Solution
For lending operations, credit teams, and portfolio managers: every borrower package collected, classified, and gap-checked into one structured file before underwriting starts.
The problem
Missing K-1s and stale financials are discovered when an underwriter finally opens the file — weeks after the borrower could have fixed them cheaply.
Analysts spend the front of every deal chasing documents, matching them to checklists by hand, and re-requesting what already arrived under a different name.
What arrives is a folder of scans and attachments. Spreading, verification, and the credit memo all wait until someone turns it into a file.
The product, not a promise
How it works
Take in borrower financials, statements, and supporting documents from every channel and format.
Identify each document and slot it against the required checklist for the deal.
Pull the identifying details and key figures that make the file searchable and checkable.
Flag gaps, stale periods, and missing schedules so the chase happens before underwriting starts.
Deliver one structured lending file, indexed and source-linked, ready for analysis.
Who it's for
Loan operations analyst
Head of lending operations
CIO / IT
Every deal starts the same way: a borrower, a checklist, and a package that arrives incomplete. Financial statements come as scans, tax returns are missing schedules, bank statements cover the wrong months — and the gaps surface only when an underwriter finally opens the file, weeks into the process. Borrower Intake & Document Collection owns that gap and closes it at the front of the pipeline.
The agents collect whatever the borrower sends — any PDF, scanned or digital, Excel spreadsheets, Word documents, web-based data — across every channel. Each document is classified against the deal’s required-documents checklist, and the identifying details are extracted: entity names, statement periods, tax years, account numbers. Cross-format document intelligence means a handwritten schedule and a clean digital statement land in the same structured file with the same treatment.
Completeness checks run continuously. A missing K-1, financials that are a fiscal year stale, an unsigned document — each gap is flagged specifically while there is still time to fix it cheaply, instead of stalling underwriting later. What comes out is a single structured lending file: indexed, complete, and organized the way your credit process expects, with every document and extracted field linked back to its source.
The intake file is the foundation for everything downstream — capacity analysis, verification, credit memo, review. If the foundation is untraceable, nothing built on it holds up. Here, every classification and extraction is recorded with its source citation, every completeness decision lands in the audit trail, and policy-governed workflows enforce the same intake standard on file one and file one thousand. Human reviewers step in at the decision points that matter, and the assembled file moves into your loan origination and document management systems through pre-built connectors — so a regulator-ready package is the default output of intake rather than a later reconstruction.
Objections, answered
Classification confidence is scored, and anything uncertain is flagged for human review rather than filed silently. Every classification is recorded with its source, so a reviewer confirms in one click instead of re-reading the package.
Yes — documents are classified against your checklist for the specific deal type, not a generic list. Completeness is measured against what your credit process actually requires.
Inside your governed environment, with access controls and an audit trail on every classification and extraction. The assembled file moves into your loan origination and document management systems through pre-built connectors.
Intake reads formats the platform already understands — scanned PDFs, Excel, Word, web data. Setup is loading your checklists and connecting your intake channels: configuration, not a development project.
Watch a raw inbound pile become one indexed, gap-checked lending file live in the demo.
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