Finance Case Study
Millward Group
A fraud detection system that reduced false positives while catching more real fraud.
-30%False Positives
The Challenge
Where things stood before
When Millward Group first reached out, manual review processes that were both slow and inconsistent was the issue sitting at the top of their list.
Their team suspected the root cause but hadn't had the bandwidth to actually address it properly.
The Solution
What we built
Rather than jumping straight to a fix, we spent time understanding the specific shape of the problem first.
The result was straightforward: a fraud detection system that reduced false positives while catching more real fraud, built specifically around what Millward Group needed.
- Built using Python and Node.js for a stable, maintainable foundation
- Designed around Millward Group's actual workflow, not a generic template
- Tested thoroughly before launch to avoid post-launch surprises
- Delivered within a 4-week timeline without cutting scope
Results
The impact, by the numbers
-30%
False Positives
-45%
Review Time
+51%
Reporting Accuracy
-39%
Close Time Saved
Tech Stack
Built with
PythonNode.jsSQLscikit-learn
Northend Group
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