AIGR™ Real Estate
Governance ratings for AI shaping property and housing decisions.
AIGR™ Real Estate is designed for AI used in valuation, tenant screening, leasing, portfolio analytics and property operations—where data quality, fairness, explainability and human review can carry direct financial or housing consequences.
Tenant screening
Eligibility, risk ranking, recommendations and adverse-action support.
Automated valuation
AVMs, appraisal support, collateral analytics and price estimation.
Leasing + operations
Lead prioritization, maintenance triage, pricing and workflow automation.
Portfolio analytics
Acquisition scoring, risk segmentation and asset-management decisions.
Evidence follows the decisions that matter.
The framework emphasizes controls that can demonstrate lawful, explainable and monitored operation across the property lifecycle.
Fair-housing impact testing and protected-class risk controls.
Valuation integrity, backtesting and error-bound monitoring.
Training-data provenance, permissible use and retention.
Human review, appeal, override and adverse-action governance.
Supplier data and model-provider accountability.
Market drift, lifecycle monitoring and material-change review.
| Control | Requirement | Artifact | Owner | State |
|---|---|---|---|---|
| FH-03 | Protected-class impact review | Fair-housing testing report | Compliance | Validated |
| VI-02 | Valuation error backtesting | Quarterly AVM validation | Model Risk | Validated |
| DP-07 | Retention and deletion | Not supplied | Privacy | Blocker |
| HR-04 | Applicant appeal workflow | Review runbook v2 | Operations | In review |
| MO-05 | Market drift thresholds | Monitoring configuration | Data Science | Validated |
Illustrative controls and evidence only. Not an issued assessment or rating.
A high-performing model can still be poorly governed.
Predictive accuracy does not substitute for evidence of permissible data use, fair-housing controls, human recourse, security or monitored operation.