This project focuses on analyzing bank loan data to identify key trends, performance indicators, and risks associated with lending activities. Using Tableau for visualization and SQL for data manipulation, the project presents insights that help improve decision-making processes in managing a bank's loan portfolio. The dashboards showcase different aspects of loan performance and borrower profiles to highlight risk factors, profitability, and repayment behaviors.
The primary goal of this project is to:
- Analyze bank loan data to gain insights into lending trends.
- Identify key performance indicators (KPIs) that reflect the overall health of the loan portfolio.
- Evaluate borrower performance based on factors like loan purpose, employment length, home ownership, etc.
- Support financial institutions in making data-driven decisions for better risk management and loan performance improvement.
- Tableau: For building interactive dashboards and data visualizations.
- SQL: For data extraction, transformation, and cleaning.
- Excel: Used for basic data manipulation and exploration.
- PowerPoint: Summarizes project insights in a professional presentation.
- Data Source: Bank loan dataset containing loan applications, borrower demographics, loan purposes, interest rates, repayment status, etc.
- Data Cleaning: SQL queries were used to clean the dataset, handle missing values, correct data types, remove duplicates, and filter important variables.
- Integration with Tableau: The cleaned dataset was imported into Tableau for analysis and visualization. Additional data transformation and refinement were performed within Tableau.
This dashboard provides a high-level overview of key metrics related to the bank’s loan portfolio:
- Total Loan Applications: The number of applications received, displayed with Month-to-Date (MTD) and Month-over-Month (MoM) trends.
- Total Funded Amount: The total loan amount disbursed by the bank, with MoM and MTD comparisons.
- Total Amount Received: Total loan repayments received, showing MTD and MoM changes.
- Average Interest Rate: Average interest rate across loans, tracked over time.
- Average Debt-to-Income Ratio (DTI): Reflecting the financial health of borrowers, this metric is analyzed for trends over time.
- Good Loan vs. Bad Loan KPIs:
- Good Loan: The percentage and count of ‘Good Loans’ (loans with healthy repayment), including total funded and received amounts.
- Bad Loan: The percentage and count of ‘Bad Loans’ (loans with issues such as defaults), along with related amounts.
- Loan Status Grid View: A detailed table displaying key metrics segmented by loan status.
This dashboard dives deeper into specific metrics, revealing patterns and trends across different dimensions:
- Monthly Trends by Issue Date: Trends in loan issuance over time, identifying peak periods and seasonal patterns.
- Regional Analysis by State: A geographic breakdown of loan activity and performance across various states.
- Loan Term Analysis: Segmenting loans by terms (short-term, medium-term, long-term) to understand default risks and repayment behaviors.
- Employee Length Analysis: Investigating the relationship between borrowers' employment lengths and loan performance.
- Loan Purpose Breakdown: Analyzing loans by their purposes (e.g., education, home improvement) to evaluate performance based on reasons for borrowing.
- Home Ownership Analysis: Understanding how homeownership status impacts loan approvals, defaults, and overall loan performance.
- Regional Disparities: Some states showed a higher tendency toward loan defaults, indicating the need for region-specific lending strategies.
- Loan Term Risks: Short-term loans generally had higher default rates compared to long-term loans.
- Employment Impact: Borrowers with stable, long-term employment histories had significantly better repayment performance.
- Interest Rate Effects: Higher interest rates were correlated with a greater likelihood of default, indicating a potential risk associated with high-rate lending.
- Loan Purpose: Loans taken for certain purposes, such as education or home improvement, had better repayment behavior compared to others.
Through this project, I gained the following skills and knowledge:
- Tableau Proficiency: Mastered creating highly interactive dashboards with dynamic filters and drill-downs.
- SQL Mastery: Wrote complex queries to clean and transform data, ensuring data integrity for analysis.
- Business Insight Development: Developed an understanding of the critical financial metrics that drive loan portfolio performance.
- Data-Driven Storytelling: Learned to tell compelling stories through data visualizations to highlight key trends and support business decisions.
- Live Tableau Dashboard
- (Links will direct users to live versions of the dashboards hosted on Tableau Public or a similar platform.)
- Download SQL Queries Document (PDF containing the SQL queries used for data preparation)
- Download Full Project Report (Detailed PDF report with findings and analysis)
- Dataset (CSV File)
In future iterations of this project, I plan to:
- Integrate Real-Time Data: Incorporate real-time data via APIs to keep the dashboards up-to-date.
- Predictive Analytics: Add machine learning models to predict loan defaults and assess risk more accurately.
- Advanced Interactivity: Introduce more advanced drill-down features and user interactivity for deeper insights.
Feel free to reach out to me for any questions, suggestions, or collaboration opportunities!
- Name: Bhushan Gawali
- WhatsApp: +91 7743927365
- Email: bhushanjg14@gmail.com
"Every data point is a stepping stone to a brighter insight. Keep analyzing, keep discovering!" 🌟🔍