Welcome to the Bank-Loan-Analysis-Python project! This application helps you analyze a bank’s loan portfolio. You can find profitable segments, identify high-risk borrowers, and gain strategic insights easily.
To get started, visit this page to download: Releases Page.
After you've downloaded the files, follow these simple steps to install the application:
- Find the latest version on the Releases page.
- Download the file that matches your operating system.
- Double-click the downloaded file to run the application.
Make sure your computer meets the following requirements:
- Operating System: Windows 10 or newer, MacOS 10.15 or newer, or a compatible Linux distribution.
- Python Version: 3.7 or newer installed on your system.
- RAM: Minimum 4 GB.
- Free Disk Space: At least 500 MB.
- Data Analytics: Analyze loan portfolios to find profitable segments.
- Risk Assessment: Identify high-risk borrowers.
- Data Visualization: Create visually appealing charts for better insights.
- Easy to Use: User-friendly interface with clear instructions.
- Comprehensive Reports: Generate reports that summarize your findings.
Once you have the application open, follow these steps to start your analysis:
- Load Data: Click on the "Load Data" button and select your loan dataset in CSV format.
- Choose Analysis Options: Use the menu to select the type of analysis you want. Options may include risk assessment, segmentation, or visualization.
- View Results: After running the analysis, view the results in graphs and summary tables.
The dataset should contain the following columns to ensure effective analysis:
- Loan Amount: The total amount of the loan.
- Borrower Credit Score: A score indicating the creditworthiness of the borrower.
- Loan Status: Whether the loan is paid, current, or in default.
- Interest Rate: The interest charged on the loan.
Ensure your data is clean for the best results. You can use the built-in data cleaning tools in the application to help with this.
Visualization is key to understanding your analysis. The application provides several chart types, including:
- Bar Charts: Great for comparing categories like loan amounts across different segments.
- Pie Charts: Useful for showing proportions, such as loan status distribution.
- Line Graphs: Perfect for showing trends, like defaults over time.
If you encounter issues while using the application, consider the following common problems:
- Data Not Loading: Confirm that you are using a CSV file with the required columns.
- Slow Performance: Make sure your system meets the RAM and CPU requirements.
- Graphs Not Displaying: Check your data format and ensure all data points are valid.
If you need help, you can reach out to the community through issues on the GitHub repository. Visit this page for assistance: Releases Page.
This project is licensed under the MIT License. Please see the LICENSE file in the repository for more information.
By following these instructions, you can effectively download and run the Bank-Loan-Analysis-Python application to analyze your loan portfolio. Enjoy exploring your data!