PD Submissions are now open
Provides risk insights directly from anonymized internal data of member banks and promotes knowledge sharing within the financial industry.
The long time series of historical credit losses allow banks to model loans’ recovery processes. GCD provides also credit rankings and obligor internal rating transition data for all key bank portfolios.
Data Pooling : PD & LGD
GCD is a unique data consortium that collects 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).
Library: Research & Publications
GCD’s library gives access to a wide variety of publications on risk-related topics. GCD members work together to analyze data and discuss methodology issues.
GCD is actively promoting academic research on the data collected.
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.
Global Credit Data collects raw data from its members and distributes it back to them for use in their own analysis and modelling.
Member banks can create dynamic Reference Data Sets and generate instant views on the data.
Global Credit Data is proud to support academic research to further the study of finance.
GCD hosts events throughout the year for members and industry leaders on topics that benefit banks.
GCD actively publishes reports and studies about how data will impact different industries.
GCD Data User Guide
Data quality is key to GCD and the extensive documentation forms an integral part of GCD's data quality approach.
Download a copy of the latest GCD Newsletter.
Insight into observed recovery levels and other key benchmarks for various exposure classes, industry sectors and collateral types.
Macroeconomic trends in 2022, initially marked by expectations of reduced government support for the pandemic, progressive tightening of monetary policies by central banks and rising inflaon rates must now consider market stress, energy cost surge and negative fallouts from the war in Ukraine. Concerns about new Covid-19 variants cannot be ignored neither.
Since 2004, GCD has continuously reinforced a framework that is used to measure and monitor Data Quality (DQ). The objective is to achieve high DQ and compliance for the GCD pooled data, as required by global regulations (BCBS 239, ECB Guide to internal models, Fed SR1107).
Downturn LGD Study 2020 This Global Credit Data (GCD) study looks into the historical effects of previous downturns on bank credit losses across various debtor types, industries and regions, with […]
This year at Global Credit Data’s North American Conference GCD’s Members came together to discuss the pressing credit risk issues that banks are facing today.