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In this webinar, Irina Korablev, Senior Director and Deniz Tudor, Director will discuss various tools that can capture economic, loan-level, and cohort-level data across several asset classes, which can be used for forecasting credit losses and benchmarking internal models.

Many financial institutions are faced with the challenge of effectively developing, benchmarking, and validating CECL compliant models as a result of incomplete data.

In this webinar, our experts Irina Korablev and Deniz Tudor discuss various tools that can capture loan-level data across several asset classes, which can be used for forecasting credit losses and benchmarking internal models. Webinar highlights:

  • Modeling the relationship between macro variables and credit risk
  • Estimating life-time losses using reasonable and supportable forecasts
  • Benchmarking and improving quantitative risk measurement accuracy
  • Generating more realistic cash flows and impairment and provisioning calculations

Related Insights

Moody's Analytics Webinar: U.S. Consumer Credit Outlook

Join Moody’s Analytics Scott Hoyt and Deniz Tudor, as they discuss the current and anticipated trends in household credit conditions based on data from Equifax.

February 27, 2019 WebPage Scott Hoyt, Dr. Deniz Tudor

Webinar: CECL for Consumer Lending Portfolios - A Checklist

As internal model development and use of vendor models for CECL submission are fast in progress for those submitting by January 2020, our analysts will review a checklist that will help you organize CECL project plans.

November 13, 2018 WebPage Dr. Deniz TudorDavid Fieldhouse
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CECL for Consumer Lending Portfolios - Checklist

As internal model development and use of vendor models for CECL submission are fast in progress for those submitting by January 2020, our analystsreview a checklist that will help you organize CECL project plans.

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August 2018 U.S. Middle Market Risk Report

Private firm default rates have declined steadily during the past five years. At 1.4%, the rolling 12-month default rate is down 74% from its September 2009 peak of 5.2%. This trend has been driven primarily by a decline in the charge-off rate, now at its lowest level in ten years. In addition, the percentage of borrowers in non-accrual status has decreased 56% since September 2009. The number of borrowers rated “Substandard” has seen a steady increase since the first quarter of 2016, above pre-crisis levels, reflecting banks' cautious lending practices.

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CreditForecast.com: U.S. Consumer Credit Outlook

Join Moody’s Analytics Scott Hoyt and Deniz Tudor, as they discuss the current and anticipated trends in household credit conditions based on data from Equifax and forecasts from Moody's Analytics

August 15, 2018 WebPage Scott Hoyt, Dr. Deniz Tudor
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CreditForecast.com: U.S. Consumer Credit Outlook

Moody's Analytics subject matter experts Scott Hoyt and Deniz Tudor discuss the current and anticipated trends in household credit conditions based on data from Equifax and forecasts from Moody's Analytics.

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CreditForecast.com: U.S. Consumer Credit Outlook

Moody’s Analytics subject matter experts Scott Hoyt and Deniz Tudor discuss the current and anticipated trends in household credit conditions based on data from Equifax and forecasts from Moody's Analytics.

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CECL for Consumer Credit Portfolios: Modeling Best Practices

In this webinar, our economists and consumer credit analyst will share insight on techniques and best practices for modeling allowances for CECL.

August 02, 2018 WebPage Dr. Cristian deRitisDr. Deniz Tudor
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CECL for Consumer Credit Portfolios: Modeling Best Practices

In this webinar, our economists and consumer credit analyst share insight on techniques and best practices for modeling allowances for CECL.

August 2018 WebPage Moody's Analytics, David FieldhouseDr. Deniz Tudor

CECL Impact Analysis for Consumer Lending Portfolios

Through case studies of mortgage and auto portfolios, our experts explore the potential impact of CECL on industry wide reserves and factors that will affect results at the institution level.

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