Abstract for: Stress-Testing Banks under Deep Uncertainty

Years of turmoil in the banking sector have revealed the need to assess bank performance under deep uncertainty and identify vulnerabilities to different types of risks. Banks are not the safe houses of old. Today, banks are highly uncertain dynamically complex systems that are permanently at risk due to internal and external stresses and uncertainties. Although external uncertainties and stresses cannot be controlled, internal design and policies can, and hence, offer opportunities for robust redesign. This paper illustrates a multi-model System Dynamics approach towards financial stress testing in view of making banks more robust, i.e. performing more appropriately in all plausible futures, especially in the most stressful futures. Various System Dynamics models are used to represent the core operation of a bank. This set of models is constantly attacked by all sorts of (combinations of) risks and shocks in order to generate insights into all sorts of plausible bank system behaviour under stress, identify the causes of undesirable dynamics, vulnerabilities and levers. Using these insights, adaptive policies are designed, and further improved under deep uncertainty using robust optimization. Finally their robustness is tested and compared with other promising policies