The Economy and Loss Given Default: Evidence from Two UK Retail Lending Datasets

Mindy Leow, Christophe Mues, Lyn C Thomas

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Loss Given Default (LGD) models predict losses as a proportion of the outstanding
loan, in the event a debtor goes into default. The literature on corporate sector LGD models suggests LGD is correlated to the economy and so changes in the economy could translate into different predictions of losses. In this work, the role of macroeconomic variables in loan-level retail LGD models is examined by testing the inclusion of macroeconomic variables in two different retail LGD models: a two-stage model for a residential mortgage loans dataset and an OLS model for an unsecured personal loans dataset. To improve loan-level predictions of LGD, indicators relating to the macro-economy are considered, with mixed results: the selected macroeconomic variable seemed able to improve the predictive performance of mortgage loan LGD estimates, but not for personal loan LGD. For mortgage loan LGD, interest rate was most beneficial but only predicted better during downturn periods, underestimating LGD during non-downturn periods. For personal loan LGD, only net lending growth is statistically significant but including this variable did not bring any improvement to R-square.
Original languageEnglish
JournalJournal of the Operational Research Society
Early online date2 Oct 2013
DOIs
Publication statusPublished - 2013

Keywords / Materials (for Non-textual outputs)

  • credit risk modelling
  • macroeconomic variables
  • retail loans
  • loss given default

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