LGD modelling for regulatory capital
Reference data sets for LGD modelling
Validation of credit risk models
Specific portfolios in credit risk modelling
- Recovery rate and its inverse, Loss Given Default (LGD), is a key metric in credit risk modelling, whether for regulatory capital, pricing models, stress testing or expected loss provisioning models. The data is however much more scarce than data for probability of default (PD) because the only cases which can be used come from defaulted loans, which represent around 1% of the total loan book of any bank. GCD member banks have been steadily collecting this data since 2004.
- This report is the first time GCD publishes such extensive analytics on its broad data set. The aim is to present the numerical evidence of recoveries and losses experienced by banks when providing credit facilities to large corporate counterparties. The data set in the report covers Large Corporate (>€50m turnover) borrowers who are recorded as defaulted in bank loan books, using the Basel default definition.
- The long term average LGD levels in this report can be compared to regulatory minima and standardised levels, allowing an industry wide discussion of prudent forward looking LGDs vs historical evidence. Note that the LGDs in this report are cash flow discounted observations of historical outcomes, not forward looking estimates.
gcd_lgd_report_large_corporates_2018.pdf (PDF, 303.67 kB)
gcd_lgd_report_large_corporates_2018-appendix.pdf (PDF, 869.40 kB)
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First ever report of extensive analytics on LGD data highlights high recovery rate for banks on defaulted debt from large corporate borrowers