EXECUTIVE INTELLIGENCE
PLATFORM FOR A
REGIONAL BANK.

A $4B regional bank's executive team was making critical strategic decisions using data that was already three days old. Their reporting process required a team of analysts to manually extract data from eleven separate systems — core banking, CRM, loan origination, treasury management, and more — then reconcile it all in spreadsheets before distributing a static PDF.

The CFO described the situation bluntly: "We're flying the plane by looking out the rear window." Leadership needed real-time visibility, consistent metric definitions, and the ability to drill into anomalies without waiting a week for the next report.

We started with two weeks of discovery — not just auditing their data systems, but interviewing every executive to understand how they actually used data to make decisions. What we found was that the problem wasn't the systems themselves; it was the absence of a single, trusted semantic layer that everyone agreed on.

We designed a modern data stack: Snowflake as the central warehouse, dbt to build a versioned, tested metric layer, and Airflow to orchestrate the ETL pipelines from all eleven source systems. For the front end, we built a custom React application with role-based views — the CEO sees a different cut than the Chief Credit Officer.

On day one of go-live, the Monday morning executive review — previously a 90-minute meeting built around a static PDF — ran in 22 minutes. The leadership team could see live data, ask questions, and drill into the numbers on a shared screen rather than debating whose spreadsheet was right.

Within 60 days of launch, the bank had identified two under-performing branches and a deposit concentration risk that hadn't been visible in the old reporting. The CFO estimated the first-year ROI at roughly 8× the cost of the engagement.