CECL Advisory Capabilities
Moody’s Analytics advisory and implementation teams work with organizations globally to strengthen their credit risk measurement frameworks. Our services include assessment, enhancement, and implementation of allowance estimation frameworks to comply with the Current Expected Credit Loss (CECL) standard.
Institutions are seeking ways to improve overall data quality, and speed and standardization of processes. They are modernizing their infrastructure and deriving smart analytics for decision making. We work with clients of all sizes to design model methodologies for CECL, develop custom credit risk models, and carry out quantitative impact analysis.
Plan and Implement a Framework to Suit Your Needs
Our advisory services can help you define the gaps between your current process and what you will need to comply for CECL. We work with clients to develop detailed timelines and road maps for implementation, and documentation support for strong governance controls. We address all aspects of CECL compliance – gap analysis, economic forecasting, model methodology, compliance, and validation, implementation, and transition support – for a successful transition to the new allowance estimation framework.
Address Accounting Standards While Improving Risk Management Practices
Leverage the broad knowledge of Moody’s Analytics credit risk professionals and economists who have extensive experience in helping clients comply with new accounting standards. We can help you implement new processes that address the changes necessary for CECL, and help enhance your existing management approaches for data, modeling, and scenario analysis.
Benefit from an Integrated Solution
The Moody’s Analytics CECL data capabilities are part of our Credit Loss and Impairment Analysis Suite, which includes credit risk models and data, economic forecasts, advisory services, and infrastructure solutions that assist with the implemention of expected credit loss and analysis. This modular, flexible, and comprehensive solution can address the many challenges of implementing impairment calculations.
