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Private Credit Default & Recovery Simulator

Stress a portfolio of private loans for default frequency, recovery, fees and yield, then see expected losses, recoveries and net income under three scenarios.

Editable assumptionsIndian rupeesBrowser-only inputs

Interactive model

Stress default frequency and loss severity

Inputs stay on this device

Model a portfolio average, then remember what it leaves out: correlated defaults, uneven position sizes, covenants and workout time.

Portfolio size

₹

Number of loans

Average yield14%0%25%Holding period3 years1 years8 yearsDefault rate8%0%35%Recovery rate35%0%100%Annual fees1.5%0%4%

Loans are treated as equally sized for expected-default count. The cash model uses portfolio averages and excludes taxes and workout delays.

Base net expected return10.2%

Expected defaults1.6Across 20 loans

Expected loss₹52 lakh

Expected recoveries₹28 lakh

ScenarioDefaultsLossNet return

Base1.6₹52 lakh10.2%

Stress2.8₹1.1 crore7.8%

Severe4.8₹2.4 crore2.8%

Explain my result

The base case loses ₹52 lakh of principal after ₹28 lakh of recoveries. Coupon income absorbs that loss in the model, but the result can deteriorate quickly when defaults rise together or recovery falls.

Compare scenario

What this means

Diversifying loan count reduces one-borrower concentration; it does not remove a shared recession, sector shock or weak documentation across the portfolio.

A private-credit portfolio can show stable income until defaults arrive together. Scenario analysis makes loss absorption visible before the benign history becomes the forecast.

Calculation method

How this tool works

Net expected income = coupon income − expected principal loss − fees. Expected loss = defaulted principal − recoveries.

The portfolio model applies an average default rate and recovery rate across equally weighted loans. It estimates coupon loss from mid-period defaults. It does not model correlated defaults, loan-level concentration, workout duration or seniority differences.

View calculation limitations

Results depend entirely on the values and scenarios entered. The model simplifies real legal, tax, liquidity, valuation and market conditions and should be used to understand relationships—not to predict an actual investment outcome.

Common mistakes

Where a correct calculation can still mislead.

01
Using average default rates for a concentrated portfolio.
02
Assuming recovery is immediate and costless.
03
Ignoring correlation between borrowers and collateral.
04
Netting PIK income against cash losses as though both were equally liquid.

Continue through the knowledge graph

Tools, guides and real cases connected to this result.

Learn the concept

Private Credit: Structures, Covenants and Recovery→Private Credit — Complete Guide→Portfolio Risk Control→

Test it in a case

Franklin Templeton's six debt schemes: when daily access met hard-to-sell credit→YPF litigation: a $16 billion judgment can still become a losing branch on appeal→

Questions investors ask

Answers without the sales pitch.

Can expected defaults be a fraction?

Yes. It is a probability-weighted portfolio estimate, not a prediction that exactly 1.6 loans will default.

Does more loans always mean safer credit?

No. Loan quality, sector overlap, underwriting standards and position size matter more than count alone.

What is loss severity?

It is one minus the recovery rate. A 35% recovery implies 65% loss severity before timing and workout costs.

Important information

AssetsNest tools and calculations are provided solely for educational and informational purposes. Results are illustrative and depend on assumptions entered by the user. Actual performance, liquidity, fees, taxes, risks and outcomes may differ materially. Nothing on this page is investment advice, a recommendation, solicitation, assurance of returns or an offer to buy or sell any security or investment product. Investors should conduct independent due diligence and consult appropriately qualified financial, legal and tax professionals where required. AssetsNest Investor Services — ARN 318691.

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Change the assumptions. Then read the evidence.

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