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Case Studies

Concept demonstrations of behavior-first scoring in operator scenarios.

Each case below is an illustrative example designed to communicate how StabilityLogic's platform operates against realistic operator problems. These are concept demonstrations — not actual customer outcomes — presented with the methodology behind every modeled number.

All numbers on this page are modeled against synthetic or benchmark data. No claim of live customer results is being made. When real pilot outcomes are available, we will publish them separately with named partner consent.
Illustrative ExampleCase 01
Multifamily operator · 500-unit Class-B portfolio

Approving more qualified renters without raising default risk.

The problem

A Sun Belt multifamily operator running credit-score-only screening was rejecting a growing share of qualified applicants — including many who had rebuilt from documented hardship — while missing early delinquency signals on approved leases.

The approach

In a modeled scenario, StabilityLogic replaced the credit-only decision layer with the Household Stability Index™. Applicants completed intake with income verification, self-reported rent history, and consented data pulls. Landlord staff reviewed HSI recommendations alongside credit reports.

Before · credit-only screening
Approval rate58%
12-mo default rate6.4%
Adverse-action defensibilityAd hoc
Fair-housing risk exposureElevated
After · HSI behavior-first
Approval rate
71%
+13 pts
12-mo default rate
5.9%
−0.5 pts
Adverse-action defensibility
FCRA-style report
Auditable
Fair-housing risk exposure
Documented + monitored
Reduced
Modeled outcome

In this concept demonstration, HSI approves a higher percentage of applicants who would have been rejected under credit-only screening, while marginally lowering 12-month default risk and adding an audit-ready adverse-action trail on every declined applicant.

Methodology & disclaimer

Modeled against a synthetic applicant pool derived from published multifamily industry benchmarks and StabilityLogic's internal backtest. Not a real customer outcome.

Illustrative ExampleCase 02
Housing-assistance provider · Regional non-profit

Placing recovering renters into permanent housing faster.

The problem

A regional housing-assistance provider works with clients transitioning out of transitional housing, family placement, and subsidized programs. Traditional credit-based screening systematically penalized these clients regardless of demonstrated rent-payment recovery.

The approach

StabilityLogic's Recovery Applicant Framework — a behavior-first scoring path that weights verified payment recovery after documented hardship — was piloted as a concept against a modeled cohort of 200 recovering renters. Housing type was not used as a scoring input.

Before · credit-only screening
Placement rate34%
Time to placement88 days
Applicant re-application rate42%
Landlord acceptance rate22%
After · HSI behavior-first
Placement rate
61%
+27 pts
Time to placement
42 days
−46 days
Applicant re-application rate
17%
−25 pts
Landlord acceptance rate
48%
+26 pts
Modeled outcome

In this concept demonstration, behavior-first scoring nearly doubles the placement rate for recovering renters while cutting time-to-placement by more than half. Landlords receive a defensible score and audit trail.

Methodology & disclaimer

Modeled against a synthetic applicant cohort informed by published housing-assistance benchmarks and StabilityLogic's Recovery Applicant Framework methodology. Not a real customer outcome.

Concept DemonstrationCase 03
Rental risk insurer · Deposit-replacement underwriter

Sharper underwriting signal beyond credit tradelines.

The problem

A deposit-replacement insurer underwriting renter risk was over-relying on credit-tradeline features and missing behavioral recovery patterns — resulting in mispriced policies on the tails of the distribution.

The approach

In a concept model, HSI category-level features (payment consistency, income adequacy, recovery signals) were joined to the insurer's existing credit-based risk model as additional predictors. No protected-class variables were used.

Before · credit-only screening
Loss ratio71%
Adverse-selection signalWeak
ExplainabilityBlack-box score
Fair-housing audit postureReactive
After · HSI behavior-first
Loss ratio
63%
−8 pts
Adverse-selection signal
Behaviorally informed
Improved
Explainability
Reason codes + audit trail
Defensible
Fair-housing audit posture
Documented + versioned
Proactive
Modeled outcome

In this concept model, adding HSI behavioral features to an existing credit-based underwriting model reduces the modeled loss ratio while producing per-policy reason codes suitable for regulatory review.

Methodology & disclaimer

Concept-level analysis, not a live insurance deployment. Modeled against synthetic policy-level data reflecting published deposit-replacement loss patterns.

Want to see a case study run against your portfolio?

Enterprise pilot partners receive a backtest report modeled on their own historical applicant data — under NDA, with a signed DPA, in about 30 days.

Request a Pilot