NEWS RELEASE, 05/14/98 Minority groups in Oakland face home loan discrimination, says new UC Berkeley report

By Cathy Cockrell, Public Affairs

BERKELEY -- For anyone who thinks that home loan discrimination is a thing of the past, think again. African Americans in Oakland are 54 percent less likely to be approved for a home loan than white applicants, according to a new report from the University of California, Berkeley. The analysis of federal mortgage data also found that Hispanic, American Indian and Asian applicants are at a significant disadvantage. The report, "Home Mortgage Lending in Oakland," was written by Jesse Blout, who received his Master's degree in City and Regional Planning last year from UC Berkeley. It was published by the campus' Institute of Urban and Regional Development (IURD). Using 1993-95 federal mortgage data obtained through the Home Mortgage Disclosure Act, Blout studied lending activity in Oakland and the factors influencing loan decisions. Blout, who now is a real estate and urban development specialist with a local consulting firm, did the analysis for his graduate thesis under the direction of John Landis, associate professor of City and Regional Planning, and Michael Smith-Heimer, a lecturer in City and Regional Planning. The 1993-95 numbers show that the home loan approval rate in Oakland was lowest for African Americans, at 66.6 percent. Hispanics were next at 75.8 percent, followed by American Indians at 76.3 percent and Asians at 81.1 percent. The approval rate for whites was 86.9 percent. "Often when people talk about discrimination in mortgage lending, there's a question of how much of that is (based on) income and how much is based on race," said Landis. The report, using multivariate regression statistical techniques, isolates the impact of race from that of income "in a very useful way," he added. For example, home loan approval rates for whites and African Americans differed by 9.2 percentage points among applicants in the lowest income quartile. In the highest income quartile the approval rates for whites and African Americans differed by 20.7 percentage points. The more than 20 percent difference between whites and African Americans in the highest income group "is a pretty overwhelming gap, which we believe can't be explained away by credit history," said Blout. He added that many mortgage industry experts claim that credit history accounts for racial disparities in approval rates. While the report's primary focus is Oakland, it also includes comparative data for all of Alameda County. This data suggests county-wide racial disparities in mortgage lending. The report also found that discriminatory trends identified in Oakland may be exacerbated in the future by automated underwriting systems endorsed by the two biggest companies in the United States' mortgage market - Freddie Mac and Fannie Mae ­ and adopted by many lenders nationwide. To evaluate a loan application using an automated, statistical scoring model, each item is assigned a weighted value. The age of the property, for example, might be a factor. But which variables are used in a particular model, and how the variables are weighted, are industry secrets, according to the report. In theory, the final score computed from these values can predict if the applicant is likely to default on the loan. The report says proponents of statistical scoring models claim these models improve consistency and speed and remove human bias from mortgage lending. Such systems, however, "are only as good as the data on which they were built," cautions the IURD report. "Subjecting all applicants to the same set of weighted measures, irrespective of the property or loan type, may result in unintended bias against certain populations." Loan applicants from Oakland's poorest neighborhoods, where duplexes and multi-family units are common, may be at a disadvantage if the scoring model assigns a numerical advantage to detached single-family homes. Blout said the automated models also may discriminate subtly against applicants who live in extended families or keep their assets in cash instead of in a bank. In contrast, the report describes an alternative underwriting program offered in Oakland by American Savings Bank, which now is owned by Washington Mutual, Inc. The bank's Special Purpose Community Lending Program has become a national model and has won numerous awards for its innovative approach to underwriting in low income communities. According to Landis, the IURD report documents how paying close attention to local market conditions "is a good business practice as well as good for a community. But you have to look past simplistic indicators, looking closely at the circumstances of the credit history of an applicant and the local housing market. And you have to want to make home loans in that market."