Bofa_Housing_Crisis

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 and qualitative information to decipher between the correlation and cause of an event. As noted by Lind et al (2008), if a strong relationship exists between two variables, the observer is tempted to assume that an increase or decrease in one variable causes a change in the other variable. A strong correlated relationship between two variables should not deduce in a relationship or parallel; change in one variable does not constitute change in the other. Correlation is not causation nor should it be inferred as the cause of an event occurring, but rather as an instrument to measure the factors to the cause. Team B must identify key indicators for BoA as they attempt to address the defaulting/foreclosing issue. The discoveries from the survey will help Team B recognize causes, comprehend contributing factors, and finally offer suggestions to the management of BoA in how to provide better loan products and services to help their valued customers. Below is a chart noting Team B’s classification of its 663 total sample from Nevada, New Jersey, and California. As noted above, the defaulted group makes up approximately 17.50% percent of the group whereas the foreclosed group is 6.03%. In comparison, according to CNN Money, the national averages for these groups are 13.6% defaulted and 4.63 foreclosed. From this point forward Team B will only focus on this subgroup of the sample population, for they are the groups of interest from which Team B hopes to derive its data as it attempts to answer its research question. Immediately, Team B hypothesized if the variance of the default and foreclosed group were unequal. Hence the following hypotheses test: H0: The default and foreclosed means are equal H1: The defaulted and foreclosed means are not equal. Significance: .05 Significance Level 2 Tail Test Mean Income $4,792.46 $2,905.75 Hypothesis Test B: Correlation Matrix Evaluation H0: The regression coefficient equals zero H1: The regression coefficient does not equal zero Significance: .05 Significance Level 2 Tail Test The above correlation matrix and hypothesis testing conclude a strong relationship between the independent variables of mean mortgage payment and mean income. These are two factors that the management of BoA must consider during the loan process, and in particular interest rate as it yields a very strong relationship to the dependent variable. Validation and Reliability Unfortunately for Team B, it is becoming apparent that the research will prove to be inconclusive. Although, correlations between the delinquency rate and mean mortgage and income have been established, additional data and analysis is require. At this time Team B cannot validate any of the finding with a 100% certainty. The survey questions will need to be revamped and additional questions asked. Source: NVAR.org Many of the observations point the cause of delinquency to loss of job followed by health issues, and increased financial responsibilities. Additional questioning during the surveying process can generate enough data to help draw a clear correlation between trigger events and delinquency; however, at this time it can only be classified as a potential cause with no validity to it. Also, the research design needs to find a way to distinguish from its finding those individuals that strategically default or walk away. At present, according to NVAR.org, as many as 25% of the foreclose homes are strategically foreclosed. Source NVAR.org Many of these strategic foreclosures are done by individuals that have stop making payments despite having the financial ability to continue making payments. Many do so as a means to restructure their debt. Recommendations BoA is concerned with the high rate of delinquent mortgage loans and foreclosures. Team B’s recommendation is for BoA to allocate their necessary resources to relinquish the root causes for this detrimental occurrence to initiate measures to curb and possibly eradicate this issue. The Federal Housing rules were not followed at the start of some foreclosures; thereby the delinquent borrowers were not contacted by BoA to propose a mortgage modification to help the struggling homeowners avoid foreclosure. These modifications will assist mortgage holders with interest rate and principle reductions. Lenders and servicers can modify all eligible loans confirming with the guidelines of the program. The banks are urged to perform their mortgage modification program except when the mortgage holders qualify for the Home Affordable Modification Program (HAMP), which was designed by the Obama’s administration. BoA’s modification offers are usually not as rewarding as HAMP, which reduces monthly payments to 31% of pretax earnings. BoA is advised to reduce more than $2.2 billion in principle on at least 50,000 mortgage modifications in the next 12 months. This will be managed by applying a medley of term extensions, interest rate reductions, and principle adjustments to assist the mortgage holders Conclusion In conclusion, after processing the data and analyzing the results, BoA can make reasonable assumptions regarding why their foreclosure rates are so high. The number one reason mortgage holders defaulted on their loans was due to loss of jobs. Unfortunately, BoA resisted in taking care of their borrowers by not offering assistance. Oftentimes, homeowners are chided for failing to pay their loans on-time. Team B’s research shows that in addition to job loss some people defaulted, due to unexpected medical bills, an addition to the family, tax increase, and death of a mortgage payer to name a few. Provided BoA chooses to make efforts to negotiate the terms of the loan to reasonably accommodate the consumer’s situation, the risk of foreclosure can be reduced or even eliminated. Since the conclusiveness of the hypothesis testing fell short, our study cannot ultimately provide proof that these measures will be completely effective, however, in reviewing survey results, we can assure that our recommendation is a step in a positive direction.   Reference Cooper, D.R., & Schindler, P.S. (2006). Business Research Methods (9th ed.).: McGraw-Hill/Irwin Leftman, J. (2011). Bank of America Corporation (NYSE:BAC) Foreclosure News. Retrieved from http://www.emoneydaily.com/bank-of-america-corporation-nysebac-foreclosure-news/6988201 Lind, D. A., Marchal, W.G., & Wathen, S.A. (2008). Multiple Regression and Correlation Analysis. Statistical Techniques in Business and Economics. (13th ed.). New York: McGraw-Hill. United States Department of Labor. (2011). Labor force statistics from the current population survey. Retrieved from http://data.bls.gov/pdq/SurveyOutputServlet'data_tool=latest_numbers&series_id=LNS14000000