By Ty Lambert, Chief Data Analytics Officer, BancorpSouth
What, for you are the benefits of attending a conference like Stress Testing USA and what can attendees expect to learn from your session?
Arguably, the greatest initial benefit to be gleaned from capital stress testing was the holistic approach to evaluating worst case scenarios and their respective impact upon business operations and profitability. The integration of enterprise risks (i.e. credit, liquidity, operational, etc.) under a common exercise laid the foundation from a technical and mechanical perspective to more comprehensively view the impact of certain business decisions when coupled with other environmental factors (i.e. primarily economic drivers).
As stress testing has become mature in the banking industry, the focus is shifting from primarily evaluating worst case scenarios to expanding the use case to be more strategic in nature. For example, what are the things that can alter the outcome of a business decision, given its relationship to other areas of risks? In other words, stress testing has evolved into sensitivity testing of key inputs for corporate planning. Granted there is still value in analysing the worst case scenario, but the mechanical infrastructure of stress testing programs today gives us much more flexibility to work through business-as-usual decisions. Our session explores some of the practical use cases for sensitivity testing in today’s environment.
In your opinion, what key considerations need to be made when modeling war gaming and capital contingency planning?
The key to effective capital contingency planning really extends beyond the standard approach of being able to continue operations and remain solvent during times of severe stress. Effective capital management also requires an understanding of how capital is utilized to measure various forms of underlying risks on the balance sheet. For example, risk-based capital is included as the denominator for how we view various risks (i.e. risk related to classified assets, portfolio concentrations, etc.). So effective capital contingency planning helps ensure that key risk indicators remain in good standing, and these metrics go beyond the regulatory thresholds for being considered well-capitalized.
What future strategies do you foresee being adopted for effective Stress Testing models?
I don’t know if the opportunity for enhancement from where we are today relates as much to the stress testing models themselves. In fact, I believe that the industry has reverted back to more simplicity in some respects. I see the opportunities to be more in regard to improving the interconnectivity of model applications and how they interact with each other. At the end of the day, what are the key components of what I’m trying to evaluate, and how do I process the necessary data and information as efficiently as possible to get a comprehensive result? As finance and risk managers, we’re often dealing with multiple options in a decision tree that have varying outcomes under varying scenarios. How do I evaluate each option under each scenario as efficiently as possible? This desire puts more emphasis on the system interaction between data, models, and visualization tools to help address the expediency in which complicated decisions can be understood more quickly.