Adapting Basel's A-IRB Models for IFRS 9 Purposes

35 Pages Posted: 6 Aug 2016

See all articles by Peter Miu

Peter Miu

McMaster University - DeGroote School of Business

Bogie Ozdemir

Standard & Poor's

Date Written: August 5, 2016

Abstract

Banks around the globe are implementing IFRS 9 which is a considerable effort. A key element of IFRS 9 is a forward-looking “expected loss” impairment model, which is a significant shift from the current incurred loss model. In this paper, we examine how we may use A-IRB models in the estimation of expected credit losses for IFRS 9 purposes. We highlight the necessary model adaptations required to satisfy the new accounting standard. By leveraging on the A-IRB models, banks can lessen their modeling efforts in fulfilling IFRS 9 and capture the synergy among different modeling endeavors within the institutions. In outlining the proposed PD, LGD, and EAD models, we provide detailed examples of how they may be implemented on secured lending. Moreover, in discussing the issues related to the estimation of the expected credit loss for IFRS 9, we highlight the challenges involved and propose practical solutions to deal with them. For instance, we propose the use of a convexity adjustment approach to circumvent the need of assigning probabilities in multiple-scenario analysis.

Keywords: Advanced internal rating-based (A-IRB) approach; IFRS 9; Basel; internal models; probability of default (PD); loss given default (LGD); exposure at default (EaD); expected loss (EL); provisions; impairment loss estimation; secured lending

JEL Classification: G21, G28, G32, M48

Suggested Citation

Miu, Peter and Ozdemir, Bogie, Adapting Basel's A-IRB Models for IFRS 9 Purposes (August 5, 2016). Available at SSRN: https://ssrn.com/abstract=2819101 or http://dx.doi.org/10.2139/ssrn.2819101

Peter Miu (Contact Author)

McMaster University - DeGroote School of Business ( email )

1280 Main Street West
Hamilton, Ontario L8S 4M4
Canada
905-525-9140 ext 23981 (Phone)

Bogie Ozdemir

Standard & Poor's ( email )

130 King Street West
Suite 1100, PO Box 486
Toronto, Ontario M5X 1E5
Canada

Register to save articles to
your library

Register

Paper statistics

Downloads
751
Abstract Views
1,892
rank
32,472
PlumX Metrics