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Moody’s Analytics ALLL Cloud is a solution designed for community banks and credit unions to facilitate those institutions’ efforts to address CECL requirements. This solution is simple to implement, and easy to operate. It automates data collection, and improves loan-level data management, providing multiple methodologies and relevant economic and peer data to allow the client to perform a CECL analysis.
Automate data collection, support future loss forecasting
- Automate data collection through using the API from multiple sources including client imports, regulatory data and economic data to support benchmarking and economic analysis.
- Create custom segmentation, loan life estimation and multiple methodologies to support historical loss calculation and future loss forecasting for CECL.
- Support future loss forecasting using economic conditions outlook data.
- Benefit from comprehensive analysis presentation with interactive tables, graphs and charts.
- Support regulatory compliance and internal controls by reporting, disclosures, and providing auditing trails.
Robust credit loss management framework
- Automatically upload loan data and charge-off data using the API and automatically compile charge off data once imported.
- Create vintage analysis for loans originated in the same periods in order to estimate the average life of loans and historical loss.
- Perform historical loss analysis, differentiated by loan segments, and supported by FDIC loan segment loss data and loan level charge off data.
- Leverage custom segmentation to separate loans with different risk characteristics, and loan level loss to support granular loss analysis.
- Benefit from our end-to-end solution from data collection, loan segmentation, loan life estimation, environmental factor setup, CECL calculation, to reporting.
Allowance for Loan and Lease Losses (ALLL)
Calculate fast, accurate reserves for loan and lease losses with our cloud-based ALLL solution.
Current Expected Credit Loss Model (CECL)
Moody’s Analytics provides tools for the most crucial aspects of the expected loss impairment model, with robust solutions to aggregate data, calculate expected credit losses, and derive and report provisions.