{"id":332762,"date":"2021-08-31T14:18:06","date_gmt":"2021-08-31T11:18:06","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/the-secret-bias-hidden-in-mortgage-approval-algorithms\/"},"modified":"2021-08-31T14:18:06","modified_gmt":"2021-08-31T11:18:06","slug":"the-secret-bias-hidden-in-mortgage-approval-algorithms","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/the-secret-bias-hidden-in-mortgage-approval-algorithms\/","title":{"rendered":"#The secret bias hidden in mortgage-approval algorithms"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6a30a347cc890\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #dd3333;color:#dd3333\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #dd3333;color:#dd3333\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a30a347cc890\" checked aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/buradabiliyorum.com\/en\/the-secret-bias-hidden-in-mortgage-approval-algorithms\/#Location_location_location\" >Location, location, location<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/buradabiliyorum.com\/en\/the-secret-bias-hidden-in-mortgage-approval-algorithms\/#Stuck_in_the_past\" >Stuck in the past<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/buradabiliyorum.com\/en\/the-secret-bias-hidden-in-mortgage-approval-algorithms\/#%E2%80%9CColor-blind%E2%80%9D_approvals\" >\u201cColor-blind\u201d approvals?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/buradabiliyorum.com\/en\/the-secret-bias-hidden-in-mortgage-approval-algorithms\/#A_Secret_algorithms_secret_decisions\" >A Secret algorithm\u2019s secret decisions<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/buradabiliyorum.com\/en\/the-secret-bias-hidden-in-mortgage-approval-algorithms\/#Laws_and_their_limits\" >Laws and their limits<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/buradabiliyorum.com\/en\/the-secret-bias-hidden-in-mortgage-approval-algorithms\/#Perseverance\" >Perseverance<\/a><\/li><\/ul><\/nav><\/div>\n<p>&#8220;<strong>#The secret bias hidden in mortgage-<a href=\"https:\/\/buradabiliyorum.com\/en\/category\/download-scripts-themes-apps\/\" data-internallinksmanager029f6b8e52c=\"9\" title=\"Download Scripts &amp; Themes &amp; Apps\" target=\"_blank\" rel=\"noopener\">app<\/a>roval algorithms<\/strong>&#8221;<br \/>\n<img decoding=\"async\" src=\"https:\/\/img-cdn.tnwcdn.com\/image?fit=796%2C417&amp;url=https%3A%2F%2Fcdn0.tnwcdn.com%2Fwp-content%2Fblogs.dir%2F1%2Ffiles%2F2021%2F08%2FMortageHed.jpg&amp;signature=0bc692da2630cffadc11944191489d24\" \/><\/p>\n<div>The new four-bedroom house in Charlotte, N.C., was Crystal Marie and Eskias McDaniels\u2019s personal American dream, the reason they had moved to this Southern town from pricey Los Angeles a few years ago. A lush, long lawn, 2,700 square feet of living space, a neighborhood pool and playground for their son, Nazret. All for $375,000.<\/p>\n<p>Prequalifying for the mortgage was a breeze. They said they had saved much more than they would need for the down payment, had very good credit\u2014scores of 805 and 725\u2014and earned roughly six figures each, she in marketing at a utility company and Eskias representing a pharmaceutical company. The monthly mortgage payment was less than they\u2019d paid for rent in Los Angeles for years.<\/p>\n<p>They were scheduled to sign the mortgage documents on Aug. 23, 2019\u2014a Friday\u2014and were so excited to move in they booked movers for the same day.<\/p>\n<p>The Wednesday before the big day, the loan officer called Crystal Marie, and everything changed, she said: The deal wasn\u2019t going to close.<\/p>\n<p>The loan officer told the couple that he had submitted the application internally to the underwriting department for approval a dozen, 15, maybe 17 times, getting a \u2018no\u2019 each time. The couple had spent $6,000 in fees and deposits\u2014all nonrefundable.<\/p>\n<p>\u201cIt seemed like it was getting rejected by an algorithm,\u201d she said, \u201cand then there was a person who could step in and decide to override that or not.\u201d<\/p>\n<p>She was told she didn\u2019t qualify because she was a contractor, not a full-time employee\u2014even though her boss told the lender she was not at risk of losing her job. Her co-workers were contractors, too, and they had mortgages.<\/p>\n<p>Crystal Marie\u2019s co-workers are White. She and Eskias are Black.<\/p>\n<p>\u201cI think it would be really naive for someone like myself to not consider that race played a role in the process,\u201d she said.