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Case study

Leasing time cut in half and fake documents intercepted every month

8 offices, 150 tenant applications per month: this New York metro property management group automated completeness and authenticity checks on every application.

Context

Industry

Network of 8 property management offices (rental + sales, New York metro)

Volume

150 tenant applications per month

Tools

AppFolio (property management software), credit screening services

Team

8 property managers

The problem

The competitive New York rental market pushes some applicants to falsify their files. Overwhelmed property managers lacked the time and tools to verify everything.

  • Tenant applications incomplete in 40% of cases on first submission
  • Rising fake document attempts (pay stubs, tax returns, bank statements)
  • Time-consuming manual checks: 20 min per file, 150 files/month
  • Average leasing delay: 12 days from showing to lease signing
  • Legal risk if a fraudulent tenant is accepted (Fair Housing liability)

The solution

CheckFile.ai automatically verifies each tenant application: regulatory completeness (Fair Housing compliance), document authenticity, information consistency.

  • Automatic verification of ID, pay stubs, tax returns, bank statements
  • Detection of inconsistencies and anomalies (amounts, dates, suspicious formatting)
  • Fair Housing Act compliance: only legally permissible documents are requested
  • Shareable verification report for the landlord or property owner

The results

100%
of applications verified before showing
No more applications processed without checks
3/mo
fake document attempts detected
Falsified documents automatically intercepted
-80%
application processing time
From 20 to 4 minutes per tenant application
12โ†’5 d
average leasing delay
Time-to-lease cut by more than half
โ€œLast month, CheckFile caught a pay stub edited in Photoshop that we would have approved by eye. That alone justifies the investment. The time savings are a bonus.โ€

Head of Property Management

Property management group, New York metro

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