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Moody’s Analytics C&I loss rate model provides a simple and effective solution to estimating CECL allowance for commercial and industrial portfolios. Combined with reasonable and supportable forecasts, the C&I loss rate model allows institutions to use readily available loan characteristics to estimate lifetime credit losses. The simplicity of the model lies in the required input data and output statistic, the lifetime loss rate. Extensive in-sample and out-of-sample back tests, and sensitivity and stability analyses demonstrate that the model captures key risk drivers and produces intuitive results.

Address your portfolio with a simple CECL methodology

  • Forecast lifetime loss rates at the pool-level by loan age relative to contractual term, credit spread, and loan size at origination.
  • Differentiate relative credit risk by regulatory rating, loan type, and industry.
  • Capture the aggregated impact of macroeconomic variables in future quarters after the reporting date on lifetime loan losses.
  • Customize reasonable and supportable forecasts, up to five years.

Gain confidence with a predictive and fully documented model

  • Uses data based on Moody’s Analytics award-winning Data Alliance, covering more than 700,000 unique loans and the most recent business cycle.
  • Lifetime expected credit losses based on  loan and portfolio characteristics and macroeconomic forecasts.
  • Results available under Moody’s Analytics baseline, consensus, and eight alternative scenarios.
  • Documentation on model methodology and validation.

    C&I Loss Rate Model is part of Moody’s Analytics Credit Loss and Impairment Analysis Suite, which improves credit loss estimation analysis and calculations. Its data integrity, analytics, and regulatory reporting solutions provide a modular, flexible, and comprehensive impairment solution that facilitates a firm’s efforts to calculate, manage, and report expected credit losses.

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Moody's Analytics | CECL

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.