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Fraud Detection Analytics Case

End-to-end fraud analysis project simulating a real fintech environment, combining data engineering, SQL analytics, risk scoring and BI dashboards.

Tech Stack

  • Python (Pandas, NumPy)

  • SQL (PostgreSQL)

  • Power BI

  • Tableau

  • Git & GitHub

  • Key Insights

  • Identified high-risk patterns in cross-border transactions

  • Detected fraud concentration in specific merchant categories

  • Highlighted increased fraud rate in newly created accounts

  • Built a risk scoring model to prioritize investigation

  • Project Structure

  • python/ → data generation, fraud rules and scoring

  • sql/ → data modeling and advanced queries

  • data/ → raw and processed datasets

  • dashboards/ → Power BI and Tableau files

  • docs/ → business context and findings