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13 - Operational Risk

Published online by Cambridge University Press:  02 March 2023

By
Filippo Curti ,
Marco Migueis  and
Robert Stewart
Edited by
David Lynch ,
Iftekhar Hasan  and
Akhtar Siddique
David Lynch
Affiliation:
Federal Reserve Board of Governors
Iftekhar Hasan
Affiliation:
Fordham University Graduate Schools of Business
Akhtar Siddique
Affiliation:
Office of the Comptroller of the Currency
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Summary

This chapter provides an overview of operational risk modeling techniques used by industry participants and regulators in the USA, recommendations for how modeling techniques can be improved, and a summary of the model risk tools necessary for any operational risk modeling framework.

Keywords

Operational risk
Type
Chapter
Information
Validation of Risk Management Models for Financial Institutions
Theory and Practice
 , pp. 331 - 358
Publisher: Cambridge University Press
Print publication year: 2023

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References

Abdymomunov, A., Curti, F., and Mihov, A. (2015). U.S. Banking Sector Operational Losses and the Macroeconomic Environment. Working Paper, Federal Reserve Bank of Richmond.Google Scholar
Admati, A. (2014). Statement for Senate Committee on Banking, Housing and Urban Affairs Subcommittee on Financial Institutions and Consumer Protection. Hearing on Examining the GAO report on Expectations of Government Support for Bank Holding Companies.Google Scholar
Akerlof, A., and Romer, P. (1993). Looting: The economic underworld of bankruptcy for profit. Brookings Papers on Economic Activity 2, 1–73.Google Scholar
Aliber, R., and Kindleberger, C. P. (2005). Manias, Panics, and Crashes: A History of Financial Crises. Wiley.Google Scholar
Ames, M., Schuermann, T., and Scott, H. (2015). Bank capital for operational risk: A tale of fragility and instability. Journal of Risk Management in Financial Institutions 8(3), 227–243.Google Scholar
Campbell, S. (2006). A review of backtesting and backtesting procedures. The Journal of Risk 9(2), 1–17.CrossRefGoogle Scholar
Chernobai, A., Jorion, P., and Yu, F. (2011). The determinants of operational risk in US financial institutions. Journal of Financial and Quantitative Analysis 46(6), 1683–1725.CrossRefGoogle Scholar
Cope, E., and Carrivick, L. (2013). Effects of the financial crisis on banking operational losses. The Journal of Operational Risk 8(3), 3–29.CrossRefGoogle Scholar
Cope, E., Mignola, G., Antonini, G., and Ugoccioni, R. (2009). Challenges and pitfalls in measuring operational risk from loss data. The Journal of Operational Risk 4(4), 3–27.Google Scholar
Curti, F., Ergen, I., Li, M., Migueis, M., and Stewart, R. (2016). Benchmarking Operational Risk Models. Finance and Economics Discussions Series, Federal Reserve Board.CrossRefGoogle Scholar
Danielsson, J. (2002). The emperor has no clothes: Limits to risk modeling. Journal of Banking & Finance 26(7), 1273–1296.Google Scholar
Gabaix, X., and Laibson, D. (2008). The Seven Properties of Good Models, The Foundations of Positive and Normative Economics: A Handbook. Oxford University Press.Google Scholar
Heckman, P. and Meyers, G. (1983). The calculation of aggregate loss distributions from claim severity and claim count distributions. Proceedings of the Casualty Actuarial Society LXX, 22–61.Google Scholar
Hess, C. (2011). The impact of the financial crisis on operational risk in the financial services industry: empirical evidence. The Journal of Operational Risk 5(2), 43–62.Google Scholar
Hoenig, Thomas. (2016). A Capital Conflict. Speech to the National Association for Business Economics (NABE) and the Organization for Economic Cooperation and Development (OECD) Global Economic Symposium, Paris, France. May 23.Google Scholar
International Monetary Fund. (2014). Global Financial Stability Report – Moving from Liquidity to Growth-Driven Markets.Google Scholar
Ioannidis, J. (2005). Why most published research findings are false. PLoS Medicine 2(8), e124.CrossRefGoogle ScholarPubMed
Kahneman, D., and Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk-taking. Management Science 39(1), 17–31.CrossRefGoogle Scholar
Leamer, E. (1983). Let’s take the con out of econometrics. The American Economic Review 73(1), 31–43.Google Scholar
Leeson, N., and Whitley, E. (1996). Rogue Trader: How I Brought Down barings Bank and Shook the Financial World. Little Brown and Company.Google Scholar
Mignola, G., and Ugoccioni, R. (2006). Sources of uncertainty in modeling operational risk losses. The Journal of Operational Risk 1(2), 33–50.CrossRefGoogle Scholar
Nešlehová, J., Embrechts, P., and Chavez-Demoulin, V. (2006). Infinite mean models and the LDA for operational risk. The Journal of Operational Risk 1(1), 3–25.CrossRefGoogle Scholar
Opdyke, J. and Cavallo, A. (2012). Estimating operational risk capital: The challenges of truncation, the hazards of maximum likelihood estimation, and the promise of robust statistics. The Journal of Operational Risk 7(3), 3–90.Google Scholar
Pannell, D. (1997). Sensitivity analysis of normative economic models: theoretical framework and practical strategies. Agricultural Economics 16(2), 139–152.Google Scholar
Schorfheide, F., and Wolpin, K. (2012). On the use of holdout samples for model selection. American Economic Review 102(3), 477–481.Google Scholar
Sekeris, E. (2012). New frontiers in the regulatory advanced measurement approach, Operational Risk: New Frontiers Explored. Risk Books.Google Scholar
Stewart, R. (2016). Bank fraud and the macroeconomy. The Journal of Operational Risk 11(1), 71–82.Google Scholar
Velleman, P. (2008). Truth, damn truth, and statistics. Journal of Statistics Education 16(2), 2–15.Google Scholar

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