Managing Operational Risk
First published:
ISBN: 9781782722861
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Estimating Exposures to Tail Events
Introduction
Three Historical Spikes in Operational Risk Losses
First-Order Effects: Transforming Credit Defaults and Market Turmoil into Operational Risk Losses
Second-Order Effects: Transforming Rising Unemployment and Falling Interest Rates into Operational Risk Losses
Conclusions and Root Causes
Regulatory Change: Part of a Perfect Storm
Macroeconomic Threats: Tax, Rising Interest Rates and New Asset Bubbles
New Technology: Changing Business Models and Risk Profiles
Three Horsemen: Societal, Political and Environmental Change
Backtesting to the Mid-1990s and Conclusions
Defining and Cascading Operational Risk Appetites
Aligning Operational Risk Management Frameworks to Appetites
Estimating Exposures to Tail Events
Solutions for a Triumvirate of Seemingly Intractable Problems
Conclusions
“…these facts [the laws of probability] contribute a great deal to understanding, but hardly anything to practical [dice] play…”
Girolama Cardano, the earliest writer on probability, describing how his understanding of the laws of probability still did not help him win at dice!
The financial crisis of 2007–8 taught the industry and regulators both the importance of operational risk and the criticality of understanding firms’ exposures to the risks of suffering unexpected losses. In response, the industry and regulators have enhanced some existing risk-management techniques, such as scenario analysis and stress testing, and also developed a new technique, reverse stress testing. Although various regulatory bodies have published guidance, industry practices are still developing. Consequently, this chapter provides insights into how to undertake these risk-management activities more effectively, and also how they should link together. The definitions of these three risk-management techniques illustrate their similarities and differences.
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Scenario analysis – the assessment of the likelihood and impacts of specific operational risk events across a one-year time
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