Gain an understanding of the nature of the problem of fraud in rental housing, as well as the tools available to help solve for it.
One year ago, as multifamily housing executives looked toward 2024, many were applying a new focus to an old problem. Application fraud weighed heavily on senior executives’ minds, and fraud prevention emerged as a top priority.
The trend aligned with the 2024 NAA and NMHC Pulse Survey, which analyzed the operational impacts of rental application fraud and bad debts. The survey revealed some shocking numbers: 93.3% of respondents reported experiencing fraud during the prior 12 months, a staggering 40% year-over-year average increase.
The causes of this uptick seem to be dependent on several factors. The lingering effect of the pandemic, eviction moratoria and the rise of a cottage industry on social media advising would-be fraudsters on how to bypass the checks designed to prevent this illicit activity.
As noted in 20for20, an annual survey of 20 senior rental housing executives, it now seems untenable for a multifamily housing organization to rely on human checks to stop fraudulent applications. While there exist numerous technologies designed to mitigate this problem, what is clear is that there are many types of fraud and different ways to combat it. Operators must balance fraud prevention against the ease of applying for an apartment.
The environment is quickly changing, with many variables in play. Not all multifamily housing operators have a clear picture of the nature of the problem and the tools available to help solve it. This article will attempt to explain both sides of this equation.
A New Twist on a Perennial Problem
While the problem of fraud is not new, the types of fraud appear to be evolving and are surprisingly ubiquitous across the industry. “We always used to use ID verification and generally thought it was highly successful,” says Mike Hogentogler, Chief Operating Officer of LCOR. “What changed is that we started to notice inconsistencies. More applicants were showing up with job offers but no pay stubs. That created a need for manual verification, which was too labor-intensive, prompting us to explore automated solutions.”
As LCOR began evaluating technologies, teams were shocked by the high rejection rates they saw when they started analyzing documents. “You don’t necessarily expect that in luxury properties like ours, but we quickly realized we were thinking about it the wrong way,” says Hogentogler. “If somebody is trying to commit fraud, why not aim for the penthouse?”
Other local factors contribute to the growth of this problem. In some jurisdictions, lengthy processes increase the incentive for fraudulent applications. That raises both the frequency and the negative consequences in markets previously unaccustomed to high volumes of fraud.
The Evolving Landscape of Fraud
Fraud keeps changing as bad actors continue to identify new gaps in the industry’s defenses, but it is helpful to think of fraud in two broad categories: First-party fraud and third-party fraud.
First-party fraud is where the applicant uses their real identity but misrepresents critical information, such as falsifying employment, references or financial documents. It is the most common form of application fraud and primarily involves fake or manipulated documents like pay stubs or bank statements. It may also involve a fake Social Security number (SSN).
More sophisticated forms of first-party fraud may include
inception fraud, where a fraudster pays another actor to process fraudulent salary payments through a legitimate LLC, thereby producing pay stubs that pass document-based checks.
Third-party fraud involves the fraudster using someone else’s identity to apply for a lease. It can entail identity theft or the creation of a new identity. Third-party fraud carries the significant risk of not knowing who the applicant is, which presents personal risk, e.g., on in-person property tours, property liability risk and substantial potential losses for housing providers because of the difficulty of eviction (it’s hard to initiate proceedings when you don’t know who the resident actually is).
Synthetic fraud is a growing and sophisticated form of third-party fraud, which involves creating a completely fabricated identity by piecing together elements like a fake name, SSN or Credit Privacy Number (CPN), and address history. It is typically used by imposters for unsecured credit: Taking out loans or opening credit card accounts in the names of contrived identities and never repaying them. In the context of rental applications, it is potentially the most complex and challenging type of fraud to detect.
It is hard to estimate the prevalence of each type of fraud. A RealPage survey published in March 2024 reported the incidence of four different fraud types among its respondents:
- Fake or manipulated identities (58%)
- Misrepresenting income (57%)
- Identity theft (53%)
- Site staff pushing through unqualified candidates (51%)
While the numbers demonstrate that these fraud types are relatively common, they do not make it any easier for property management companies to decide where to focus their efforts at prevention.
Anecdotal evidence suggests that between 5% to 8% of applications involve some form of fraud. This figure excludes potential fraudsters who abandon their attempts when they encounter anti-fraud measures. The rising cost of fraud justifies the expense of prevention. Monthly rent, eviction time and fees can easily result in $10,000 in bad debt, which quickly compounds with multiple cases.
Team workload is also a consideration, as Hogentogler says: “Since implementing these verification measures, our delinquencies have dropped significantly, but the main motivation for us was addressing our team’s frustrations. When our training team made us aware of the time this problem was taking, we decided to filter out fake applications early. Tackling the problem up front avoids the much bigger problem of dealing with fake applications on the back end.”
A New Breed of Solutions
The industry’s response to the rise in fraud has been to adopt one or multiple of a growing population of best-of-breed fraud prevention tools. Operators are implementing these tools in addition to the resident screening applications that most have been using for many years. So, it’s important to think about what the tools do to warrant the additional expense.
While each company takes a slightly different approach to fraud prevention, they represent at least one of three broad sets of capabilities:
- ID Verification checks that prospects are who they say they are based on the official IDs that they present.
