Expected Consumer Credit Losses (ECCL) Service
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Through econometric models based on Equifax industry performance data, Moody's Analytics can quickly deliver cumulative lifetime loss forecasts under the CECL standard using “reasonable and supportable” economic scenarios. Ideal for small consumer lending portfolios or as a benchmark for large consumer lending portfolios, we provide a dashboard plus documentation summarizing the results, assumptions and model methodology. Our service can help you effectively analyze your portfolio for all consumer credit product lines: Auto, Bankcard, Home Equity, First Mortgage, Consumer Finance, Retail and Student Loans.
Use trusted industry-based forecasts to assess your expected credit losses
- Lifetime expected credit losses based on client footprint and exposure.
- Quarterly updated dashboard with accompanying report.
- Output based on economic forecasts of consumer credit data from Equifax.
- Extensive historical data covering the most recent business cycle.
- A 30-year forecast horizon, with mean reversion in long-run.
- Results available under baseline, consensus, regulatory, or eight alternative scenarios.
- Documented methodology and scenario documentation.
- Access to economists and consumer credit analysts for interpretation of results.
Manage portfolio credit risk
- Obtain expected credit losses (ECL) by vintage, geography, score band, and term.
- Gain insight into specific risk factors, such as interest rate changes.
- Account for different discount rates, expected lifetime, loss given default (LGD).
- Better identify correlations between economic variables and credit risk.
- Evaluate results under multiple, defensible forecast scenarios.
- Reduce losses for easy consumption and comparison.
- Use a detailed report summarizing the results and methodology.
- Benefit from the help of our economists for interpretation of results.
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.