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USE CASE

Collusion Fraud

Objective

  • Detect buyer and seller collusion

  • Analyze activities, accounts, addresses, device IDs, coordinates, biometrics to expose suspicious patterns and coordinated activities suspected of making fake orders 

  • Account for volume and threshold variances

Outcome

  • Increased accuracy from 0.89 to 0.947, resulting in significant reduction in loss due to large transaction volume

  • Increased speed with H2O GPU drivers by 6x

Business Value

  • Improved decision making

H2O's AI and Data Approaches

  • Automatic feature representation to graph data and merge with expert engineered features

  • Machine Learning interpretability and explainability

Resources

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