Fake pay stubs used to be easy to spot. Now, they’re crafted with AI tools that mimic real payroll systems and bank payments, down to the last detail. Leasing teams and property managers need to question if those documents could have been generated by an algorithm designed to outsmart them.

The playbook for screening applicants is changing. New types of fraud are slipping past traditional checks, and old habits aren’t enough to keep up. It’s time to rethink how your team approaches screening, and what it means to trust the paperwork in front of you.

The new fraud frontier

When people hear about AI in the rental industry, they picture smoother workflows or faster application processing. Some expect chatbots. Others imagine clever marketing tools that fill units quicker. But what else is happening behind the scenes?

AI now powers tools that generate fake pay stubs in seconds. With the right prompt, anyone can fabricate employment histories or spin up convincing references. There are even how-to videos circulating on TikTok, walking viewers step-by-step through the process of generating fake documents. Even seasoned leasing teams have been fooled by documents that look authentic on the surface.

The National Multi-family Housing Council’s January 2024 Pulse Survey on Fraud found that operators wrote off an average of nearly $4.2 million in bad debt over the past year. Almost a quarter of that stemmed from applicants who never intended to pay rent, slipping through the cracks with falsified documents. An overwhelming 84% of survey respondents reported seeing pay stubs or references that were fabricated.

This is the new reality. Asking for a pay stub isn’t enough. You need to know how it was created, what signals confirm its validity, and whether your process can keep up with tactics you haven’t seen before.

The screening playbook is outdated: what has to change

Traditional screening once relied on a simple formula. Landlords would request a pay stub or W-2, run a credit check, and confirm the applicant’s identity. These steps filtered out some risk. For years, that was enough to keep most problem tenants at bay.

When income and credit histories can be stitched together with false data, these defenses fall short. There’s also the added problem of disconnected tools. When each part of your screening process lives in a separate system, you miss out on important context that could reveal hidden risks.

Many property teams have tried patching together a toolkit of point solutions—one tool for ID verification, another for document analysis, and maybe a third for spotting device fraud. Each is strong on its own, but these standalone products rarely communicate or share signals. That gap leaves blind spots. If your document checker can’t factor in behavioral cues from the rest of the application, or your identity tool isn’t seeing the full applicant journey, risks can slip through.

An all-in-one screening platform brings these elements together. It doesn’t just scan an ID or review a pay stub in isolation. Instead, it combines signals from every step—identity, income, device, and behavior—to give you fuller context into every applicant. When systems work together, you can catch more fraud, streamline approvals for legitimate renters, and keep your policies consistent no matter who is on your team.

Effective screening now depends on looking through three distinct lenses.

1. Identity and behavioral signals

What to look for: 

Start with the basics. Does the applicant’s selfie match the photo on their ID? Even small mismatches or poor-quality images should raise concern. 

Next, examine the device and network Next, examine the device and network. Many systems can’t automatically flag burner phones or suspicious IP addresses, but Findigs does this in real time—integrating device intelligence directly into every screening. Watch for patterns in behavior, like rushed answers or multiple applications submitted from a single device in a short window. These signals don’t always mean fraud, but they make a strong case for a closer review.

Fraudsters often get creative with identity numbers. If a Social Security Number exists but is new to the system, or seems linked to different names across multiple applications, you could be dealing with a synthetic identity. Systems like Findigs will catch this automatically. Others may not surface the risk until it’s too late.

Ask your vendor: 

• Does your platform perform biometric selfie checks and ID scanning on every applicant?
• Can it spot when a selfie and ID photo don’t match, or when an ID barcode doesn’t align with public records?
• How does your system handle device fingerprinting? Will it catch burner phones, VPNs, or mismatched geolocations?
• What behavioral signals are monitored? For example, does the system flag unusual typing speeds or copy-paste behavior as signs of stolen information?
• Can you share metrics on how many identity fraud attempts have been blocked, and how often legitimate applicants are incorrectly flagged?

Update your process: 

Make biometric and device checks a required step early in your workflow, not an afterthought. Train your team to look beyond the “pass/fail” status—review every flagged device, location, or behavioral anomaly. If you see a red flag, follow a documented escalation path. 

Collect feedback from your leasing and operations teams. When an incident does slip through, log it. Share those insights with your vendor and ask for system improvements. Over time, these data points will help you stay one step ahead as fraud patterns evolve.

Learn how Findigs approaches fraud protection.

2. Income validation beyond the pay stub

What to look for:

First, check if the applicant’s claimed income on their pay stub matches what their bank records or payroll links show. If the app shows an income line that’s too regular or too uniform, it might be generated. Look for income sources that don’t fit a typical pattern—side gigs, contract work, variable hours—and ask how they’re verified. Also watch for documents uploaded as PDFs that bear signs of tampering, like mismatched fonts or inconsistent metadata.

Ask your vendor: 

• Do you support secure bank‑linking and payroll‑linking so applicants can prove income in a way that goes beyond a static upload?
• What is your coverage for non‑traditional income streams, under‑banked applicants, or people without a W‑2?
• If an applicant uploads a document instead of linking, does your system analyze that document for red flags like tampering or missing metadata?
• How does your algorithm compute income averages for unstable earnings? Do you account for variations so you don’t deny good applicants unfairly but still spot risks?

