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Loss given default models incorporating macroeconomic variables for credit cards

  • Tony Bellotti
  • , Jonathan Crook*
  • *Corresponding author for this work

Research output: Journal PublicationArticlepeer-review

Abstract

Based on UK data for major retail credit cards, we build several models of Loss Given Default based on account level data, including Tobit, a decision tree model, a Beta and fractional logit transformation. We find that Ordinary Least Squares models with macroeconomic variables perform best for forecasting Loss Given Default at the account and portfolio levels on independent hold-out data sets. The inclusion of macroeconomic conditions in the model is important, since it provides a means to model Loss Given Default in downturn conditions, as required by Basel II, and enables stress testing. We find that bank interest rates and the unemployment level significantly affect LGD.

Original languageEnglish
Pages (from-to)171-182
Number of pages12
JournalInternational Journal of Forecasting
Volume28
Issue number1
DOIs
Publication statusPublished - Jan 2012
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Free Keywords

  • Basel II
  • Credit cards
  • Loss given default

ASJC Scopus subject areas

  • Business and International Management

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