Section 3: Focus Group Sessions, Fair Housing Index and Home Mortgage ...

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48 Section 3: Focus Group Sessions, Fair Housing Index and Home Mortgage Disclosure Act Data (HMDA) Introduction This section of the analysis of impediments to fair housing choice is made up of three parts; a report of focus group sessions held in Bentonville in March 2005, an analysis of a fair housing index created for this report and an analysis of Home Mortgage Disclosure Act (HMDA) data for Bentonville. The first part of this section will report on the results from the focus group sessions. The groups were gathered via invitations sent to select residents and industry professionals. The participants of the focus groups included representatives from City staff, non-profit organizations, the housing industry, and other community representatives. In addition to the focus group sessions held on March 30 th , 2005, interviews with key stakeholders were conducted. The fair housing index constructed for this study is an attempt to localize geographical areas of concern. Ten variables were standardized and combined to concentrate attention on those areas of Bentonville that were most vulnerable to fair housing abuse. Analysis of the HMDA data provides a glimpse into lending practices in Bentonville. The data look at federally insured mortgage lending, conventional lending, refinancing, and home improvement loans. The data were analyzed by income class, geography, and racial group. 49 1. Focus Group Sessions Focus group sessions were held in Bentonville on March 30, 2005. The session attendees included City officials, representatives of non-profit organizations, local housing industry, and individuals from the community. Attendees were invited by the City based on their knowledge of the local housing environment. After the focus group sessions, key person interviews were conducted to provide more insight into the issues broached in the focus groups and to get a better sense of the local housing market. A list of attendees is included at the end of this section. It should be noted that the methodology employed in the focus group sessions was not designed to provide a statistically representative set of observations about the Bentonville housing market. Conclusions drawn here are to be recognized as the observations of a select group of individuals, picked for their knowledge of the local market. Findings Much of the discussion in the focus group sessions centered on the issue of affordable housing in the city of Bentonville. Participants felt that rising costs, which include the cost of construction, land, impact and other development fees, and labor, have made affordable housing scarce in Bentonville. The City of Bentonville charges impact fees to offset the cost of new development, and participants felt that these fees have had both positive and negative impacts. On the one hand, the fees are used to provide essential services such as funding for a fire station. On the other hand, participants also felt that the fees had a negative impact on the availability of new affordable housing. Some felt that the fees were a significant portion of the cost of smaller, more affordable homes. The cost of land in Northwest Arkansas continues to increase rapidly, especially in Bentonville, making housing less affordable for those below the median income. Although there have been some actions to provide affordable housing, most felt that this housing is not enough to meet the growing need. Developers of affordable housing said that it is increasingly difficult to produce housing for those below 80 percent of the 50 median family income, while others felt that developers were reluctant to sell or finance more moderately priced homes due to first-time homebuyer credit issues. Participants expressed concerns that many in the community feel there is an economic stratification in the city, and that the majority of housing within the city was not affordable to fully-employed families earning between 30 to 50 percent of the city’s median family income. There was also some concern that the current supply of affordable housing, particularly single-family rental housing, did not meet HUD’s standard of safe and decent housing. Also, participants mentioned that aside from the overall cost of land, the high costs of flood insurance also made housing less affordable in some areas. This was seen as a factor which “pushed” affordable housing to certain areas. The “Not In My Back Yard” or “NIMBY” factor was also seen as limiting both the amount and location of affordable housing options. Participants stated that affordable housing was being forced to locate further and further outside of the city. Areas such as Bella