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Case Study
Revolut: $4M Growth Opportunity Identified
AI-powered analysis of 200K+ transactions revealed profitability drivers that manual analysis would have taken weeks to find.
The Challenge
Revolut needed to analyze over 200,000 transactions to understand profitability drivers. The manual approach - spreadsheets, pivot tables, analyst hours - would take weeks and still might miss patterns in the data.
They needed insights faster, and they needed to find patterns that human analysts might overlook.
The Solution
AI-Powered Analysis Pipeline
Built a system that could process the entire transaction dataset, applying AI to identify patterns, correlations, and anomalies.
Automated Pattern Recognition
The AI identified profitability drivers across customer segments, transaction types, and time periods - insights that would be nearly impossible to find manually.
Actionable Insights Delivery
Findings packaged into clear recommendations with supporting data. Not just "what" but "why" and "what to do about it."
The Results
- $4M growth opportunity identified through pattern analysis
- Weeks of work compressed into hours
- Patterns discovered that manual analysis would have missed
- Repeatable process for ongoing analysis
Watch the Walkthrough
What Would This Look Like for You?
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