After the delivery of Fundamental Review of the Trading Book on April 16, 2015, CCFA Risk Study group held the fourth study session. The topic is Enterprise Wide Stress Testing (EWST) on August 12, 2015. It was an honour to invite three experienced practitioners in the field of stress testing to lead the round table discussion. They are: Xiaobo Wang, Director in Liquidity Management at Scotiabank, Jeff Xue, Senior Director from CIBC and Beizhen Lei, Senior Manager of BMO Model Risk Validation. Yicent Chen, Model Risk Specialist from BMO was the facilitator. Other practitioners from leading Canadian financial institutions also joined the discussion and exchanged their views on the industry practice.
The discussion started from a high-level overview of the stress testing practice, including the objectives, approaches and components. Stress testing is a key risk and business management tool to identify and quantify key risks and assess capital adequacy during stressed periods. There are two approaches commonly used for stress testing: A top down approach starts with a systematic adverse scenario defined by the regulator and assesses the impact of such scenario on bank’s financial statements. This approach enables the regulator to assess impacts across different banks under adverse scenario. On the other hand, a reversed approach starts with defining a severely stressed outcome of the bank and then identifies the scenarios that would cause such severe loss. This enables a bank to tailor the stress testing practice to its unique business exposures. Components of stress testing include risk components (credit risk, counterparty credit risk and market risk) as well as stress scenarios (US recession, Emerging Markets, crude oil, etc.).
Then the discussion leads to a closer look on the methodology of corporate credit stress testing, especially the methodology of Probability of Default (PD) stress testing. Stress testing models are built with internal or external historical rating and default data. The conditional transaction matrix approach is commonly used for PD stress testing. Under this approach, first transition matrices are constructed with chosen horizon based on historical data. Then a summary statistic, such as downgrade and default probability (DDP) is constructed to measure the changes in the transitions. After that an econometric model is developed to relate the summary statistic to relevant macroeconomic/financial variables. Finally a stress transition matrix is derived corresponding to the model predicted DDP for a macroeconomic scenario.
The discussion concludes with some cases studies in actual stress testing practice of the banks. It is pointed out that stress testing should be viewed as a system instead of individual components/models. By the end of the day, stress testing seeks to answer the question of financial statements projection under adverse scenarios. Knowledge of business, accounting, strategic planning as well as risk management should be integrated for a meaningful stress testing practice. Stress scenario could potentially affect both asset and liability side on the balance sheet. Output analysis is valuable in the aspect of assessing out-of-sample model performance as well as soundness of model methodology.
The participants in the discussion also exchanged opinions on data collection, modelling methodology and implementation of stress testing. Topic for next study session will be operational risk.