competitor’s page gives you a different answer from the same inputs, this is the text that settles which of you is right.
Exposure at default ($) (example value 120,101) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Recovered value ($) (example value 98,250) 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.
Workout & legal costs ($) (example value 12,500) is a plain measured quantity — the unit shown in the label is the unit the formula expects. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
Loss Given Default with real numbers, step by step
Abstract formulas are hard to trust, so here is the complete substitution using the default inputs, written the way an examiner would want it. Starting figures: Exposure at default ($), Recovered value ($), Workout & legal costs ($). Run to the end, the loss given default resolves to 28.6% — Severity on this claim: 28.6% on the bands this tool uses.
- Net recovery = $98,250 − $12,500 = $85,750
- LGD = 1 − $85,750 ÷ $120,101 = 28.6%
Net proceeds rate — 71.4 %. If your inputs change, this is usually the first companion figure to move.
Dollar loss — $34,351. If your inputs change, this is usually the first companion figure to move.
Recovery needed for LGD = 40% — $84,561. Compare it against the main result of 28.6% before drawing conclusions.
With costs ignored — 18.2 %. Compare it against the main result of 28.6% before drawing conclusions.
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.
The Loss Given Default corridor: your result across a realistic band
Single-point answers invite false confidence, so the same engine was run across a band around the input that matters most here. Each row is a full recalculation of Loss Given Default, not an interpolation.
| Recovered value setting | Loss given default |
|---|---|
| 80 % of the example value | 45.0% |
| 90 % of the example value | 36.8% |
| example inputs | 28.6% |
| 110 % of the example value | 20.4% |
| 120 % of the example value | 12.2% |
Across 5 settings of Recovered value, the result spans 12.2% to 45.0%. 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 Recovered value alone; the substitution steps will follow your figures exactly.
Where Loss Given Default is fragile — and where it is not
Nobody should have to guess which input matters. The engine was re-run once per field below — ten percent up, ten percent down, everything else frozen — and the results ranked by how far they moved the loss given default. For Loss Given Default the ranking is measured rather than guessed, and it belongs to these defaults: shift the starting point and the order can shift with it.
- Recovered value: ten percent up gives 20.4%, ten percent down gives 36.8% — ≈28.6 % of the loss given default either way
- Nudge Exposure at default by ±10 % and Loss Given Default lands between 20.7% and 35.1% (sensitivity ≈27.7 %)
- Workout & legal costs: ten percent up gives 29.6%, ten percent down gives 27.6% — ≈3.6 % of the loss given default either way
Recovered value is the dominant lever here: ten percent either way moves the result by about 28.6 %, from 20.4% to 36.8%. Measure that input from a document rather than from memory, and Exposure at default is effectively tied with it (≈27.7 % 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.
Is your Loss Given Default good — reading the result bands
Nobody acts on a bare figure — they act on a figure with a comparison attached. On the example inputs the band reads “Severity on this claim: 28.6%”; your own figures place you on a different rung of the same ladder. How much of that band is luck? On Recovered value alone ten percent either way covers 20.4% to 36.8%. The practical reading rules: compare against your own history before comparing against other people; treat band boundaries as zones, not walls — one point on the wrong side of a threshold rarely changes a real outcome; and when a companion output contradicts the headline, believe the pair.
In Investing & Markets, Loss Given Default is one instrument in an orchestra: on its own it is a number, next to Net proceeds rate and Dollar loss it becomes a diagnosis. The tools linked above exist so the headline never has to carry that weight alone.
How people get Loss Given Default wrong
Recovery timing matters — a 70% recovery spread over four years is far worse than 60% next quarter. Discount recoveries or model the loss with the funding cost of the delay. 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.
Reporting the headline and quietly discarding Net proceeds rate. The companions are where the shape of the trade-off survives the rounding.
One mistake is specific to this engine: assuming every input matters equally. The computation above shows Recovered value dominating — a careful figure there beats false precision everywhere else.
The subtlest error is answering the wrong question precisely. Confirm that loss given default is actually the quantity your decision needs — the arithmetic is flawless either way, which is what makes the mistake invisible.
A quick check for any Loss Given Default figure
- Compare the result with one independent method or published benchmark.
- Note the date and the inputs beside the number so the figure can be audited later.
- Re-verify Recovered value against a source document — ten percent of error there moves the headline by ≈28.6 %.
- Compare the output against one published benchmark or a colleague’s independent estimate.
- State, in one sentence, which convention each rate, unit or period in the form is using.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
Step by step: getting a trustworthy Loss Given Default out of this tool
Using a calculator well sounds trivial, but the difference between a decision-grade figure and a throwaway one lives entirely in the routine. The routine for Loss Given Default takes a minute to learn and applies to every input above.
Step 1 — gather before you type. Loss Given Default depends on exposure at default ($), recovered value ($), workout & legal costs ($). Collect them from a source document — a statement, a report, an invoice, a log — rather than from memory, because recalled inputs are the single largest cause of wrong results. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
Step 2 — start from the case you can defend. Enter pessimistic-but-honest figures first; the optimistic run is a ceiling, not a plan. A conclusion that holds on conservative inputs holds everywhere. Repeating a calculation with the same numbers proves only that the arithmetic is reliable — which is worth knowing.
