Blueprint: Real-Time Fraud Detection for a Digital Bank
A reference architecture for a streaming ML pipeline that scores transactions in real time, learns from every decision, and keeps false positives from punishing good customers.
This is an illustrative blueprint — a representative engagement scenario showing how we architect systems. It is not a client history. No invented logos. No inflated numbers.
The Problem Worth Solving
The scenario: a digital bank bleeding money to fraud while its rule-based system blocks legitimate customers — losing on both sides of the same coin.
How We Would Architect It
Our blueprint builds a real-time ML fraud detection pipeline with ensemble models, behavioral signals, and adaptive thresholds that learn from each decision — designed for high-throughput transaction streams.
The Reference Stack
What the System Is Built to Do
Related Reference Architectures
Explore how we approach intelligent systems across other industries.
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