Journal of Credit Risk

Risk.net

Adapting the Basel II advanced internal-ratings-based models for International Financial Reporting Standard 9

Peter Miu and Bogie Ozdemir

  • 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.
  • We examine how we may use A-IRB models in the estimation of expected credit losses for IFRS 9 purposes.
  • 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.

Banks around the globe are implementing International Financial Reporting Standard 9 (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 incurred-loss model. We examine how we may use advanced internal-ratings-based (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 between different modeling endeavors within institutions. In outlining the proposed probability of default, loss given default and exposure at default 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 for assigning probabilities in multiple-scenario analysis.

To continue reading...

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an indvidual account here: