Mortgage Approval Case Study 2
Mortgage Approval Case Study 2
Diane Joyner
MAT 510
Dr. Eliette Barrios
December 01, 2020
Problem Statement
A major financial services company wishes to better understand its mortgage approval process. In particular, the company is interested in learning about the effects of good versus fair credit history, the size of the mortgage (less than $500,000 versus greater than $500,000), and the region of the United States (western versus eastern) on the time it takes to get a mortgage approved. The database of mortgages approved in the last year is accessed, and a random sample of five approved mortgages is chosen for each of the eight combinations of the three variables. The data are shown in the table.
Mortgage Approval Time Study
Credit History Mortgage Size Region Approval Times (days) Approval Times (days) Approval Times (days) Approval Times (days) Approval Times (days)
Good <$500,000 Western 59 50 64 62 47
Fair <$500,000 Western 81 58 69 65 74
Good >$500,000 Western 38 52 58 60 65
Fair >$500,000 Western 146 159 133 143 129
Good <$500,000 Eastern 28 26 38 41 21
Fair <$500,000 Eastern 42 53 40 50 64
Good >$500,000 Eastern 49 31 49 42 38
Fair >$500,000 Eastern 106 115 126 118 138
Design of Experiment (DOE)
Regression Coefficients Model Equation
Interaction Charts
5
Sample Size Analysis
Alternate Variables of DOE
Employment History
Debt-to-income ratio
Income
In the mortgage approval process, employment history
7
RunCredit History (X1)Mortgage Size (X2)Region (X3)X1X2X1X3X2X3X1X2X3Sample 1Sample 2Sample 3Sample 4Sample 5AverageStandard Deviation
1Good (-)<$500,000 (-)Western (-)+++-595064624756.47.50
2Fair (+)<$500,000 (-)Western (-)--++815869657469.48.73
3Good (-)>$500,000 (+)Western (-)-+ -+385258606554.610.38
4Fair (+)>$500,000 (+)Western (-)+- --14615913314312914211.79
5Good (-)<$500,000 (-)Eastern (+)+- -+282638412130.88.41
6Fair (+)<$500,000 (-)Eastern (+)-+ --425340506449.89.60
7Good (-)>$500,000 (+)Eastern (+)--+-493149423841.87.66
8Fair (+)>$500,000 (+)Eastern (+)++++106115126118138120.612.07
Sum+381.8359243349.8281.4288.2275.4
Sum-183.6206.4322.4215.6284277.2290
Avg+95.4589.7560.7587.4570.3572.0568.85
Avg-45.951.680.653.97169.372.5
Effect49.5538.15-19.8533.55-0.652.75-3.65
Regression Coeffients
b0=141.35
b1=24.775
b2=19.075
b3=-9.925
b4=16.775
b5=-0.325
b6=1.375
b7=-1.825