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executive-summary

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This repository contains the Business Intelligence insights generated as part of the final project challenge for the DTU Data Science course 42578: Advanced Business Analytics

  • Updated Feb 14, 2021
  • Jupyter Notebook

Robust insurance fraud detection project using Python and Power BI. Covers data preprocessing and EDA, three machine learning algorithms (Logistic Regression, Random Forest, and tuned XGBoost with SMOTE and Optuna), SHAP for model interpretability, and a business dashboard with KPIs, fraud trends, category insights, and per-claim fraud explanations

  • Updated Sep 5, 2025
  • Jupyter Notebook

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