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So you've built a fraud detection model — trained it on real-world data, tuned the thresholds, evaluated its performance, and you’re confident it can spot suspicious activity. Great! But building the model is only half the battle. Now comes the crucial step:...

In our previous blog post, we covered the foundational concepts for designing an AI-powered fraud detection system. Now, we’ll explore the core stage: training and evaluating your model so it performs reliably in real-world financial ecosystems. A model is only as...

Introduction As digital transactions become the norm, fraudsters are evolving just as fast. Traditional fraud detection methods—mostly static rule-based engines—are not equipped to handle modern payment dynamics. Let's build a scalable, intelligent AI-based fraud...

With global payment fraud losses exceeding $48 billion annually, the need for intelligent, real-time defenses has never been greater. Traditional rule-based systems can’t keep up. That’s where AI-powered fraud detection steps in—redefining payment security at scale....