Neighborhood performance has long been difficult to measure at scale. Attom is launching a tool that aims to change that.
Attom has introduced ResiScore, an artificial intelligence-powered analytics offering that ranks residential neighborhoods by projected housing market performance.
The tool assigns each residential census tract a percentile ranking from 1 to 100 within its metropolitan area based on expected home price appreciation over a 24-month horizon, according to the company. It is built on technology from ResiShares, which Attom acquired in January 2026.
ResiScore pulls from decades of residential property data, combining signals, including long-term price trends, recent appreciation, price acceleration, forecasted growth and volatility, into a single composite score, Attom said in a statement. The model is designed to balance responsiveness with stability, avoiding overreaction to short-term market shifts.
“ResiScore builds on our strategy to deliver AI-powered property intelligence through our data foundation and enterprise data licensing,” Rob Barber, CEO of Attom, said in a statement. “Our clients have always relied on us for comprehensive property data, but they have not had a consistent way to evaluate neighborhoods within a market at scale.”
“The gap between the strongest and weakest neighborhoods within a single market is often larger than the gap between markets themselves,” Aaron Wagner, head of data science at Attom, said in a statement. “By ranking neighborhoods within a market by expected appreciation, ResiScore helps clients identify where upside is emerging, and where downside is building.”
Attom said the tool supports investment targeting, lending and portfolio risk assessment, site selection and market analysis. It also works alongside the company’s existing automated valuation models to give users a broader view of property value and neighborhood performance.
ResiScore is available through Attom’s data delivery platforms, including bulk data licensing and Snowflake.