Vista, which were once expensive to develop, have become more affordable by comparison. Development, participants felt, was sprawling out to the outlying areas, including Centerton, Gravette, and into Missouri. Another major concern of the focus group participants was the lack of affordable housing developers. One participant observed that the high up-front cost of development in terms of permit and impact fees, has eliminated many of the smaller developers who could do affordable infill housing projects. Due to the rising costs of housing, participants felt that developers are finding it increasingly difficult to make a reasonable profit on affordable housing, and that greater profits can be made with higher-end housing. Participants felt that there indeed is a demand for high-end homes in Bentonville with the influx of residents, but there is also a great need for affordable homes. The demand for high-end homes, which are much more profitable, and the perceived lack of incentives for developing affordable housing contributes to the inadequate participation by builders in the development of affordable housing. 51 Most participants felt that race was not an issue in terms of fair housing in Bentonville, stating that income was the major force driving the housing market. One person observed that the percentage of Hispanic persons inside Bentonville was lower than in the surrounding areas, and stated that this was probably due to the greater availability of affordable housing outside of Bentonville. Lack of income was also thought of as a barrier to affordable housing. When asked if local employers paid wages that would allow a full-time employee to afford home payments in the City of Bentonville, participants were quick to respond that most homes were out of reach for a person making an entry-level wage, particularly in retail sales positions. According to the US Bureau of Census, in 2000, the median home value for a single-family house in the city was $91,200 and the median contract rent was $432 per month. A person who earned the minimum wage of $5.15 per hour would take home just under $893 a month. For an individual earning $893 to not be cost burdened, meaning paying more than 30 percent of income on housing, their monthly housing costs can be no more than $267.90 for the contract rent or mortgage, insurance, and utilities combined. It was noted that incomes, especially in the service industry, have not kept up with increasing home prices. It was suggested that housing and employment should be thought of together instead as separate problems. Participants indicated that credit education is a factor in many households’ inability to borrow for home purchases. Northwest Arkansas Community College offers financial literacy education, although local banks do not require attendance at the classes prior to loan origination. While these classes are helpful to the households looking to buy a home, there is a wider population that has a need for financial education, either to correct problems in their credit history or to provide a solid foundation that could prevent financial problems that they might otherwise encounter. Credit was seen as one barrier that limits the housing choices in Bentonville. Lenders and developers feel that they cannot find qualified buyers in the lower income groups. 52 Some participants commented on the sometimes incorrect perceptions others have of Bentonville and Northwest Arkansas in general. One such perception was the idea that there is no poverty in the area. While Benton County is among the more affluent in Arkansas, according to the US Bureau of Census, 10.1 percent of all persons in the county were below the poverty line in 1999, and in Bentonville the percentage is 10.3 of all residents. Other issues that were mentioned by focus group participants included NIMBY (not-in- my-back-yard) issues, the lack of affordable and accessible multifamily housing, disinvestment in low-income areas, the positive City stance on gated communities, and the lack of affordable housing for elderly individuals on fixed incomes. 53 Solutions Focus group participants and interviewees suggested some solutions to problems discussed above. Education on topics such as fair housing laws, the definition of affordable housing, and particularly financial literacy was recommended as a solution to some issues of fair housing. Northwest Arkansas Community College’s “Building the Future” program was seen as an asset in this regard. Some participants expressed their feeling that many, especially those included within the protected classes, were unaware of their fair housing rights. This lack of awareness and education on fair housing translated to a continuation of acts of discrimination as some residents may be fearful of possible retaliation. Another segment of the focus group participants felt that the increased development costs within the City of Bentonville, as compared to surrounding areas, impeded progress in affordable housing development. Changing zoning regulations to allow for increased density in housing was suggested numerous times as a solution for the affordability problem and one that City Planners are currently exploring. 