The Challenge
What FinBot Was Facing
FinBot had built powerful AI that processed financial data automatically — but the surrounding operational workflows were entirely manual. Staff hand-triggered AI processes, copied outputs between systems, and chased exception approvals over email threads. Despite the AI investment, month-end close still consumed three full business days because humans, not the technology, were the bottleneck.
The Solution
What We Built
We built an end-to-end automation layer that connected FinBot's AI engine to every downstream system: automatically triggering analysis when new data arrived, routing low-confidence exceptions to the right reviewer with full context pre-populated, pushing approved outputs downstream without manual intervention, and generating client summary reports on schedule — with zero human involvement in the standard flow.
Results