Question

Take the scenario presented in the Bank Loan case study. For this scenario, come up with 1) the Business opportunity, 2) Business Objectives, 3) Business Questions, 4) Data Analytic questions, 5) Data collection plan of action and 6) the actual hypothesis tests or regression analyses you would do to answer the questions in step 4. (You don't have to do the hypothesis tests or regression analysis here. Just mention what you would do.)

Bank Loan Case Study Scenario

This case study concerns a bank's efforts to reduce the rate of loan defaults. A loan officer at a bank needs to be able to identify characteristics that are indicative of people who are likely to default on loans and use those characteristics to identify good and bad credit risks. The loan officer also needs to be able to better quantify an individual’s credit risk level.

Information on 850 past and prospective customers in contained in bankloan. The first 700 cases are customers who were previously given loans. The last 150 cases are prospective customers that the bank needs to assess.

The data set includes the following variables:

Age: customer age in years.

College: an indicator of whether the customer has a college education

Employment: years that the customer has been with his/her current employer

Address: years that the customer has lived at his/her current address

Income: household annual income (in $1,000)

Debt _to _Income: debt to income ratio (x100)

Credit _Debt: credit card debt (in $1,000)

Other _Debt: other debt (in $1,000)

Risk _Score: Credit risk score (the higher the score, the more risky)

Default _Indicator: an indicator of whether the customer had previously defaulted

Answer 1

In the Problem we have to identify the characteristics that are indicative of people who are likely to default on loans.

We have collected the data for that. we are considering the several variable to identified who will default on loans.

Here we use logistic regression model to identify who is Default or Not.

We will consider Default_Indicator variable as independent variable and considering as:

1= he will Default

0= He is not default

And all other as independent variable. After running the model we will get who is default and who is not.

And also from S shape graph of Logistic regression we get threshold value that

Values greater than x are default and values less than y are not default