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Point-in-time loss-given default rates and exposures at default models for IFRS 9/CECL and stress testing/ created by Gaurav Chawla, Lawrence R. Forest and Scott D. Aguais

By: Contributor(s): Material type: TextTextSeries: Journal of risk management in financial institutions ; Volume 9, number 3London : Henry Stewart Publication, 2016Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISSN:
  • 17528887
Subject(s): LOC classification:
  • HD61.J687 JOU
Abstract: In contrast with Basel II rules, which call for the use of through-the-cycle (TTC) probabilities of default (PDs) and downturn (DT) loss-given default rates (LGDs) and exposures at default (EADs), the regulatory stress tests and the new IFRS 9 and proposed Current Expected Credit Loss (CECL) accounting standards require institutions to use point-in-time (PIT) projections of PDs, LGDs and EADs. By accounting for the current state of the credit cycle, PIT measures track closely the variations in default and loss rates over time. In past publications the authors have described the derivation of industry-region credit-cycle indices (CCIs) and the use of those indices in converting legacy wholesale credit PD models, which typically understate cyclical variations, into fully PIT ones. This paper extends that framework to cover estimation of PIT LGDs and EADs for wholesale exposures. The authors offer options for the formulation of such models and discuss their experience in building PIT LGD and EAD models, and show that, by accounting for the probabilistic evolution over time in industry-region CCIs, one can derive joint, PD, LGD and EAD scenarios for use in the regulatory stress tests or in estimating the term structures of expected credit losses (ECLs) as needed for IFRS 9/CECL.
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Item type Current library Call number Vol info Status Notes Date due Barcode
Journal Article Journal Article Main Library - Special Collections HD61.J687 JOU (Browse shelf(Opens below)) Vol. 9, no.3 (pages 249-263) Not for loan For in house use only

In contrast with Basel II rules, which call for the use of through-the-cycle (TTC) probabilities of default (PDs) and downturn (DT) loss-given default rates (LGDs) and exposures at default (EADs), the regulatory stress tests and the new IFRS 9 and proposed Current Expected Credit Loss (CECL) accounting standards require institutions to use point-in-time (PIT) projections of PDs, LGDs and EADs. By accounting for the current state of the credit cycle, PIT measures track closely the variations in default and loss rates over time. In past publications the authors have described the derivation of industry-region credit-cycle indices (CCIs) and the use of those indices in converting legacy wholesale credit PD models, which typically understate cyclical variations, into fully PIT ones. This paper extends that framework to cover estimation of PIT LGDs and EADs for wholesale exposures. The authors offer options for the formulation of such models and discuss their experience in building PIT LGD and EAD models, and show that, by accounting for the probabilistic evolution over time in industry-region CCIs, one can derive joint, PD, LGD and EAD scenarios for use in the regulatory stress tests or in estimating the term structures of expected credit losses (ECLs) as needed for IFRS 9/CECL.

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