Worked case · Failure and stress · 12 figures

Product promises and exposure

Define the product and open promises

Figure 01 / 12

Separate probability, severity, and exposure

Separate probability, severity, and exposure — Product promises and exposure. One-year synthetic credit case. Exact values are in the figure data below.
One-year synthetic credit case

The simplified one-year expected loss is PD × LGD × EAD = $87,264.94. PD is 13.34%, LGD is 88.40%, and EAD is $740,000. This is a teaching expected-value calculation, not an accounting allowance method or a capital standard.

Figure data and text version
InputValueUnit
PD13.34Percent over one year
LGD88.4Percent of exposure lost conditional on default
EAD740,000USD at default
Expected loss87,264.94USD over the stated horizon

A platform can promise rapid merchant access to funds before the underlying transactions are final. The interval creates a funding and recovery exposure.

Marketing shortens the payout promise without changing underwriting or liquidity capacity.

All amounts, rates, capacity limits, and outcomes in this case are synthetic. The three conditions are separate assumptions for comparison. A better result in the response condition is not measured proof that the proposed control causes that improvement. The figures expose the calculation and its limits; a real deployment needs its own evidence.

Read the result

The case has $740,000 of exposure. Its stated one-year PD and LGD imply $87,264.94 of expected loss, while the cover analysis leaves $440,500.00 of stress exposure. Monthly cash coverage is 0.82×. These are separate measures: one describes an average under probability assumptions, one describes available cover, and one describes a period’s funding capacity.

Model inputs and calculated values

Inputs below are the case-specific values. Each figure states the condition-specific assumptions and units used in its calculation. Calculated values are rounded for display.

InputValue
pd0.058
lgd0.68
collateral390,000
reserve85,000
cash135,000
debtService102,000
exposure740,000
Calculated valueResult
ead740,000
pd0.1334
lgd0.884
expectedLoss87,264.94
eligibleCover214,500
reserve85,000
uncovered440,500
cash83,700
debt102,000
dscr0.8206
Figure 02 / 12

Probability and severity move the result together

Probability and severity move the result together — Product promises and exposure. USD expected loss; fixed exposure. Exact values are in the figure data below.
USD expected loss; fixed exposure

Each cell is the same exposure multiplied by the row default probability and the column loss severity. The grid makes joint stress visible. A downturn can affect both factors; the calculation does not assume that the two causes are independent.

Figure data and text version
PDLGD 25%LGD 50%LGD 75%
2%3,7007,40011,100
5%9,25018,50027,750
10%18,50037,00055,500
20%37,00074,000111,000
Figure 03 / 12

Recorded collateral and eligible cover

Recorded collateral and eligible cover — Product promises and exposure. USD; some measures overlap. Exact values are in the figure data below.
USD; some measures overlap

The collateral record is $390,000, but a 45% illustrative haircut leaves $214,500.00 eligible in this scenario. Reserve cover adds $85,000. The resulting uncovered exposure is $440,500.00. Eligibility also needs enforceability and operational access; this arithmetic does not establish either.

Figure data and text version
MeasureUSD
Recorded collateral390,000
Eligible collateral214,500
Recorded reserve85,000
Combined usable cover299,500
Uncovered exposure440,500
Figure 04 / 12

Cash available for the period’s debt service

Cash available for the period’s debt service — Product promises and exposure. USD for one month. Exact values are in the figure data below.
USD for one month

Defined cash available is $83,700.00 against $102,000.00 of debt service, for a 0.82× ratio. The ratio uses one period and one defined cash measure. It does not establish affordability, suitability, or a required underwriting threshold.

Figure data and text version
ComponentUSDMeaning
Cash available83,700After the expenses included in this illustration
Debt service102,000Principal and interest due in the same period
Cash after debt service-18,300Negative means a modeled shortfall
Figure 05 / 12

A constant-hazard illustration

A constant-hazard illustration — Product promises and exposure. Percent of an initial synthetic cohort. Exact values are in the figure data below.
Percent of an initial synthetic cohort

The curve converts the stated one-year PD of 13.34% to a constant monthly hazard using h = 1 − (1 − PD)^(1/12). Survival after 12 months is therefore 1 − PD. Constant hazard is an assumption; seasonality and changing exposure are omitted. Horizontal positions are the labeled observations or scenarios; equal spacing does not imply equal numerical increments.

Figure data and text version
Months since startSurvival %
M0100
M297.64
M495.34
M693.09
M890.9
M1088.75
M1286.66
Figure 06 / 12

Cumulative expected loss at comparable age

Cumulative expected loss at comparable age — Product promises and exposure. Cumulative expected USD; fixed exposure. Exact values are in the figure data below.
Cumulative expected USD; fixed exposure

This curve multiplies cumulative modeled default probability by a fixed EAD and LGD. It is useful for separating observation age from the chosen assumptions. It omits amortization, recoveries over time, prepayment, and changing utilization. Horizontal positions are the labeled observations or scenarios; equal spacing does not imply equal numerical increments.