<\/p>\n<p>An investigation by The Markup has found that lenders in 2019 were more likely to deny home loans to people of color than to White people with similar financial characteristics\u2014even when we controlled for newly available financial factors that the mortgage industry for years has <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.mba.org\/2018-press-releases\/february\/mba-statement-on-flawed-reveal-news-analysis-on-mortgage-lending\">said would explain<\/a> racial disparities in lending.<\/p>\n<p>Holding 17 different factors steady in a complex statistical analysis of more than two million conventional mortgage applications for home purchases, we found that lenders were 40 percent more likely to turn down Latino applicants for loans, 50 percent more likely to deny Asian\/Pacific Islander applicants, and 70 percent more likely to deny Native American applicants than similar White applicants. Lenders were 80 percent more likely to reject Black applicants than similar White applicants. These are national rates.<\/p>\n<p>In every case, the prospective borrowers of color looked almost exactly the same on paper as the White applicants, except for their race.<\/p>\n<p>The <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/4375365-ABA-Statement-to-Reveal.html\">industry<\/a> had <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/4364490-MBA-Statement-to-Reveal.html\">criticized<\/a> previous similar analyses for not including financial factors they said would explain disparities in lending rates but were not public at the time: debts as a percentage of income, how much of the property\u2019s assessed worth the person is asking to borrow, and the applicant\u2019s credit score.<\/p>\n<p>The first two are now public in the Home Mortgage Disclosure Act data. Including these financial data points in our analysis not only failed to eliminate racial disparities in loan denials, it highlighted new, devastating ones.<\/p>\n<p>We found that lenders gave fewer loans to Black applicants than White applicants even when their incomes were high\u2014$100,000 a year or more\u2014and had the same debt ratios. In fact, high-earning Black applicants with <em>less<\/em> debt were rejected more often than high-earning White applicants who have <em>more<\/em> debt.<\/p>\n<p>\u201cLenders used to tell us, \u2018It\u2019s because you don\u2019t have the lending profiles; the ethno-racial differences would go away if you had them,\u2019 \u201d said Jos\u00e9 Loya, assistant professor of urban planning at UCLA who has studied public mortgage data extensively and reviewed our methodology. \u201cYour work shows that\u2019s not true.\u201d<\/p>\n<p>We sent our complete analysis to industry representatives: The American Bankers Association, The Mortgage Bankers Association, The Community Home Lenders Association, and The Credit Union National Association. They all criticized it <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/general\/\" data-internallinksmanager029f6b8e52c=\"3\" title=\"General\" target=\"_blank\" rel=\"noopener\">general<\/a>ly, saying the public data is not complete enough to draw conclusions, but did not point to any flaws in our computations.<\/p>\n<p>Blair Bernstein, director of public relations for the ABA, acknowledged that our analysis showed disparities but that \u201cgiven the limitations\u201d in the public data we used, \u201cthe numbers are not sufficient on their own to explain why those disparities exist.\u201d<\/p>\n<p>In written statements, the <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/20985433-statement-from-the-american-bankers-association\">ABA<\/a> and <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/20988518-statement-from-the-mortgage-bankers-association\">MBA<\/a> criticized The Markup\u2019s analysis for not including credit scores and for focusing on conventional loans only and not including government loans, such as those guaranteed by the Federal Housing Administration and Department of Veterans Affairs.<\/p>\n<p>Isolating conventional loans from government loans is common in mortgage research because they are different products, with different thresholds for approval and loan terms. Government loans bring people who wouldn\u2019t otherwise qualify into the market but tend to be more expensive for the borrower.