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Data Interview Question

Fraud Detection System for Banking

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Requirements Clarification & Assessment

  1. Objective:

    • Develop a model to identify fraudulent activities on a banking platform.
    • Implement an SMS notification system to alert customers of potential fraudulent transactions.
  2. Data Understanding:

    • Source: Historical transaction data, chargebacks due to fraud, and customer feedback.
    • Attributes: Transaction amount, time, location, card information, user behavior, and merchant details.
    • Quality: Ensure data accuracy and completeness, identify missing values, and assess labeling consistency.
  3. Stakeholder Needs:

    • Minimize false negatives to prevent undetected fraud.
    • Balance false positives to avoid unnecessary customer alerts.
    • Ensure real-time processing capability for immediate alerts.
  4. Technical Constraints:

    • Handle imbalanced datasets efficiently.
    • Ensure model interpretability and scalability.
    • Integrate seamlessly with existing banking systems and SMS services.