AI Rent Roll Analysis
The Problem
“Slow, error-prone rent roll review delays deals”
Organizations face these key challenges:
1
Non-standard rent roll formats and inconsistent field definitions across property managers (unit IDs, lease dates, concessions, charges)
2
Manual reconciliation between rent roll, leases, T-12/GL, and PMS data creates delays and increases underwriting and credit risk
3
Hidden data quality issues (duplicate units, stale move-in/out dates, missing deposits, incorrect market rents) lead to inaccurate NOI and DSCR assumptions
Impact When Solved
Standardized, audit-ready rent roll dataset in minutes instead of hoursAutomated exception reporting (below/above market rents, occupancy gaps, lease expirations, concessions) improves underwriting accuracy and consistencyFaster deal cycles and improved risk controls support higher throughput without adding headcount