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Data Science and Machine Learning Interview Handbook

ML in Finance: Fraud Detection

Explore how to apply the Isolation Forest algorithm to detect fraudulent transactions in financial datasets. Learn data preprocessing essentials, synthetic data simulation, and evaluating anomalies to build effective fraud detection systems.

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You’re working on a fraud detection system for a payment processor. Your job is to identify transactions that are statistically anomalous and may indicate potential fraud. Implement an anomaly detection function for financial transactions using the Isolation Forest algorithm. The function should:

  • Accept normalized transaction data as input.

  • Use Isolation Forest to identify potential fraudulent transactions.

  • Allow configuring the expected proportion of anomalies.

  • Return ...