A data analysis project using a financial loan dataset to explore patterns, customer profiles, and risk factors related to loan approval and defaults. Useful for building classification models and understanding loan risk.
This project explores a comprehensive financial loan dataset to analyze lending trends, risk factors, and repayment behaviors. It also includes two interactive dashboards and a pivot table to visualize business insights.
The Excel file (financial_loan_main.xlsx) contains four sheets:
| Sheet Name | Description |
|---|---|
financial_loan |
✅ Raw dataset with 38,576 records and 25 features (e.g., income, DTI, grade) |
Design |
📊 Pivot table with summarized metrics (loan amount, interest, bad loans) |
Dashboard |
📈 Excel dashboard for visual analysis |
Overview Dashboard |
📉 Additional dashboard view for KPIs and performance |
- Perform exploratory data analysis (EDA) on loan applications.
- Identify trends in loan defaults, interest rates, and borrower profiles.
- Analyze key risk indicators like DTI, employment type, and loan purpose.
- Create pivot summaries and interactive Excel dashboards.
| Feature | Description |
|---|---|
loan_status |
Status of the loan (e.g., Fully Paid, Charged Off) |
Good v Bad Loan |
Binary classification of loan risk |
loan_amount |
Total loan sanctioned |
total_payment |
Amount repaid |
int_rate |
Interest rate |
dti |
Debt-to-Income ratio |
emp_length |
Employment duration |
purpose |
Reason for loan |
grade, sub_grade |
Creditworthiness grade |
The Excel file includes:
- ✅ Loan KPIs Overview
- 📌 Default Rate by Purpose/Grade
- 💡 Average Interest & DTI Trends
- 📍 Total Funded vs Repaid Amounts
- Microsoft Excel (Pivot tables, charts, slicers)