Property Shield
Data Security Firm is Changing the Face of Fraud Protection
by Carole VanSickle Ellis
Property Shield is, by any definition, “new to the scene” of data security. In fact, the company launched in February of last year. However, said the company’s co-founder and CEO Alex Fahsel, the data security firm hit the ground running by tackling emerging issues around fraud, data security, cyber security, and even artificial intelligence.
“As much as we love all this technology, it can be used for all sorts of nefarious things,” Fahsel said. “Property Shield specializes in using this technology for good and to stay ahead of scammers and fraud. Cybersecurity has historically been a ‘cat-and-mouse’ game where the good actors have always been a few steps behind. We started Property Shield to give those good actors the opportunity to stay ahead.”
“We are basically the data police,” explained Luke Lind, co-founder and CTO of the company. “Our system is constantly monitoring the web for potential fraudulent listings, and whenever it finds one, we immediately notify whichever client owns the data.” At the same time as the notification is going out, Property Shield tackles the process of having the fraudulent listing removed from consumer access as soon as possible.
“The combination of these two workflows helps reduce illegal activity at the physical property level,” Lind continued. “Because our system is able to identify and remove fraud listings within hours, we can effectively cut down on the threat they pose to the property.”
That threat is growing exponentially larger every day as cyber criminals, already frighteningly internet savvy, add psychological manipulation to their roster of skills. According to the Boston Division of the Federal Bureau of Investigation (FBI), rental scams increased 64% between 2020 and 2021. Cumulative losses exceeded $350 million in 2021 alone.
“The actual losses are most likely much higher,” the bureau added, “because many people are hesitant to report they were scammed.”
“These are very sophisticated crime syndicates that push these scams and frauds,” Fahsel said. He explained that large syndicates of cyber criminals based in countries with low or no regulation on this behavior may run hundreds of variations on dozens of distinctly “stamped” scams, from romance scams to employment scams to rental fraud. When one strategy begins to work particularly well, the lessons from that strategy may then be applied across the board. There is a great deal of intense analytics involved.
“Cyber criminals look closely for certain criteria to indicate if a certain geographical region or market is ripe for real estate scams,” Fahsel said. “When they home in on a market, they will check net domestic migration patterns, for example, to determine where a large volume of people is moving. Then, they tailor the scam to fit the mindset of the people moving into or out of those areas.”
Because an individual moving into a new area may not have a clear idea about the nature of the rental landscape, they are particularly prone to falling for what Fahsel calls “too-good-to-be-true” offers.
“Scammers compile data about properties, rental prices, images, and listings, then hire virtual assistants or even college students looking for part-time jobs to put together these offers and facilitate the exchange of security deposits, rent, or other funds,” he explained. This makes the entire process even muddier for law enforcement because there are often innocent parties involved in the middle of the process between the victim and the cybercriminal.
“The ‘employees’ get scammed too, because they frequently never get paid,” Fahsel noted. The “salaries” for these positions are also often too good to be true; the Federal Trade Commission estimates in 2022, job seekers lost $68 million in labor, lost income, and fraudulent fees associated with fake jobs.
Cutting Off Fraud at the Source
Because most real estate scams are carried out by large syndicates running multiple scams and multiple variations on these scams in multiple locations around the country, identifying trends early and acting preemptively to identify and eliminate fraud related to an investment portfolio is one of the few ways to make a significant dent in the potential money, time, and opportunity lost when a real estate scam succeeds. There are multiple victims at every point in the scam, from the property owner to the “employees” and “interns” working unwittingly for the scammer to the renter hoping to establish a household in the property shown by the fraudulent listing.
According to Georgia Legal Aid, an organization based in Atlanta, Georgia, which is currently a hotbed of rental fraud, the two primary types of rental listing scams actively deployed at present included renting properties that the scammer is not authorized to rent and creating property listings for properties that do not exist and soliciting deposits or application fees using those listings. However, this simple explanation barely scratches the surface when it comes to the ingenuity and brainpower cybercrime syndicates dedicate to this type of fraud, Fahsel said.
