💰 Bank Loan Analysis (Tableau + SQL)

This case study explores customer behavior and financial risk patterns in loan data. SQL is used for querying and KPI development, while Tableau delivers intuitive dashboards to present insights effectively to stakeholders.

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🎯 Project Objectives

• Explore trends in loan approvals, denials, and funding patterns
• Identify key indicators of loan default risk and customer segmentation
• Build a dynamic, interactive Tableau dashboard for business insights

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🛠 Tools and Technologies

• SQL (PostgreSQL or MySQL) – for data extraction, transformation, and analysis
• Tableau – for data visualization and dashboard creation
• Microsoft Excel – for light preprocessing and validation

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📂 Folder Structure

bank-loan-analysis-tableau-sql/
│
├── data/              # Raw or cleaned datasets (e.g., .hyper)
├── scripts/           # SQL scripts used for data analysis
├── dashboards/        # Tableau workbook files (.twb, .twbx)
├── screenshots/       # Dashboard images and visuals
└── README.md

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🚀 Key Insights

• Applicants with lower credit scores are more likely to be denied loans
• Loan amount and applicant income strongly influence approval outcomes
• Self-employed applicants have a slightly higher default risk
• Month-to-month analysis reveals seasonal fluctuations in funding and repayment behavior

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📊 Dashboard Preview

Screenshots from the Tableau dashboard are stored in the screenshots/ folder and embedded below:

![Loan Dashboard](screenshots/loan_dashboard.png)

Example image:

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📬Contact

For questions, feedback, or collaboration:

• 🔗 LinkedIn – Semiu Ajala
• 📧 ajalasemiu@yahoo.com