Update your process: 

Consider a direct income verification step whenever possible—preferably bank or payroll linking. If linking can’t be done, enforce that document uploads pass an automated analysis before you proceed. Let external experts, like Findigs, find flags such as “income claims without supporting link” or “uploaded income document failed authenticity check.” Make a standard escalation path: for example, if the income link fails or the document is flagged, place the application on hold or require supplementary proof (e.g., tax transcript). 

Finally, track outcomes—how many applicants’ incomes were verified via linking versus uploaded docs, how many ended up delinquent—and feed that data back into your vendor review and your internal policy adjustments.

See how Findigs verifies income.

3. Document authenticity analysis

What to look for:

Check metadata and file history. A document created or modified in unusual software or at odd times can be a red flag. Next, inspect for formatting inconsistencies—fonts that don’t match bank‑issued statements, mismatch in logos, headers, or watermark styles. Also watch for documents that appear too “perfect”—no noise, no variation on deposits, clean margins—as those may have been generated or heavily altered. 

Finally, pay attention to submission context. If an applicant uploads multiple document types in the same session or in quick succession, it may indicate batch processing by fraud‑actors.

Ask your vendor:

• Does your system automatically validate document type on the spot?
• Can your platform scan PDFs for tampering, metadata anomalies, hidden layers, or signs of foreign edits?
• How many documents has the system analysed to date, and what are the false‑positive/false‑negative rates for fraud detection on uploads?
• Do you support auto‑analysis for documents from all major banks, and can the system link flagging to a user‑driven review workflow with actionable next steps?

‍Update your process:

Make automated document analysis tools a built‑in part of your workflow. Train your team to review the analysis engine’s output (metadata flag, tamper alert, consistency score) before accepting an uploaded document. If a document is flagged, follow a defined escalation path: request a linked bank or payroll verification, require an original digital document, or delay approval until further review is complete. 

Maintain a record of flagged uploads and resulting outcomes (approved, denied, delinquency). Use this data to refine your vendor criteria, document requirements, and internal thresholds for escalation.

Explore Findigs’ document analysis tools.

Upgrading your defense: practical steps for teams

Screening isn’t just about keeping out bad actors. It’s a lever that strengthens your entire portfolio. When you catch fraud before move-in, you cut down on costly evictions and unpaid rent. Over time, this shift improves not just risk metrics, but resident satisfaction and property performance.

The most effective teams stop thinking of screening as a one-way filter. Instead, they see it as a partnership with legitimate renters—protecting their community while raising the standard for everyone. This mindset builds trust on both sides.

Modern automation gives leasing teams an edge. The same AI that enables fake documents can be deployed to spot them, in real time and at scale. With solutions like Findigs, teams can review biometric checks, device fingerprints, and document integrity without slowing down their process. Let AI handle the heavy lifting so staff can focus on the cases that need real attention.

Ready to move forward? Start with a clear plan:

• Update your policy. Schedule a dedicated fraud review phase for every application. Build checkpoint gates into your workflow so risky applicants can’t slip through on a technicality or simple oversight.
• Educate your team. Hold regular training sessions to share the latest red flags and tactics. Use real-life visuals or flagged examples, and refresh this training at least twice a year. With turnover in leasing teams often reaching 50% annually, relying solely on staff education isn’t enough. That’s why partnering with a vendor like Findigs helps you keep fraud defenses consistent, no matter who’s on your team.
• Ask sharper questions. When evaluating technology partners, go beyond “Do you screen for fraud?” Instead, ask: Can your system flag synthetic identities? How many documents has your AI reviewed in production? What percentage of bank-link attempts are successful, and how are failures handled?
• Balance speed and safety. Automation doesn’t mean adding friction for everyone. Findigs’ auto-analysis reviews high volumes quickly while our staff gives risky applications the attention they deserve. When something needs a closer look, Findigs ensures there’s always a real person on the other end—ready to review, reach out, or help applicants get unstuck. This blend of technology and hands-on support means genuine renters move forward without delay, while potential fraud gets a second layer of expert review.
• Build your data loop. Track every fraud hit, denied application, and eventual delinquency. Use this data to adjust your criteria and challenge your vendors to do better.
• Communicate openly. Let applicants know that document analysis is part of the process. Make it clear this step helps keep rates stable and units available for qualified residents.

Upgrading your defense isn’t a one-time task. It’s a process of continual improvement, driven by data and made possible by technology that evolves just as quickly as the threats you face.

Elevating resident screening for the modern era

AI-driven fraud is changing how property managers think about every application that crosses their desks. Rental teams may feel exposed, but new tools and smarter strategies mean they are far from powerless.

Manual review alone is no match for today’s tactics. To stay ahead, screening must go deeper. Signal-driven analytics catch what the human eye might miss. End-to-end verification—layering identity, income, and document checks—gives your team the coverage needed to protect your properties and your residents.

Now is the time to raise your standard for resident screening. Don’t settle for the old way of doing things. Consider partnering with a modern screening agent like Findigs, where every application gets the benefit of advanced automation, expert support, and a defense strategy that grows stronger with every new challenge.