24× employee productivity. In production.
The challenge
The lender's own growth was the constraint. Every loan application arrived as a package of unstructured financial documents — bank statements, company accounts, director information, supporting evidence — read, extracted, and validated by hand before it could reach credit decisioning. The only lever was adding people, but manual processing does not scale the way a fintech needs: headcount grows linearly, consistency drifts, and a bottleneck forms exactly where deal velocity matters most. The work was structured and rule-bound, yet trapped inside a manual process.
Our approach
Ariviti deployed an intelligent document-processing workflow on TurfAI: ingestion of each application package, classification by document type, field extraction into structured data, validation with confidence-threshold exception flagging, human-in-the-loop on exceptions only (reviewers get the partial extraction with the uncertain fields pre-identified), and structured output into the existing credit-decisioning system. Integration was via REST API into the lender's platform — no downstream migration — and the workflow was live within weeks. Delivered through Ariviti's Virtual Technology Office (VTO) model: the outcome owned end to end and accountable through go-live.
The result
24× employee productivity on loan-document processing. Live in production at scale, with standardised output quality and growth decoupled from headcount — deal velocity no longer gated by processing capacity.
