After the Crisis: Bank Stress Tests Part II

Even in the best of economic times, stress testing a bank’s portfolio is a sound practice for assessing the sufficiency of capital reserves as well as the responsiveness of the institution’s infrastructure and reporting process. However, as we all learned in the 2008-09 financial crisis, there were significant weaknesses in these internal stress testing programs. The major shortcoming: an inability to assess vulnerabilities arising from interrelated events across all risk and asset types.

It is this inadequacy that prevented institutions from seeing the interactions across risk types that surfaced in the crisis. As a result, “siloed” risk models in various asset classes lacked the synergy and interrelationships to properly forecast the cross-asset impact of abnormal conditions and events.
Today, the need is clear for firm-wide stress testing across asset classes, positions and business lines to improve. This will ensure appropriate risk capture and will aggregate stress-test and risk-calculation results more consistently and effectively.
However, until regulators stepped up their mandates for stress testing last year, there was no precedent or strong impetus driving banks to aggregate their information. Although the completed first round of the Supervisory Capital Assessment Program (SCAP) provided some useful insights into 19 of the largest U.S. banks, those tests were limited by the available data and the restriction to two basic scenarios – a continuing downturn and a slightly more adverse condition.
What’s more, the SCAP tests were a process nightmare. It took three to four months for the U.S. Treasury Department to design valid and meaningful stress tests, send regulatory letters mandating that banks perform the tests, compile results, compare bank submissions, adjust values and interpret the findings. It was no better inside banks. Most had to create one-time manual processes to comply with the Treasury mandates – processes that will be difficult to extend or repeat.
Shift to Scenario Analysis
Simply replicating the stress tests on an industry-wide basis would be challenging enough. But as the thin and limited results of the first round of SCAP show, it’s clear that regulators and institutions alike will need to expand their view from just simple stress testing.
The SCAP tests were not a one-time exercise. Improved stress-testing processes and analytics will remain a high priority for the foreseeable future. Mastery of these tests will not only be required to respond to regulatory requirements; they will also enable banks to perform ad hoc stress analyses and more effectively manage their economic capital.
But this first phase only hints at the scale and scope of the broader challenge. Going forward, banks will need a broader class of scenario analyses that leverage on standardized processes and improved data aggregation.
In simple stress testing, the bank models and calculates the effect on a particular asset class of a change by a given amount to a single risk factor or set of risk factors. For instance, what happens to the mortgage-securities assets if equity prices decrease by 10 percent? This can be used to analyze how sensitive an asset is to a large change in a specific market factor, i.e. how exposed it is.  


But banks need to expand stress testing across the portfolio, which is often called scenario analysis. This involves calculating the effects on a portfolio of stressing all underlying risk factors arising from a pre-defined market scenario. Scenario analysis is better suited to reproducing the effects of historical events, such as Black Monday, a period of loss in the bank’s history or a potential future event.
Integrated Framework
To achieve this broader scope of testing, banks need a framework that allows managers and analysts to easily run many different market and credit risk scenarios across a variety of risk factors and portfolios. This framework should help them understand events that have effects across risk types – for example, market risk, credit risk, and operational risk – that, when combined, could result in exposure beyond isolated test results.
Business users and risk analysts also need a graphical interface to simplify the building and review of stress-test scenarios. The ability to use pre-defined scenarios or create user-defined scenarios is critical, as is a robust visualization capability to compare the impact of scenarios across specific key performance indicators.
A framework that enables senior executives and business analysts to view consolidated results for a variety of stress test scenarios – and extends and enhances the ability to perform sensitivity and “what if” analyses – would be a powerful asset, especially in the current challenging economic conditions.
There are challenges. Coverage of asset types and consistency of criteria are large barriers to more effective stress tests and scenario analyses. Coverage is hindered because disparate information prohibits a consolidated view of all assets. What’s more, multiple versions of data, valuation methods and models persist throughout the process.
Clear regulatory and industry standards are also essential. Their aim should be to align asset classes and risk measurement methodologies across the industry for use within banks and between the banks and regulators. These standards would help remove some of the subjectivity from asset valuation and provide a more consistent risk-calculation methodology.
Information from stress testing and scenario analyses provides tremendous benefits to financial institutions. Their outcomes identify specific operational gaps, vulnerabilities and threats that the banks can address. This makes the institutions stronger, more competitive and better positioned to provide better services to customers.
About the Author
Michael Stefanick is currently the Senior Manager of US Risk Practice for SAS. Prior to joining SAS, he served as Vice President of Risk Architecture and Finance Transformation for SunTrust Group, and as Chief Architect and Vice President of Business Risk Systems for Fifth Third Bank. He also has extensive consulting experience with numerous leading financial institutions, including ING, GMAC, American Express, Fidelity and Bank of America.



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