Case study · Financial services · Credit operations
A leading lender marketplaceA document extraction agent that reads what analysts used to retype.
Every application arrives with a stack of financial documents, from complex packets to photos of forms, that someone has to turn into a spread before a lender can make a decision. We built an agent that extracts the financials, spreads the data into the marketplace's format, and flags issues for lender review, so underwriting starts from a judgment call instead of hours of data entry.
The problem
Borrowers upload financial statements in every imaginable format: scanned PDFs, spreadsheets, statements from a dozen accounting systems. Before any lender on the marketplace could evaluate a deal, someone had to manually extract the numbers and build the spread.
Hours of manual extraction before the credit decision could even start.
Spreading is the definition of an expensive, mission critical queue: high volume, error sensitive, and squarely in the path of revenue. Exactly the kind of workflow custom AI should own.
Uploaded financials · deal #4172
6 docsscanned
export
142 pages
scanned
every format an accountant has ever invented
What we shipped
A financial spreading agent, built around the marketplace's own formats and review standards.
Document extraction
Reads financial documents in whatever shape they arrive: complex packets, scanned statements, exports, even photos of forms.
Automated spreading
Normalizes the extracted financials into the marketplace's spreading format, line by line.
Issue flagging
Surfaces anomalies, gaps, and inconsistencies for lender review instead of letting them hide in the spread.
Outcomes
What changed after the rollout.
Less manual intervention
Spreads arrive prebuilt with the source documents linked. Analysts review and approve instead of extracting and retyping.
Cleaner lender review
Issues are flagged up front with the evidence attached, so lenders start from the judgment call, not the data entry.