Fraud Analytics
Using data analysis, statistical models, and pattern recognition to detect, investigate, and prevent fraudulent activity.
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Why It Matters
AI-generated deepfakes and synthetic identities are making fraud more sophisticated. Analysts who can tune detection models and interpret their outputs are critical to staying ahead of evolving threats.
How to Get Started
Learn SQL and Python for data analysis, then study fraud detection patterns through ACFE (Association of Certified Fraud Examiners) resources. Kaggle hosts fraud detection datasets for hands-on practice.
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