Lending and underwriting automation
Targeting the repetitive parts of underwriting — document review, extraction, summaries — to speed deal flow while keeping judgment human.
A specialty lender reviewing borrower information, documents, and deal terms as part of underwriting.
The problem
Underwriting meant reading documents, cross-checking borrower details, analyzing deal data, and writing up internal summaries. A lot of it was repetitive, slow, and built on manual review.
They wanted more speed without taking human judgment out of the equation.
What we explored
We pinpointed which parts of underwriting AI could realistically support — document review, data extraction, summary writing, and risk flagging being the obvious candidates.
The point was never to replace underwriters. It was to let them get through information faster and more consistently.
The solution
An underwriting assistant that could:
- 01Read borrower documents
- 02Pull out the key financial details
- 03Summarize loan files
- 04Flag missing or inconsistent data
- 05Check deals against lending guidelines
- 06Draft internal credit memos
- 07Leave the final call with the underwriting team
Impact
The goal was less time spent on manual review, faster deal flow, and more consistency across underwriting decisions.
Why this matters
In lending, AI earns its keep when it backs up the decision-maker instead of trying to be one. The sweet spot is usually faster prep, cleaner summaries, and a clearer view of the risk.