Data-Driven Loan Approvals: Optimizing for Risk
Project Details
- Tools: SQL for data manipulation and Tableau for visualization
- Key Concepts: Data Aggregation & Summarization, KPIs, Customer Segmentation, Date & Time Analysis
- View Project on GitHub
The bank's loan department aims to minimize risk by utilizing both historical and current loan data. By analyzing borrower demographics, financial details, and loan history, I developed a comprehensive data-driven approach to optimize loan approvals.
This project identified key risk factors that could reduce loan default rates and enhance loan approval efficiency, translating to significant financial benefits for the bank, including increased loan approvals and cost saving