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Getting over the stress testing hump

December 20, 2014
Read Time: 0 min

It’s like the buzzword that doesn’t go away: stress testing may have seemed like an unnecessary step for many institutions in the past, a buzzword that applied only to the big banks. But with the support of the regulatory agencies, the buzzword is becoming more of a minimum standard.

Given the task is often assigned to the Chief Credit Officer or other leaders within the credit department, developing a stress testing methodology may come at the risk of losing steam on other areas, even business development if the stress tester is also responsible for lending.

Clearly, stress testing is not a good replacement for other critical functions, so banks look for ways to perform the analysis without setting back other priorities.

The good news is that institutions can “get over the hump” pretty easily if they recognize components of the analysis they may already have within the bank. By using the data and results already available, banks can get a jump-start.

Banks and credit unions are already preparing and documenting the allowance for loan and lease losses calculation, which includes determining loss rates for FAS 5 pools and impaired loans. Furthermore, executives already dedicate time to determining and justifying qualitative factor (Q Factor) adjustments that may need to be made to historical loss rates to make them better predictors of expected losses.

These loss rates and adjustments are key components of a top down or institution-level stress test, which may be a good starting place for institutions seeking to get over the stress testing hump.


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Clearly, there will be other pieces of data needed. Financial institutions should gather data on:

1. their historical loss rates over several stress periods,
2. peer and market loss rates over several stress periods and
3. the results of any bottom up stress tests to develop “stressed” loss rates for each segment. 

With this data, institutions can then calculate stress-period loss amounts using a two-year timeframe and estimate their earnings impact and Tier 1 Capital ratios.

The documentation and analysis used in Q Factor adjustments also inform the stress test. For example, what if unemployment rates increase to 10 percent in the counties where the institution operates? Having historical data within Q Factors on how unemployment rates correlate to or track with loss rates over various time horizons can be valuable in creating a realistic top down scenario. 

Why are top down stress tests valuable to the institution? While they may not offer the granularity of a bottom up stress test, institution level analysis like that shown in the example provides financial institutions with a high-level picture of their portfolio under stress scenarios that are not immediately apparent when analyzing loans on the individual level. It also forces institutions to look at and consider concentrations or products that are inherently riskier than others and the influence riskier concentrations have (or could have, in a stress scenario) on the larger portfolio.

In other words, aside from checking a compliance box, these top down tests also make risk appetites, strategic conversations, loan pricing, and capital plans more informed and therefore less susceptible to failures like we saw in the financial crisis.

Stress testing isn’t a band-aid, but it can be an effective “vitamin” the institution takes to ward off unexpected catastrophes within the portfolio, caused by economic and process changes. And, with the suggestions here, hopefully it’s easier for the bank to get started.


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