54 Focus Group Attendees • Shelli Rushing (City of Bentonville) • Bob McCaslin (City of Bentonville) • Rod Sanders (City of Bentonville) • Dan White (City of Bentonville Fire) • James Allen (City of Bentonville Police) • Kristin Netterstrom (press – The Morning News) • Mike Bender (City of Bentonville) • Troy Davis (City of Bentonville) • Danielle Semsrott (City of Bentonville) • Rachel Davis (media – Northwest Arkansas News) • Brian Bahr (City of Bentonville) • Diane Shastid (City of Bentonville) • Ed Clifford (Bentonville/Bella Vista Chamber of Commerce) • Lynn Markel (Rebuilding Together of Northwest Arkansas) • Annette Brightwell (City of Bentonville) • Floretta Bush (Northwest Arkansas Community College) • Gene Schneider (Northwest Arkansas Community College) • Nancy Leake (Bentonville/Bella Vista Community Development Corporation) • Debbie Wieneke (Benton County Habitat for Humanity) • Troy Galloway (City of Bentonville) 55 2. Fair Housing Index The Fair Housing Index is a measure developed specifically for Analyses of Impediments to Fair Housing. The index combines the effects of several demographic variables with Home Mortgage Disclosure Act (HMDA) data and maps the results by census tract. The map provides a general indication of geographic regions within Bentonville where residents might experience some level of housing discrimination or have problems finding affordable, appropriate housing. Methodology Data for ten variables were gathered, by census tract, for analysis. These ten variables were: percent minority, percent female-headed households with children, median housing value, median contract rent, percent of the housing stock constructed prior to 1960, median household income, percent of the population with less than a high school degree, percent of the workforce unemployed, percent using public transportation to go to and from work, and the ratio of loan denials to loan originations for 1998 through 2003 from the Home Mortgage Disclosure Act (HMDA) report published by the Federal Financial Institutions Examination Council. With the exception of the HMDA data, all data were found in the 2000 U.S. Census of Population and Housing. Each variable contained data for every census tract in Benton County. When the database was complete, Pearson correlation coefficients were calculated to assure that all variables displayed a high relationship to each other. It is important, in this type of analysis, that the variables selected are measuring similar aspects of the population. The results of the calculations showed that all variables displayed moderate to high degrees of correlation with other variables in the model, ranging up to 0.8713. Once the relationships of the variables were established, each variable was standardized. This involves calculating a Z-score for each record by variable. For instance, for the variable percent minority, a mean and standard deviation were 56 calculated. The mean for the variable was subtracted from data for each census tract and divided by the standard deviation. The result was a value representing the distance that the data point lay from the mean of the variable, reported in number of standard deviations. This process allows all variables to be reported in the same units (standard deviations from the mean) and, thus, allows for mathematical manipulations using the variables. When all variables were standardized, the data for each census tract were summed with negative or positive values given to each variable to assure that effects were being combined. For instance, in a fair housing environment, high minority concentrations raise suspicions that there may be problems in the area. Therefore, the percent minority variable would be given a negative value. Conversely, one would think that in areas of high housing values, the current residents are not having problems with fair housing choice. Median housing value, therefore, would be assigned a positive value. Each variable was considered in this light and assigned an appropriate sign, thus combining effects. This new variable, the total for each census tract, was then standardized as described for the original ten variables above. The standardized form of the total variable provides a means of identifying individual census tracts where fair housing choice is at high risk due to demographic factors most