- Document verification uses smart, usually AI-driven technology to analyze documents like pay stubs and bank statements to determine whether they are genuine and whether they have been tampered with.
- Income verification uses data from the applicant’s bank account to assess whether they can afford the lease for which they are applying.
ID verification is the most straightforward of these solutions, with widely used software that checks ID documents, usually against proprietary or government databases, in real-time rather than relying on the vigilance and training of property teams. This step in the process may be used prior to the application, e.g., at the point when a prospect registers or arrives for a tour.
Many companies implement ID verification for the safety of property staff. It is unclear whether ID checks detect much application fraud, but the presence of a check appears to deter some fraudsters. It can also be costly if done on every tour, which leads some companies to opt for cheaper alternatives, such as the checks incorporated into self-tour applications.
There is good reason to believe that most of the fraud currently exists in the documents that properties request to verify income. “In 2020 and 2021, the focus was on IDs,” says Hogentogler. “But in 2022 and 2023, we saw a shift towards fake pay stubs. It’s shocking how many companies sell realistic-looking fakes. We added document checks, and if applicants can’t prove their job or income, we cut the process short, which causes the applicant to drop out.”
Document verification is a logical approach to prevention in this increasingly common use case. But inception fraud demonstrates potential weaknesses in a “documents-only” approach. “A new challenge we’re facing is from small HR companies that are legitimate but affordable for small businesses,” says Hogentogler. “These companies produce real pay stubs but can be manipulated by fraudsters. When we encounter pay stubs from these companies, we have to verify the deposits.”
That is one of many strong arguments for basing income verification on bank records. While bank statements can be forged, the contents of bank accounts cannot. Open banking protocols have made it relatively easy for prospects to grant software suppliers access to information that comes directly from their bank accounts.
The Fraud Prevention Dichotomy
The best-of-breed fraud prevention suppliers fall broadly into two categories: “Documents-first,” i.e., solutions are designed to stop fraud through document analysis, with a subset of companies offering bank-linking as a secondary check. The alternative “bank-linking-first” solutions seek to analyze income stability using data accessed through open banking intermediaries.
There are strong arguments in favor of both the “documents-first” and “bank-linking-first” suppliers approaches, particularly since opinion is also divided among property managers on which approach is best. Bank linking removes the opportunity for most document fraud, but communities cannot require all applicants to take this step. And applicants willing to grant access to their bank account information are unlikely to be attempting fraud. Some level of document checking will, therefore, still be necessary.
Increasingly, document verification companies are performing income verification using the contents of the bank statements during their verification process. That works today, but we also know that fraud is moving quickly, with sophisticated technology making it easy for applicants to obtain high-quality fake documents. We are in an arms race between the AI that generates fake documents and the AI that detects them. In that environment, neither bank linking nor document verification alone is a silver bullet.
The synthetic fraud mentioned earlier exemplifies how fraud continues to change. Some suppliers believe that the high correlation between fake credit records and fake supporting documents means that most applicants will fail document checks. However, some operators are not so sure.
“Falsified SSNs and the misuse of CPNs are significant challenges,” says Phyllis Metevier, Director of Applicant Screening at Dallas-based LUMA Residential. A CPN is a nine-digit number similar to a Social Security number. CPNs may be sold to consumers to hide poor credit history or bankruptcies or to build credit.
“Fraudsters can buy a CPN and use it to create a fake credit profile, or they can obtain an SSN that belongs to somebody else,” says Metevier. “They may start by opening a checking account and then open a secured credit card and, from there, build a false history that can pass background checks. We have to monitor applications for red flags, such as document inconsistencies or recently established credit files. Training leasing consultants to recognize these details is crucial in preventing fraud.”
When synthetic fraud scams are well-executed, they can be hard to detect. Creating a fake credit history requires patience, but the generous rewards on offer in pro-renter jurisdictions can make the effort worthwhile. Most detection techniques rely on identifying anomalies like unfeasibly short credit histories relative to the applicant’s age. While that may stop some fraudsters, it also risks false positives in cases where an applicant legitimately has few purchases on their credit record.
The Human Element
The synthetic fraud example illustrates some important things about fraud prevention. First, there is no single tool that solves fraud. Some apps offer a holistic solution; others seek to be best-in-class in some specific area (bank checks, document metadata analysis, etc.) “We’ve tested various verification companies and systems to balance the need for security with ease of use, but no system is foolproof,” Metevier says.
To combat fraud effectively, operators must implement a “waterfall” of checks, combining multiple technologies with a well-defined process. This requires understanding which technology suits each community. As fraud continues to evolve, operators must clearly identify the problems they aim to solve and the metrics to measure progress for successful outcomes.
“Above all, we try to make the application process as easy as possible for honest applicants,” Metevier says. That may be one of the most important philosophical considerations. The nature of work is changing, with younger generations making more of their income from gig work and other sources that are harder to track using conventional methods. In tackling the problem of fraud, operators can focus on stopping bad actors, or they can focus on qualifying good residents. That focus may guide companies’ progress in an arms race that shows no signs of stopping.
Dom Beveridge is Principal with 20for20, a multifamily technology consultancy.