Bofa Housing Crisis
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Business Research Methods, Part III
Following the burst of the housing bubble in mid to late 2000, the rate of foreclosures among US homeowners soared. The housing crisis sparked the Great Recession, which compounded the problem with outrageous levels of unemployment, peaking at 10.1% in October 2009 (United States Department of Labor, 2011.) US banks have been scrambling to meet the demands of the new environment where so many consumers were found to be struggling to pay their mortgages. Bank of America, (BoA) the largest financial institution in the country, was greatly affected by this foreclosure crisis. Team B has been hired by BoA to survey and analyze customer information to see if there is a correlation between customer situations and foreclosure, or if the correlation lies between loan elements and instances of foreclosure. BoA wants to ultimately assess whether they can alter loan agreements to help keep customers in their homes and avoid foreclosure.
Team B has hypothesized that homeowners are defaulting on mortgages because of specific characteristics of the loan that the lender (BoA) has the prerogative to adjust to avoid foreclosure. Team B has decided to sample mortgage holders in the states of California, Nevada, and New Jersey to obtain a better understanding for the reasons people are defaulting and forecasting. Team B’s proposes the stratified random sampling design, classifying the sample populations into one of three categories foreclosed, delinquent, and in good standing (Cooper & Schindler, 2006). Based on the known population of one million BoA mortgage holders in these three states, Team B calculated the sample population to be 663 within a 99% confidence level and 5% acceptable margin of error.
Correlation opposed to Cause – Finding a resolve to the foreclosure dilemma
The intent of data analysis is to look past the answers and arrive at its root meaning and significance. The process allows the examiner to gauge quantitative...
Following the burst of the housing bubble in mid to late 2000, the rate of foreclosures among US homeowners soared. The housing crisis sparked the Great Recession, which compounded the problem with outrageous levels of unemployment, peaking at 10.1% in October 2009 (United States Department of Labor, 2011.) US banks have been scrambling to meet the demands of the new environment where so many consumers were found to be struggling to pay their mortgages. Bank of America, (BoA) the largest financial institution in the country, was greatly affected by this foreclosure crisis. Team B has been hired by BoA to survey and analyze customer information to see if there is a correlation between customer situations and foreclosure, or if the correlation lies between loan elements and instances of foreclosure. BoA wants to ultimately assess whether they can alter loan agreements to help keep customers in their homes and avoid foreclosure.
Team B has hypothesized that homeowners are defaulting on mortgages because of specific characteristics of the loan that the lender (BoA) has the prerogative to adjust to avoid foreclosure. Team B has decided to sample mortgage holders in the states of California, Nevada, and New Jersey to obtain a better understanding for the reasons people are defaulting and forecasting. Team B’s proposes the stratified random sampling design, classifying the sample populations into one of three categories foreclosed, delinquent, and in good standing (Cooper & Schindler, 2006). Based on the known population of one million BoA mortgage holders in these three states, Team B calculated the sample population to be 663 within a 99% confidence level and 5% acceptable margin of error.
Correlation opposed to Cause – Finding a resolve to the foreclosure dilemma
The intent of data analysis is to look past the answers and arrive at its root meaning and significance. The process allows the examiner to gauge quantitative...