Rental fraud is a $275 million problem. Most of it goes unreported.
The FBI counted $275 million in rental fraud losses last year. Steve Carroll says that number is the floor, not the ceiling. Here's what the data actually shows.
Key takeaways
- The FBI logged over $275 million in reported rental fraud losses across more than 12,000 cases last year, and that figure undercounts the real damage because most property managers absorb the loss quietly instead of filing complaints.
- Fraud is now a near-universal operating condition. 93% of NMHC members reported it in the prior year, at an average $15,000 to mitigate per incident.
- Generative AI broke the old defenses. MRI bought 200 AI-generated fake IDs, some for as little as $5, and optical card readers flagged only 26%, letting 74% pass.
- One Los Angeles landlord spent seven months and an estimated $90,000 on a single fraudulent resident, then decided to sell the building. Enforcement cannot close the gap, with LAPD alone fielding over 400 identity fraud complaints a month.
- Credit scores and document review were not built to catch synthetic identities. Findigs verifies income and identity directly at the source, where a fabricated pay stub cannot survive, and backs its decisions with a contractual fraud guarantee.
Rental fraud crossed $275 million in reported losses last year. That number, published by the FBI’s Internet Crime Complaint Center in its 2025 report, represents more than 12,000 tracked cases of real estate fraud. It puts rental fraud roughly on par with credit card and check fraud combined. And it almost certainly undercounts the real damage.
Steve Carroll, CEO and co-founder of Findigs, puts it plainly: “One can say with certainty that the $275 million figure in reported losses is underestimated, as much of the rental fraud goes unreported due to property managers absorbing the loss quietly or not realizing what happened until well after an eviction.”
Property managers don’t file federal complaints. They eat the cost, complete the eviction, and move on to the next applicant.
The Scope the Industry Already Knows
By the time the FBI published its 2025 data, the industry had already been tracking its own version of the problem. In 2024, 93% of National Multifamily Housing Council members reported experiencing rental fraud in the previous year. Not a one-time event. Not an outlier case. A near-universal operating condition.
The cost per incident averages $15,000 to mitigate. Multiply that across a portfolio with hundreds of annual applications, and the exposure is not theoretical. It’s a line item.
Mortgage fraud is moving in parallel. Cotality reported in November 2025 that 1 in 118 mortgage applications shows indications of fraud. Mortgage fraud risk increased 8.2% year-over-year in Q3 2025. Housing fraud, broadly, is accelerating. Rental is not an exception.
AI Broke the Old Defenses
The traditional fraud playbook involved effort. Forgers needed connections. Social media put document fabricators in contact with buyers, but the barrier was still human friction and coordination. That friction is gone.
Generative AI now produces convincing pay stubs, bank statements, and photo IDs at minimal cost. MRI Real Estate Software ran a direct test: they purchased 200 AI-generated fake IDs, some costing as little as $5, and ran them through optical card readers, the industry-standard identity verification system. Only 26% were flagged. The other 74% passed.
Industry operators are now facing a more sophisticated adversary than a convincing PDF. Steve describes an emerging pattern: fraudsters are setting up real LLCs and issuing pay stubs from those businesses, creating documentation that is technically legitimate. The business exists. The paperwork exists. The income does not.
This is what the industry calls synthetic identity fraud at its worst. The documents are real. The person behind them is constructed. Credit checks and one-time document review, the tools the industry has relied on for decades, were not built to catch this.
What $90,000 Looks Like on the Ground
Michael Renkow is a 74-year-old landlord in Los Angeles. In 2024, a fraudster applying under the name “Igor,” later identified as Alfred Earl Jackson, submitted applications for two of Renkow’s apartments simultaneously, each at $5,300 per month. The application came with fraudulent cashier’s checks and falsified documents. Jackson moved in, then sublet the units.
Renkow spent seven months navigating the eviction process. His total estimated cost: $90,000. Jackson was eventually caught only because his fake ID used a false name paired with his actual photo. Not because any verification system flagged the documents. Because the photo matched a known individual.
After it was over, Renkow said: “I’m pretty sure I’m going to sell the building. I don’t need this at 74 years old.”
That’s what fraud costs. Not $275 million in the abstract. One landlord, one case, $90,000, and an exit from the business.
Enforcement Won’t Fix It
LAPD receives more than 400 identity fraud complaints per month. The department acknowledges it does not have the resources to pursue most of them. Federal data captures what gets reported. Local law enforcement handles what it can. Most cases fall between the two.
