Company: KEY-PI
Filing Date: 2025-02-21
Form Type: 10-K
Source: 0000091576-25-000038
Chunk: 38

Company: KEYCORP /NEW/
Filing Date: 2025-02-21
Form: 10-K
Item: Item 8
Chunk 38
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 ALLL represents management’s current estimate of lifetime credit losses inherent in the loan portfolio at the balance sheet date. Management estimates the ALLL using relevant available information, from internal and external sources, relating to past events, current economic conditions, idiosyncratic risk factors and reasonable and supportable forecasts. The ALLL is the sum of (i) asset specific / individual loan reserves; (ii) quantitative (formulaic or pooled) reserves; and (iii) qualitative (judgmental) reserves. Management estimates the quantitative reserves using probability of default / loss given default / exposure at default models (“loss forecasting models”), as well as other estimation methods for smaller loan portfolios. The ALLL also considers qualitative factors related to idiosyncratic risk factors, changes in current economic conditions that may not be reflected in quantitatively derived results, and other relevant factors to reflect management’s best estimate of current expected credit losses. Auditing management’s ALLL was complex due to the loss forecasting models used to compute the quantitative reserve and involves a high degree of subjectivity and judgment in evaluating management’s determination of the economic forecast and qualitative factor adjustments to the ALLL described above. How We Addressed the Matter in Our AuditWe obtained an understanding, evaluated the design and tested the operating effectiveness of controls over KeyCorp’s ALLL process, including controls over the appropriateness of the ALLL methodology, operation and monitoring of loss forecasting models, the reliability and accuracy of data used in developing the ALLL estimate, and management’s review and approval process over the economic forecast, qualitative adjustments and overall ALLL results. With the assistance of EY specialists, we tested management’s loss forecasting models including evaluating the conceptual soundness of model methodology, assessing model performance and governance, testing key modeling assumptions and independently recalculating model output. We also verified the underlying economic forecast data used to estimate the quantitative reserve was complete and accurate.To test the qualitative factor adjustments, among other procedures, we assessed management’s methodology and considered whether relevant risks were reflected in the models and whether adjustments to the model output were appropriate. We tested the completeness, accuracy and relevance of the underlying data used to estimate the qualitative adjustments. We evaluated whether qualitative adjustments were reasonable based on changes in economic conditions, the loan portfolio, and management’s policies and procedures. For example, we evaluated the reasonableness of qualitative adjustments (or lack thereof) for concentrations of credit by independently comparing to loan portfolio information. We also assessed whether qualitative adjustments were consistent with publicly available information (e.g., macroeconomic data