Step 3 — change one input at a time. Nudge a single field by ten percent, watch the headline and its companions move, then undo it. Two or three fields will dominate — the sensitivity table above already ranks them for this engine. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
Step 4 — ask what would have to be true. Take the result you want and work backwards through the inputs until you find the assumption that produces it; then decide honestly whether that assumption is defensible. Re-running a number costs seconds; retracting a decision costs considerably more.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the 28.6% output. Six months from now the context is what turns this figure into a trend. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
Where Loss Given Default matters in practice
Numbers earn their keep in conversations, and Loss Given Default is no exception. In Investing & Markets discussions around Fixed Income, this figure decides whether an option stays on the table: it converts an opinionated debate into an arithmetic one, and arithmetic is the only referee both sides accept. Rounding early is the quietest way to introduce a permanent error.
The companion outputs — Net proceeds rate and Dollar loss — exist for the second stage of that screen: the headline sizes the prize, while the companions describe the trade-off you are accepting to get it. When two sources disagree, it is almost never the arithmetic that differs.
Treat Loss Given Default like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. Rounding early is the quietest way to introduce a permanent error.
Quick answers: what searchers ask about Loss Given Default
What affects Loss Given Default the most?
The short answer: Recovered value. The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the loss given default recalculated — Recovered value moved it furthest, by roughly 28.6 % (20.4% to 36.8%).
Do exposure at default and recovered value matter equally?
Effectively. Measured on this engine they land at ≈28.6 % and ≈27.7 % for the same ten-percent nudge, so the honest advice is to get both right; chasing precision in only one of them buys almost nothing.
What is a typical Loss Given Default?
On the worked example above Loss Given Default comes out at 28.6%. 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 Loss Given Default by hand?
LGD = 1 − (recovery − costs) ÷ EAD is the entire method. Work the inputs in that order — Net recovery = $98,250 − $12,500 = $85,750 — and you will reach 28.6% on the default figures, the same number this tool prints.
What happens to Loss Given Default if recovered value changes by 10 %?
Try it in the form above and the printed substitution will follow you; the pre-computed answer for the defaults is 20.4% to 36.8% across the ten-percent probe, i.e. ≈28.6 % sensitivity on the loss given default.
Is the Loss Given Default result of 28.6% good or bad?
Neither, on its own — the label “Severity on this claim: 28.6%” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives, and remember that a ten-percent error in Recovered value alone moves it by ≈28.6 %.
What is a good Loss Given Default?
Markets give away free benchmarks: anything that beats the relevant index after costs earns the label "good", and this tool’s verdict band translates Loss Given Default against experience ranges. Before that, check that the inputs are realistic — a great Loss Given Default built on optimistic inputs is just a nicer-looking error.
How do I calculate Loss Given Default manually?
Write down the inputs, then follow the printed steps in order — LGD = 1 − (recovery − costs) ÷ EAD. A spreadsheet replicates it with two or three cells. The manual route is worth doing once to build intuition; after that the calculator saves time and eliminates transcription slips.
Why is unsecured bank lending so high in LGD?
Nothing attaches, and in a restructuring suppliers and junior creditors share a thin residual. The 75% unsecured corporate assumption comes from decades of default data (Moody's / Altman studies).
Is LGD the same as a defaulted bond's haircut?
Directionally, but LGD is measured from the lender's economic perspective including workout costs and timing; published index "recovery rates" are often cents-on-par without those frictions.
Does this Loss Given Default 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 Investing & Markets figures and the reason you can re-run this page as often as you like.
The vocabulary of Loss Given Default
- Net proceeds rate
- 71.4 % in the default Loss Given Default calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Dollar loss
- $34,351 for the Loss Given Default worked case; it sits next to the main result because it carries context the headline leaves out.
- Recovery needed for LGD = 40%
- $84,561 in the default Loss Given Default calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Loss given default
- The primary output of this tool: 28.6% for the default inputs, computed exactly from LGD = 1 − (recovery − costs) ÷ EAD.
- Worked example
- The step-by-step substitution printed above, so the arithmetic can be re-derived by hand or in a spreadsheet.
- Verdict band
- A named zone on the range of plausible results; the example inputs land in “Severity on this claim: 28.6%”, and your inputs may not.
- Sensitivity (±10 %)
- How far the Loss Given Default 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
Everything above runs on one stated formula, applied without hidden coefficients: LGD = 1 − (recovery − costs) ÷ EAD. Source of record: Altman, Brand & Satterfield (2005) "LRRA"; Basel II Annex 7 LGD floors. 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.
Treat the output as a precise answer to the question you typed: exact arithmetic, transparent formula, published source, no hidden rounding. The sensitivity table above is part of that promise rather than a bonus: it lets you see how much of the result depends on how carefully you measured.
What to do with your Loss Given Default next
Save the number together with its inputs and today’s date; a Loss Given Default figure without context is unusable the moment an input changes.
Whoever you are (people who need one trustworthy number before their next decision), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Investing & Markets, a dated figure is a trend, and an undated one is a rumour.