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The Risks of Financial Institutions$
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Mark Carey and Rene M. Stulz

Print publication date: 2007

Print ISBN-13: 9780226092850

Published to Chicago Scholarship Online: February 2013

DOI: 10.7208/chicago/9780226092980.001.0001

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PRINTED FROM CHICAGO SCHOLARSHIP ONLINE (www.chicago.universitypressscholarship.com). (c) Copyright University of Chicago Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in CHSO for personal use.date: 17 September 2021

Implications of Alternative Operational Risk Modeling Techniques

Implications of Alternative Operational Risk Modeling Techniques

Chapter:
(p.475) 10 Implications of Alternative Operational Risk Modeling Techniques
Source:
The Risks of Financial Institutions
Author(s):

Patrick de Fontnouvelle

Eric S. Rosengren

John S. Jordan

Publisher:
University of Chicago Press
DOI:10.7208/chicago/9780226092980.003.0011

This chapter employs data supplied by six large, internationally active banks to identify if the regularities in the loss data will make consistent modeling of operational losses possible. It is noted that operational risk is a material risk faced by financial institutions. The data indicate that it may be difficult to fit parametric loss-severity distributions over the entire range of loss amounts, even if separate analyses are conducted for each business line and event type. Loss-severity distributions at the six banks under consideration have tail indexes ranging between 0.50 and 0.86. Assuming a Pareto severity distribution yielded capital estimates that were broadly consistent with the Basel Committee's expectation that operational risk accounts for 12 percent of minimum regulatory capital. As banks obtain three or more years of good operational loss data, the ability to differentiate across alternative distributional assumptions should improve.

Keywords:   loss data, modeling, operational losses, operational risk, financial institutions, loss-severity distributions, regulatory capital

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