From simple automation to embedded intelligence: The future of AI in mortgage lending
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From simple automation to embedded intelligence: The future of AI in mortgage lending
"At Blend Forum 2025, our annual executive gathering where more than 100 leaders from the nation's top banks, credit unions, and IMBs came together to talk about the future of lending, one theme stood out. In his opening keynote, Nima Ghamsari, Co-Founder and Head of Blend, put it plainly: the speed of technology adoption is now the defining advantage for lenders. Institutions that move quickly from pilots to practice, with use cases that lower costs and strengthen relationships, will set the pace for the industry."
"Lenders don't need more bolt-on tools that add complexity. They need intelligent systems that sit at the core of origination and actually execute the work. The industry has spent the last decade investing heavily in digitization. Online applications, e-signatures, borrower portals, and automated verifications have transformed the front end of the borrower experience. Those investments paid off in higher pull-through rates, shorter cycle times, and better engagement."
"But the core economics haven't changed. Origination still costs $1012K per loan, cycle times average 2030 days, and exceptions still send files back to human hands. What digitization modernized were the touchpoints, not the process itself. Files sit in queues, documents are checked manually, and quality control happens after the fact. The result is an industry weighed down by rigid workflows while consumer expectations and market pressures accelerate."
Speed of technology adoption is the defining advantage for lenders, with institutions that move quickly from pilots to production gaining market edge. Lenders must prioritize intelligent systems that sit at the core of origination and execute work, rather than adding bolt-on tools that increase complexity. A decade of digitization improved front-end touchpoints—online applications, e-signatures, borrower portals, and automated verifications—but left core origination economics unchanged: roughly $10–12K per loan, 20–30 day cycle times, and persistent manual exceptions. Agentic AI can interpret information, reconcile inconsistencies, and act autonomously while escalating to humans for oversight. The opportunity lies in rethinking process flows, not simply accelerating individual steps.
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