GCD's Mission is to help banks understand and model credit risks. The comprehensive data pools are collected over a decade and distributed back to members for their own research and modelling.

 

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GCD is a unique data consortium that owns banks internal data for both PD and LGD. GCD’s data pools support the key parameters of banks’ credit risk modelling: Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD).

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GCD’s library gives access to wide variety of publications on risk related topics. Global Credit Data members work together to analyse the data and discuss methodology issues. GCD has published numerous papers and is actively promoting academic research on the data collected.

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Members not only benefit from exclusive rights and access to credit databases and analytics, but also from knowledge and research facilitation possible via the unique industry association.

Through a variety of forums such as workshops, webinars and surveys, GCD is an active industry participant facilitating the discussion in key strategic areas.

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Global Credit Data collects raw data from its members and distributes it back to them for use in their own analysis and modelling. GCD supports its members by providing a flexible high-end tool on the data pool: the GCD Visual Analyzer. Member banks can create dynamic Reference Data Sets and generate instant views on the data.

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Banks recover 75% of defaulted debt owed by large corporate borrowers, finds new Global Credit Data report

by | Apr 9, 2018 | Newswire Page, Uncategorized

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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

Global Credit Data has released its LGD Report 2018 – the first ever examining the Loss Given Default (LGD) for banks lending to corporate borrowers with a turnover of more than €50m. The report finds that banks, on average, recover 75% of debts owed by large corporate borrowers after default and confirms the hitherto untested principle that seniority and collateral drive low rates of LGD.

 

The findings are the result of the most precise LGD analytics yet, based on a reference data set containing 9,361 defaulted borrowers and 16,665 facilities from over 50 lenders worldwide.

“LGD data is considerably scarcer than data on other metrics, such as probability of default (PD),” says Philip Winckle, Executive Director at Global Credit Data. “This is because the only cases that can be used come from defaulted loans, which account for just 1% of the total loan book of any bank. This report therefore represents a unique and vital resource for every aspect of banks’ credit risk modelling, whether for regulatory capital, pricing, stress testing or expected loss provisioning models.”

The report contains a number of interesting insights. Recovery rates for individual facilities vary greatly with each borrower – to the point where banks typically recover either most of a outstanding loan or none at all. Yet aggregated results across many borrowers and over time show that the average LGD level differs by just 1% between borrower-level and facility-level averages.

“The LGD Report 2018 finally provides the statistical data to underpin the principle that seniority of debt and collateral have a central role to play in ensuring minimal loss in the case of a default,” adds Nina Brumma, Head of Analytics and Research. “Consistently over time, secured LGD is lower than unsecured LGD, while senior unsecured defaults have a significantly lower LGD than subordinated unsecured defaults.”

The report also shows that LGD varies over time – with LGDs higher in the early 2000s and between 2007 and 2008, compared to the rest of the period from 2000 to 2014 – indicating a relationship between economic conditions and recoveries.

Other insights include the observation that North America and Europe have similar levels of LGD, Time to Resolution and Time to Recovery, compared to the other regions covered. Asia & Oceania show comparatively high, Africa and the Middle East comparatively low, LGDs.

Click here to download the full report

Click here to download the Appendix: Database & Methodology

Click here to download the Reference Dataset Guidelines and the Reference Dataset used to create the report (member login required)

For further information, please contact Nina Brumma