Getting to yes: How AI is redefining success for mortgage lenders

"AI continues to emerge as a powerful assistant for originators to streamline workflows, reduce human bias, fill in knowledge gaps, and uncover the best-possible loan options. For mortgage originators, the first hurdle is gathering and analyzing all the borrower's data, including credit reports, employment verification, pay stubs, tax returns, and bank statements. Instead of entering and rechecking data, artificial intelligence tools can help digitize these documents, extract key fields, and cross-check them against thousands of loan products."

"On the pricing side, AI-powered tools can run borrower data against thousands of loan programs simultaneously. While structured data (FICO, DTI, LTV) is matched with agency and investor guidelines in pricing engines, AI can be incorporated to modify structured data to see if there are improvements to the programs and pricing that have been identified for the borrower helping to ensure the best possible fit."

"This process can also reduce unconscious bias during the early stages of loan qualification. In contrast to humans, technology simply analyzes data such as debt ratios, income stability, and payment history. It's purely mathematical. However, its effectiveness depends on how the models are trained and validated. This process creates a more consistent workflow for originators, allowing them to focus on borrower circumstances, exceptions, and other relevant factors."

Affordability pressures and intense borrower competition require lenders to do more than approve loans; they must find the best product and terms for each borrower. AI helps originators digitize and extract data from credit reports, employment verifications, pay stubs, tax returns, and bank statements, then cross-check that information against thousands of loan programs. AI-enhanced pricing engines can modify structured inputs like FICO, DTI, and LTV to uncover improved program and pricing fits. AI-driven processes can reduce unconscious bias, create consistent workflows, and free originators to address exceptions and borrower-specific circumstances.

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