Policy is not keeping pace either. The FTC’s December 2025 report tracking $65 million in rental scam losses since 2020 reflects reports from renters who were defrauded by phantom listings. The operator side of the ledger, fraudulent applicants, bad checks, fabricated income, is largely invisible to regulators.
The gap between the scale of the problem and the capacity of enforcement is structural. It won’t close through legislation or increased policing. The volume is too high and the methods change too quickly.
The Arms Race Has No Finish Line
Steve doesn’t frame this as a problem waiting to be solved. He frames it as a permanent condition. “It’ll continue to be an arms race, as there’s these tools that are used to create fraud, and there are these tools that are used to detect fraud, and I don’t see that stopping.”
That framing matters for how property management companies think about their technology choices. A tool that catches today’s fraud methods may be obsolete in 18 months. The question is not whether your current system passed a test in 2024. The question is whether it can adapt as the methods evolve.
Why the Old Model Is the Wrong Foundation
The industry built its fraud defenses on two pillars: credit scores and document review. Generative AI has compromised both. Credit scores don’t detect synthetic identities built from real data. Document review doesn’t catch fabrications that pass optical scanners 74% of the time.
Findigs was built after this shift, not before it. The platform makes automatic yes/no decisions on rental applications by working from source data, verifying income and identity directly at the source rather than relying on documents an applicant submits. A fraudster can fabricate a pay stub. They cannot fabricate a direct data connection to a payroll provider. That structural difference is why Findigs backs its decisions with a contractual fraud guarantee, and why the guarantee holds even as the fraud methods keep changing.
The $275 million figure is the floor, not the ceiling. The industry that treats it as an alarming headline and returns to credit checks and document PDFs will keep absorbing losses that never make it into the FBI’s count.
Steve Carroll co-founded Findigs in 2018 and runs it as CEO. He writes about strategy, fraud accountability, and where leasing decisioning is headed.
Frequently asked questions
What are the biggest warning signs of rental application fraud?
The strongest fraud signals often come from inconsistencies between an applicant’s claimed identity, income, and independently verifiable data, not simply from how authentic their uploaded documents appear.
- Compare identity information across verification sources rather than relying on a photo ID alone.
- Validate income against source data when possible instead of treating a polished pay stub as proof.
- Escalate mismatches between application details and verification results for additional review.
- Apply the same verification workflow consistently instead of relying on leasing-team intuition.
For more tactics, see Findigs’ guide to rental fraud.
Why isn’t manual document review enough to prevent rental fraud?
Manual review is vulnerable when fraudulent documents are convincing enough to appear legitimate, particularly as generative AI lowers the effort required to create them.
- Treat uploaded documents as one input rather than the sole source of truth.
- Use direct income or identity checks when available to validate the information provided by the applicant.
- Analyze documents systematically for inconsistencies instead of expecting leasing staff to identify sophisticated alterations visually.
- Route questionable applications to an exception workflow rather than making every application a manual investigation.
See how Findigs approaches document analysis as part of the screening workflow.
How should property managers measure the real financial impact of rental fraud?
Operators should track fraud exposure beyond confirmed incidents by connecting suspicious applications and screening outcomes to downstream delinquency, eviction, bad debt, and operational costs.
- Tag suspected or confirmed fraud cases consistently so they can be analyzed across the portfolio.
- Measure losses beyond unpaid rent, including legal expenses, staff time, vacancy, and unit turnover.
- Compare pre-lease screening signals with post-lease performance to identify patterns associated with costly residents.
- Monitor results by property and application cohort rather than relying only on industry-wide fraud statistics.
For a broader view of reducing portfolio exposure, explore Findigs’ approach to fraud, delinquency, and bad debt.
How does Findigs verify income when pay stubs or bank statements could be fabricated?
Findigs supports income verification that goes beyond relying solely on applicant-uploaded documents, reducing dependence on paperwork that may be manipulated.
- Connected data can provide stronger verification than accepting a document at face value.
- Document analysis provides another verification path when applicants need to submit documentation.
- Verification can feed into the broader underwriting workflow instead of requiring leasing teams to reconcile evidence manually.
- Standardized verification reduces property-by-property variation in how income evidence is reviewed.
Learn more about Findigs’ income verification capabilities.
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