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What data is needed for top down stress testing?

Sageworks
April 9, 2015
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The OCC defines “top down” stress testing as “applying estimated stress loss rates under one or more scenarios to pools of loans with common risk characteristics.” This method of stress testing provides deeper insight into a financial institution’s portfolio or portfolio segment during stressed scenarios. For top down stress testing to be performed properly, banks and credit unions must appropriately segment their portfolio into pools of like characteristics, to which loss rates can then be applied.

Top down stress testing can uncover concentration and/or portfolio-wide risks – something that isn’t immediately apparent when analyzing individual loans or even groups of loans. If bankers know where vulnerabilities exist, they can use stress test results to allocate capital and make more effective risk management decisions. Here are two examples:

• Set appropriate capital reserves in preparation for potential adverse scenarios. Stress testing can determine if current capital reserve levels are sufficient or if changes are needed.
• Understand where your portfolio may be overexposed in a concentration – either due to type of asset, geography or potentially damaging economic events.

While the benefits are clear, obstacles to implementing a top down stress test certainly exist. One common issue faced by bankers surrounds the data requirements to accurately perform top down stress testing. Attempting to collect and update data can be a deterrent to stress testing, especially if the practice isn’t required (or enforced) by regulators.

 

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The data set needed for top down stress testing differs from that of bottom up stress testing. To get started with top down stress testing, loan data is necessary to properly segment the portfolio into pools with similar risk characteristics. Next, banks and credit unions should gather data on:

• Historical loss rates over several stress periods
• Peer and market loss rates over several stress periods
• The results of any bottom up stress tests to develop “stressed” loss rates for each segment

Once this data is available, stress-period loss amounts can be calculated using a two-year timeframe to estimate their impact on earnings and capital ratios. Collecting macroeconomic and regional/local data can supplement the historic loss rate data.

Much of the macroeconomic and regional/local economic data can be accessed from internal data, or from external resources like Federal Reserve Economic Data (FRED). Institutions using an automated solution will more easily retrieve and centralize the data, while avoiding common errors found when using spreadsheets.

Rob Ashbaugh, Executive Risk Management Consultant at Abrigo, recommends banks and credit unions run at least two scenarios in stress testing – mild and severe. “The mild scenario can replicate the current FAS 5 (ASC 450-20) expectations, while severe should use a scenario that is severe enough but still possible.” For the severe scenario, Ashbaugh suggests replicating the worse year the bank has faced, which may have occurred during the recent economic crisis.

 

 
About the Author

Sageworks

Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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About Abrigo

Abrigo enables U.S. financial institutions to support their communities through technology that fights financial crime, grows loans and deposits, and optimizes risk. Abrigo's platform centralizes the institution's data, creates a digital user experience, ensures compliance, and delivers efficiency for scale and profitable growth.

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