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Tech, Bias, and
Housing Initiative

Whether you are trying to buy a home, apply for a rental property, or you’re looking for a roommate, there are an endless number of brand new companies and digital products offering to help you do just that. They promise speed, efficiency, and a modern approach to slow and sometimes exclusionary rental or homeownership processes.

These new companies are venture-backed and digitally-enabled—and they play an increasingly influential role in the economy. From new modes of housing construction to automated home buying, tech-enabled companies promise to scale to massive market share and reap higher valuations along the way.

As unprecedented capital investment flows into this space, venture-backed companies’ winner-take-all approach to growth has the potential to exacerbate inequality in the housing space. Under these conditions, startups’ disruption mindset creates a risky landscape that could—without ethical frameworks and processes to ensure equitable outcomes—dramatically accelerate racial and economic inequities.

The Tech, Bias, and Housing Initiative examines these potential harms and biases through comprehensive research, corporate practice, and public policy advocacy.

What we're building

What We're Building

The Tech, Bias, and Housing Initiative has three main components:

Research

We will shed light on spaces where these new classes of companies could exacerbate—or mitigate—racial bias in the housing market.

Policy

In close partnership with other organizations in the housing justice movement, we will develop and advocate for public policy that addresses the harms we identify through our research.

Corporate Practice

We will work with companies who operate in this ecosystem to develop practices, standards, programming, and tools that can help prevent the types of harm identified in our research.

our research papers

Tech bias in tenant screening

It’s time to take a closer look at tenant screening tools that can be the gateway to rental housing and the impact they have on housing accessibility.

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Rent to own the American dream

Aspiring homeowners are turning to alternative home financing options such as rent-to-own. But this model can be just as perilous as it is promising.

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Sold to the highest bidder

Tech is enabling an emerging new class of corporate landlords that exacerbate harm and take advantage of increasingly desperate renters and would-be homeowners.

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Housing + Tech Company Landscape

To lay the groundwork for the Tech, Bias, and Housing Initiative, we developed a landscape of the major subsectors of the venture-backed housing ecosystem. We’ve identified major players in each subsector and shared funding traction, product descriptions, and scale of impact for each company.

Tenant Screening

Tenant Screening

Current Market Size: $3 Billion

Homebuying

Homebuying

60% of home sale transactions by 2025

Home Financing

Home Financing

Market Size:
$315 Billion by 2025

Construction

Construction

Market Size:
$13 Billion by 2025

Shared Living

Shared Living

Market Size:
$14 Billion by 2025

Tenant Screening

Landlords are taking leasing and property management online, relying on automated background checks when selecting renters. Companies use algorithms that score potential renters based on data inputs that are often obscured to both renters and landlords. Click each row for more details about the company.

CompanyTypeCapital RaisedKey Investors
Tenant Screening
Naborly
Risk Assessment Report$8.5 millionTrinity, First Round Capital, Y Combinator
Tenant Screening
RentSpree
Tenant Verification Package$10.4 million645 Ventures, TenOneTen Ventures
Tenant Screening
TurboTenant
Property Management Platform with Tenant Screening$10.2 millionRET Ventures, Access Ventures, Crescendo Capital Partners, FrontRange Capital Partners
Tenant Screening
Avail
Landlord/Tenant Relationship Management Platform$9.7 millionCultivation Capital, Bigfoot Capital, Nameless Ventures, Charmides Capital

Areas for Research

Our initial landscape assessment revealed harms that these tools and business models could potentially exacerbate—ultimately perpetuating bias and inequity in housing. Over the next year, we will explore these issues in depth in our working papers.

Exclusionary Listings

Inaccurate Background Checks

Tenant screening includes background checks that may search outdated or inaccurate databases. In particular, criminal history records can show expunged convictions or unlawful arrests that did not lead to any charges. Eviction records are notoriously inaccurate, which will undoubtedly come into play as the COVID eviction moratoria begin to lift. Landlords may unknowingly make a housing determination based on inaccurate information when they’re only shown the final outcome of an applicant’s third-party assessment, rather than the underlying reports. When this happens, prospective tenants can be barred from housing without justification or their legal right to an individualized assessment.

Exclusionary Listings

Predatory Ownership Schemes

Payment plan, rent-to-own, and home swap homebuying models have historically targeted low-income communities of color with home “ownership” programs that place all of the risk and almost none of the benefit of homeownership onto the borrower. Do rent-to-own and other payment plan homeownership companies put a shine on age-old contract-for-deed schemes that conned homeowners of color out of wealth-building opportunities for generations? How might those contract terms, such as the potential for eviction based on one late payment, exacerbate housing instability for vulnerable people, historically and disproportionately people of color?

Exclusionary Listings

Exclusionary Listings

Companies like Redfin restrict listing privileges and white-glove services to owners with homes valued above a certain amount. Because of longstanding racism in the home appraisal process, this practice can unfairly limit access to tools for homeowners of color, potentially violating the Fair Housing Act.

Exclusionary Listings

Hard-Coding Exclusionary Lending

Many years of exclusionary lending by banks contributed to the housing segregation and racial wealth inequities we see today. If existing housing market data shaped by racist housing policies are used to train loan origination software, bias will be hard-coded in digital home financing products—the very products that promise to expand access to customers that traditional banks have discriminated against. This may cause first-time buyers to be targeted for onerous loan terms and higher interest rates when navigating these pathways to homeownership. Bias in lending decisions will only exacerbate inequity for those who are not served by traditional financing, and could contribute to regressive homeownership costs.