Case Study
ML Fraud Model Caught £2.4M in First Quarter
A detailed write-up of a real project — what we built, the tradeoffs we made, and what changed for the client.
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What the client asked for vs. what we ended up shipping.
Why. Three or four key technical choices.
Adoption work. Results.
What's next.
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finance banking ai case studyfraud detection case study
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Industry
Risk, fraud, ops, and customer work for banks and fintechs
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Senior-only delivery. Fixed-scope pilots. Your data stays yours.
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