This project was developed for the Visual Analytics course of the Bachelor's degree in Mathematical Engineering in Data Science.
- Develop a classification model to predict if a future customer will pay back the loan
- Create a training dataset formed by internal data without outliers
- Create a cluster method to identify main characteristics of customers that paid back the loan or not
- Identify the most important causes that are related with customers that did not pay back the loan
- Benefits: Assess whether or not a new customer is likely to pay back the loan.
- Customer data: Home ownership, annual income
- Loan data: Loan amount, term, interest rate, grade, loan status, ...
- Location
- Propensity model
- List of most important variables
- List of characteristics to refuse/accept a loan issue
- Dashboard in Tableau to discover the characteristics of customers that pais back and the ones that did not
- Questions to answer: How are each customer type? Is there any relationship with amount/interest rate/term/grade?...
- Map plots can be put together with bar, line, scatter plots