often associated with housing discrimination. With the data presented in standardized form, the results can be compared to the standard normal distribution, represented by a bell curve with a mean of 0 and a standard deviation of 1. The analysis shows high potential problem areas as those census tracts with standard scores below –2.00. Scores between -1.99 and -1 are designated as areas with a moderate potential for problems. Scores between -0.99 and 0 are reported as a low potential for fair housing problems and above 0 as above average areas. The results are summarized in the following section. It should be emphasized that the data used to perform this analysis do not directly report fair housing violations. The data were utilized in order to measure potential 57 problems based on concentrations of demographic groups who most often experience restrictions to fair housing choice. Areas identified as having potential problems are those where there is a high concentration of minorities, female-headed households, unemployment, high school dropouts, low property values, and, most likely, are areas where a large proportion of loans (conventional home mortgages, FHA or VA home mortgages, refinance, or home improvement) have been denied. Findings In looking at the correlation table (Table 1) there are several high and moderate correlations are worth noting. The first is the correlation between those between the percent of those having less than a high school degree and: - median household income (-0.8030), - percent of pre-1960 housing stock - median housing value (-0.7806), - median rent (-0.6543), and - the ratio of loan denials to originations (0.5774) This would indicate that persons with less than high school degree are more likely to have lesser incomes and tend to live in older housing with lower values or rents. The moderate correlation with the ratio of loan denials to originations indicates that high school dropouts are less likely to obtain a home loan. There is also a moderate correlation between the percent minorities with: - percent less than high school degree (0.6999) - median household income (-0.5963), and - median housing value (-0.5828) This indicates that minorities tend to fall in lower income groups and are likely to live in housing with lower values. There is, however, a low correlation between percent 58 minority and the ratio of originations to denials (0.0717), indicating that race / minority status is not a factor in obtaining a loan. A moderate positive correlation between percent minorities and percent female headed households (0.6438) indicates that these minority households are likely to be headed by females with children. Map 1 shows the fair housing index scores for Bentonville and surrounding census tracts. As discussed, the scores are the measure, in standard deviations from the mean, of the fit for the nine indicators. These ranges are categorized into “high potential for problems”, “moderate potential for problems”, “low potential for problems” and “above average areas”. On this scale, the farther below average the score, the higher the likelihood that problems exist. As indicated on Map 1, the census tracts designated as having the lowest scores, designated as “high potential for problems” are concentrated in the eastern census tracts of Bentonville. A majority of Bentonville’s census tracts fall into the “low potential for problems” category or are “above average areas” – those with a very low likelihood of fair housing problems, as measured by the index. Though there are some tracts in the county which fall into the “moderate potential for problems” category, they are outside the city limits, and are not shown in the map. Included following the map is the correlation table (Table 1). MedValue is the median home value according to the 2000 census. MedRent is the median contract rent. XMinority is the percent minority. XFemHH is the percent female-headed household. XPre60 is the percent of housing built prior to 1960. MedHHI is the median household income. XLessHS is the percent of the population 25 years of age and older that has less than a high school degree. XUnemp is the unemployment rate for the population aged 16 and older considered being in the labor force. XPubTrans is the percent utilizing public transportation to get to and from work. ALLRAT is the ratio of denials to originations from the HMDA data from 1998 to 2003. 