Four focus areas for successful stress testing
Increased complexity, expected frequency and firm-wide nature of scenarios present new challenges
By David Rogers, Global Risk, SAS
Stress testing is not new to the risk world. For a number of years, stress testing has helped analytical specialists quantify various aspects of potential loss. What is new is the increased complexity, expected frequency and firm-wide nature of scenarios that are required to be stress tested.
This change in scope has introduced several challenges. On the technology side, the challenges are mainly due to the scale and complexity of the underlying data required to build out the scenarios and stress tests. This is stretching the capabilities of existing computing resources to deliver timely responses.
To deliver a successful stress testing program, the key areas that should be considered include:
- Efficiency: Integration of existing risk models and data hierarchies into a streamlined data infrastructure for firm-wide stress testing. Data, computations, reporting – must all be part of a unified platform.
- Performance: The efficient aggregation of results for all major risk models across the organization with the ability to run complex, forward looking stress tests with multiple parameters.
- Enterprise View: Views of economic capital and pro forma financials at the enterprise level with a view of market, credit and liquidity risk.
- Transparency: The ability to understand and document model assumptions, design and structure so they are readily apparent to management and regulators with the elimination of the “Black Box” characteristic of some models.
Compliance: The capability to address major regulatory stress testing issues as they evolve with the ability to integrate them into the risk decision making process.
To explore the challenges involved around creating a comprehensive stress testing program and how the advances in technology can help firms meet the evolving requirements, listen to the on-demand version of “Stress testing: A fresh point of view.” Industry expert Rodney Nelsestuen and Jeff Hasmann, SAS, discuss how banks are using analytics to clarify required risk parameters and guidelines; create consistent and repeatable processes; and handle numerous valuation methods, disparate data and stress testing models.