“These are teams of people who wake up every day and think, ‘How do we scam these people? How can we hack the system and take advantage of it?’ If they put half the effort they do into pushing these scams into a legitimate business that would help people, they could do really well,” Fahsel explained. “Sadly, that is not the route they take, so Property Shield spends every waking moment thinking about how to stop them.”
Lind added, “Our system stands out from other fraud-prevention platforms because we are using the same tools that the scammers are using to fight them. Machine learning is a critical component of our system, and we have been ‘training’ our models for a long time.”
To “train” a machine learning model, the algorithm is “fed” data from which it can learn. The more training the model receives, the better it becomes at identifying threats and classifying them as such.
Lind noted, “Our model is also multi-modal, meaning it can process multiple mediums of data, including text and images.” This enables Property Shield to identify potential issues for clients from many angles, including the ones from which the two most common scams (fake properties and false listings) stem.
Because Property Shield uses machine learning as well as a vast array of algorithms in its daily operations, the programs continue to learn from real-life review and experience and may also expose emerging behavioral trends in real estate fraud.
“Today, just knowing a property is vacant and actively listed is enough to make a property a target for a rental scam,” Lind said. “The results of this targeting can be people moved into the home on a fake lease, fraudulent collection of up-front rent and security payments, and outright break-ins.”
Fahsel continued, “Those are just the results today. Tomorrow, things could be both worse and different. That is why Property Shield is actively researching and developing predictive analytic models using AI and machine learning so we can really dive into the data, find trends, and stay ahead of those trends. Doing this means we can offer our clients an opportunity to stay ahead of the fraud.”
Lind concluded, “If you do not have measures in place to prevent and mitigate these types of risks, your assets are liable to fraud.”
The Looming Threat of GenAI
Property Shield prioritizes cutting off fraud at the source, and that means keeping a close investigative eye on tomorrow’s threats, including generative artificial intelligence, abbreviated GenAI. This form of AI can produce a vast array of content, including text, imagery, audio, and something called “synthetic data,” which is defined by IBM Research as “computer-generated information designed to improve AI models, protect sensitive data, and mitigate bias.” Not surprisingly, synthetic data comes with its own set of pitfalls due to its artificial manufacture and the difficulties associated with distinguishing between real and artificial data sets.
“GenAI is going to make distinguishing between real and fake on the internet really difficult,” Lind warned. “In real estate, the ‘fakes’ would be impersonating real estate listing data, and this has real-life consequences when placed in the wrong hands.” Lind warned that GenAI will make bad actors’ “jobs infinitely more scalable, but also more believable.” He added, “This is a dangerous combination.”
Property Shield models are constantly being trained on real-life, real-world data and scenarios, thus equipping the platform to better spot the “latest and greatest” versions of real estate scams the cybercrime world can throw at it. Even more importantly, Fahsel said, the Property Shield system monitors social media posts and listings as well as more traditional real estate listings.
“We are building out machine learning models that can monitor the web from many angles; our real goal is to de-platform the scammers,” he said proudly.
“When we help a company cut down on fraud, it cuts down on the evictions in an area, the victims of fraud in a locale, and the huge damage that can be done to a company’s professional brand if it becomes associated [in the public eye] with people falling victim to fraud.” Fahsel concluded, “I’m so proud to say we have helped our clients save more than half a billion dollars for U.S. renters and homebuyers by shutting these cases down as soon as they come online. It is very fulfilling to run a company that helps clients make a positive impact not only for themselves, but for the larger rental and residential real estate communities.
SIDEBAR 1
By the Numbers
300,000 — Today, Property Shield protects more than 300,000 properties nationwide from online threats.