<\/p>\n<p>Even the Federal Reserve and Consumer Financial Protection Bureau, the agency that releases mortgage data, separate conventional and FHA loans in their research on lending disparities. Authors of one academic study out of Northeastern and George Washington universities said they focus on conventional loans only because FHA loans have \u201c<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/20491481-friedman-and-squires-does-the-cra-help-minorities-access-july-2004\">long been implemented in a manner that promotes segregation<\/a>.\u201d<\/p>\n<p>As for credit scores, it was impossible for us to include them in our analysis because the CFPB s<a href=\"https:\/\/buradabiliyorum.com\/en\/category\/trip-and-travel\/\" data-internallinksmanager029f6b8e52c=\"10\" title=\"Trip &amp; Travel\" target=\"_blank\" rel=\"noopener\">trip<\/a>s them from public view from HMDA data\u2014in part due to the mortgage industry\u2019s <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/21011405-mortgage-bankers-trade-groups-letter-to-cfpb-10-29-14\">lobbying<\/a> to remove them, citing borrower privacy.<\/p>\n<p>When the CFPB first proposed expanding mortgage data collection to include the very data that industry trade groups have told us is vital for doing this type of analysis\u2014credit scores, debt-to-income ratio, and loan-to-value ratio\u2014those same groups objected. They didn\u2019t want the government to even collect the data, let alone make it public. They cited the risk of cyberattack, which could reveal borrowers\u2019 private information.<\/p>\n<p>\u201cThese new [data] fields include confidential financial data,\u201d <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/21011405-mortgage-bankers-trade-groups-letter-to-cfpb-10-29-14\">several large trade groups wrote<\/a> in a letter to the CFPB, including the ABA and MBA. \u201cConsequently, if this [sic] data are inadvertently or knowingly released to the public, the harm associated with re-identification would be even greater.\u201d<\/p>\n<p>Government regulators do have access to credit scores. The CFPB analyzed 2019 HMDA data and found that accounting for credit scores <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/files.consumerfinance.gov\/f\/documents\/cfpb_data-points_updated-review-hmda_report.pdf\">does not eliminate lending disparities for people of color<\/a>. <s\/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Location_location_location\"><\/span>Location, location, location<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>In addition to finding disparities in loan denials nationally, we examined cities and towns across the country individually and found disparities in 89\u00a0metropolitan areas spanning every region of the country. In Charlotte, where Crystal Marie and her family searched for a home, lenders were 50\u00a0percent more likely to deny loans to Black applicants than White ones with similar financial profiles. In other places, the gap was even larger.<\/p>\n<p>Black applicants in Chicago were 150 percent more likely to be denied by financial institutions than similar White applicants there. Lenders were more than 200 percent more likely to reject Latino applicants than White applicants in Waco, Texas, and to reject Asian and Pacific Islander applicants than White ones in Port St. Lucie, Fla. And Native American applicants in Minneapolis were 100\u00a0percent more likely to be denied by financial institutions than similar White applicants there.<\/p>\n<p>\u201cIt\u2019s something that we have a very painful history with,\u201d said Alderman Matt Martin, who represents Chicago\u2019s 47th Ward. \u201cRedlining,\u201d the now-outlawed practice of branding certain Black and immigrant neighborhoods too risky for financial investments that began in the 1930s, can be traced back to Chicago. <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/muse.jhu.edu\/chapter\/1535256\">Chicago activists exposed<\/a> that banks were still redlining in the 1970s, leading to the establishment of the Home Mortgage Disclosure Act, the law mandating the collection of data used for this story.<\/p>\n<p>\u201cWhen you see that maybe the tactics are different now, but the outcomes are substantially similar,\u201d Martin added, \u201cit\u2019s just not something we can continue to tolerate.\u201d<\/p>\n<p>Who makes these loan decisions? Officially, lending officers at each institution. In reality, software, most of it mandated by a pair of quasi-governmental agencies.