From messy borrower docs to a finished memo in minutes

Commercial credit has a speed problem that everyone has quietly accepted. A single deal can sit in analysis for weeks, not because the decision is hard, but because the work in front of the decision is slow, manual, and repetitive.

The five weeks nobody talks about

Walk a deal backward from committee and the time disappears into a handful of places:

• Spreading. Analysts re-key multi-year statements into a template, line by line, reconciling subtotals by hand.
• Chasing documents. Tax returns, AR/AP aging, inventory, borrowing-base certificates, each in a different format, each requiring interpretation.
• Writing the memo. A first draft of the borrower overview, financial analysis, risks, and recommendation, mostly assembled from scratch.

None of this is judgment. It is data entry wearing a suit.

Compressing the work, not the rigor

The instinct when people hear “AI for credit” is to assume corners get cut. The opposite should be true. The goal is to remove the manual labor around the decision so your team spends more time on the decision itself.

That means three non-negotiables:

1. Every number traces to its source. If you can’t click a figure and land on the exact page it came from, it doesn’t belong in the spread.
2. The math is deterministic. Ratios and coverage come from a transparent engine, not a model guessing. Same inputs, same outputs, every time.
3. The human still decides. The AI drafts; the analyst verifies and signs.

What changes day to day

When spreading and the first draft take minutes instead of weeks, the shape of the job changes. Analysts move from transcription to review. Relationship managers stop waiting on analysis to get back to the borrower. And the institution can simply look at more deals with the same team.

That is the entire thesis: compress the work, keep the rigor, deploy more capital.