How to select a stress testing methodology?

As the world is crawling out of the global economic crisis, several efforts are underway by regulators as well as international organizations, such as the International Monetary Fund (IMF) and Bank of International Settlements, to institutionalize stress testing as an integral part of bank’s functioning. The intent is to better understand system-wide risks that can trigger widespread economic and financial instability. US Fed, therefore, has mandated an annual Comprehensive Capital Adequacy Review (CCAR) exercise for all banks to submit their capital plans for multiple scenarios (Baseline and Stressed scenarios).

However, the road to implementing these methodologies is not as smooth. There are questions which frequently trouble any risk practitioner: Which stress-testing method should be used? Which system would pass muster with the regulators? What level should we stress at – loan or portfolio level? This becomes especially challenging in the scenario when there are multiple methodologies which can be used to conduct a stress test.

The figure below highlights the different types of techniques available for stress testing:

In ‘Parameter Stressing’ approach, the default rate is directly stressed without evaluating or worrying about the fundamental default risk drivers. In ‘Risk Driver Stressing’ approach, the drivers of model parameters (such as Probability of Default (PD) or roll rates) are stressed and an estimate of the parameter is computed based on stressed values of risk drivers.

Each of these approaches has its fair share of advantages and disadvantages. While parameter stressing approaches are simple to conduct and understand, they provide little insight into portfolio dynamics, for example which factor is responsible for migration of population from low risk grade to higher risk grades during the downturn?

On the other hand, risk driver based stress testing allows greater insights into portfolio dynamics by allowing the user to determine causality of account migration from lower risk to higher risk grades. However, computationally these approaches make high demand on physical infrastructure like data processing capabilities as well as skilled analytical professionals.

In our experience, what is important is the appreciation of objective of conducting a stress test and bank’s own risk culture. While objective can vary from testing model robustness to prediction of future state of banks’ finances in case of a stress event re-occurring, a key factor is whether the bank treats it as a regulatory tick mark exercise or as a means to establish risk leadership.

We at Axtria believe that stress testing, with or without regulatory pressure; can be a source of competitive advantage to a diligent risk manager. It has the ability to empower a risk manager with deep knowledge of portfolio dynamics with respect to internal and external drivers - which can help avoid significant future losses.

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Sandeep Gupta

Sandeep leads the risk analytics practice at Axtria BFSI unit. Specific area of focus is Risk and Basel analytics for retail banking clients. Worked on Basel model development for more than five regulators around the globe.