AI-driven compliance checks
A nationwide non-bank lender embedded AI into the application workflow to check identity, income, credit and policy on every file, with a full audit trail.
- Manual QA
- About 10%
- of applications sampled, after settlement
- With Trippl
- 100%
- checked in real time, before decisions are final
The case in three parts
The challenge
- Manual QA could only sample around one in ten applications
- Policy breaches were found after settlement, when they were expensive to fix
- Growing volumes meant more QA staff, or more risk
- Regulators expected every decision to be explainable
What we built
- AI that reads payslips, statements and IDs as they arrive
- Lending policy, credit rules and QA checklists applied to every application
- Clean cases routed straight through, exceptions sent to a QA officer
- Every check logged with its reasons for audit
What changed
- 100% of applications checked in real time
- Issues caught before decisions are final, not after settlement
- QA time spent on genuine exceptions
- A traceable, audit-ready record for every decision
Compliance moves from a sample checked after the fact to every case checked as it happens. That is the pattern we bring to every regulated workflow.
Have a workflow like this?
Start with the rules that carry the most risk.
- hello@trippl.co
- Office
- Ponsonby, Auckland 1021
- Teams
- Auckland and India