Project3_SharanyaVaratharajan.docx - Banking Personal Loan Modelling 1 Project Objective The primary objective of this project is to build a model for

Project3_SharanyaVaratharajan.docx - Banking Personal Loan...

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Banking Personal Loan Modelling
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1 Project Objective The primary objective of this project is to build a model for Thera bank that will help them identify the potential customers who have higher probability of purchasing the loan. This will increase the success ratio while at the same time reduce the cost of the campaign. The past data of 5000 customers with their demographic information and their relationship with the bank in terms of mortgage, security, account etc. will be used to build the model. Exploratory data analysis will be performed to find the relationship between independent variables and later come up with a model based on the results. It is to be noted that only 9.6% of the customers who attended the past campaign accepted the offer. 2 Understanding the attributes A glimpse of the Bank_Personal_Loan_Modelling excel file: It contains 5000 such rows. Here the personal loan column which has zero or one represents whether or not the customers availed for personal loan in the previous campaign. Here Personal Loan is the dependent variable and all other variables such as Age, Experience, Income, zip code, Family Members, CCAvg etc. are the independent variables.
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2.1 Correlation between the Independent Variables: Correlation can be defined as the connection between the variables. Here Personal Loan is the dependent variable. ID is neither independent nor dependent and hence this can be eliminated. Doing a correlation using R Programming after reading the input dataset will help us understand more on the relationship between the attributes. Prior to correlation, data cleansing (removing null and negative values were done. Refer to Appendix A for Code. Correlation between Independent Variables: By using the correlation function, the following data is obtained: This tells us the Age and Experience are highly correlated Income and CCAvg are highly correlated Income is correlated to Education, CCAVG, Personal Loan CD Account.Personal Loan is correclated with income,CCAvg and CD Account Mortgage is correlated to CDAccount and CCAvg Visualization of Correlation using corplot & ggcorrplot:
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The visualization clearly tells that Age and Experience are highly correlated.
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CCAvg, Income, CD account are correlated to Personal Loan. CD account is correlated to online usage. Credit card is correlated to cd account. Also by seeing this, we can arrive at a conclusion that Independent variables like zip code and Family Member can be eliminated as they are not correlated to the dependent variable personal loan as well as the independent variable 3 Business Objective Statement Thera bank would like to achieve the goal of building a model to identify potential customers who have higher probability of purchasing the loan. This will increase the success ratio while at the same time reduce the cost of the campaign which has been devised with better target marketing to increase the success ratio with minimal budget.
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  • Fall '18
  • Prof V K
  • Predictive Modeling

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