Practical methods for measuring and managing operational risk in the financial sector: a clinical study
AbstractThis paper analyzes the implications of the advanced measurement approach (AMA) for the assessment of operational risk. Through a clinical case study on a matrix of two selected business lines and two event types of a large financial institution, we develop a procedure that addresses the major issues faced by banks in the implementation of the AMA. For each cell, we calibrate two truncated distributions functions, one for "normal" losses and the other for the "extreme" losses. In addition, we propose a method to include external data in the framework. We then estimate the impact of operational risk management on bank profitability, through an adapted measure of RAROC. The results suggest that substantial savings can be achieved through active management techniques.
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Bibliographic InfoPaper provided by ULB -- Universite Libre de Bruxelles in its series ULB Institutional Repository with number 2013/14158.
Date of creation: 2008
Date of revision:
Publication status: Published in: Journal of Banking & Finance (2008) v.32,p.1049-1061
Other versions of this item:
- Chapelle, Ariane & Crama, Yves & Hübner, Georges & Peters, Jean-Philippe, 2008. "Practical methods for measuring and managing operational risk in the financial sector: A clinical study," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1049-1061, June.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- François Longin, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, 04.
- Chavez-Demoulin, V. & Embrechts, P. & Neslehova, J., 2006. "Quantitative models for operational risk: Extremes, dependence and aggregation," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2635-2658, October.
- Huisman, Ronald, et al, 2001. "Tail-Index Estimates in Small Samples," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 208-16, April.
- Patrick de Fontnouvelle & John Jordan & Eric Rosengren, 2005.
"Implications of Alternative Operational Risk Modeling Techniques,"
NBER Working Papers
11103, National Bureau of Economic Research, Inc.
- Patrick de Fontnouvelle & Eric Rosengren & John Jordan, 2007. "Implications of Alternative Operational Risk Modeling Techniques," NBER Chapters, in: The Risks of Financial Institutions, pages 475-512 National Bureau of Economic Research, Inc.
- Patrick de Fontnouvelle & Eric Rosengren & John Jordan, 2004. "Implications of alternative operational risk modeling techniques," Working Papers 1, Federal Reserve Bank of Boston.
- Frachot, Antoine & Roncalli, Thierry & Salomon, Eric, 2004. "The Correlation Problem in Operational Risk," MPRA Paper 38052, University Library of Munich, Germany.
- Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
- Drees, Holger & Kaufmann, Edgar, 1998. "Selecting the optimal sample fraction in univariate extreme value estimation," Stochastic Processes and their Applications, Elsevier, vol. 75(2), pages 149-172, July.
- Huisman, Ronald & Koedijk, Kees G. & Kool, Clemens J.M. & Palm, Franz, 2001. "Tail-index estimates in small samples," Open Access publications from Maastricht University urn:nbn:nl:ui:27-5756, Maastricht University.
- Hela Dahen & Georges Dionne, 2007.
"Scaling Models for the Severity and Frequency of External Operational Loss Data,"
Cahiers de recherche
- Dahen, Hela & Dionne, Georges, 2010. "Scaling models for the severity and frequency of external operational loss data," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1484-1496, July.
- Wang, Zongrun & Wang, Wuchao & Chen, Xiaohong & Jin, Yanbo & Zhou, Yanju, 2012. "Using BS-PSD-LDA approach to measure operational risk of Chinese commercial banks," Economic Modelling, Elsevier, vol. 29(6), pages 2095-2103.
- Elshahat, A. & Parhizgari, Ali & Hong, Liang, 2012. "The information content of the Banking Regulatory Agencies and the Depository Credit Intermediation Institutions," Journal of Economics and Business, Elsevier, vol. 64(1), pages 90-104.
- Stefan Mittnik & Sandra Paterlini & Tina Yener, 2011. "Operational–risk Dependencies and the Determination of Risk Capital," Center for Economic Research (RECent) 070, University of Modena and Reggio E., Dept. of Economics.
- Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
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