126 — The number of markets in which Property Shield currently operates
36 — The number of states in which Property Shield currently operates
$53,000 — Amount of money saved in two months by [Case Study] Maymont Homes
71 — Number of fraudulent listings prevented by Property ShielD in Maymont Homes over the first two months
2,207 — Number of fraudulent threats identified and removed over the course of a year during the Maymont Homes case study
$10,000 — Estimated amount, per eviction, each squatter costs Maymont Homes (includes uncollected rent, legal costs, property damage, cleaning fees, opportunity costs, and time)
10% — Maymont Homes estimated 5-10% of fraudulent listings lead to squatter-occupied properties
SIDEBAR 2
The Steady Emergence and Growth of Cyber Fraud in Real Estate
In January of this year, a software developer wired nearly $400,000 to JPMorgan Chase at the request of her broker, who was working with her to place a down payment on a property in a highly desirable San Francisco suburb. This tech-savvy homebuyer, whose resume included time at a cybersecurity firm, was thrilled; she had beaten three other bidders to snag the property. Unfortunately, the next day, her real broker and the real seller sent a real request for that down payment. Sadly, the would-be homebuyer’s life savings were already gone.
CNBC reported on this story in June 2024, noting that real estate scams are particularly attractive to cybercriminals because it is common to wire large amounts of money over the course of a real estate transaction. As hacking techniques and strategies become more invasive and harder to detect, real estate cyberfraud has skyrocketed. In 2015, real estate fraud involving fake deals cost consumers about $9 million in losses. In 2022, those cumulative losses came closer to $446 million, and that tally only includes the consumer side of the equation, not the cost to the property owner.
One of the biggest elements that comes into play in real estate fraud is a sense of urgency, which causes all parties to make decisions more quickly than they normally would. Thanks to the ongoing shortage of housing inventory, there is no need to invent urgency when creating a listing or interacting with a potential renter or buyer. The urgency has been part of the environment for years. CoStar News contributor Paul Owers observed, “Those posing as buyers often use social engineering or the use of deception or manipulation to trick victims.” With only about half of the adult population aware of the significant threats posed by real estate fraud, the potential for real estate-related scams remains rampant.
“This is not an individual scammer trying to rip off another individual,” warned Property Shield CEO Alex Fahsel. “These are sophisticated syndicates using AI, scraping listings, monitoring data like domestic migration patterns, and using it all against property owners and residents.”
SIDEBAR 3
The Maymont Homes Case Study
In May 2023, Property Shield published a case study covering the experience of client Maymont Homes over the first two months of the relationship and, later, updated it to include data once Maymont Homes reached the year-long benchmark.
Maymont Homes was founded in 2011 and was previously known as Conrex Property Management. The company operates in the Midwest and Southeast and has a portfolio of more than 10,000 homes. The case study noted, “As their portfolio expanded, Maymont faced an increasing number of squatters, leading to months of uncollected rent and long legal battles. These issues prompted Maymont to seek a comprehensive solution to address this issue.”
Property Shield also noted this fraudulent activity posed “a severe financial risk for Maymont Homes” and “incidents not only cost the company monetarily, but also tarnished its reputation and strained relationships with clients.”
Property Shield reported it was able to integrate its software into the Maymont Homes platform in less than 12 hours and “with minimal disruption.” The Maymont Homes team was trained and received ongoing assistance in leveraging the software’s capability. Within two months, Property Shield reported, Maymont had:
» Prevented 71 fraudulent listings
» Saved an estimated $53,250
Over the course of the ensuing year, Maymont reported it had, with Property Shield’s help, removed 2,207 fraudulent threats, significantly reduced squatters, and saved U.S. renters a “potential total” of $6.7 million.
Maymont Homes COO, Scott Kelly, described these results as “a major improvement in thwarting scams” and warned proactive protection from real estate fraud “will only be more critical as the economy gets worse this year.”
Read more about the Maymont Homes case study at PropertyShield.co/resources/studies.
