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Bank Loan Data Set Analysis - SPSS

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Please provide recommendations to a company based on the data. The dataset provided is information on applicants for a bank loan. The bank is seeking advice as to their current loan approval guidelines Based on the dataset, what recommendations can be made to the bank? should the bank consider lowering their approval standards, maintaining their current standards, or should the bank approve fewer loans? What criteria should be most strongly considered in the decision? At a minimum the statistics should include calculations for correlations, descriptive statistics, and multiple regression.

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The solution provides step by step method for the calculation of descriptive statistics and regression analysis. Formula for the calculation and Interpretations of the results are also included. Attached in Word and .spv.

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Bank Loan Data Set Analysis - SPSS
Please provide recommendations to a company based on the data. The dataset provided is information on applicants for a bank loan. The bank is seeking advice as to their current loan approval guidelines Based on the dataset, what recommendations can be made to the bank? Should the bank consider lowering their approval standards, maintaining their current standards, or should the bank approve fewer loans? What criteria should be most strongly considered in the decision? At a minimum the statistics should include calculations for correlations, descriptive statistics, and multiple regression.
Answer
Let us consider a financial institution (bank) to analyse the factors commonly affect the chance to default the loan. For the purpose, let us consider the variables age, education level, number of years working with current employer, household income, debt to income ratio, credit card expenses, other debts, etc. of some randomly selected loan applicants. The data is provided in the attached SPSS data sheet. We are required to analyse the data and recommend the bank to attain the maximum efficiency in their operations.
Descriptive statistics
Age in years
The mean age of applicants with no previous default record is slightly greater than that of applicants with previous default record. That is, older applicants tend to have no previous default record of loan. The standard deviation of the age is higher for applicants with previous default record.
Years with current employer
The applicants with no previous default record tend to work more years on average with the current employer than that with previous default record. That is, applicants work more years with current employer tends to have no previous default record of loan. The standard deviation of the number of years is higher for applicants with no previous default record.
Household income in thousands
On average the household income of applicants with previous default record is higher than applicants with previous default record. That is higher the household income, higher the chance to default the loan. The standard deviation of household income is higher for persons with previous default record.
Debt to income ratio
The average debt to income ratio of applicants with previous default record is approximately two times higher than that of applicants with no previous default record. In other words higher the debt to income ratio, higher the chance to default the loan. The standard deviation is higher for debt to income ratio of applicants with previous default record.
Credit card debt in thousands
The average credit card debt of applicants with previous default record is approximately 2.5 times higher than that of applicants with no previous default record. That is, the higher the credit card debt, the higher the chance to default the loan. The standard deviation of credit card debt is significantly higher for applicants with previous default record.
Other debt in thousands
On average, other debts are higher for applicants with previous default record. In other words, the higher the debts, the higher the chance to default the loan.
Details
Descriptive Statistics
Previously defaulted Age in years Years with current employer Household income in ...

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