# Lifetime Models for Probability of Default

Develop and validate Lifetime models for probability of default (PD) based on a lifetime analysis conditional on macroeconomic scenarios. Calculate the estimated loss reserves using Expected Credit Loss (ECL) calculator.

## Functions

## Objects

`Logistic` | Create `Logistic` model object for lifetime probability of
default (Since R2020b) |

`Probit` | Create `Probit` model object for lifetime probability of
default (Since R2020b) |

`Cox` | Create `Cox` model object for lifetime probability of
default (Since R2021b) |

`customLifetimePDModel` | Create `customLifetimePDModel` object for lifetime probability
of default (Since R2022b) |

## Topics

**Overview of Lifetime Probability of Default Models**Estimate loss reserves based on a lifetime analysis conditional on macroeconomic scenarios.

**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, and

*p*-values.**Compare Logistic Model for Lifetime PD to Champion Model**This example shows how to compare a new

`Logistic`

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 with

`portfolioECL`

using simulated loan data, macro scenario data, and an existing lifetime probability of default (PD) model.**Compare Model Discrimination and Model Calibration to Validate of Probability of Default**This example shows some differences between discrimination and calibration metrics for the validation of probability of default (PD) models.

**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.

**Interpret and Stress-Test Deep Learning Networks for Probability of Default**Train a credit risk for probability of default (PD) prediction using a deep neural network.

**Create Custom Lifetime PD Model for Credit Scorecard Model with Function Handle**This example shows how to use

`customLifetimePDModel`

to create a lifetime model for the probability of default.**Create Custom Lifetime PD Model for Decision Tree Model with Function Handle**This example shows how to fit a decision tree model for credit scoring and then use the

`customLifetimePDModel`

object to create a lifetime model for probability of default.**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.

**Create Weighted Lifetime PD Model**This example shows how to use

`fitLifetimePDModel`

to create a PD model using weighted credit and macroeconomic data.