CoreLogic has launched Total Home ValueX, a new automated valuation model (AVM) that eliminates the need for multiple AVMs. Building on the existing Total Home Value suite, the new, single model methodology dramatically increases home value accuracy and hit rate for all AVM applications.
“In 2020, the appraisal industry saw an immediate need to shift from traditional in-person appraisals to consistently precise and dependable digital valuation tools — a need that continues to grow and has no end in sight,” said Frank Martell, president and CEO, CoreLogic. “Record low mortgage rates and a home supply shortage has meant home sellers need immediate valuations to remain competitive. This has created an even higher demand for efficient, accurate and reliable valuation tools.”
Traditionally, AVMs were designed with broad applications in mind, requiring businesses to choose between various models. However, this choice creates an additional risk of leveraging the incorrect AVM, which can have long-lasting and negative impacts on business growth and hit rates. To address this industry-wide problem, Total Home ValueX utilizes a singular, uniform model methodology to render highly accurate valuations across all business use cases — without sacrificing hit rate — even on hard-to-value properties.
Total Home ValueX provides current market values for the U.S. residential housing stock. The model leverages CoreLogic’s industry-leading property records that capture 99.9%+ of U.S. properties and span 50+ years, as well as MLS data and newly added data sources not traditionally used in AVMs to support diverse use cases and markets spanning mortgage, real estate, ReTech, FinTech, PropTech, government, insurance and even consumers.
“The market continues to change, and it was time to re-imagine the traditional approach to building AVMs,” said Olumide Soroye, Managing Director, Property Intelligence & Risk Management Solutions, CoreLogic. “This ground-breaking AVM platform is powered by a rich data set that is refreshed daily, cloud computing, and machine learning techniques leading to superior AVM performance that can be validated with independent testing.”
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