How Data Brokers Collect Facts, Then Guess at Your Health and Finances

From information to predictions

Data brokers may collect details such as addresses, phone numbers, relatives’ names and estimates of home values. They then analyze information from different sources, using algorithms to sort people into categories and predict their behavior.

The resulting profiles can include estimates about health, finances, religious beliefs and vulnerabilities. Some may be inaccurate, while others may reveal sensitive details people did not intend to share. Depending on the company and information involved, profiles may be sold or shared with businesses unfamiliar to the people described.

Sensitive audience labels

The Federal Trade Commission documented brokers combining information from multiple sources to infer characteristics such as income, religion, political views and health conditions. These labels were generated from data rather than written by the people classified.

The FTC also documented companies using location information to form targeted advertising audiences. InMarket offered categories including “Christian church goers,” “parents of preschoolers” and “wealthy and not healthy.” The FTC later restricted InMarket’s use and sale of sensitive location data.

Health data and protections

Oracle’s BlueKai advertising business helped advertisers target consumers using extensive data. Oracle shut down its advertising products in September 2024, but the company’s history illustrates the sophistication of the industry.

Financial profiles and risks

A label does not need to be accurate to influence how a company views someone. The article also notes that browsing activity can help data brokers develop detailed profiles, even when people are simply using the internet.