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CECL Sensitivity Testing: From Forecast Shocks to Meaningful Reserve Insights

This webinar focuses on practical CECL sensitivity testing techniques to help financial institutions understand how their models respond to changing economic forecasts. Attendees will learn how to select meaningful forecast adjustments and clearly interpret the resulting impact on the ECL reserve for stronger audit and regulatory support.
Upcoming
DATE

Friday, July 10, 2026
11:00 am - 12:30 pm

INSTRUCTOR

Austin Dunkle

FORMAT

Webinar

$299.00 or 1 Token

Includes: Live Access, 30 Days OnDemand Playback, Presenter Materials and Handouts

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As financial institutions navigate the complexities of Current Expected Credit Loss (CECL), it is crucial to move beyond simply running the models and effectively test the model’s response to varying economic forecasts.

This session focuses on the practical techniques for designing and executing meaningful sensitivity tests. Furthermore, the webinar will emphasize how to develop a strong conceptual framework for understanding the expected relationships between your key model variables and their associated macroeconomic covariates.

We will provide a structured approach for selecting appropriate forecast adjustments (shocks). Attendees will leave with the ability to better interpret the resulting model impact on the Expected Credit Loss (ECL) reserve.

What You'll Learn

  • Decoding Variable Relationships:

Develop a strong conceptual framework for understanding the expected relationships between your key model variables (e.g., probability of default, loss given default) and their associated macroeconomic covariates (e.g., unemployment rate, GDP growth, housing prices).

  • Selecting Meaningful Adjustments:

Learn a structured approach to identifying and selecting appropriate forecast adjustments (shocks) that effectively test the model's response to various economic scenarios. We will discuss how to choose inputs that challenge the model's underlying assumptions.

  • Interpreting Model Impact:

Gain insight into how a selected forecast adjustment will translate into an impact on your final Expected Credit Loss (ECL) reserve, allowing you to better justify your CECL methodology to auditors and regulators.

Who Should Attend

This session is designed for credit risk, finance, and accounting professionals responsible for CECL modeling and allowance reporting. It is also valuable for risk managers, model validation teams, and leaders involved in regulatory and audit discussions.
Austin Dunkle

Instructor Bio

Austin has been providing quantitative analysis and financial risk consulting services within the financial industry for over ten years. He holds an undergraduate degree in Applied Mathematics and has obtained the prestigious Certificate in Quantitative Finance (CQF). His prior experience includes working as a Quantitative Researcher and Portfolio Manager for several publicly traded ETFs.


Austin is the Financial Risk and Regulatory Services Manager at ARCSys. In his
role, he is heavily focused on managing consulting projects and building even more rigorous quantitative analyses of client data to address complex regulatory and credit loss challenges related to CECL.


ARCSys is a consulting firm specializing in Allowance for Credit Loss software and CECL, started in 2009 with the sole purpose of building a solution for CECL and its challenges.

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