The economy and loss given default: evidence from two UK retail lending data sets

Abstract

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 data set and an ordinary least squares model for an unsecured personal loans data set. To improve loan-level predictions of LGD, indicators relating to the macroeconomy 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 R².

Keywords:

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

Notes

1 Note that, partially because of data limitations, we are using nominal loss here as opposed to discounted loss.

2 Repossession rate here is defined as the proportion of loans defaulting in the corresponding time period that would end up being repossessed.

3 It is possible to include more than one macroeconomic variable and possibly get better predictions, in which case we could consider principal components to remove some correlation. However, this would introduce other minor complications, for example, in applying the model for prediction purposes, one would now need to collect data about multiple indicators and apply a calculation to produce a factor score; also ease of interpretation of the factors may be a concern.