Bulk valuation of real estate assets is a key tool in portfolio, market and macro-economic analysis.
AI models enable highly accurate estimation of the value of real estate portfolios by merging macroeconomic information with asset-specific characteristics in the database or automatically extracted from public or private data repositories.
To perform automated valuations of real estate portfolios, replacing statistical models introducing portfolio-level biases or manual models requiring more than one minute of analysis per property.
The system must be flexible faced with the variable quality of the information on the asset to be valued. It must be able to work with a detailed record or with a simple address or property tax registry number (referencia catastral), and must always report the confidence range of the prediction.
To be user friendly, the system must be usable through an API that supports full asset portfolios and returns estimates, margins of error and confidence ranges in an individual form for each asset.
The tool developed by Foqum was rated as Top 3 by the Spanish Association for Value Analysis (AEV) in a blind test, committing errors under 1% compared to official valuations in portfolios of more than 1,000 assets.
The speed of the model allows portfolios of thousands of assets to be valued in 30 seconds, forming a key part of more complex systems such as Cajamar, which uses real estate valuation as part of the analysis process.