Worked case · Reference condition · 12 figures

Festival ticket merchant

Separate the risk families

Figure 01 / 12

Separate probability, severity, and exposure

Separate probability, severity, and exposure — Festival ticket merchant. 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 = $9,240.00. PD is 4.00%, LGD is 55.00%, and EAD is $420,000. This is a teaching expected-value calculation, not an accounting allowance method or a capital standard.

Figure data and text version
InputValueUnit
PD4Percent over one year
LGD55Percent of exposure lost conditional on default
EAD420,000USD at default
Expected loss9,240USD over the stated horizon

A ticket seller collects money months before an event. Cancellation creates a refund obligation that can outlast the seller’s cash.

The reference case starts with the stated population and a functioning evidence path. The owner is risk operations.

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 $420,000 of exposure. Its stated one-year PD and LGD imply $9,240.00 of expected loss, while the cover analysis leaves $288,000.00 of stress exposure. Monthly cash coverage is 1.22×. 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
exposure420,000
collateral90,000
reserve60,000
cash22,000
debtService18,000
Calculated valueResult
ead420,000
pd0.04
lgd0.55
expectedLoss9,240
eligibleCover72,000
reserve60,000
uncovered288,000
cash22,000
debt18,000
dscr1.2222
Figure 02 / 12

Probability and severity move the result together

Probability and severity move the result together — Festival ticket merchant. 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%2,1004,2006,300
5%5,25010,50015,750
10%10,50021,00031,500
20%21,00042,00063,000
Figure 03 / 12

Recorded collateral and eligible cover

Recorded collateral and eligible cover — Festival ticket merchant. USD; some measures overlap. Exact values are in the figure data below.
USD; some measures overlap

The collateral record is $90,000, but a 20% illustrative haircut leaves $72,000.00 eligible in this scenario. Reserve cover adds $60,000. The resulting uncovered exposure is $288,000.00. Eligibility also needs enforceability and operational access; this arithmetic does not establish either.

Figure data and text version
MeasureUSD
Recorded collateral90,000
Eligible collateral72,000
Recorded reserve60,000
Combined usable cover132,000
Uncovered exposure288,000
Figure 04 / 12

Cash available for the period’s debt service

Cash available for the period’s debt service — Festival ticket merchant. USD for one month. Exact values are in the figure data below.
USD for one month

Defined cash available is $22,000.00 against $18,000.00 of debt service, for a 1.22× 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 available22,000After the expenses included in this illustration
Debt service18,000Principal and interest due in the same period
Cash after debt service4,000Negative means a modeled shortfall
Figure 05 / 12

A constant-hazard illustration

A constant-hazard illustration — Festival ticket merchant. 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 4.00% 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
M299.32
M498.65
M697.98
M897.32
M1096.66
M1296
Figure 06 / 12

Cumulative expected loss at comparable age

Cumulative expected loss at comparable age — Festival ticket merchant. 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
M21,566.31
M43,122
M64,667.15
M86,201.81
M107,726.07
M129,240
Figure 07 / 12

Expected loss sensitivity to PD

Expected loss sensitivity to PD — Festival ticket merchant. USD; LGD and EAD held fixed. Exact values are in the figure data below.
USD; LGD and EAD held fixed

Exposure stays at $420,000 and LGD stays at 55.00% 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%2,310
3%6,930
5%11,550
8%18,480
12%27,720
20%46,200
Figure 08 / 12

A shared dependency can dominate exposure

A shared dependency can dominate exposure — Festival ticket merchant. 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
festival operator — primary168,000
Independent group B126,000
Independent group C84,000
Independent group D42,000
Figure 09 / 12

A weak month can disappear inside an average

A weak month can disappear inside an average — Festival ticket merchant. 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
M115,40018,000
M218,70018,000
M324,20018,000
M419,80018,000
M528,60018,000
M625,30018,000
Figure 10 / 12

Terms belong in the decision record

Terms belong in the decision record — Festival ticket merchant. Synthetic underwriting record. Exact values are in the figure data below.
Synthetic underwriting record

This record concerns separate the risk families. 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
entityFestival ticket merchant
exposure_usd420,000
horizonOne year for PD; one month for cash coverage
pd_percent4
lgd_percent55
review_triggerThe event is cancelled after the seller has paid suppliers.
Figure 11 / 12

One cause can affect several loss components

One cause can affect several loss components — Festival ticket merchant. Scenario logic. Exact values are in the figure data below.
Scenario logic

The stress path connects festival operator 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 shockThe event is cancelled after the seller has paid suppliers.
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 — Festival ticket merchant. USD; distinct horizons and meanings. Exact values are in the figure data below.
USD; distinct horizons and meanings

Expected loss ($9,240.00), uncovered exposure ($288,000.00), and monthly cash gap ($0.00) 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 loss9,240
Uncovered stress exposure288,000
Monthly cash gap0

Connect the result to the system

Measure unfulfilled obligations, eligible cover, and the ability to fund the weak month.

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. Federal Reserve: payment systems
  2. Stripe: PaymentIntent lifecycle (provider example)