Moody’s Analytics helps financial institutions develop a collaborative, auditable, repeatable, and transparent stress testing program to meet regulatory expectations, inform the bank’s risk appetite framework, and improve strategic business decisions.
Stress testing and capital planning are increasingly linked to many risk management processes that require coordination across risk, treasury, and financial planning and analysis functions.
Regulatory stress tests like CCAR, DFAST, ECB/EBA/SSM, and PRA have pushed banks toward the implementation of robust stress testing frameworks.
A successful stress testing program demands flawless integration and execution of numerous tasks, including program governance, process and results validation, documentation, data quality management, economic scenario development, expected loss modeling, forecasting, and reporting. Establishing an integrated approach to the use of stress testing results requires infrastructure, analytics, data, clear governance, and active participation of all stakeholders across divisions, business units and geographies.
Keep pace with evolving regulatory stress testing expectations
Moody’s Analytics stress testing suite supports governance and auditability, as well as model risk management, allowing firms to meet the growing demands of the regulatory stress testing process. Transparency with configurable business workflows enables monitoring of disparate business activities for coordinated regulatory stress testing submissions. Our software also facilitates stress testing model development, testing, validation, and implementation, resulting in an enhanced framework to monitor and govern the models used within the firm. Lastly, our centralized data warehouse cross-validates data sources within the firm to ensure data integrity and support daily business functions.
Enhance your stress testing capabilities
Moody’s Analytics supports financial institutions in developing next-generation stress testing capabilities that enhance risk management. Our solutions support bank-wide strategies, enabling you to design and implement integrated stress testing frameworks that can be used across regulatory boundaries. They also support macroeconomic scenario design and implementation, customized to the unique strategies and risks of your portfolio. Enjoy improved coordination and feedback from model development that is integrated across asset classes and lines of business. Moody’s Analytics models can be relied upon as the industry standard to be used as challenger models.
Douglas W. Dwyer leads Corporate Credit Research in Predictive Analytics. This group produces credit risk metrics of small businesses, medium sized enterprises, large corporations, financial institutions, and sovereigns worldwide. The group’s models are used by banks, asset managers, insurance companies, accounting firms and corporations to measure name specific credit risk for a wide variety of purposes. We measure credit risk using information drawn from financial statements, regulatory filings, security prices, derivative contracts, behavioral and payment information. For each asset class, the methodology is developed based on the available information for each obligor. <br><br> Current projects include developing a climate adjusted probability of default and incorporating ESG factors into credit analytics. We also are developing an approach to produces comparable PDs across asset classes that opportunistically uses whatever information is available. <br><br> Prior to working at Moody’s Analytics, Dr. Dwyer was a Principal at William M. Mercer, Inc., in their Human Capital Strategy practice. Dr. Dwyer earned a Ph.D. in Economics at Columbia University and a B.A. in Economics from Oberlin College.
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