Exposure at Default Models

Estimate exposure at default

Calculate the Exposure at Default (EAD) using a Regression, Tobit, or Beta model to predict the amount of loss exposure for a bank when a debtor defaults on a loan. Calculate the estimated loss reserves using Expected Credit Loss (ECL) calculator.

Functions

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EAD Functions

`fitEADModel`	Create specified EAD model object type
`predict`	Predict exposure at default
`modelDiscrimination`	Compute AUROC and ROC data
`modelDiscriminationPlot`	Plot ROC curve
`modelCalibration`	Compute R-square, RMSE, correlation, and sample mean error of predicted and observed EADs
`modelCalibrationPlot`	Scatter plot of predicted and observed EADs

Lifetime Expected Credit Loss (ECL) Calculator

portfolioECL Compute the lifetime ECL at individual or portfolio level

Objects

`Regression`	Create `Regression` model object for exposure at default
`Tobit`	Create `Tobit` model object for exposure at default
`Beta`	Create `Beta` model object for exposure at default

Topics

Compare Results for Regression and Tobit EAD Models
This example shows how to use fitEADModel to create a Regression model and a Tobit model for exposure at default (EAD) and then compare the results.
Expected Credit Loss Computation
This example shows how to perform expected credit loss (ECL) computations with portfolioECL using simulated loan data, macro scenario data, and an existing lifetime probability of default (PD) model.
Incorporate Macroeconomic Scenario Projections in Loan Portfolio ECL Calculations
This example shows how to generate macroeconomic scenarios and perform expected credit loss (ECL) calculations for a portfolio of loans.
Modeling Probabilities of Default with Cox Proportional Hazards
This example shows how to work with consumer (retail) credit panel data to visualize observed probabilities of default (PDs) at different levels.
Overview of Exposure at Default Models
Exposure at default (EAD) is the loss exposure for a bank when a debtor defaults on a loan.