In a small market, comparable transactions are scarce and the data that does exist is fragmented. Vertio turns collateral valuation from a bottleneck into part of the decision.
Property valuation in a small market is a hard problem. There are fewer comparable transactions than in a large market, prices vary sharply by micro-location, and the data that does exist is fragmented. For a mortgage lender, this means collateral valuation is often slow, expensive and based on limited evidence.
We built Vertio to address this. It is a machine learning model trained on Latvian real estate market data that forecasts the value of individual properties. The output can be used in two ways: as an automated collateral assessment during mortgage underwriting, and as an input feature into credit scoring models.
Because Vertio connects to our lending platform, a mortgage application can be scored against a current model-driven valuation rather than a manual appraisal completed weeks earlier. The valuation stops being a bottleneck in the process and becomes part of the decision itself.