Optimal Blue, a mortgage technology provider, is accelerating artificial intelligence deployment through its new AI Labs initiative. Kevin Foley, the company's leader on this front, outlined how the division will compress timelines for bringing AI tools to market.
The Virtual Economist stands out as the first major product from AI Labs. This forecasting tool pulls from public economic data and proprietary lock data covering 35% of mortgage volume across the market. It generates predictions on interest rates and lock behavior, giving lenders visibility into market trends before they fully materialize.
For mortgage lenders, this matters immediately. The Virtual Economist provides early signals on rate movements and customer lock-in patterns. Lenders can adjust pricing, staffing, and pipeline strategy before competitors react to changing conditions. A lender watching Virtual Economist forecasts gains weeks or months of lead time on market shifts.
Brokers benefit from clearer pipeline visibility. When the Virtual Economist signals rising rates or falling locks, brokers can tighten communication with borrowers and push closings forward. Conversely, when forecasts show declining rates, brokers can advise clients to wait, protecting relationships and repeat business.
Borrowers see indirect benefits through faster loan processing. Lenders using Virtual Economist insights optimize their operations, reducing turn times and closing delays. Better rate predictions also help borrowers time their locks more intelligently, though advisory quality depends on their broker's sophistication.
Optimal Blue's AI Labs framework represents a structural shift in how the mortgage industry innovates. Rather than pushing out finished products annually, the company now operates a rapid-deployment model. This speeds product iteration and lets Optimal Blue respond to market feedback faster than traditional development cycles allow.
The 35% lock coverage is substantial. It reflects Optimal Blue's central position in the mortgage ecosystem, giving the Virtual Economist dataset depth that smaller competitors cannot match. This data moat