usamnet000 / Data-Communication-Findings-and-Visualization

We are using a Loan Prosper Data to find interesting relations between its various components using Data Visualization.

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Prosper Loan Data

by Nidhi Mishra

Dataset

This dataset about the various variables and factors related to a Loan taken. It has 113937 entries with 81 features, including features of primary importance including loan Term, Loan Amount, Interest Rate, MonthlyIncome, etc. This dataset can be found at: https://s3.amazonaws.com/udacity-hosted-downloads/ud651/prosperLoanData.csv. with feature documentation available here: https://docs.google.com/spreadsheets/d/1gDyi_L4UvIrLTEC6Wri5nbaMmkGmLQBk-Yx3z0XDEtI/edit?usp=sharing.

Summary of Findings

In the Univariate exploration of Prosper Loan Data, I made plently of exciting discoveries. Firstly I found that the average interest rate charged was 18%. Over 85% of loan prospers were employed with an average monthly income of 10K USD. Over 50% of loan is taken for Debt consolidation! Quite unexpected. Another interest discovery was that a 3 year loan term is the most preferred. And finally Credit score of 1000 is average, which is very good.

During the seconf exploration of Bivariate, I got more insights. Found that Loan amount was directly proprtional to monthly loan payments and inversely to interest rates. That is, interest rates are lower on higher loan amounts. Thats some relief!. Being a Defaulter is has no excuse, there are defaulters even with an income of 100,000+ !! And thats why they are charged almost over 10% more than non-defaulters. There was a inverse relation between open revolving monthly payments and current Delinquencies. There was a inverse relation between Credit utilization and credit score Owning a home is a necessity but has its advantages. Like lower Interest rates. There are lot of factors that affect your credit score like current Delinquencies, credit utilization, debt-to-income ration. A credit score garauntees a good interest rate.

In the final Multivariate Exploration I found that you can end up paying more interest rate for the same loan amount if the loan term is higher, not a surprise. If you have a income of 75000+ USD you are sure to get a above average credit score provided you are Non-Defaulter! Larger revolving payment leads lower to lower monthly loan payment ie, lower credit scores. We has seen previously that most people opted for 3 years term, but here we get more insight that larger the loan amount, longer the term of loan which is common for all income ranges. Having more current Delinquencies is not a good factor, Available credit increses with time. Like i mentioned before, having home has its benefits. We can have an egde over non-home owners even we have higher debt-to-income ratio.

Key Insights for Presentation

For the presentation, I will introduce the key variables of the dataset including but not limited to Loan amount, Interst rate, Creadit score, term, etc. Then after that, I will show how each of these variables affect each other and also how they are related or how much they are dependent on other not so known factors like Delinquencies, Debt-to-income ration, credit lines, credit utilization etc.

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We are using a Loan Prosper Data to find interesting relations between its various components using Data Visualization.


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