Comprehensive Bank Loan Analysis and Prediction
This repository demonstrates a data-driven approach to analyzing and predicting bank loan outcomes. Using SQL for data processing, Power BI for visualization, and machine learning for predictive modeling, this project bridges actionable insights and decision-making efficiency.
Highlights
- Dynamic Loan Analysis Dashboards Created three visually rich Power BI dashboards to explore: Trends in loan types and approval rates Average interest rates and demographic insights Borrower behavior patterns and portfolio composition
- Accurate Loan Status Prediction Implemented a Random Forest machine learning model to predict loan approval outcomes. Achieved a high 97% accuracy, offering reliable predictions.
- Technical Stack
SQL: Handled data preparation and KPI extraction.
Power BI: Designed detailed and interactive dashboards.
Python: Leveraged for predictive modeling and data assessment.