Recent reporting on the Baltimore foreclosure crisis has brought renewed attention to a critical vulnerability in DSCR lending, the reliance on valuations and projected income without sufficient, independent verification of a property’s true condition and market value.
In this case, literally hundreds of properties were allegedly purchased at distressed prices, that were encumbered with liens and deferred maintenance, then appraised and financed at dramatically inflated values. Renovations were claimed but never completed. Appraisals appeared to rely on questionable condition and dissimilar comparables. The result was phantom equity—leaving lenders, tenants, and entire neighborhoods exposed when loans inevitably failed.
While the scale of the situation is alarming, the takeaway for the broader industry is clear - fraud thrives when property-level insights and transparency is limited.
Where Traditional Valuation Review Falls Short
DSCR lending is not inherently risky. However, it does place greater emphasis on appraised value and rental assumptions—making it especially vulnerable to manipulation when:
● Property condition is misrepresented
● As-repaired” values are unsupported by comparable sales
● Comparables do not reflect the subject’s true quality
● Renovations exist on paper but not in reality
● Manual appraisal review alone often struggles to consistently detect these issues, especially at scale and on a national level.
“Seeing” the Property and the Comparables, Not Just the Appraisal
Restb.ai Lens helps close this gap by enabling lenders to move beyond static reports and into dynamic, property-specific insights. It analyzes millions of residential listings across the U.S., this allows lenders and reviewers to:
● Identify current and previous listings tied to the subject property and comparables
● Validate historical pricing and condition trends
● Detect valuation increases that are inconsistent with visible improvements
● Cross-check whether a property marketed as “renovated” ever actually appeared that way
● In fraud scenarios, historical listing data often tells the story!
Interior Photos: A Critical Signal in DSCR Risk
One of the most overlooked assets in valuation risk management is interior listing photography.
Restb.ai’s computer vision models analyze interior photos to objectively assess:
● Property condition and quality using the FNMA and Freddie Mac definitions
● Signs of deferred maintenance or disrepair
● Whether claimed renovations are cosmetic or substantive
In cases like Baltimore, where properties were financed as improved assets despite remaining in poor condition, interior photos provide crucial, visual evidence that can either support—or directly contradict—value conclusions.
Objective Computer Vision for Condition and Quality
Restb.ai models apply consistent and objective scores across every property, subject and comparables, eliminating inconsistencies that can arise from subjective interpretation.
This enables lenders to:
● Compare subject properties and appraiser-selected comparables on an apples-to-apples basis
● Identify misrepresented condition of the subject and comparables and confirm the condition using the original listing photos.
● Flag inflated valuations driven by inappropriate or mischaracterized comparables.
For DSCR lenders, where margins can be thin and unvalidated assumptions compound risk, this level of objectivity is essential.
Strengthening DSCR Lending Through Transparency
The Baltimore situation illustrates an important point, technology-enabled transparency is no longer optional.
As fraud schemes become more sophisticated, lenders need tools that independently verify what’s being financed - not just what’s being reported. By combining nationwide listing intelligence with objective computer vision analysis, Restb.ai empowers the industry to validate value, reduce fraud risk, and support sustainable lending practices.
What Lenders Can Do Today
To reduce DSCR fraud risk and strengthen valuation confidence, lenders can take immediate steps:
● Incorporate Restb.ai Lens to verify historical pricing, condition, and marketing claims.
● Leverage interior photo analysis to confirm appropriate condition and quality assumptions.
● Objectively validate comparables to ensure they truly reflect the subject property.
● Flag unsupported “as-repaired” values when visual evidence does not align.
● Use scalable, repeatable technology to apply consistent risk checks across every loan.
To schedule a meeting and learn more about Restb.ai Lens, please click here:
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