Algorithmic tenant screening is already widespread, disproportionately impacting low-income and other vulnerable renters. We’ve expanded on our original research in California to examine how these practices are impacting renters in Georgia and North Carolina.
Key takeaways
We surveyed renters and landlords to understand how automated tenant screening tech is used by landlords to screen renters in Georgia and North Carolina—and how these opaque algorithms leave both renters and landlords in the dark. Here are our key takeaways.
Georgia and North Carolina surveys confirm California findings: algorithmic tenant screening is prevalent.
- 60% of all surveyed landlords received AI-enabled tenant screening reports, including 57.5% of California landlords, 65% of Georgia landlords, and 63% of North Carolina landlords.
Minority Report-esque predictive analytics are just as, if not more, prevalent in Georgia and North Carolina as in California.
- One in four of the North Carolina landlords received predictive analytics from tenant screening services.
California, Georgia, and North Carolina renters are all often left in the dark, deepening power imbalances that threaten housing rights.
- Only 3% of the roughly 2,200 tenants surveyed across the three states could name the screening or consumer reporting agency that assessed them.
New findings confirm the negative impact of eviction records on housing application decisions.
- Across states, applicants with an eviction record are 84% more likely to have their housing application denied than applicants without an eviction history.
Increased reliance on screening recommendations by smaller landlords is consistent across states.
- Landlords with 1-4 unit portfolios were 5.5% more likely to accept a screening recommendation without additional review than landlords with larger portfolios.
Download the paper below. Want to learn more about how tech is impacting renters? Check out our housing page for more resources.
