Assignment Task: Background

Using the Universal Bank data, determine the factors that influence whether a customer takes out a loan for SCM 651 - Business Analytics Homework 4 and Loan Analysis Universal Bank.

Outline

Perform a logit and probit analysis of the variables that affect whether a customer takes out a loan for SCM 651 - Business Analytics Homework 4 and Loan Analysis Universal Bank. Consider only main effects (main variables, no moderating effects). Which variables are significant? How do the significant variables influence the likelihood of taking out a loan? Copy screen snapshots of your analysis in R to your report.

Add moderating effects (interactions of variables). Which interactions make sense conceptually? Which interactions are statistically significant? How do you interpret the coefficients on these variables? Copy screen snapshots of your analysis in R to your report for SCM 651 - Business Analytics Homework 4 and Loan Analysis Universal Bank.

Create a final regression model with the variables that you feel are important (both main effects and interaction terms). Use the moderating effect that was significant and its two individual main effects. Create a spreadsheet prediction of the model. Perform a sensitivity analysis as seen earlier in the semester. Which variables have the greatest influence on the customers’ loan behavior (combined main effects and interaction effects)? Copy screen snapshots of your analysis in R to your report.

Perform a neural network analysis of the variables in part 3 above. Copy screen snapshots of your final neural network model in R to your report for SCM 651 - Business Analytics Homework 4 and Loan Analysis Universal Bank.

Create a prediction model of the neural network in part 4. Using the prediction model, perform a sensitivity analysis for the neural network model like the logit and probit sensitivity analysis.

Justify your answers. Provide a snapshot of output from your analysis in your final paper for SCM 651 - Business Analytics Homework 4 and Loan Analysis Universal Bank.

Universal Bank Data Fields

• ID - unique identifier
• Personal Loan - did the customer accept the personal loan offered (1=Yes, 0=No)
• Age - customer’s age
• Experience - number of years of professional experience
• Income - annual income of the customer ($000)
• Zip code - home address zip code
• Family - family size of the customer
• CCAvg - average spending on credit cards per month ($000)
• Education - education level (1) undergraduate, (2) graduate, (3) advanced/professional
• Mortgage - value of house mortgage ($000)
• Securities - does the customer have a securities account with the bank? (1=Yes, 0=No)
• CDAccount - does the customer have a certificate of deposit with the bank? (1=Yes, 0=No)
• Online - does the customer use internet banking facilities? (1=Yes, 0=No)
• CreditCard - does the customer use a credit card issued by Universal Bank? (1=Yes, 0=No)