This Wilary Winn webinar, originally presented in July 2025 to Baker Tilly staff, offers a detailed and practical overview of the top-down process used for the validation of both ALM and CECL models.
This Wilary Winn white paper examines duration analysis in ALM and its significance for institutions in strategically managing interest rate risk, optimizing capital allocation, and enhancing profitability.
This Wilary Winn-led training for the FDIC provides insights on CECL as well as liquidity risk management in a regulatory context, compares CECL models, and gives actionable guidance.
Key Takeaway The immediate recognition of the potential credit losses from COVID by the largest banks are a good illustration of how CECL should work. Wilary Winn offers CECL estimates…
Key Takeaway Wilary Winn provides robust life-of-loan credit loss estimates that quantify capital at risk under various macroeconomic scenarios. How Can We Help You? Released April 2020 Introduction The Community…
Key Takeaway Our CECL Resource Center includes information on implementing the new standard, including the advantages and disadvantages of the modeling techniques that can be used and the data you…
Released June, 2017, this white paper is the third in a three-part series that presents the business benefits resulting from incorporating lifetime credit losses required under the CECL accounting standard into analyses designed to optimize the risk/return tradeoffs for a financial institution.
This May 2017 presentation provides practical ways to estimate credit losses in full accordance with the CECL standard and touches on the advantages and disadvantages of the various models that can be utilized and reasons why we utilize discounted cash flow models.
Summary The Credit Union National Association (CUNA) interviewed Douglas Winn for the May 2017 issue of the Credit Union Magazine, highlighting the Current Expected Credit Loss (CECL) model. The focus…
Released January 2017, this white paper is a part of Wilary Winn’s series of white papers regarding the Current Expected Credit Loss (CECL) Model and highlights best practices in collecting data for CECL.