Fraud rarely happens in isolation. Organized fraud operates through coordinated networks—multiple actors sharing infrastructure, moving money, and hiding in plain sight.
In this module, you’ll use graph algorithms to uncover these hidden networks and identify suspects who haven’t been flagged yet.
You’ll learn:
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How Louvain community detection finds groups of densely connected nodes—and reduces your search space by 98%
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How Degree Centrality identifies high-connection nodes to filter noise from your analysis
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How Weakly Connected Components (WCC) provides deterministic, explainable community assignment
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How to encode domain hypotheses as graph relationships for targeted fraud detection
By the end of this module, you’ll have identified 211 previously unknown fraud risk users who account for 13% of all transaction volume—using algorithms that are simple by design but powerful when combined with domain knowledge.