Solution · Finance & procurement
Credit decisions, without the backlog.
Applications processed, documents classified, financials extracted, risk scored. Qualifying applications fast-tracked by your rules; the rest recommended with supporting analysis.
Delivers
- Faster decisions
- Rule-based fast-track
- Supporting analysis for every file
- Audit log of every decision
Time to live8-10 weeks
Where it breaks
Credit decisions take days. Volume can't scale.
Manual credit analysis takes days per application. Risk assessment inconsistent across analysts. High-volume periods create dangerous backlogs.
The fix
We process applications, extract financials, and score risk automatically.
- Underwriting time: DaysSame-day for qualifying
- Fast-track: NoneBy your rules
- Underwriter capacity: BottleneckFocused on complex files
What we build
An agent is a stack.
2 capabilities working as one, built in your finance & procurement stack.
- Multi-channel application intake
- Tax return and bank statement classification
- Financial metric extraction
- High-accuracy data capture
- ML risk scoring models
- Rule-based fast-track for qualifying files
- Decision with supporting analysis
- Underwriter sign-off where policy requires it
How it works
Process. Score. Decide.
- Step 01Application arrivesMulti-channel intake captures applications automatically.
- Step 02AI processes documentsFinancial documents classified, metrics extracted, risk scored.
- Step 03Decision deliveredQualifying applications fast-tracked by your rules. The rest recommended with supporting analysis.
Under the hood
Plugs into your stack.
Credit underwriting agent works inside the tools your team already uses, on infrastructure you own. Typically live in 8-10 weeks.
- Credit Bureaus (Experian, Equifax, TransUnion, etc.)
- Banking APIs (Plaid, MX, or your integration)
- Loan Origination Systems (Encompass, Calyx, or your platform)
- Runtime & Orchestration (Trinity by Ability AI)
Time to live8-10 weeks
Questions
Before you ask.
How does ML risk scoring work?
Models are trained on your historical credit performance (defaults, payment patterns, financial ratios) against your lending criteria, and every model change is on the record.
What documents can it process?
Tax returns (1040, 1120, 1065), bank statements, P&L, balance sheets, credit reports. OCR handles scanned and digital documents.
What results should we expect?
Underwriters spend their time on the complex files, decisions arrive faster, and every recommendation comes with its supporting analysis. We agree the measures with you before go-live.
How long does implementation take?
8-10 weeks from kickoff to production. Week 1-3: Data integrations (credit bureaus, LOS). Week 4-6: ML model training on historical data. Week 7-10: Testing and validation.
Do we own the system?
Yes. You own the system. We build the infrastructure in your stack, hand over the keys, and you own it forever - no vendor lock-in.
Next step
Want this in your company?
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