Abstract
The new credit risk specifications include, inter alia, the implementation of higher floors for the PD, LGD, and EAD in the IRBA models, which allow banks to estimate these parameters internally. It also requires the migration of certain exposures from the AIRBA to the FIRBA and SA. However, the utmost goal of the Basel reform package is the reduction of the variability of RWAs across time. These revisions target the reduction of the variability of RWAs across time, and implicitly amongst banks with similar portfolio risk profiles. The current chapter examines the quantitative impact of the structural changes that Basel introduces in the calculation of capital requirements under the FIRBA and AIRBA.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
The reader could contact the authors to request details on the exact methodology for the estimation of the default rates and LGD inputs.
- 2.
The analysis does not consider the impact of the transition of equity exposures from AIRBA to SA, as it is straightforward and it depends exclusively on banks’ individual exposures.
- 3.
Excluding equities which are currently subject to a different regime and migrate to the SA under the final Basel III.
- 4.
The results are subject to the quality of data used but they are indicative of the impact of the structural changes between AIRBA and FIRBA.
- 5.
The data used in this analysis are supposed to be robust enough to reflect the actual impact.
References
Basel Committee on Banking Supervision (BCBS). (2016, March). Reducing variation in credit risk-weighted assets – Constraints on the use of internal model approaches – Consultative document. Retrieved from http://www.bis.org/bcbs/publ/d362.pdf
Basel Committee on Banking Supervision (BCBS). (2017, December). Basel III: Finalising post-crisis reforms – Standards. Retrieved December 7, 2017, from https://www.bis.org/bcbs/publ/d424.pdf
Bonsall, S., Koharki, K., Muller, K., & Sikochi, A. (2017). Credit rating adjustments prior to default and recovery rates. Harvard Business School. Retrieved from http://www.hbs.edu/faculty/conferences/2017-imo/Documents/Siko_BKMS_03_07_17.pdf
Elizondo-Flores, J. A., Lemus-Basualdo, T., & Quintana-Sordo, A. R. (2010). Regulatory use of system-wide estimations of PD, LGD and EAD 2010. Financial Stability Institute (FSI) Award 2010 Winning Paper, Bank for International Settlements. Retrieved from http://www.bis.org/fsi/awp2010.pdf
Johnston-Ross, E., & Shibut, L. (2015). What drives loss given default? Evidence from commercial real estate loans at failed banks. Federal Deposit Insurance Corporation (FDIC). Centre for Financial Research. Working Paper Series. FDIC CFR WP 2015-03. Retrieved September 2017, from https://www.fdic.gov/bank/analytical/cfr/2015/wp2015/2015-03.pdf
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 The Author(s)
About this chapter
Cite this chapter
Akkizidis, I., Kalyvas, L. (2018). Credit Risk: Quantitative Impact. In: Final Basel III Modelling. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-70425-8_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-70425-8_5
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-319-70424-1
Online ISBN: 978-3-319-70425-8
eBook Packages: Economics and FinanceEconomics and Finance (R0)