How a Tier-1 Bank Validated 7,000 Investor Records with AI

Financial data verification is unglamorous, high-stakes and brutally repetitive — exactly the work manual QA burns out on and spreadsheets get wrong. One tier-1 bank needed to validate roughly 7,000 investor records against a new statement system without a single row leaving their network.

Data-driven, not hand-written

Instead of scripting thousands of near-identical checks, the team authored one data-driven test and pointed it at a CSV of records. Each row became a run: load the investor, then assert that balances, holdings and tax figures matched the source of truth.

Zero egress, by design

Because the records were regulated, execution ran on an on-prem agent inside the bank's own VPC. The application, the data and the PII never crossed the perimeter — only pass/fail results came back to the dashboard.

The result: a verification pass that used to take a squad weeks ran in a controlled window, with every discrepancy logged and traceable — and a reusable test the team now runs on every statement release.