默认概率的终身模型

Estimate loss reserves based on lifetime analysis

Lifetime models for probability of default (PD) estimate loss reserves based on a "lifetime" analysis conditional on macroeconomic scenarios.

Functions

`fitLifetimePDModel`	Create specified lifetime PD model object type
`predict`	Compute conditional PD
`预测时间`	Compute cumulative lifetime PD, marginal PD, and survival probability
`modelDiscrimination`	Compute AUROC and ROC data
`modelDiscriminationPlot`	Plot ROC curve
`modelAccuracy`	Compute RMSE of predicted and observed PDs on grouped data
`modelAccuracyPlot`	Plot observed default rates compared to predicted PDs on grouped data

Objects

`逻辑`	Create`逻辑`model object for lifetime probability of default
`Probit`	Create`Probit`model object for lifetime probability of default
`Cox`	Create`Cox`model object for lifetime probability of default

Examples and How To

Basic Lifetime PD Model Validation

This example shows how to perform basic model validation on a lifetime probability of default (PD) model by viewing the fitted model, estimated coefficients, andp-values.

Compare Logistic Model for Lifetime PD to Champion Model

This example shows how to compare a new逻辑model for lifetime PD against a "champion" model.

Compare Lifetime PD Models Using Cross-Validation

This example shows how to compare three lifetime PD models using cross-validation.

Expected Credit Loss Computation

This example shows how to perform expected credit loss (ECL) computations using simulated loan data, macro scenario data, and an existing lifetime probability of default (PD) model.

Compare Model Discrimination and Accuracy to Validate of Probability of Default

This example shows some differences between discrimination and accuracy metrics for the validation of probability of default (PD) models.

Concepts

Overview of Lifetime Probability of Default Models

Estimate loss reserves based on a lifetime analysis conditional on macroeconomic scenarios.

Featured Examples

使用面板数据对消费者信用默认概率进行压力测试

Use consumer credit panel data to visualize default rates, fit a model to predict probabilities of default, and perform a stress testing analysis.

Open Live Script

Modeling Probabilities of Default with Cox Proportional Hazards

工作与消费者(retail) credit panel data to visualize observed probabilities of default (PDs) at different levels. It also shows how to fit a Cox proportional hazards (PH) model, also known as Cox regression, to predict PDs. In addition, it shows how to perform a stress-testing analysis, how to model lifetime PDs, and how to calculate the lifetime expected credit loss (ECL) value.