Loan Repayment Financial Correlation Analysis

This project investigates the relationships between borrower financial characteristics and loan repayment outcomes using statistical correlation analysis. The goal is to identify key financial indicators affecting repayment behavior to inform risk management strategies.

🚀 Technologies Used:

• Python.
• Pandas.
• NumPy.
• Correlation Analysis.
• Jupyter Notebook.

📊 Project Highlights:

• Comprehensive financial data cleaning and preparation.
• Correlation matrix generation and heatmap visualization.
• Insight extraction on the most influential repayment factors.

📂 Files:

• loan_borrower_data.csv — borrower financial dataset.
• Loan_Repayment_Financial_Analysis.ipynb — Jupyter Notebook analysis.

▶️ How to View & Run:

Click in the Loan_Repayment_Financial_Analysis.ipynb Jupyter Notebook in this repository (recommended for non-technical people) OR Access the read-only executable version of the notebook in Google Colab:

This enables an interactive review of the analysis without requiring local installation.

📄 License

MIT License

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