<\/p>\n<p><a rel=\"nofollow noopener\" target=\"_blank\" href=\"http:\/\/www.freddiemac.com\/\">Freddie Mac<\/a> and <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.fanniemae.com\/\">Fannie Mae<\/a> were founded by the federal government to spur homeownership and now buy about half of all mortgages in America. If they don\u2019t approve a loan, the lenders are on their own if the borrower skips out.<\/p>\n<p>And that power means that Fannie and Freddie essentially set the rules for the industry, starting from the very beginning of the mortgage-approval process.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Stuck_in_the_past\"><\/span>Stuck in the past<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Fannie and Freddie require lenders to use a particular credit scoring algorithm, \u201cClassic FICO,\u201d to determine whether an applicant meets the minimum threshold necessary to even be considered for a conventional mortgage, currently a score of 620.<\/p>\n<p>This algorithm was developed from data from the 1990s and is more than 15\u00a0years old. It\u2019s widely considered detrimental to people of color because it rewards traditional credit, to which White Americans have more access. It doesn\u2019t consider, among other things, on-time payments for rent, utilities, and cellphone bills\u2014but will lower people\u2019s scores if they get behind on them and are sent to debt collectors. Unlike more recent models, it penalizes people for past medical debt even if it\u2019s since been paid.<\/p>\n<p>\u201cThis is how structural racism works,\u201d said Chi Chi Wu, a staff attorney at the National Consumer Law Center. \u201cThis is how racism gets embedded into institutions and policies and practices with absolutely no animus at all.\u201d<\/p>\n<p>Potentially fairer credit models have existed for years. A <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/20986644-vantagescore-slides-june-2021\">recent study<\/a> by Vantage Score\u2014a credit model developed by the \u201cBig Three\u201d credit bureaus to compete with FICO\u2014estimated that its model would provide credit to 37\u00a0million Americans who have no scores under FICO models. Almost a third of them would be Black or Latino.<\/p>\n<p>Yet Fannie and Freddie have resisted a steady stream of plaintive requests since 2014 from advocates, the mortgage and housing industries, and Congress to update to a newer model. Even the company that created Classic FICO has lobbied for the agencies to adopt a newer version, which it said expands credit to more people.<\/p>\n<p>\u201cA lot of things that minorities and underserved borrowers are doing, responsible financial behaviors, are going under the radar,\u201d said Scott Olson, executive director of the Community Home Lenders Association, a trade group representing small and midsized independent mortgage lenders.<\/p>\n<p>Fannie\u2019s and Freddie\u2019s regulator and conservator, the Federal Housing Finance Agency, continues to allow the companies to stick with Classic FICO, more than five years after ordering them to study the effects of switching to something newer. The FHFA has also expressed concern about the \u201ccost and operational implications\u201d if they would have to continually test new credit scoring models.<\/p>\n<p>Neither of the companies would answer questions from The Markup about why they still require Classic FICO.<\/p>\n<p>\u201cThey\u2019ve been testing alternate scores for years, and I don\u2019t know why the process is taking so long,\u201d said Lisa Rice, president and CEO of the National Fair Housing Alliance, a consortium of hundreds of fair housing organizations. \u201cWell-deserving consumers are being left behind.\u201d<\/p>\n<h2><span class=\"ez-toc-section\" id=\"%E2%80%9CColor-blind%E2%80%9D_approvals\"><\/span>\u201cColor-blind\u201d approvals?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Fannie\u2019s and Freddie\u2019s approval process also involves other mysterious algorithms: automated underwriting software programs that they first launched in 1995 to much fanfare about their speed, ease and, most important, fairness.<\/p>\n<p>\u201cUsing a data base as opposed to human judgment can avoid influences by other forces, such as discrimination against minority individuals and red-lining,\u201d Peter Maselli, then a vice president of Freddie Mac, told The New York Times when it launched its software, now called Loan Product Advisor. A bank executive told Congress that year that the new systems were \u201cexplicitly and implicitly \u2018color blind,\u2019 \u201d since they did not consider a person\u2019s race at all in their evaluations.