Trade-Credit Exposure

Estimate trade-credit portfolio exposure and covered expected loss.

Description

Trade-credit expected loss weights each buyer receivable by its supplied probability of default.

Trade-credit expected loss weights each buyer receivable by its supplied probability of default. Coverage percentage and a limit then scale the aggregate estimate.^[1]

Estimate trade-credit portfolio exposure and covered expected loss.

When to use Trade-Credit Exposure

Use this tool to estimate trade-credit portfolio exposure and covered expected loss.

Prepare the supplied policy terms, dates, assumptions or recorded indicators requested. Keep monetary amounts on one currency basis and select the applicable thresholds separately.

How to use Trade-Credit Exposure and understand its results

Prepare the supplied policy terms, dates, assumptions or recorded indicators requested. Keep monetary amounts on one currency basis and select the applicable thresholds separately.
Enter buyerReceivables, buyerDefaultProbabilities, coveragePercent, policyLimit using the field table and calculation rules, then run the tool.
Read grossReceivables, expectedCreditLoss, coveredExpectedLoss, uncoveredExpectedLoss. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
buyerReceivables	Buyer receivables	list of number	Required
buyerDefaultProbabilities	Buyer default probabilities	list of number	Required
coveragePercent	Trade-credit coverage (%)	number; minimum: 0; maximum: 100	Required
policyLimit	Policy limit	number; minimum: 0	Required

Enter nonempty aligned nonnegative receivables and probabilities 0–1, coverage 0–100 and nonnegative limit. Return receivables, expected loss, covered estimate and residual.

expected=Σreceivable_i×probability_i; covered=min(limit,expected×coverage/100)

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
grossReceivables	Gross receivables	number; minimum: 0
expectedCreditLoss	Expected credit loss	number; minimum: 0
coveredExpectedLoss	Covered expected loss	number; minimum: 0
uncoveredExpectedLoss	Uncovered expected loss	number; minimum: 0

json

{
  "input": {
    "buyerReceivables": [
      1000,
      2000
    ],
    "buyerDefaultProbabilities": [
      0.1,
      0.2
    ],
    "coveragePercent": 80,
    "policyLimit": 1000
  },
  "output": {
    "grossReceivables": 3000,
    "expectedCreditLoss": 500,
    "coveredExpectedLoss": 400,
    "uncoveredExpectedLoss": 100
  }
}

Limitations and assumptions

The model assumes the full receivable is lost on default. No loss-given-default, dependency, recoveries, probability fitting or actual policy entitlement is modeled.

Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use PML Aggregation: Aggregate modeled occurrence losses into a caller-parameterized PML. For a complementary task, use Supplier Dependency Loss: Estimate contingent business-interruption loss from supplier dependency.

References

Trade-Credit Exposure — tool.io

Similar or alternative tools

PML Aggregation
Aggregate modeled occurrence losses into a caller-parameterized PML.
Supplier Dependency Loss
Estimate contingent business-interruption loss from supplier dependency.