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AI for Fraud Detection

89 words·1 min
Table of Contents

Definition
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Neural networks detecting patterns in transactional data to flag suspicious behavior.

Key Characteristics
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  • Graph network analysis
  • Behavioral biometrics
  • Real-time scoring
  • Adaptive learning

Why It Matters
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Catches 300% more fraud than rules-based systems with 50% fewer false positives.

Common Use Cases
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  1. Credit card fraud
  2. Insurance claim fraud
  3. Account takeover

Examples
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  • Featurespace ARIC
  • SAS Fraud Management
  • Feedzai

FAQs
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Q: Model refresh rate?
A: Continuous learning updates models every 15 mins for new patterns.

Q: Regulatory compliance?
A: Explainable AI meets PSD2/Strong Customer Authentication requirements.