<\/p>\n<p>But, like similar promises that algorithms would make color-blind decisions in criminal risk assessment and health care, research shows that some of the factors Fannie and Freddie say their software programs consider affect people differently depending on their race or ethnicity. These include, in addition to credit histories, the prospective borrowers\u2019 assets, employment status, debts, and the size of the loan relative to the value of the property they\u2019re hoping to buy.<\/p>\n<p>\u201cThe quality of the data that you\u2019re putting into the underwriting algorithm is crucial,\u201d said Aracely Paname\u00f1o, director of Latino affairs for the Center for Responsible Lending. \u201cIf the data that you\u2019re putting in is based on historical discrimination, then you\u2019re basically cementing the discrimination at the other end.\u201d<\/p>\n<p><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/cpb-us-e1.wpmucdn.com\/sites.suffolk.edu\/dist\/3\/1172\/files\/2014\/01\/Rice-Swesnik_Lead.pdf\">Research<\/a> has shown that payday loan sellers usually place branches in neighborhoods populated mainly by people of color, where bank branches are less common. As a result, residents are more likely to use these predatory services to borrow money. This creates lopsided, incomplete credit histories because banks report both good and bad financial behavior to credit bureaus, while payday loan services only report missed payments.<\/p>\n<p>Gig workers who are people of color are more likely to report that those jobs are their primary source of income\u2014rather than a side hustle they\u2019re using for extra cash\u2014than White gig workers. Having multiple sources of income or unconventional employment can complicate the verification process for a mortgage, as Crystal Marie and Eskias learned.<\/p>\n<p>Considering an applicant\u2019s assets beyond the down payment, which lenders call \u201creserves,\u201d can cause particular problems for people of color. People with fatter bank accounts present a lower risk because they can more easily weather a setback that would leave others unable to pay the mortgage. But, largely due to intergenerational wealth and past racist policies, the typical White family in America today has <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.federalreserve.gov\/econres\/notes\/feds-notes\/disparities-in-wealth-by-race-and-ethnicity-in-the-2019-survey-of-consumer-finances-20200928.htm\">eight times the wealth<\/a> of a typical Black family and five times the wealth of a Latino family. People of color are more likely to have smaller savings accounts and smaller (or nonexistent) stock portfolios than White people.<\/p>\n<p>\u201cThis is a relatively new world of automated underwriting engines that by intent may not discriminate but by effect likely do,\u201d said David Stevens, a former president and CEO of the Mortgage Bankers Association, now an independent financial consultant.<\/p>\n<p>Not even home valuations are free from controversy. The president of the trade group representing real estate appraisers, who determine property values for loans, <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.bloomberg.com\/news\/articles\/2021-03-03\/appraisers-acknowledge-bias-in-home-valuations\">recently acknowledged<\/a> that racial bias is prevalent in the industry and launched new programs to combat it.<\/p>\n<p>\u201cAny type of data that you look at from the financial services space has a high tendency to be highly correlated to race,\u201d said Rice, of the National Fair Housing Alliance.<\/p>\n<p>In written statements, Fannie said its software analyzes applications \u201cwithout regard to race,\u201d and both Fannie and Freddie said their algorithms are routinely evaluated for compliance with fair lending laws, internally and by the FHFA and the Department of Housing and Urban Development. HUD said in an email to The Markup that it has asked the pair to make changes in underwriting criteria as a result of those reviews but would not disclose the details.<\/p>\n<p>\u201cThis analysis includes a review to ensure that model inputs are not serving as proxies for race or other protected classes,\u201d Chad Wandler, Freddie\u2019s director of public relations, said in a written statement. He declined to elaborate on what the review entails or how often it\u2019s done.