Loan Eligibility Determinator

About This Project

This project, coded in Python, determines if a loan applicant is eligible for a loan based off answers to questions. There are two sets of questions, a fast-track set of 3 questions and a larger set of 7 more in-depth questions. Additionally, if the user is determined to be ineligible for the loan based on the fast-track questions, they can move into the in-depth. Based off of the user's inputted answers, the program uses truth tables and boolean logic/boolean equations to determine the applicant's eligibility.

Objective

To learn more about coding with Python and create a project with potential real-world implications, use, and purpose.

Running The Project's Code

First clone the project using the command git clone [email protected]:lussierc/loan_eligibilty_determinator.git. Then ensure Python3 is installed on your machine.

Navigate to the src directory in terminal.

Then run the command:

python3 loan_eligibility_determinator.py

Results

Results and more information about this project and its potential uses can be found in the folder docs, with the major results coming inside of the file report.md. Results included the idea that a Loan Eligibility Determinator would be a good tool for banks and loan agencies to use to prevent costly bad loans. Additionally, the while the determinations made by the project seem to be on the right track, there is no questions that improvements could be made.

Problems, Praise or Ideas?

If you have problems, issues, or ideas for this project, please add an issue to the issue tracker. As this is project is likely done being updated, there is no guarantee that the issue will be addressed.

Contributors

Thanks to the following people who contributed to this project.

• Christian Lussier (See GitHub Profile)
• Mikey Spurr (See GitHub Profile)
• Trent Faulkner (See GitHub Profile)
• Robert Samuel (See GitHub Profile)

File Organization

Information about the file structure and files in the project repository.

src folder

• Contains the projects Python source code and output.

docs folder

• Contains the writing folder and presentation slides.

writing Folder

• proposal.md: The writing for the project proposal.
• report.md: The writing for the project's final report.
• images folder: Contains a variety of images of results from analysis in RStudio. These images are used in the final report.