59 Conclusions Correlations in the fair housing index model were generally moderate to low. Lower correlations indicate a lower likelihood of fair housing violations. Typically, census tracts or the areas of greatest concern for fair housing choice are areas with high correlations in the fair housing index variables. These area contain the oldest housing stock (more likely than new housing to be in poor condition), with low housing values and rents, and are primarily occupied by minority households, which are often headed by females with children and have educational levels lower than high school. There are no such areas of strong concentrations in Bentonville. The correlation between minority status and the other nine indicators in Bentonville was moderate to low in some cases. A moderate or low correlation in areas with a large minority population yields a positive and reliable result. In areas with a low minority population, outlier data becomes more of an issue, and lower correlations could also be attributed to the low percentage of minorities in the jurisdiction. A high correlation is an indicator that housing choice is at high risk due to demographic factors most often associated with housing discrimination. The moderate or low correlations between minorities and other nine variables indicates that there is lesser likelihood of fair housing violations overall. 60 61 Table 1 Correlation Table of Index Variables AllRat XPubTrans XLessHS XUnemp MedHHI XPre60 MedRent MedValue XMinority XFemHH AllRat 1.0000 XPubTrans -0.0842 1.0000 XLessHS 0.5774 0.2098 1.0000 XUnemp -0.0029 -0.0698 0.2459 1.0000 MedHHI -0.4890 -0.2352 -0.8030 -0.1135 1.0000 XPre60 0.6741 -0.1670 0.5959 0.3242 -0.5203 1.0000 MedRent -0.5816 0.0445 -0.6543 -0.0283 0.6999 -0.5400 1.0000 MedValue -0.5859 -0.2666 -0.7806 0.1015 0.8713 -0.4996 0.7271 1.0000 XMinority 0.0717 0.3998 0.6999 0.3335 -0.5963 0.2407 -0.4390 -0.5828 1.0000 XFemHH 0.0113 0.3269 0.4108 0.1894 -0.5202 0.2038 -0.3896 -0.4478 0.6438 1.0000 Variable Definition XFemHH % Female Headed Households, 2000 XMinority % Minority, 2000 MedValue Median Home Value, 2000 MedRent Median Contract Rent, 2000 XPre60 % of Housing Built Prior to 1960, 2000 MedHHI Median Household Income, 2000 XLessHS % Less than High School Degree, 2000 XUmemp % Unemployed, 2000 XPubTrans % Taking Public Transportation to Work, 2000 AllRat Ratio of Denials to Originations, All Loan Types, 1998 - 2003 62 3. Home Mortgage Disclosure Act (HMDA) Data Analysis Introduction The Federal Financial Institutions Examination Council (FFIEC) gathers data on home mortgage activity from the federal agencies that regulate the home mortgage industry. The data contain variables that facilitate analysis of mortgage lending activity, such as race, income, census tract, loan type, and loan purpose. The FFIEC provides the HMDA databases and retrieval software on compact disk. Data can be summarized within the software package or downloaded in its raw form for analysis. For this analysis, the FFIEC databases were utilized for 1998 through 2003. The data reported here are summarized by tables, charts, and maps provided at the end of this section. Table 1, on page 7, compares the loan activity in Bentonville with Benton County as a whole. Tables 2 and 3, on pages 8 and 9, provide information for the County. The maps, provided at the end of this section, present data according to census tract for Bentonville. The analysis will focus on the tracts within Bentonville and provides a description of mortgage industry specific to the city. Analysis Table 1 examines home loan activities in Bentonville and Benton County. In the county, data are presented by loan type, ethnicity, income, and loan purpose. For the county, White applicants represented the largest number of loan applicants at 80,343. Origination rates (the percentage of applications that result in loans being made) for Whites were nearly 69 percent. Hispanics were the next largest applicant group with over 4,920 applications submitted and an origination rate of nearly 62 percent. Asian origination rates were over 66 percent, but with only 807 applications reported. The African-American origination rate was nearly 62 percent with 411 applications. High-income applicants, those earning more 63 than 120 percent of the median household income, showed both the highest number of applications, nearly 61,290, and the highest origination rate, at over 68 percent. Both the number of applications and the origination rates drop significantly for all other income groups, with over 11,870 applications from middle-income applicants and over 60 percent origination rate. Conventional loans account for the largest number of applications for loan type, nearly 92,660, and the highest origination rate, at just over 59 percent. Refinance loans show the highest number of applications for loan purpose, at nearly 53,580, and the origination rate of over 56 percent. Home improvement loans had the highest origination rate at over 68 percent. Isolating the tracts within Bentonville, for Loan Type, “Conventional” shows the highest number of loan applications, over 