Summary of the Study

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Frontcover New Landlord

The New Landlord, a Study on the Three-Part Leasing Strategy, Powered by Big Data, and Artificial Intelligence©

Section 1, What is the Artificial Intelligence-Driven Technology? And the Growth of Data Platforms Toward Analytics for Multifamily Real Estate:

The nature and source of the new AI-driven technology explained, and what the developers of the technology are promising for the billions of dollars they are receiving from the rental housing industry. We look at the market drivers, Greystar, the owner of the shared Operating Platform.  RealPage, the owner of the technology powering the platform, and the various critical IT programs and databases they provide to make the whole leasing strategy work. But, It’s all about the AI-powered platform.

 

The Platform- By the Numbers

The shared RealPage Platform began in 2006 and has become the most widely used in the industry. The platform shares private information on tens of millions of tenants, and a database of over 30 million historical lease records gathered nationwide from over 20,000 apartment complexes. Information on over 18 million units they manage (nationwide 92,000 properties) along with 20 years of recorded data. Includes a database of all apartment properties  (more than  50 units) and all single-family homes built since about 2000.  Including a national database containing every state and county,  municipal laws, ordinances (zoning), and regulations. There are well over 12 thousand platform members. They operate in more than 180 markets across the country and 400 markets worldwide, and the decision-making algorithm sets the rates based on all of this shared data. RealPage provides a dedicated pricing algorithm that connects and flow information to and from multiple algorithms.

 

Section 2, The New Landlords:

We look at the rental housing industry and the massive changes that have recently taken place. Including a deep-dive into the top ten property managers explained their vertical trust organizational structures and detailed their massive financial size and ties to Wall Street. Also, how they operate, the AI technology they are using, and discuss their significant interconnections and consolidations within the industry. At the heart of the issue is the fierce competition for the lucrative property management contracts—tens of billions at stake by fewer and fewer players.

 

Section 3, The Tenant Experience:

Part 1: To test the price-fixing theory, we conducted a detailed rent analysis of the increase in rental rates for two Washington segments. We compared rents in three metropolitan areas where the RealPage platform was deployed to those where it was not.

Part 2: The managers' process to aggressively lock the tenants into those long-term and high-rate contracts is detailed and explained.  Violations in the Fair Credit Reporting Act, Fair Housing Laws, Discrimination, and Debt Collections exposed—they are erecting barriers to housing. This program was found to be one of the Primary Causes of Homelessness.

Part 3: We detail the Effective Rental Rate Program (the new Economic Occupancy)—market manipulation and how the whole process works. In this Study, we outlined the process of how our tenant, who requested a rental rate of $2,400, ended up with housing costs of $2,890 and severely rent-burdened—and how the entire process of increasing that rental payment over the lease contract price was by design.  However, the whole leasing strategy is dependent upon their relationship with Experian RentBureau—the unquenchable thirst for more and more timely data.

The Process of Balancing Supply and Demand:

1. Demand: Simply put, the platform maintains some measure of control over the number of tenants allowed in the applicant rental pool at any given period. When they want to increase or decrease the pool, they simply loosen or tighten their scoring models to match their desired outcome—they tell their operators, “Leave it to us.” [Demand does not provide a constraint to profits]

2. Supply: The Study concluded that, more likely than not, the platform controls the supply of apartment units (controls supply).

  • Economically: supply is considered inelastic (unaffected by price).
  • Self-Regulation: The industry has been left to self-regulate; therefore, regulations do not provide any meaningful constraint to profits.
  • Therefore, the only remaining significant constraint to increasing rental prices appears to lie in the tenant's ability to make that renal payment increase.
  • Enter Experian RentBureau: The knowledge of this constraint matched with Experian RentBureau and all that tenant data, along with the algorithm's prime directive of maximizing profits, sheds light on the relationship's immense value and the co-interdependency for success between its members, the platform, and Experian.

3. Conclusion: Therefore, it appears that the new landlords use Experian to prescreen tenants and improve debt collections. But more importantly, they maintain (in real-time) income data on the tenants that the algorithm uses in establishing the “highest” rent that can be generated to maximize profits for the property owners.

4. The rise in gentrification and homelessness are a byproduct of the pricing model’s programming.

Nevertheless, the players in this process have failed to adequately disclose how they are using the private tenant data to enrich themselves.

The Study includes our findings and recommendations to fix the rental housing industry.

Summary of Study: Document Size: 500 Pages:  160,000 Words. Over 700 Citations