Market volatility has made one thing clear for banks and credit risk teams: broad market signals are no longer enough. National indices and headline trends may suggest stability or recovery, but they often mask risks at the asset level, particularly deterioration in cash flow and equity.
Credit distress still comes down to two variables. Can a property support its debt service, (as measured by debt service coverage ratios), and how much equity remains to absorb losses, (reflected in loan-to-value ratios).
In today’s bifurcated market, those fundamentals are diverging sharply from what aggregate data implies. Two office buildings in the same metro can perform very differently based on asset quality, tenant mix, and post-pandemic demand, yet those distinctions are poorly reflected in broad indices.
As a result, banks are rethinking how they assess risk. “The question isn’t whether the market is improving or deteriorating in the abstract,” said Manus Clancy, head of Data Strategy at LightBox. “It’s where stress is actually forming inside portfolios.”
Why Broad Indices Are Losing Their Edge
National and regional property indices still provide useful context, but their limitations are more pronounced in uneven markets. Most are designed to smooth volatility across asset classes, geographies, and building types. That approach obscures meaningful differences when outcomes vary widely within the same sector.
In office markets, performance can diverge sharply based on building quality and location. Blended indices struggle to capture those differences, even as banks rely on them to update loan-to-value assumptions, set loss provisions, and assess refinancing risk. Directional signals alone are often insufficient for decisions that require precision.
This challenge is not new. Banks have long faced a portfolio visibility gap when risk signals are embedded in individual documents rather than observable across assets. As markets become more fragmented, that gap becomes harder to manage.
A $75M Office Loan and the Limits of Averages
“We often talk about risk in general terms, but it shows up deal by deal,” Clancy said. To illustrate the point, he described a hypothetical $75 million office loan originated in 2019, secured by a property valued at $125 million at origination. In this example, the loan remains current, cash flow has held up, and the maturity date is 12 months away.
Using broad market data, a lender might assume elevated risk. Office values have fallen sharply in many markets since the pandemic, particularly for lower-quality buildings. National or metro-level indices could suggest higher loan-to-value ratios and justify a more conservative risk rating or higher loss provision.
That conclusion depends on the asset itself. If the property is a Class C office with limited amenities and weak tenant demand, the index-based assumption may be appropriate. Equity may have eroded and refinancing risk may be real. But if the same hypothetical loan is secured by a highly amenitized Class A or creative office in a submarket that has attracted tenants and investment capital, the risk profile may look very different.
The distinction, Clancy said, is the kind of nuance that broad market data struggles to capture. “They smooth over the very differences that matter most when you’re trying to understand risk at the asset level,” he noted. They do not account for building quality, tenant durability, or how comparable assets are actually being valued today. For banks making decisions about risk ratings and capital allocation, those differences matter.
What Appraisal Data Reveals That Indices Miss
Appraisal data captures the inputs that directly shape credit risk. Debt service coverage ratios (DSCR) show whether an asset can support its loan, while loan-to-value ratios (LTV) indicate how much protection remains if conditions deteriorate. Appraisals also reflect assumptions about rent, vacancy, expenses, and capitalization rates that vary meaningfully by property.
When viewed across comparable assets, appraisal data reveals patterns that market-wide indices often miss. Banks can see where DSCRs are tightening, where values are holding, and where equity cushions are thinning. “By the time risk shows up in an index,” Clancy said, “it’s usually already visible in the underlying appraisals.”
Many banks are already working to unlock this visibility by modernizing how appraisal data is structured and analyzed. Across the industry, there has been growing focus on how appraisal extraction is expanding beyond basic fields, as well as on why trust and governance matter as much as automation when working with appraisal data at scale.
This evolution allows risk teams to evaluate loans in context, comparing them to recently appraised properties with similar characteristics. It supports more accurate risk ratings and better-informed decisions as loans approach maturity or refinancing.
Where Asset-Level Risk Starts to Affect Bank Portfolios
Many banks are managing portfolios where loans remain current but assumptions are under pressure. Maturities are approaching, refinancing conditions remain uncertain, and asset performance continues to diverge. In that environment, imprecise signals carry real costs.
Overestimating risk can lead to elevated loss provisions and tighter capital constraints. Underestimating it can leave banks exposed as conditions change. This tension is particularly acute in office and other transitional sectors, where recovery paths vary widely and capital decisions depend on asset-level clarity.
Banks that can identify stress at the property level are better positioned to respond early. That visibility supports clearer decision-making, more defensible risk assessments, and stronger alignment with regulators and internal stakeholders.
Turning Appraisal Insight into Portfolio Action
Identifying risk at the asset level is only valuable if banks can act on it consistently. As appraisal volumes grow, reviewing individual reports in isolation becomes less effective for portfolio-level decision-making. What risk teams increasingly need is a way to compare assumptions, cash flow metrics, and valuation outcomes across similar assets using data that reflects current market conditions.
LightBox Fundamentals supports this shift by enabling banks to systematically extract and analyze appraisal data across portfolios. Rather than relying on blended market benchmarks, teams can ground their assessments in recent, comparable appraisal inputs, particularly DSCR and LTV trends across similar assets.
What Asset-Level Risk Means for Banks
Market volatility has not eliminated risk, but it has changed how it shows up inside loan portfolios. Broad indices still provide useful context, but they are no longer sufficient for understanding where stress is forming.
For banks, the most meaningful signals increasingly come from the details: how cash flow is trending, how much equity remains, and how individual assets compare to similar properties appraised under current conditions. “Institutions that can surface and interpret those signals early will be better positioned to manage risk through the next phase of the cycle, with fewer surprises and greater confidence in their decisions,” Clancy said.
For a closer look at how asset-level appraisal insights can improve CRE risk assessment, book a demo of LightBox Fundamentals.
