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Registration is now open for our 40th Annual Conference! 

About Us
Data-Driven Solutions
Model Validation & MRM
Asset/Liability Management

But Are You REALLY Ready for CECL?

On-Demand Webinar (March 30, 2022)

Michael Guglielmo

Managing Director

Darling Consulting Group

With over 30 years of experience in strategic risk management, Mike Guglielmo has provided technical and strategic consulting to a diverse group of financial institutions. Mike is also a frequent author and top-rated speaker on a variety of financial and operational risk management topics and serves as Finance Council Chairman and board member for the Financial Managers Society and as a faculty member of the Association for Management Information in Financial Services (AMIfs) Institute.

During his tenure at DCG, Mike has served in various capacities, including director of financial analytics. In addition, he is a technical resource for the ongoing development of many of DCG's quantitative and strategic risk management products and services. Prior to joining DCG, Mike managed the ALCO and strategic planning processes for a regional bank in the northeast. Mike is a graduate of Fairfield University with a degree in economics.

Years of research and planning have brought us to the precipice of CECL: arguably the most significant change to financial institution accounting in decades. Are you confident you can depend on your CECL model starting in January 2023?

Don't leave it to chance. Join Darling Consulting Group Managing Director Mike Guglielmo on March 29, 2022 at 2:00 PM ET to learn more about what most accountants and regulators expect prior to CECL model implementation. This timely session will help your institution answer critical questions:

  • Are your methodology and segmentation justifiable?

  • Is your data accurate, reliable, and representative?

  • Are your key assumptions and qualitative factor adjustments defensible?

  • Are your ongoing performance testing, model documentation, and ACL governance sufficiently robust and aligned with regulatory model risk management expectations?

  • Does your model have limitations?

  • Are there opportunities to enhance your model's accuracy, reliability, or strategic utility?

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