New nCino Mortgage Solution feature reduces manual paystub and W-2 review, helping lenders qualify borrower income earlier at lower cost
nCino, the leading provider of intelligent, best-in-class banking solutions, announced the launch of nCino Doc VOI powered by Argyle, a new feature within the nCino Mortgage Solution designed to help banks, credit unions and independent mortgage lenders verify borrower income more efficiently.
Lenders increasingly automate verification of income (VOI), a critical requirement in mortgage underwriting, using direct-source, consumer-permissioned connections to payroll and bank account data. These real-time connections can satisfy income verification requirements in a majority of loan files. When they are unavailable, lenders traditionally rely on time-consuming manual review of borrower-provided paystubs and W-2s. nCino Doc VOI replaces that manual process with automated data extraction and analysis, enabling fast, cost-effective income verification across the mortgage pipeline.
nCino Doc VOI integrates with Freddie Mac AIM Check API, allowing lenders to submit document-derived income data to the API for automated income assessment early in the underwriting process, prior to a full Loan Product Advisor® (LPA®) submission. This document-based income verification can also support assessment of representation and warranty relief eligibility related to the income calculation when submitted to LPA.
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“Income verification remains one of the most operationally intensive steps in mortgage lending,” said Casey Williams, general manager of Global Mortgage at nCino. “nCino Doc VOI lets lenders extend automation across more of their pipeline, qualify borrowers earlier and reduce manual touchpoints without introducing new systems or added complexity.”
“No single verification method covers every borrower scenario,” said John Hardesty, senior vice president of revenue at Argyle. “By bringing Argyle-powered Doc VOI directly into nCino, lenders can extend automation across a much larger share of their pipeline, qualify more borrowers and significantly reduce the manual reviews that slow down operations.”
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