How would you approach creating a machine learning model to detect anomalies in financial transactions in real-time?

Instruction: Describe the data preprocessing steps, feature engineering, model selection, and the deployment strategy for a low-latency, high-availability system.

Context: The question tests the candidate's skills in designing real-time, high-performance anomaly detection systems, crucial for financial fraud prevention.

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I would design this as a low-latency decision system with layered risk signals...

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