37,810, and the highest percentage of loan originations, over 61 percent of all applications. FHA loans show over 51 percent origination rate. For loan purpose, over 60 percent of home purchase loans originated out of about 19,480 applications. The origination rate in home improvement loans was over 70 percent and refinance loans was about 58 percent. In Bentonville, White applicants had the highest origination rate of nearly 71 percent with the highest number of loan applications, about 33,580. The origination rate in African-Americans and Hispanics was about 64 percent. The origination rate in very low-income group was over 48 percent compared to over 70 percent in high-income group in the tracts within the city. Table 2 displays the HMDA data for the same data categories (Loan Type, Ethnicity, Income, and Loan Purpose). On this table, however, percentages are taken within category, rather than demonstrating the percentage of applications that result in loan originations. For instance, the first percentage in the “Origin.” column indicates that 85.75 percent of originations in the county were for conventional loans. For comparison, ethnic percentages were included under the “Pop.” column to compare the percentage of originations by ethnic group to their percentage in the population. 64 For Loan Type, “Conventional” shows the highest percentages, nearly 86 percent of all originations. FHA loans, which are government insured and have more stringent lending criteria, were about 10 percent of the originations. Referring back to Table 1, the origination rates were over 50 percent for FHA versus over 59 percent for conventional. For Ethnicity, “White” shows the highest percentage of origination at nearly 87 percent of the total. The percentage of Whites in the population was over 87 percent. African-American applicants account for 0.4 percent of originations, while their presence in the population was 0.9 percent of all residents. Asian applicants represent 0.8 percent of originations with 2.4 percent of the total population. Hispanic applicants accounted for 4.8 percent of all originations, with 6.1 of the total population. These trends in income and ethnicity data show that African-Americans and Hispanics are more likely to fall within lower-income groups and, therefore, less likely to qualify for mortgage financing. For Income, the highest income group (>120% median) displays the highest percentage of originations, at over 69 percent of all originations. By contrast, the very low-income group accounts for less than three percent of all originations. Loan Purpose data show that home purchase loans accounted for nearly 44 percent of the originations. Refinance loans were the most frequent purpose, over 47 percent. Home improvement loans accounted for just below nine percent of all originations. Table 3 compares origination rates between minorities and White applicants for the various loan purposes and income groups. For all loan purposes shown, White origination rates are higher than minorities. For home purchase loans, origination rates were over 65 percent for Whites and about 62 percent for minorities, a difference of 2.6 percentage points. White applicants for home 65 improvement loans are successful about 19.2 percentage points more often than minorities. The rates for refinance loans show over 11.2 percentage points difference. Looking at the income group comparison, minorities have origination rates 0.1 to 7.9 percentage points lower than Whites with the exception of very low-income group. In Low-Income group (<51% MFI), White origination rates were 2.3 percentage points higher. In the High-Income group (>120% MFI), White origination rates were 7.9 percentage points higher. With Middle-Income applicants (96-120% MFI), White origination rates nearly 2.9 percentage points higher than Minorities. Even though Whites and Minorities in each income group are entering the loan market with relatively equal incomes, origination rates show the above disparities among the two groups. Chart 1 provides a look at origination rates by census tract income for the loan types: conventional, FHA, and VA. Conventional loans have higher origination rates in all income groups than government insured. Chart 2 shows origination rates by ethnicity and income of the census tract. In Very Low- and Middle- income tracts, White rates are exceeded by Asians. While Asian rates are sometimes higher than White rates, these numbers are based on relatively low number of applications. African-American origination rates exceed Hispanic and White rates only in Very Low-Income tracts. Chart 3 looks at origination rates by the income of the applicant and the income of census tract the loan is applied in. There is no loan activity in the county in very low-income tracts except in ‘unknown’ category in 1990s. The 2000 census data shows that there are no very low-income tracts in the city. Ideally, origination rates should be similar among same income groups across different income group of tracts. In moderate-, middle-, and high-income tracts, the origination rates of all the income groups increase as the tract income increases. 