Attom. a curator of land, property data and real estate analytics, has debuted Transparent Owner, a new data product that identifies the true individuals behind residential property ownership in the United States.
Transparent Owner is built using proprietary identity resolution techniques that combine public record data, machine learning and advanced linking logic to uncover and connect beneficial ownership across properties and geographies. By assigning standardized Owner IDs and resolving inconsistencies in how names appear in public filings, the dataset provides a clearer and more actionable view of who actually controls a property.
“Property ownership has gotten more complex, and public records do not always tell the full story,” said Todd Teta, chief product and technology officer at Attom. “Transparent Owner helps our clients cut through that complexity and see the real picture, whether they are vetting a deal, analyzing portfolios or building compliance checks.”
Key features of Transparent Owner include owner name standardization that normalizes thousands of variations in how individuals, LLCs and trusts are recorded across jurisdictions; entity matching that solves owner identities across counties and legal entities using geographic, linguistic and behavioral signals; assignment of a consistent, persistent identifier to each owner; mailing address linkage and classification of owners into types such as Person, Investor, Lender, Company, Education or Government, based on ownership patterns and scale.
Transparent Owner is now available as a licensed dataset delivered via Snowflake. It integrates with other Attom data products through shared identifiers, enabling clients to build a more complete picture of residential ownership and investment activity.
