Stop keying the same statement data by hand
Credits, debits, deposits, average balances, negative days, and NSFs should not require a fresh spreadsheet on every file. Structured analysis gives the team a consistent starting point.
MCA Underwriting Automation
MCA Underwriting Automation
Without Removing Human Judgment.
Big Tuna helps brokers and funders turn bank statements and application data into a structured first-pass review, giving underwriters faster access to the numbers and flags that matter.
Cash-flow and deposit analysis from bank statements
NSFs, negative days, balances, and risk flags
Competitor position and payment pattern detection
Review data connected to lender matching and routing
Surface problems before submission
Existing positions, unusual activity, missing pages, inconsistent balances, and other risk signals are more useful when they appear early enough to change how the package is reviewed or routed.
Keep the underwriter in control
Automation should prepare the facts, not pretend every deal fits a universal score. Your team sets the rules, reviews the evidence, and makes the final credit and submission decisions.
Workflow
Turn raw documents into a reviewable package.
1
Collect the complete file
Bring application data, statements, IDs, entity documents, and supporting files into the same deal workflow.
2
Parse and review
Extract transaction and cash-flow data, summarize monthly performance, and surface the issues that deserve a closer look.
3
Route the decision
Use the reviewed data to qualify the deal, match lenders, request more information, or move the package to submission.
Questions
Straight answers for funding teams.
Can MCA underwriting be automated?
Many repetitive parts can be automated, including document intake, bank statement parsing, metric calculations, risk flags, and workflow routing. Final underwriting decisions should remain under the control of the funding team.
What bank statement data can Big Tuna analyze?
Workflows can analyze deposits, credits, debits, balances, NSFs, negative days, revenue patterns, existing payment activity, and other indicators used during review.
Can analysis feed lender matching?
Yes. Structured application and statement data can be used with your partner criteria to help identify better lender fits before submission.