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"A_Secret_algorithms_secret_decisions\"><\/span>A Secret algorithm\u2019s secret decisions<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>No one outside Fannie and Freddie knows exactly how the factors in their underwriting software are used or weighted; the formulas are closely held secrets. Not even the companies\u2019 regulator, the FHFA, appears to know, beyond broad strokes, exactly how the software scores applicants, according to Stevens, who served as Federal Housing Administration commissioner and assistant secretary for housing at HUD during the Obama administration.<\/p>\n<p>The Markup\u2019s analysis does not include decisions made by Fannie\u2019s and Freddie\u2019s underwriting algorithms because, while lenders are required to report those decisions to the government, the CFPB scrubs them from public mortgage data, arguing that including them \u201c<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/21010234-cfpb-final-policy-guidance-disclosure-of-loan-level-hmda-data\">would likely disclose information about the applicant or borrower<\/a> that is not otherwise public and may be harmful or sensitive.\u201d Lenders\u2019 ultimate mortgage decisions are public, however. Borrowers\u2019 names are not reported to the government and addresses are not in the public data.<\/p>\n<p>Fannie and Freddie declined to answer our questions about why their algorithms\u2019 decisions are excluded from the public data but said in a 2014 letter to the CFPB that the revelation could allow their decision-making algorithms to be <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/21011380-letter-from-freddie-mac-to-cfpb-10-29-2014\">reverse-engineered<\/a>.<\/p>\n<p>Loan officers say the software\u2019s decisions are mysterious even to them.<\/p>\n<p>\u201cWhen you run so many deals through the automated system, you\u2019ll look at one deal that didn\u2019t get an approval, and you just know that that\u2019s a better client than someone else that might\u2019ve gotten approved,\u201d said Ashley Thomas\u00a0III, a broker and owner of LA Top Broker, Inc., a minority-owned real estate agency and brokerage in South Los Angeles. \u201cThat lack of transparency in the <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/technology\/\" data-internallinksmanager029f6b8e52c=\"4\" title=\"Technology\" target=\"_blank\" rel=\"noopener\">technology<\/a> is very concerning.\u201d<\/p>\n<p>The Community Home Lenders Association <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.nationalmortgagenews.com\/news\/fannie-mae-freddie-macs-automated-underwriting-changes-irk-lenders\">sent a letter<\/a> to Fannie and Freddie in April complaining about unannounced changes to both of their underwriting software programs that members discovered when applicants who had previously been approved suddenly were denied.<\/p>\n<p>Olson, executive director of CHLA, said there\u2019s no good reason to keep lenders in the dark: \u201cThe more transparent, the more clear the guidance is, the easier it is for borrowers to know what they need to do to be in a position to qualify.\u201d<\/p>\n<p>Earlier this month\u2014and weeks after we began asking about its algorithms\u2014Fannie announced in a press release that it would start incorporating on-time rent payments in its loan approval software starting in mid-September. When we asked about the timing of that change, spokesperson Katie Penote emailed The Markup a statement saying the company wanted prospective borrowers \u201cto have this option as soon as possible\u201d but was silent about what prompted it.<\/p>\n<p>In addition to using Fannie\u2019s or Freddie\u2019s software, many large lenders also run applicants through their institutions\u2019 own underwriting software, which may be more stringent. How those programs work is even more of a mystery; they are also proprietary.<\/p>\n<p>When we examined the reasons lenders listed for denying mortgages in 2019, the most common reason across races and ethnicities, with the exception of Native Americans, was that applicants had too much debt relative to their incomes. When lenders did list \u201ccredit history\u201d as the reason for denial, it was cited more often for Black applicants than White ones in 2019: 33\u00a0percent versus 21\u00a0percent.