AI transformation for specialty finance, payments and fintech operations
Financialservices
Native puts AI agents into credit, onboarding, servicing and reconciliation for specialty finance, payments and fintech teams. Pilots live in weeks.
Where AI has an impact in financial services
Credit application drafting
A full applicant pack turned into your own application format, with every figure traced to its source page.
Financial statement spreading
Several fiscal years spread into your template, with the balance sheet tied out before anything is generated.
Credit narratives
A written credit narrative drafted at the depth your analyst chooses, ready to edit.
Onboarding and KYB
Business applications checked for validity, not just presence, with the follow-up request drafted the same day.
- Reconciliation
- Collections and servicing
- Dispute and chargeback packets
- Portfolio enrichment
Native helps specialty finance, payments and fintech companies put AI agents into the operations work behind every account: credit applications, onboarding, servicing and reconciliation. The agents read the documents, apply your rules and hand your team a finished draft to approve. A first workflow goes live in weeks, and the whole operations function can work AI native within months.
Case study · A captive equipment-finance lender
An equipment-finance lender cut dealer credit applications from days to minutes.
Native helped a captive equipment-finance lender turn each dealer's document pack into its own credit application. A draft that took an analyst three to four days now takes under fifteen minutes, and every figure traces back to the page it came from.
The challenge
Each dealer floorplan application arrived as a pack of eight or nine documents: financial statements, tax returns, credit reports, personal financial statements and earlier credit memos. Analysts keyed them into a two-sheet workbook by hand, reconciled documents that disagreed, and wrote the credit narrative from scratch.What we built
- An extraction layer that reads scanned, faxed and dealer-system statements, ranks sources so tax returns win a conflict, and flags any year with low scan quality.
- A spreading agent that fills the lender's own workbook across five fiscal years and refuses to generate anything until the balance sheet ties out.
- A narrative agent that drafts the credit write-up at three depths, enriched from the lender's portfolio tables and cited web research, for the analyst to choose and edit.
The result
Analysts start from a complete, checked draft instead of a stack of PDFs, and the decision on every application stays with the credit team.Frequently asked questions
What does an AI transformation partner do for a financial services company?
An AI transformation partner maps how documents and decisions move through your operations, finds where files wait, and builds agents that do the reading, checking and drafting inside your systems. At Native the same forward-deployed engineers who map the work build the agents and stay until they run in production.
Can AI make credit decisions?
AI can assemble the file, spread the financials, run the policy checks and draft the recommendation. The decision itself stays with your credit team, and the line between the two is written down before anything goes live.
How do you keep financial data secure when using AI?
Everything is built in your own cloud accounts, with models that do not retain your data, the narrowest access each agent needs, and a log of every action. See our security page for the controls.
Where should a lender or fintech start with AI?
Start with the document-heavy step your analysts like least, usually credit application drafting or onboarding review. The rules are known, the volume is steady, and the impact is visible within weeks.
How long does it take to put an AI agent into production in financial services?
A first agent typically reaches production within weeks. Taking a whole operations function AI native, from onboarding to servicing, takes months rather than years.
