Exposure at Default Models

Estimate exposure at default

Exposure at Default (EAD) uses a Regression or Tobit model to predict the amount of loss exposure for a bank when a debtor defaults on a loan.

Functions

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

portfolioECL Compute the lifetime ECL at individual or portfolio level

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

Compare Results for Regression and Tobit EAD Models
This example shows how to usefitEADModelto create aRegressionmodel and aTobitmodel 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 withportfolioECLusing simulated loan data, macro scenario data, and an existing lifetime probability of default (PD) model.
Economic Scenarios and Expected Credit Loss 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.