66 The origination rates of high-income applicants in moderate-income tracts are almost equal to the origination rates of low-income applicants in high-income tracts. This suggests that redlining may be occurring in lower income tracts. Chart 4 looks at origination rates by loan purpose and income of the census tract. Applications for all loan types have a higher success rate as the tract income increases, as do home improvement loans, peaking at almost 75 percent for the High Income tracts. Refinance loans have the lowest origination rates, in Middle- and High-Income tracts. In all income categories except Very Low-Income Tracts, home improvement loans show the highest origination rates. Ideally, origination rates should remain constant regardless of the tract income level. Maps 1 through 6 look at loan activity by census tract. The ratio of denials to originations was calculated for each loan purpose and loan type. Tracts shown in the darkest red indicate those areas where at least 100 applications are denied for every 100 applications that are originated. The medium red areas indicate those areas where between 75 and 100 applications are denied for every 100 applications originated. The mauve areas show 50 to 75 applications denied for every 100 applications originated. The pink areas show 0 to 50 applications denied for every 100 applications originated. Map 2 shows the total number of loan originations by census tract. Less active areas are shown in the lighter colors, with the most active areas in dark red. Unlike the other maps, the light areas are meant to indicate areas of concern, either for a lack of loan activity or for their low rate of application originations in relation to denials. Maps 3 and 4 compare the ratio of loan denials to originations for Conventional loans and Government Backed loans. Maps 5 and 6 compare the ratio for home purchase loans and home improvement loans. A look at reasons for denial showed that the majority related to the applicants’ credit history or their debt-to-income ratio. Nearly 4,390 denials were related to 67 the applicants’ credit history in the five years of the study. Nearly 1,870 denials were related to the applicants’ debt-to-income ratio and over 1,610 denials blamed on collateral in those same years. Other possible reasons for not originating a loan included incomplete applications, employment history, mortgage insurance denied, unverifiable information, and insufficient cash for downpayment and/or closing costs. Conclusions Overall, the mortgage markets in Bentonville seem to be growing vigorously, providing new opportunities for borrowers to buy housing or refinance existing higher interest loans. Low interest rates coupled with a positive business environment appear to have had a large positive impact on lending activity in the city. The generally higher income and education rates in Bentonville are consistent with higher origination rates. Origination rates in Bentonville are high across racial, ethnic and income levels. The highest success was in the home improvement loan sector with origination rates at above 70 percent. Origination rates in the refinancing loan sector, which accounted for almost half of loan activity, reached 58 percent. During the period between 1998 and 2003, the majority of loan denials were related to the applicants’ credit history. The correlation between minority status and the other nine indicators used in the housing index analysis in Bentonville was moderate to low in some cases. A high correlation would indicate that housing choice is at high risk due to demographic factors most often associated with housing discrimination. The moderate or low correlations between minorities and other nine variables indicates that there is lesser likelihood of fair housing violations overall. In terms of origination rates, there is little change in rates based on ethnicity or income levels of the applicant or income level of the census tracts. Hispanic applicants make up just under 6.1 percent of the population and account for 4.8 percent of the originations. 