Figure data and text version
AgeExpected USD
M00
M215,425.41
M430,487.09
M645,193.61
M859,553.33
M1073,574.45
M1287,264.94
Figure 07 / 12

Expected loss sensitivity to PD

Expected loss sensitivity to PD — Product promises and exposure. USD; LGD and EAD held fixed. Exact values are in the figure data below.
USD; LGD and EAD held fixed

Exposure stays at $740,000 and LGD stays at 88.40% while PD changes. The linear relationship follows the simplified expected-loss formula. It is not evidence that real-world losses respond linearly to economic stress. Horizontal positions are the labeled observations or scenarios; equal spacing does not imply equal numerical increments.

Figure data and text version
One-year PDExpected USD
1%6,541.6
3%19,624.8
5%32,708
8%52,332.8
12%78,499.2
20%130,832
Figure 08 / 12

A shared dependency can dominate exposure

A shared dependency can dominate exposure — Product promises and exposure. USD; buckets sum to total exposure. Exact values are in the figure data below.
USD; buckets sum to total exposure

The four amounts are disjoint portions of this case’s exposure. The largest bucket represents one shared supplier, funding source, or other specified dependency. Counting customers alone would not reveal this common loss driver.

Figure data and text version
Dependency bucketExposure USD
external service — primary296,000
Independent group B222,000
Independent group C148,000
Independent group D74,000
Figure 09 / 12

A weak month can disappear inside an average

A weak month can disappear inside an average — Product promises and exposure. USD per month. Exact values are in the figure data below.
USD per month

The six-month path applies explicit seasonal factors to the defined monthly cash amount and compares it with fixed debt service. These are constructed cash assumptions, not a forecast. A negative month needs a funding or terms response even when the average ratio looks comfortable. Horizontal positions are the labeled observations or scenarios; equal spacing does not imply equal numerical increments.

Figure data and text version
MonthCash availableDebt service
M158,590102,000
M271,145102,000
M392,070102,000
M475,330102,000
M5108,810102,000
M696,255102,000
Figure 10 / 12

Terms belong in the decision record

Terms belong in the decision record — Product promises and exposure. Synthetic underwriting record. Exact values are in the figure data below.
Synthetic underwriting record

This record concerns define the product and open promises. A binary approval omits the amount, observation horizon, cover assumptions, and review trigger. Retaining those terms makes the decision reproducible and identifies when changed facts require another assessment.

Figure data and text version
FieldIllustrative value
entityProduct promises and exposure
exposure_usd740,000
horizonOne year for PD; one month for cash coverage
pd_percent13.34
lgd_percent88.4
review_triggerMarketing shortens the payout promise without changing underwriting or liquidity capacity.
Figure 11 / 12

One cause can affect several loss components

One cause can affect several loss components — Product promises and exposure. Scenario logic. Exact values are in the figure data below.
Scenario logic

The stress path connects external service to repayment cash, default probability, recovery, and funding needs. Arrows state the scenario’s assumed causal chain. They are hypotheses to test with evidence, not proof that every affected customer will default.

Figure data and text version
StageMechanism
Dependency shockMarketing shortens the payout promise without changing underwriting or liquidity capacity.
Cash pressureReceipts fall or essential payments move earlier
Default and severityRepayment probability and recovery can both worsen
ResponseReassess terms, usable cover, and exposure within the approved process
Figure 12 / 12

Expected loss, uncovered exposure, and cash gap

Expected loss, uncovered exposure, and cash gap — Product promises and exposure. USD; distinct horizons and meanings. Exact values are in the figure data below.
USD; distinct horizons and meanings

Expected loss ($87,264.94), uncovered exposure ($440,500.00), and monthly cash gap ($18,300.00) answer different questions. The bars are deliberately separated measures and must not be added. A low expected value can coexist with a large stress exposure.

Figure data and text version
MeasureUSD
Expected one-year loss87,264.94
Uncovered stress exposure440,500
Monthly cash gap18,300

Connect the result to the system

Map the promise to loss timing, usable cover, and funding needs before changing limits.

Check the population, evidence, permitted action, and actual effect together. A balanced calculation can still use the wrong population; a successful response can still leave an unknown financial outcome. The case’s numerical result applies only to its stated assumptions.

Sources and further reading

The chapter sources support the concepts and scope. They do not prescribe the synthetic model rates.

  1. OCC Comptroller’s Handbook: merchant processing
  2. Federal Reserve SR 23-4: third-party relationships
  3. OFAC: A Framework for Compliance Commitments
  4. Federal Reserve SR 26-2: revised model-risk guidance (2026)