Loan Data from Prosper

by Gabriel Michael O.

Dataset

This data set gotten from here contained 113,937 loans with 81 variables on each loan, including loan amount, borrower rate (or interest rate), current loan status, borrower income, and many others. However, a subset of the dataset consisting of 15 variables was carved out to inspect, analyze and draw conclusions from. The variables used had the following description as gotten from here:

Summary of Findings

The wrangling, analysis, and visualization of data from Prosper loans was carried out with the following findings realized:

• A majority of loan repayments were classified as current.
• There were generally higher overall credit ratings.
• An overwhelming majority of the loans under consideration were medium or long-term.
• Debt Consolidation was the most prominent reason for loan collection.
• There were generally more home owners amongst the loanees,
• There seemed to be a positive relationship between Monthly income and amount loaned.
• Loan defaulters tended to have a lower average income compared to the other categories.
• Higher loan amounts were associated with higher credit scores.
• Greater Debt-income ratio was associated with higher loan amounts.
• There was a positive relationship between work experience and reported monthly income.

Key Insights for Presentation

• An overwhelming majority of the loans under consideration were medium or long-term.
• Debt Consolidation was the most prominent reason for loan collection.