AI Mortgage Document Processing
The Problem
“Slow, error-prone mortgage document intake and review”
Organizations face these key challenges:
1
High manual effort to sort, index, and extract data from heterogeneous borrower and third-party documents (scans, photos, multi-page PDFs)
2
Frequent errors and inconsistencies (mis-keyed income/assets, missing signatures, outdated disclosures) leading to underwriting conditions, rework, and delayed closings
3
Limited visibility and auditability across document versions and conditions, increasing QC burden, compliance risk, and secondary market exceptions
Impact When Solved
30–50% reduction in document handling time via automated classification, extraction, and LOS-ready data output1–3 day faster clear-to-close through earlier detection of missing items and automated condition identification20–40% fewer document-related defects and stipulations, lowering post-close audit findings and secondary market suspensions