Fraud is connected and contextual. Graph analytics adds layer of context to boost detection, triage, and uncover what rules and ML on their own can’t.
Composite AI fights fraud smarter by combining ML, rules, graphs & behavior analytics. Real cases show why silos lose & synergy wins.
Outsmart fraud with synthetic data: generate on-demand fake scenarios to train, test, and stress-test your rules and models - privacy-safe, scalable, and bias-free.
What is confusion matrix? How do we calculate the most common KPIs? Which of the KPIs are the most relevant and which can be misleading?