AI house valuation: how it works and how accurate it is

A traditional property valuation (tasación) works like this: a certified valuer visits the property, takes measurements, checks its condition, looks at comparables in the area and issues a report that takes between 3 and 10 days and costs between €250 and €500. Valuation with artificial intelligence works very differently: it analyses millions of data points simultaneously in seconds and can give you an estimated value with a margin of error below 5% in data-rich markets.

What data an AI valuation system analyses

AI property valuation models (known as AVMs, Automated Valuation Models) simultaneously process:

• Actual transaction prices in the area (notaries, land registries)
• Current asking prices on property portals (Idealista, Fotocasa, Pisos.com)
• Property features: floor area, floor level, orientation, state of repair, year of construction, energy certificate
• Local area data: proximity to transport, amenities and green spaces, and the socio-economic profile of the neighbourhood
• Historical price trends in the area
• Macroeconomic variables: Euribor, local employment, new supply under construction

Why it can beat a traditional valuation

A traditional valuation has structural limitations: the valuer can only consult a limited number of comparables, their judgement is subjective in certain respects, and the time between the visit and the report introduces a lag. AI, on the other hand, processes tens of thousands of transactions, removes subjective bias and works with data updated in real time.

That said, AI has its own limitations: it works best where there's more data (big cities, liquid markets) and less well in rural areas or with very unusual properties, where comparables are scarce.

What AI valuation is used for in practice

• Checking whether the price you're asking, or being asked, is reasonable before negotiating
• Estimating the market value of an auction asset without needing a formal valuation
• Managing large-scale asset portfolios at banks and investment funds
• Comparing assets in different areas with the same objective metric

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