The US rental housing market has experienced significant turmoil recently as soaring prices have made it difficult for millions of Americans to keep a roof over their heads.
A company called RealPage has been scrutinized for its role in this crisis as its property management software helps landlords determine the price at which they will rent.
RealPage collects data from thousands of properties and uses an algorithm that analyzes vacancy rates, unit prices, and other similar metrics to suggest the most optimal rental prices.
Although its service seems harmless at first glance, the company’s reach and the widespread use of its software have resulted in a de-facto rent-fixing scheme that translated into inflated rental prices across multiple states.
RealPage’s Omnipresence in the US Exacerbates Rent-Fixing Issues
The scale of RealPage’s influence in the marketplace is significant. Estimates indicate that its software is used to determine rental prices for over 16 million units nationwide – which represents a little more than a third of the total renting households in the country.
Meanwhile, the company has a presence in 40 markets within the United States while up to 60% of multifamily units could be relying on its platform and algorithm to determine how much they will charge for rent.
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Even though RealPage claims that they have a much smaller market share of just 7%, critics believe that its algorithm is being used widely and could be one of the main factors causing elevated rent inflation figures in the US lately.
Rent prices have increased by 19% to 33% since 2020. The largest increases have been seen in lower a mid-tier departments rented to low-income tenants and households. Statistics show that renters are spending up to 30% of their income on housing while rising shelter costs now reportedly account for two-thirds of the country’s inflation levels.
Although it is quite difficult to estimate the impact of RealPage’s algorithm on inflating rent prices, analysts have calculated that tenants may pay between $234 and $491 more than they would if the price-fixing scheme was dismantled.
Algorithmic Collusion Could Be Considered a Far-Fetched Legal Argument
RealPage has drawn scrutiny from regulators due to the software’s inner workings. Competing landlords have to share sensitive pricing information with a single platform and that puts the company in a unique position to be able to fix rent prices to their best interest.
Collusion in the digital era appears to be easier as information that was previously inaccessible and scattered across the market has now been centralized by platforms like RealPage.
The algorithm is designed to optimize rental prices and that can be accomplished by providing similar recommendations to landlords that keep prices at or above a certain level. The widespread use of the software makes the problem worse.
For law enforcement agencies, building up a case against RealPage is tougher than usual as it requires the interpretation of price-fixing laws and their application to new scenarios like this that involve the use of an algorithm and not actual verbal or written communications between the alleged colluders.
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Lawsuits have been brought against RealPage already in the states of Arizona and Washington. These cases allege that the company has conspired to keep rent prices high and has violated antitrust laws as a result of its algorithm’s design.
However, proving antitrust violations in these cases remains challenging. Under existing antitrust law, showing that companies used a common algorithm to raise prices isn’t enough; plaintiffs need to show that there was some kind of agreement between the companies, and they need to allege a specific factual basis for that agreement before they can formally request evidence of it.
Plaintiffs need evidence to make their case, but can’t access that evidence without first making a plausible allegation of collusion.
Algorithmic Price Recommendations Could Distort Prices in Other Industries
Shelter costs are a significant component of the United States Consumer Price Index (CPI), the key inflation metric for the country. Hence, the impact of price-fixing for rental prices has huge implications on inflation rates.
This distortion can lead policymakers like officers from the Federal Reserve to make decisions based on faulty information as their monetary policy is commonly shaped based on how inflation evolves within the country’s economy.
Moreover, rising rents appear to affect lower-income households disproportionately and potentially exacerbate economic inequality.
The concerns raised by RealPage’s rental pricing algorithm are not unique to the housing market. Similar practices are being observed and challenged in other industries. RealPage’s subsidiary, Rainmaker, faces legal challenges for allegedly facilitating price-fixing in the hotel industry.
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Some health insurers have also been accused of using shared algorithms to coordinate pricing while allegations of algorithmic collusion are emerging in industries such as tire manufacturing and meat processing as well.
As awareness of algorithmic price-fixing grows, policymakers and regulators are beginning to respond.
This year, a group of Senate Democrats led by Amy Klobuchar introduced a bill that would update existing antitrust laws to address algorithmic collusion. The proposed legislation would create a legal basis to prevent companies from engaging in a price-fixing agreement when “competitors share competitively sensitive information through a pricing algorithm to raise prices.”
The challenges of regulating algorithm-based price recommendations will likely increase now that artificial intelligence (AI) has made its way to marketplaces and other similar software.
These programs could use the vast information they have at their disposal and may break the law unknowingly by fixing prices to the benefit of the customers they serve. Although they may not be explicitly instructed to do so, they could figure out that the optimal outcome is one where landlords as a group make more money in general.
As more businesses adopt AI and machine learning tools for pricing, the potential for algorithmic collusion could spread to a wide range of industries and markets.
Authorities Start to Crack Down on Algorithmic Price Recommendations
Some local governments are taking matters into their own hands. In early 2024, San Francisco passed a groundbreaking ordinance that bans “both the sale and use of software which combines non-public competitor data to set, recommend or advise on rents and occupancy levels.”
The Federal Trade Commission (FTC) and the Department of Justice have also issued guidance on the application of antitrust law to algorithmic pricing. The agencies emphasized that using an algorithm to evade laws banning price-fixing agreements is still illegal and that an agreement to use shared pricing recommendations, lists, calculations, or algorithms can be unlawful even if co-conspirators retain some pricing discretion or occasionally deviate from the recommendations.
As lawmakers and regulators keep struggling to find legal alternatives to limit the impact of algorithmic price recommendations in markets like rental properties and insurance, Democrats have kept blaming platforms like RealPage for negatively impacting inflation rates.
As the debate continues, several key questions will need to be answered:
- How can antitrust laws be updated to effectively address the challenges of algorithmic collusion?
- What responsibility do software providers like RealPage have in ensuring that their tools don’t facilitate anti-competitive behavior?
- How can regulators balance the benefits of technological innovation with the need to maintain truly competitive markets?
- What role should transparency play in the use of pricing algorithms, particularly in essential markets like housing?
The answers to these questions will shape not only the future of the rental market but also how technological tools assist companies and help them optimize their financial performance without breaking the law.