Equifax: Data Practices

How This Data Gets Used

The data points listed above are not collected in isolation. Equifax combines these signals into comprehensive user profiles that enable real-time behavioral prediction, targeted advertising, and in many cases, sales to third-party data brokers and government agencies. The cross-referencing of seemingly innocuous data points like device identifiers with sensitive information like location history creates a surveillance capability that far exceeds what most users understand when they agree to terms of service.

Internal documents and regulatory investigations have revealed that Equifax retains much of this data indefinitely, even after users request deletion. Backup systems, analytics pipelines, and machine learning training datasets often preserve personal information long after the user-facing copy has been removed. This creates a permanent digital footprint that users have limited ability to control or erase.

Privacy researchers estimate that Equifax generates over 600 derived data points per user by combining the raw signals above with probabilistic modeling, purchase prediction algorithms, and behavioral clustering. The resulting profile is far more detailed than what any single data point would suggest, and it is this composite profile that drives the majority of Equifax's revenue through targeted advertising and data licensing arrangements.