How Loss Given Default Is Actually Computed in the Real World (A practical guide that starts exactly where PD ends)

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In the previous article,

“How Probability of Default Is Actually Calculated in the Real World”

we did one thing clearly:

We showed that PD is nothing but loans migrating into the 90+ DPD bucket over a defined time window.

PD answers:

Which loans enter default?

Once that happens, PD’s job is over.

From that exact moment, a new question takes over:

Out of the money that was outstanding at default, how much will we finally lose — and when?

That question is LGD.

This guide explains LGD the same way the PD guide explained PD:

  • Using tables

  • Using behaviour

  • Using time

  • Using cash

No theory first. Reality first.

Step 0: Fix the universe (this is non-negotiable)

LGD is never computed on:

  • The full portfolio

  • Performing loans

  • Stage 1 accounts

LGD universe is only loans that have already defaulted.

Meaning:

  • Loans that crossed 90+ DPD

  • Loans that entered Stage 3

So your LGD input table must look like this:

Table 1: Default entry universe (output of PD)


This number is sacred.
Everything in LGD flows from this.

If this is wrong, LGD is wrong.

Step 1: Reset time at the moment of default

Once a loan defaults:

  • EMI schedules stop being relevant

  • Calendar months become misleading

LGD works on relative time, not absolute dates.

So instead of:

  • “Recovered in Dec-22”

We think in:

  • “Recovered in Month 6 after default”

This allows us to compare loans that defaulted at different times.

Step 2: Track recoveries loan-wise, month-since-default

Now we track actual cash inflows.

Table 2: Raw recovery tracking (loan level)


This table is messy by design.
That’s how collections work.

Step 3: Convert loan-wise chaos into time-wise behaviour

Now zoom out.

Instead of looking loan by loan, we ask:

Across all defaulted loans, how much cash do we recover by Month 1, Month 3, Month 6, etc.?

Table 3: Portfolio-level recovery build-up


Now divide this by total default exposure.

Table 4: Recovery curve (behavioural view)

This curve is the heart of LGD.

Not the final percentage.
The shape.

Step 4: Do NOT aggregate blindly (this is where most people go wrong)

A very important pause here.

If you simply aggregate:

  • All defaults from last 5 years

  • And divide total recoveries till date

You will almost always overstate LGD.

Why?

Because:

  • Recent defaults are included in the denominator

  • But their recovery curve has barely started

So LGD looks worse than reality.

Step 5: Introduce maturity discipline (without overcomplicating)

LGD should be estimated using mature default cohorts.

Meaning:

  • Defaults that have had enough time to recover

  • Typically 24–36 months old

So you build recovery curves by default vintage.

Table 5: Recovery curves by default cohort



Now you can see:

  • Where curves stabilise

  • Where recoveries stop adding meaningfully

LGD is defined after this point, not before.

Step 6: Why discounting is unavoidable (even if recoveries look decent)

Up to now, we’ve talked in raw cash.

But time quietly destroys value.

₹1 recovered after 3 years is not worth ₹1 today.

So recoveries must be discounted back (cost of funds or a conservative hurdle rate) to the default date.

Step 7: Discount recoveries month-wise

Table 6: Discounted recovery build-up


Notice something subtle:

  • Gross recovery keeps increasing

  • Present value recovery peaks and flattens

That flattening point is critical.

Step 8: LGD finally emerges (properly)

If:

  • Default exposure = ₹10 crore

  • PV of recovery = ₹2.3 crore

Then:

LGD = (10 − 2.3) / 10 = 77%

Same recoveries.
Same borrowers.
Different time.

Very different LGD.

Step 9: Segment LGD (because behaviour is not uniform)

LGD is rarely one number.

Example segmentation:

Table 7: LGD by resolution stage


This table alone explains:

  • Why early action matters

  • Why delayed resolution destroys value

How this completes the PD story

PD answered:

  • Which loans will default?

LGD answers:

  • How much money will we lose once they do?

PD is forward-looking migration.
LGD is post-default cash erosion.

Together, they describe loss mechanics.

Why this is still incomplete (on purpose)

This guide intentionally stopped before:

  • Choosing discount rates

  • Forecasting recoveries for new portfolios

  • Collateral-wise LGD

  • Forward-looking overlays

Because the moment you cross that line,
you are no longer reading a guide.

You are building a model.

That is exactly where the ECL course begins.

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