Understanding Today’s Real Estate Landscape
Since COVID‑19, housing prices have surged while interest rates have climbed—creating a real estate environment far different from the one that fueled the 2008–2009 housing crisis. Unlike that period, when many homeowners simply walked away from homes that were underwater, today’s borrowers generally possess significant equity due to inflation and elevated housing demand.
Many owners now have tens or even hundreds of thousands of dollars in instant equity. These dynamics have contributed to a reduced mortgage reserve requirement in the Allowance for Credit Loss (ACL) calculation. A lower reserve may not be in the best interest of the credit union.
Why Regulators Are Paying Closer Attention
Over the past year, financial examiners have intensified their scrutiny of ACL calculations, focusing particularly on documentation and support for forecasts. Incomplete or minimal documentation often triggers closer review.
My personal approach to Current Expected Credit Loss (CECL) modeling has always leaned toward conservatism. I reserve for the unexpected—using the environmental factor to cover unanticipated events such as the sudden loss of a long‑time borrower whose property later requires costly rehabilitation.
(As a side note, it’s still puzzling why some heirs simply hand over keys to a credit union and leave thousands of dollars of equity unclaimed.)
Market Risk Factors and the Potential for Change
While the current market remains strong, risk always exists. A future downturn or a wave of sell‑offs by speculative investors—especially those in short‑term Airbnb markets—could introduce disruption almost overnight.
Under ASC 326, credit unions must use relevant data and reasonable forecasts to estimate credit losses. This includes:
- Past events
- Current conditions
- Reasonable and supportable forecasts
- Borrower‑specific and portfolio characteristics
So where can credit unions find the data they need to build sound estimates?
Key Resources for ACL and CECL Modeling
✅ NCUA Simplified CECL Tool
For credit unions with little or no historical mortgage loss data, the NCUA Simplified CECL Tool offers an accessible, peer‑based approach. It provides benchmark data across various credit union asset sizes to help estimate expected losses. Visit the NCUA and download the tool that is available by clicking the below link.
✅ Federal Housing Finance Agency (FHFA)
The FHFA provides detailed home‑price data from national to county levels, enabling deeper insight into local housing trends.
The FHFA County Map visually illustrates annual home‑price changes across the U.S.:
2021–2023: widespread price appreciation (over 2%)
2024: mild declines emerging in select counties
For a detailed analysis, check out the Housing Price Index Reports—specifically pages 6–8 of the 2025 Q4 report for relevant charts and figures.
✅ Mortgage Bankers Association (MBA)
The MBA publishes data and analysis that can support credit loss assumptions, such as delinquency trends across FHA, VA, and Conventional loan types. The below link is an article showing delinquency trends by various loan types (FHA, VA, Conventional).
✅ Federal Reserve Economic Data (FRED)
The FRED database tracks single‑family residential mortgage charge‑off rates across the last 35 years—an invaluable reference for understanding long‑term risk patterns. Click here to access this chart.
Additional Best Practices
Segment High LTV Loans:
If a material portion of your mortgage portfolio exceeds 80% loan‑to‑value, consider pooling those loans into a separate segment with adjusted risk parameters.
Use Real‑Time Valuation Data:
Tools like Zillow or Realtor.com provide quick value estimates for Individually Evaluated Loans (IELs), helping refine reserves for potential losses.
Expect the Unexpected:
Charge‑off rates have remained historically low for over a decade, but history suggests that downturns—especially recessions—can cause sharp increases. Strategic forecasting should always include that perspective.
Conclusion
Calculating a credit union’s Allowance for Credit Loss can be complex, with considerable subjectivity in the modeling process. Examiners increasingly demand more documentation to support environmental factor calculations but often provide limited guidance on how to do so.
There’s no one‑size‑fits‑all formula—each credit union’s portfolio, lending strategy, and risk appetite are unique. However, with the right data sources and sound methodology, your estimates can be both defensible and forward‑looking.
For questions or customized CECL support, feel free to reach out at don@mycu360.com.