An affordable housing finance company needed a consistent and defensible way to assess property marketability for lending decisions. While location and contextual property data existed, insights were fragmented, one-off, and difficult to embed into credit workflows. Underwriting teams relied heavily on subjective judgment, while risk and audit stakeholders lacked a clear, governed basis to review decisions at scale.
Property-linked lending decisions often hinge on resale liquidity, rental demand, and location quality. The challenge was to bring structure to these judgments without introducing brittle signals or inflating false positives. The institution needed a stable, explainable score that underwriting teams could stand behind and audit teams could examine with confidence.
Dhurin designed a property marketability scorecard using structured location intelligence, neighborhood demand indicators, amenity proximity measures, and market liquidity proxies influencing resale and rental outcomes. The framework created a reusable property intelligence layer, standardizing property-level data for underwriting and portfolio review. Co-designed with risk and credit teams, the scorecard emphasized conceptual soundness, data integrity, stability, and governed overrides. Signals were deployed through secure APIs to enable workflow adoption and internal ownership.
The firm gained an auditable intelligence layer that reduced subjectivity in lending decisions and improved cross-team adoption. Property intelligence became dependable in production, strengthening confidence across underwriting, portfolio review, and audit. The scorecard did not replace judgment. It reduced the cost of making the wrong one.
