Kolena AI Agent

Rent Roll Analysis

Build clean, normalized rent rolls and unit-mix, occupancy, and loss-to-lease analytics from messy source files across any PMS.

Real EstateBanking / LendingAsset & Property Management

Impact

Hours of manual rent-roll cleanup per acquisition eliminated by normalizing any PMS export into one comparable schema

per acquisition

Volume fit

Works best for

teams normalizing rent rolls from many properties and PMS vendors, especially across acquisitions and monthly portfolio reporting

Too small for

a single property on a single PMS where no normalization is needed

Typical inputs

Documents

  • Rent roll export (PDF or Excel)
  • Unit detail report
  • Lease summary / lease charges report

Systems

  • Yardi
  • RealPage / OneSite
  • AppFolio
  • Entrata
  • MRI
  • ResMan
  • Email
  • Google Drive

Output

One normalized, unit-level rent roll with a source-system label per row, plus unit-mix, occupancy, loss-to-lease, expiration/WALT, and reconciliation tabs

Delivered to

  • Acquisition underwriting model
  • Deal folder
  • Portfolio data warehouse
  • Asset-management system

What it extracts

· 9 fields
  • Form

    Rent Roll Summary

    A one-look roll-up of the property: unit and occupancy counts, total in-place and market rent, loss to lease, and the source system, so a reviewer can orient before reading unit detail.

  • Classification

    Source System

    The property management system that produced the export, which drives how every field is mapped and normalized downstream.

  • Table

    Normalized Unit Rent Roll

    The core deliverable: one row per unit mapped onto a standard schema so rent rolls from any PMS line up, including vacant, model, down, and employee units, with a source-system label on every row.

  • Table

    Unit Mix Summary

    The unit mix aggregated to one row per floor plan, showing counts, average size, occupancy, and average in-place versus market rent and loss to lease by type.

  • Form

    Occupancy and Vacancy Analysis

    Physical versus economic occupancy with true rentable vacancy separated from non-revenue model, down, and employee units, and an occupancy count that must foot to total units.

  • Table

    Charge Code Normalization

    A crosswalk mapping each source charge code to a standard revenue category (base rent, parking, pet, storage, utility/RUBS, concession) so rent from different systems is comparable and not double-counted.

  • Table

    Concessions and Loss to Lease

    Unit-level concessions and the gap between market and in-place rent, with per-unit and portfolio loss-to-lease percentages and outlier flags.

  • Table

    Lease Expiration Schedule and WALT

    The lease rollover schedule by period with the share of units and rent expiring, plus weighted average lease term remaining, to surface turnover risk.

  • Table

    Data Quality and Reconciliation

    The reconciliation and data-quality checks an analyst runs before trusting a rent roll: unit-count and occupancy footing, rent totals, missing dates, rent outliers, duplicate units, and status-rent mismatches.

Prerequisites

  • The rent roll export for each property
  • Its as-of date
  • Any market-rent or unit-mix reference you underwrite against

Human review

An acquisitions or asset-management analyst reviews the flagged data-quality checks, occupancy and unit-count reconciliation, and rent outliers before the normalized rent roll feeds the underwriting model.

Where it fits

Acquisition and asset-management underwriting

Rent roll exports pulled from each property's PMS (RealPage/OneSite, Yardi, AppFolio, Entrata, MRI, ResMan) and delivered per property during diligence or monthly reporting, in mixed layouts

This step

Rent roll normalization and analysis

After

T-12 Extraction
Acquisition underwriting model
Portfolio rent-roll aggregation
Lender and investor reporting

Who uses it

Acquisitions AnalystAsset ManagerUnderwriterReal Estate Data Analyst

Grounded in

  • CREFC Investor Reporting Package (IRP) v8.4verified as of 2026-07-22

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