Now that most community banks have eight to ten quarters of CECL experience under their belts, many are still grappling with foundational issues such as overreliance on qualitative factors, lack of responsiveness to risk rating changes, and opaque “black box” models that defy intuitive understanding.

But beyond these basics lie deeper, more nuanced challenges that are rarely discussed. Unfortunately, many commonly used software-as-a-service (SaaS) solutions especially those built on “one-size-fits-all” frameworks struggle to address these complexities. Here are several underappreciated issues that deserve greater attention:

Construction Loans with Built-In Permanent Financing

Many banks originate construction loans with short maturities aligned to development timelines typically 18 to 36 months. These loans are often expected to be “taken out” by permanent financing, either from the same bank or another institution, with maturities ranging from 10 to 30 years.

However, some banks structure these loans as a single instrument. For example, a loan originated in 2025 with a maturity in 2053 might include:

• An initial 3-year interest-only construction phase
• A subsequent 25-year amortizing phase, reclassified as CRE once the project is stabilized

From a CECL perspective, this can be problematic. Without proper context, such loans may appear to be long-dated construction loans, leading to inflated reserve estimates. If your CECL model lacks the flexibility to distinguish between these phases, you risk significant over-reserving.

Unfunded Commitments for Construction Loans

Unlike other unused commitments (e.g., C&I lines or HELOCs), construction loan commitments typically have near-100% utilization rates. This creates a CECL modeling challenge:

• The unfunded portion often has a longer expected life than the funded balance
• The unfunded amount is expected to grow over time as the project progresses
• GAAP requires separate ACLs for funded and unfunded portions, housed in different GL accounts

If not modeled carefully, this can lead to confusion and misaligned reserves.

Cross-Collateralization Complexities

Loan structures can be intricate:

• A single loan may be backed by multiple collateral assets
• One asset may support multiple loans
• Multiple assets may support multiple loans with varying liquidation preferences

Most SaaS models oversimplify these relationships, often relying on a combined loan-to-value (LTV) ratio if it’s even accurate. These ratios frequently depend on manual inputs, which are prone to error. Robust CECL models should be able to parse these relationships algorithmically, reducing human error and improving reserve accuracy.

Government Guarantees (e.g., SBA Loans)

Many banks use shorthand adjustments for SBA loans, which can be risky. Loss rates on SBA loans can be high, and simplistic modeling may obscure true risk.

A waterfall analysis is strongly recommended, tailored to the specific guarantee structure:

• SBA 7(a) loans have a different loss-sharing profile than
• SBA 504 loans, which follow a “50-40-10” structure

Does your model account for these nuances? If not, your ACLs may be misaligned.

Loan Participations (Inbound and Outbound)

Modeling expected losses for participations requires precision:

• Ensure LTVs aren’t understated or collateral overstated by misapplying appraised values
• Understand which portions of the loan your bank owns
• Account for lien position relative to other participants

Again, waterfall modeling is essential to capture the full risk ecosystem across multiple lenders.

From CECL 101 to CECL 401

These challenges reflect a “301” or “401” level of CECL maturity, while many banks are still navigating “101.” Yet those with the foresight to anticipate these complexities—and proactively address them are far more likely to make smarter, long-term decisions. For many, that means seriously considering a transition to a more advanced and flexible CECL model sooner rather than later. Waiting until problems surface may lead to costly missteps, while early adoption of a better-suited model can position your institution for greater accuracy, defensibility, and strategic clarity.

Other Resources: 

Watch our latest video: Video Library
Read our latest insights : Intel Blog
Follow us on LinkedIn for expert analysis & industry updates: LinkedIn