Better matching starts with better data
Lender matching is only useful when the package data is clean. Big Tuna connects intake and AhiDoc analysis so teams have more context before choosing partners.
Lender Matching
Big Tuna helps funding teams use application data, document analysis, partner criteria, and workflow rules to decide where a package is most likely to fit before it gets submitted.
Use deal data from intake and document analysis
Organize partner fit by criteria and workflow rules
Support selected submissions through TunaSub
Reduce wasted time on poor-fit submissions
Lender matching is only useful when the package data is clean. Big Tuna connects intake and AhiDoc analysis so teams have more context before choosing partners.
Every funding company has different partner relationships, product mixes, and submission preferences. Matching workflows should reflect the way your team actually routes deals.
Big Tuna does not promise every package will get approved. It helps teams organize deal data, partner criteria, and submission steps so they can make faster, more consistent routing decisions.
Workflow
Start with application data, files, ownership information, requested product details, and team notes.
Use AhiDoc to review statement metrics, competitor activity, risk signals, and deal strength.
Apply partner criteria and workflow rules so the team can submit to the right destinations through TunaSub.
Questions
MCA lender matching software helps brokers and funding teams route packages to partners based on deal data, criteria, and workflow rules. It is meant to improve consistency, not guarantee an approval.
Big Tuna can support matching logic and partner criteria, but your team controls the final routing strategy. The software helps organize the decision and reduce manual work.
Yes. Matching workflows can be customized around your products, partner criteria, submission rules, and internal process.