about the books

The introduction of AI-powered technology ushered in the transition from an oil-driven / industrial economy to a data-driven economy representing the most significant economic development in the last 100 years. We are in the midst of a fourth economic revolution, which is seeing the lines between the physical and digital worlds merged ever closer. Technology's transformation is demonstrably game-changing; think of Blockbuster vs. Netflix. The technological revolution entered the rental housing industry in 2002, disrupted it, and presented massive opportunities for those early adopters. However, property managers who were slow or resistant to this change were left behind, so the threat of becoming obsolete was real.

These technology leaders, such as Apple, Google, Amazon, and Microsoft, have set themselves up as benchmark companies. They have introduced data-driven business models that have taken entire industries by surprise—providing operational efficiencies and earning vast sums of wealth. Accordingly, the same pattern of automation and disruption we have seen in other markets is being deployed at a rapid pace throughout the entire rental housing industry.

This book, The New Landlord, details how they implemented the data-driven economy in the rental housing industry. It begins using an industry-wide common pricing platform, the RealPage DOP (referred to as Platform). Through the Platform, landlords access and share all data on their applicants, tenants, and properties. They jointly employ numerous algorithms using shared data to price their rental units for them, thus, avoiding direct competition on pricing---it provides a 50% advantage over their non-using competitors.

In 2019, RealPage acquired a dedicated AI-based screening algorithm for the rental housing industry. It's uniquely supported by a two-sided DOP with Experian. Two-sided platforms solve a transaction-cost problem that makes it difficult for agents in different sectors to get together—in this case, renters, landlords, and Experian, to exchange massive amounts of near-perfect in-real-time data.

The Experian-RealPage connection provides its users an enormous advantage by decreasing losses by 80% while doubling their profits. However, the Platform and its third-party providers have assumed broad authorization and permission to access the data. Failing to adequately disclose how they collect tenant data, use it, and disseminate or share it. However, at what point does unregulated data gathering become an invasion of privacy?

For instance, although RentBureau’s ( now Experian) original purpose was gathering and obtaining tenant data for the pricing algorithm, their relationship now extends much deeper into all phases of the tenant life cycle. For example, their debt collection program increases profits by colluding and establishing a literal housing blockade—holding the tenants as hostages, forcing them into the streets until they paid their prior landlord in full and without due process.

They use economic occupancy, which is the effective rent rate, the total revenue generated on a property, regardless of whether or not it’s occupied. The program parallels the banking’s pre-1960s bait and switch program, which artificially increases the spread between the effective rate of return over the stated or advertised rate. What’s happening is that rather than lumping all costs together under one transparent stated rental rate, landlords break this down into other fees to do a bit of bait and switch with renters. It’s not that the landlord shouldn’t be including expenses like maintenance costs in the rent; it’s that they are separating these out on purpose to be sneaky about higher rates.

However, the problem is more about the abusive methodologies, not the technologies, but the methods that were built into the pricing algorithm that has become the problem. The methodology has been around for centuries, if not longer. However, until now, it lacked the AI-driven power to adequately harness its ancillary generating potential---increasing the spread by nearly 35%.

The stark truth of the pricing algorithm’s core programming is that it's designed to price out the bottom 15% of tenants to maximize profits, referred to as ‘the 15% tenant elimination rule.’ The question remains, how responsible is this pricing program for increasing homelessness?

One of the primary purposes of the Concentration Study was to establish the growth in Platform membership. The study used the number of rental units in the market vs. the percentage that obtained the pricing technology to establish growth. Additionally, the date the operators obtained the technology was verified to establish a correlation between the market concentrations in pricing and the ability to influence the rental rates.

The property management industry is considered profoundly interrelated and interconnected. For example, roughly half of all rental units in Seattle are priced by a small group of 13 managers who originated from a single company. Thus, these culturally connected companies, integrated with deeply connected communications and cooperation through the Platform, have created market power.

The Seattle Concentration Study concluded that they price up to 95% of all rental units through the RealPage industry-wide common pricing Platform. And platform membership concentrations in 2014 contributed to increased rental rates of 40%. Powerful proof that a direct correlation between market share and the ability to influence pricing exists.

Tenants aren’t only ‘priced-out’ due to income inequality, i.e., wealth discrimination, but landlords also jointly discriminate against minorities. It isn’t news to anyone that systemic racism is an issue in America. What might surprise people to hear, however, is that new, modern AI technology is being used to cement racism further into our current housing system. So, what exactly is happening here, and just how widespread is this practice? The study concluded that minorities have more than a 95% chance of enduring housing and pricing discrimination throughout the rental process. For example, in 2016, governing oversight bodies left over 28,000 registered housing discrimination complaints unanswered. Also, 91.5 percent of all acts of housing discrimination occur during the prescreening process [all hidden within the algorithms].

Additionally, a 2017 lawsuit found they categorically forbid anyone from renting an apartment with certain misdemeanors or pending misdemeanor charges which disproportionately adversely affects people of color. Moreover, in 2015, the Seattle Office of Civil Rights filed illegal discrimination complaints against the owners of 13 properties. Our Study found that all 13 properties were part of the RealPage Platform. Chapter 9 details that rather than changing its perspective on Fair Housing and Civil Rights, the Platform embraces qualified immunity to avoid fines for breaking the law.