68 Table 1 Home Mortgage Disclosure Act (HMDA) Analysis Comparison of Number of Loan Applications and Origination Rates Bentonville and Benton County, Arkansas 1998 - 2003 Bentonville Benton County Number Origin. Number Origin. Loan Type: Conventional 37,815 61.12% 92,656 59.01% FHA 4,611 51.31% 12,500 50.31% VA & Other 2,338 56.54% 5,114 54.71% Ethnicity: Native 191 58.12% 609 56.16% Asian 367 69.75% 807 66.54% Black 185 63.78% 411 61.56% Hispanic 1,139 63.74% 4,923 61.91% White 33,576 70.88% 80,343 68.97% Other 274 55.47% 625 57.60% Not Provided 4,814 26.78% 12,118 25.83% Unknown 4,218 8.37% 10,434 6.55% Income: <51% median (very low) 1,212 48.02% 3,118 48.49% 51-80% median (low) 4,157 56.72% 10,808 54.47% 81-95% median (moderate) 2,686 60.76% 6,700 57.46% 96-120% median (middle) 4,632 62.63% 11,875 60.15% >120% median (high) 25,438 70.08% 61,286 68.41% Loan Purpose: Home Purchase 19,478 60.18% 48,573 57.54% Home Improvement 3,419 70.37% 8,037 68.41% Refinance 21,845 57.92% 53,577 56.44% Totals 44,764 59.87% 110,270 57.82% 69 Table 2 Home Mortgage Disclosure Act (HMDA) Analysis Comparison of Originations Within Categories Benton County 1998- 2003 Origin. Percent Pop. Loan Type: Conventional 54,675 85.75% FHA 6,289 9.86% VA & Other 2,798 4.39% Ethnicity: Native 342 0.54% 1.33% Asian 537 0.84% 2.43% Black 253 0.40% 0.88% Hispanic 3,048 4.78% 6.07% White (non-Hispanic) 55,409 86.90% 87.55% Other 360 0.56% 4.43% Not Provided 3,130 4.91% Unknown 683 1.07% Income: <51% median 1,512 2.51% 51-80% median 5,887 9.76% 81-95% median 3,850 6.38% 96-120% median 7,143 11.84% >120% median 41,923 69.51% Loan Purpose: Home Purchase 27,947 43.83% Home Improvement 5,498 8.62% Refinance 30,240 47.43% Totals 63,762 70 Table 3 Analysis of Home Mortgage Disclosure Act Data HMDA Activity for Benton County, 1998 - 2003 # Apps. % of Apps. % Denied % Orig. Home Purchase Loans Minorities 4,770 9.82% 16.14% 62.47% White 36,221 74.57% 15.44% 65.04% Not Provided 7,582 15.61% 8.11% 18.60% Home Improvement Loans Minorities 319 3.97% 25.39% 60.50% White 6,164 76.70% 12.41% 79.67% Not Provided 1,554 19.34% 39.96% 25.35% Refinance Loans Minorities 2,284 4.26% 15.19% 59.76% White 37,905 70.75% 10.35% 70.94% Not Provided 13,388 24.99% 23.74% 14.82% All Loan Purposes Minorities 7,375 6.69% 16.24% 61.56% White 80,343 72.86% 12.80% 68.97% Not Provided 22,552 20.45% 19.57% 16.91% Income Groups <51% MFI Minorities 357 11.45% 29.13% 55.46% White 2,346 75.24% 32.27% 53.45% Not Provided 415 13.31% 46.51% 14.46% 51 to 80% MFI Minorities 1,341 12.41% 23.64% 56.90% White 8,286 76.67% 23.35% 59.22% Not Provided 1,181 10.93% 48.94% 18.37% 81 to 95% MFI Minorities 693 10.34% 18.33% 62.48% White 5,193 77.51% 18.85% 62.58% Not Provided 814 12.15% 40.17% 20.52% 96 to 120% MFI Minorities 1,335 11.24% 15.73% 62.40% White 9,157 77.11% 16.47% 65.31% Not Provided 1,383 11.65% 35.94% 23.86% >120% MFI Minorities 3,222 5.26% 12.63% 65.55% White 51,076 83.34% 9.44% 73.49% Not Provided 6,988 11.40% 29.45% 32.56% Not Provided Minorities 427 2.59% 7.73% 47.07% White 4,285 26.00% 6.51% 57.92% Not Provided 11,771 71.41% 6.47% 6.49% Demographics % Minority % Owner Occ. % Vacant Countywide 13.32% 65.38% 9.44% 71 Chart 2 Origination Rates by Ethnicity by Income of Census Tract 0 10 20 30 40 50 60 70 Very Low Low Moderate Middle High Income Group of Tracts O
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Va 72 Chart 4: Origination Rates by Loan Purpose by Income of Census Tract 0 10 20 30 40 50 60 70 80 Very Low Low Moderate Middle High Income Group of Tracts Or ig
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Refinance Chart 3: Origination Rates by Applicant Income by Income of Census Tract 0 10 20 30 40 50 60 70 80 Verylow Low Moderate Middle High Income Group of Tracts Or ig
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High 73 ´ 0 1 2 3 4 0.5 Miles J-Q UAD & A S S OC IAT ES , LLC . Map 1: Ratio of All Loan Types
Denials to Originations, 1998-2003 Legend Bentonville City Limits Census Tracts 0.0 - 0.505 0.506 - 0.755 0.756 - 1.005 1.006 - 1.147 Map 2: Total Number of Loans,
1998-2003 Bentonville, Arkansas Legend BentonvilleCityLimits Total Number of Loans 28 - 1,197 1,198 - 2,646 2,647 - 4,698 4,699 - 6,833 74 ´ 0 1 2 3 4 0.5 Miles J-Q UAD & A S S OC I AT ES , LLC . Map 3: Ratio of Conventional Loan
Denials to Originations, 1998-2003 Legend Bentonville City Limits Census Tracts 0.118 - 0.505 0.506 - 0.755 0.756 - 1.005 1.006 - 1.259 Map 4: Bentonville, Arkansas Legend BentonvilleCityLimits Census Tracts 0.000 - 0.505 0.506 - 0.755 0.756 - 1.005 1.006 - 2.000 Ratio of Government Backed Loan
Denials to Originations, 1998-2003 75 ´ 0 1 2 3 4 0.5 Miles J-Q UAD & A S S OC IAT ES , LLC . Map 5: Ratio of Home Purchase Loan
Denials to Originations, 1998-2003 Legend Bentonville City Limits Census Tracts 0.105 - 0.505 0.506 - 0.755 0.756 - 1.005 1.006 - 1.525 Map 6: Bentonville, Arkansas Legend BentonvilleCityLimits Census Tracts 0.000 - 0.505 0.506 - 0.555 Ratio of Home Improvement Loan
Denials to Originations, 1998-2003

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