Predicting the Utilization Rate and Risk Measures of Committed Credit Facilities
a National Bank of Ukraine, Kyiv, Ukraine
Abstract

This study proposes a model for predicting the expected drawn amount of credit facilities. To model the committed credit facilities we rely on the conditional expected utilization rate derived from a joint truncated bivariate probability distribution. The expected monthly liquidity conversion factors for corporate credit lines are compared to actuals and the bivariate normal distribution is concluded to be appropriate for a practical estimate of the future utilization rate.

Publication History
Avaliable online 25 June 2017
85
views
45
downloads
Full Text
Citation
Cite as: Voloshyn, I. (2017). Predicting the Utilization Rate and Risk Measures of Committed Credit Facilities. Visnyk of the National Bank of Ukraine, 240, 14-21. https://doi.org/10.26531/vnbu2017.240.014
Citation Format

Metrics
References

BIS (2001). The standardised approach to credit risk. Supporting document to the New Basel capital accord. Basel Committee on Banking Supervision. Retrieved from http://www.bis.org/publ/bcbsca04.pdf

BIS (2013). Basel III: The liquidity coverage ratio and liquidity risk monitoring tools. Basel Committee on Banking Supervision. Retrieved from http://www.bis.org/publ/bcbs238.pdf

GPPC (2016). The implementation of IFRS 9 impairment requirements by banks. Considerations for those charged with governance of systemically important banks. Global Public Policy Committee of representatives of the six largest accounting networks. Retrieved from https://assets.kpmg.com/content/dam/kpmg/pdf/2016/06/gppc-ifrs9-implementation-considerations-20160617.pdf

Deloitte (2014). IFRS 9 Financial Instruments (replacement of IAS 39). Retrieved from https://www.iasplus.com/en/standards/ifrs/ifrs9#link0

Jacobs, M. (2009). An empirical study of exposure at default. Risk Analysis, Division / Credit Risk Modelling Moody's KMV Credit Practitioner's Conference. September 9, 2009.

Kim, H., DeVaney, S. A. (2001). The determinants of outstanding balances among credit card revolvers. Association for Financial Counseling and Planning Education. Retrieved from https://afcpe.org/assets/pdf/vol1216.pdf

Korn, G. A., Korn, T. M. (1968). Mathematical handbook for scientists and engineers: Definitions, theorems, and formulas for reference and review. Mineola, New York: Dover Publications, Inc.

Moral, G., de Espa-a, B. (2006). EAD Estimates for Facilities with Explicit Limits. The Basel II Risk Parameters, 201-246. https://doi.org/10.1007/978-3-642-16114-8_11 

National Bank of Ukraine (2016). Regulation for Measuring Credit Risk Generated by Banks' Asset Operations (In Ukrainian). Resolution NBU No. 351. Retrieved from https://bank.gov.ua/document/download?docId=33378802

Osipenko, D., Crook, J. (2015). The comparative analysis of predictive models for credit limit utilization rate with SAS/STAT. Paper, 3328-2015. Retrieved from https://support.sas.com/resources/papers/proceedings15/3328-2015.pdf

EU (2013). Regulation EU No. 575/2013 of the European Parliament and the Council on prudential requirements for credit institutions and investment firms and amending regulation (EU) No. 648-2012. Official Journal of the European Union, 56, 1-337. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=uriserv:OJ.L_.2013.176.01.0001.01.ENG

Taplin, R., To, H. M., Hee, J. (2007). Modeling exposure at default, credit conversion factors, and the Basel II Accord. Journal of Credit Risk, 3(2), 75-84. https://doi.org/10.21314/JCR.2007.064

Tong, E. N. C., Mues, C., Brown, I., Thomas, L. C. (2016). Exposure at default models with and without the credit conversion factor. European Journal of Operational Research, 252(3), 910-920. https://doi.org/10.1016/j.ejor.2016.01.054

Wilhelm, S., Manjunath, B. G. (2010). tmvtnorm: A package for the truncated multivariate normal distribution. Contributed research articles. The R Journal, 2/1, 25-29. https://doi.org/10.32614/rj-2010-005

Yang, B. H., Tkachenko, M. (2012). Modeling of EAD and LGD: Empirical approaches and technical implementation. Retrieved from https://mpra.ub.uni-muenchen.de/id/eprint/57298
 

Rights and Permissions
This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material.
Submit Your Paper