Fintech / banking

Cutting fraudulent transactions by 75% for a bank

Consulting independently across fintech and banking, I built a fraud-detection model that sharply cut losses - one of a series of predictive systems delivered for measurable business outcomes.

-75%
Fraudulent transactions
+60%
Lead engagement (chatbots)
+40%
Operational efficiency

The problem

A banking client was losing money to fraudulent transactions that rule-based checks kept missing, while non-technical teams needed insight they could actually act on.

What I did

I built a machine-learning fraud-detection model tuned to the client's transaction patterns, paired it with real-time analytics dashboards, and ran hands-on training so non-technical staff could use and trust the outputs.

The result

Fraudulent transactions dropped 75%. Across the wider engagement, AI chatbots lifted lead engagement 60% and predictive solutions improved operational efficiency up to 40%.

Python scikit-learn XGBoost Dashboards A/B Testing

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