Pub. 11 2021 Issue 1

6 www.azbankers.org According to a report by Zillow that examined the impacts of the long-abandoned color-coded maps, the median home value in the neighborhoods that had been designated “best” had risen 230.8% to $640,238 between 1996 and 2018. In contrast, the median value in red-colored “hazardous” areas grew only 203.1%, to $276,199. In addition to housing, legitimate race- neutral credit factors such as credit score, income, and wealth continue to show racial disparities. According to a 2019 report published by the Consumer Financial Protection Bureau, “the 2018 HMDA data shows that the credit scores of Black and Hispanic White applicants, on average, are lower than those of non-Hispanic White and Asian applicants overall and across all enhanced loan types. Additionally, there are higher percentages of Black and Hispanic White applicants whose credit scores fall on the low end of the distribution and fall below the common underwriting cutoff points.” As for wealth, the disparities are very high. A typical white family’s net worth ($171,000) is nearly 10 times greater than that of the average Black family ($17,150). In a 2017 study, the Federal Reserve stated: “Wealth tends to increase with income because of higher levels of saving among higher-income families, and because of the feedback effect on higher incomes from the returns generat- ed by accumulated assets.” This same study provided findings on the income gap. It found that in 2016, median incomes for white fami- lies were $61,200, while median incomes for Black and Hispanic families were $35,400. Independently, the disparities described above are concerning and problematic enough; when considered simultaneously and along with the lasting impacts of redlin- ing, the interrelated and multiplying effect demonstrate a vicious cycle in desperate need of attention. In cases where the risk of unlawful credit discrimination is mitigated through a business justification, compliance officers may want to go further to review within the context of wider corporate social responsibility, conduct or ethics lens. Special Purpose Credit Programs Regulation B §1002.8 is dedicated to Special Purpose Credit Programs, intended to promote access to credit through lending products and programs designed to meet special social needs and benefit economically disadvantaged groups. This includes meeting the needs of a prohibited basis group that is being underserved in the market. These programs allow collecting prohibited basis characteristics, such as race, to ensure the credit programs are appropriately targeted to intended prohibited basis group applicants. While companies across various industries can make commitments through philanthropy, diversity initiatives or public statements denouncing racism, a Special Purpose Credit Program is clearly one fairness-boosting opportunity unique to the banking industry. The basic components of a Special Purpose Credit Program include demonstrating the unmet need, drafting a written plan to lay out the specifics of how the program will operate, and engaging with whichever regulator has responsibility for oversee- ing Regulation B for your institution. The commentary to Regulation B clarifies that “a for-profit organization must determine that the program will benefit a class of people who would otherwise be denied credit or would receive it on less favorable terms. This determination can be based on a broad analysis using the organization’s research or data from outside sources, including govern- mental reports and studies.” In its summer 2016 Supervisory Highlights, the CFPB set forth observations regarding credit decisions made pursuant to the terms of programs that for-profit institutions have described as Special Purpose Credit Programs. Two examples observed by the CFPB included: a Small business lending programs provid- ing credit to minority-owned businesses that were otherwise more likely to be de- nied credit than non-minority owned firms. a Mortgage lending programs with special rates and terms for individuals with income below certain thresholds or, for those buying property in areas where the median income was below certain thresholds, which otherwise would have resulted either in denial of mortgage credit or in higher-priced mortgage credit. The CFPB stated it “generally takes a favorable view of conscientious efforts that institutions may undertake to develop special-purpose credit programs to promote extensions of credit to any class of persons who would otherwise be denied credit or would receive it on less favorable terms.” The CFPB also recently published an article on July 31, 2020, reminding creditors of the availability and opportunity related to Special Purpose Credit Programs. Responsible Innovation In some ways, it’s difficult for banks to make loans that meet safety and sound- ness standards without using commonly accepted creditworthiness factors — such as a credit score, income, net worth or collateral value — that have been his- torically correlated with racial groups. The use of certain types of data has been shown to have a disparate impact on Black applicants, even though these data types can still be fair-lending compli- ant if accompanied by a valid business necessity. Thus, the resulting outcomes of reduced access to credit for Blacks are in effect perpetuated. Regulators have encouraged responsible use of alternative data and have highlighted a “success sto- ry” involving machine learning modeling techniques which increased access to credit while still being fair. A Special Purpose Credit Program, used in conjunction with alternative data (e.g., perhaps an alternative to using a tradi- tional credit score), or machine learn- ing while adding risks, complexity and uncertainty that comes from “unproven” techniques, offers an exciting possibility to explore alongside your regulators. Es- tablishing principles regarding the ethical use of data is another action that can have a far-reaching impact, given that good use of data is foundational to responsible innovation. continued from page 5