A growing number of real estate companies are now using some form of AI-powered software. The adoption spans across a few use cases but none is more consequential for investors than deal screening. The reason is straightforward. A single mid-sized US city can have thousands of active listings at any given moment. An investor, or a platform serving investors, can’t manually run cap rate and cash-on-cash return calculations on all of them just to find the handful that are worth a closer look. Something has to do the first pass. That’s the job of a predictive score API. Instead of returning raw numbers that still require interpretation, it returns a score. The score is a single value that tells you whether a property is worth investigating further, calculated automatically from the underlying investment data. We built Mashvisor’s Predictive Scores endpoint for exactly this workflow. If you haven’t seen how it fits into the broader API, our overview of the Mashvisor API is a good starting point before diving into scoring specifically. Key Takeaways A predictive score API converts underlying investment metrics (cap rate, cash-on-cash return, rental income, market trends) into a single s...
How to Use a Predictive Score API to Find High-ROI Rental Properties
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