ResiScore by ATTOM

ATTOM’s ResiScore white paper outlines an AI-driven approach to a longstanding challenge in residential real estate: determining which neighborhoods within a market are most likely to outperform. While market selection is typically fixed, evaluating hyperlocal opportunity has remained inconsistent and difficult to scale. ResiScore by ATTOM addresses this by assigning each residential census tract a percentile ranking within its metro area based on projected home price appreciation over a 24-month horizon, creating a standardized, forward-looking way to compare neighborhoods.

Built on decades of residential transaction data, ResiScore uses a multi-stage AI system to model historical price patterns, forecast future trends, and combine key signals such as trend, appreciation, acceleration, forecast, and volatility into a single composite score. The result is a stable and interpretable ranking that helps identify stronger and weaker neighborhoods, enabling more precise investment targeting, risk assessment, and strategic decision-making at the hyperlocal level.