Federal regulators want to know how JPMorgan Chase, Mastercard and other companies may use people’s personal data to sell them a product at a different price than what other consumers might see.
The practice — which the Federal Trade Commission calls “surveillance pricing” and which is also known as dynamic pricing or price optimization — has long been used by retailers such as Amazon and Walmart, along with ride-sharing providers, to boost profits.
More recently, companies have deployed artificial intelligence and other advanced software tools to collect personal information about consumers, including their location, credit history, device type, and browsing or shopping history, which can then be used to individualize prices.
“Firms that harvest Americans’ personal data can put people’s privacy at risk. Now firms could be exploiting this vast trove of personal information to charge people higher prices,” FTC Chair Lina Khan said Tuesday in a statement regarding the agency’s inquiry. “Americans deserve to know whether businesses are using detailed consumer data to deploy surveillance pricing, and the FTC’s inquiry will shed light on this shadowy ecosystem of pricing middlemen.”
A spokesperson for JPMorgan Chase declined to comment. A spokesperson for Mastercard also declined to comment, but said the credit card giant is cooperating with the FTC.
The agency is also seeking information from six other companies as part of its review of surveillance pricing: management consulting firms Accenture and McKinsey & Co., and retail technology makers Bloomreach, PROS, Revionics and Task Software.
Specifically, the FTC is asking the companies named in its inquiry to provide information on the surveillance pricing products and services they have developed or licensed to a third party, including how they’re used. The agency is also examining how those products and services can affect the prices consumers pay.
In a blog post, the FTC pointed to media reports that a growing number of retailers and grocery stores may be using algorithms to set targeted prices for different consumers.
“Advancements in machine learning make it cheaper for these systems to collect and process large volumes of personal data, which can open the door for price changes based on information like your precise location, your shopping habits or your web browsing history,” the agency said. “This means that consumers may now be subjected to surveillance pricing when they shop for anything, big or small, online or in person — a house, a car, even their weekly groceries.”
Lawmakers are also looking at the impact of dynamic pricing. In May, Sen. Sherrod Brown, D.-Ohio, held a hearing examining how such retail technologies may have contributed to ferocious inflation during the pandemic.