<\/p>\n<p>When we examined the decisions by individual lenders, many denied people of color more than White applicants. An additional statistical analysis showed that several were at least 100 percent more likely to deny people of color than similar White borrowers. Among them: the mortgage companies owned by nation\u2019s three largest home builders.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Laws_and_their_limits\"><\/span>Laws and their limits<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The two principal laws forbidding housing and lending discrimination are the 1968 Fair Housing Act and the 1974 Equal Credit Opportunity Act. An alphabet soup of federal agencies can refer evidence of violations of these laws to HUD or the justice department for investigation, but referrals have <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.documentcloud.org\/documents\/20802985-ags-annual-report-to-congress-re-ecoa-2019\">dropped precipitously over the past decade<\/a>.<\/p>\n<p>Marcia Fudge, who took over HUD leadership earlier this year, <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.axios.com\/hud-secretary-black-homeownership-decline-cc680b3d-347e-48e6-8985-4697b1194ad5.html\">told Axios<\/a> in June that part of the reason Black ownership rates are so low in America is that \u201cwe have never totally enforced the Fair Housing Act.\u201d In an email, HUD press secretary Meaghan Lynch told The Markup that Fudge intends to tackle \u201csystemic discrimination in the housing and credit markets that is at the heart of the racial homeownership gap.\u201d<\/p>\n<p>\u201cWe do have laws that explicitly protect against discrimination, and yet you still see these disparities that you\u2019re finding, so that suggests that we need better enforcement of existing laws, and more investigations,\u201d said Kevin Stein, deputy director of the California Reinvestment Coalition. \u201cAgencies need to do a better job of ferreting out discrimination and taking serious action once they find it.\u201d<\/p>\n<p>Another key housing law, the federal Community Reinvestment Act (CRA) of 1977, allows the federal government to penalize lenders who fail to invest in low-income or blighted neighborhoods but makes no requirements regarding borrowers\u2019 race. Stein\u2019s group has lobbied for the law to be reformed.<\/p>\n<p>Lenders who violate fair lending rules can be punished with fines in the millions of dollars. Rep. Al Green (D-TX) has sponsored legislation wending its way through Congress that would make it a crime to engage in lending discrimination.<\/p>\n<p>\u201cBanks already have laws that punish people who commit fraud,\u201d he said. \u201cYou can be imprisoned for\u2014I hope you have your seatbelt on\u201430 years. Why not have some similar law that deals with banks who are invidiously discriminating against people who are trying to borrow money?\u201d<\/p>\n<p>And some fair lending advocates have begun to ask whether the value system in mortgage lending should be tweaked.<\/p>\n<p>\u201cAs an industry, we need to think about, what are the less discriminatory alternatives, even if they are a valid predictor of risk,\u201d said David Sanchez, a former Federal Housing Finance Agency policy analyst who currently directs research and development at the nonprofit National Community Stabilization Trust. \u201cBecause if we let risk alone govern all of our decisions, we are going to end up in the exact same place we are now when it comes to racial equity in this country.\u201d<\/p>\n<p>Crystal Marie said whatever effect race may have had on her denial, it wasn\u2019t overt.<\/p>\n<p>\u201cI\u2019m not sure you ever really know, because there\u2019s no Klansmen in our yard or anything\u2014but it\u2019s definitely something we always think about,\u201d she said. \u201cIt\u2019s just something that we always understand might be a possibility.\u201d<\/p>\n<p>The lender, loanDepot, denied race had anything to do with the decision. The company\u2019s vice president of communications, Lori Wildrick, said in an email that the company follows the law and expects \u201cfair and equitable treatment\u201d for every applicant. \u201cWe take the issues raised by Ms. [McDaniels] very seriously and are conducting a thorough review of her concerns.\u201d<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Perseverance\"><\/span>Perseverance<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Crystal Marie said that buying a house was crucial for her because she wants to pass on wealth to her son someday, giving him an advantage she never had. So when the loan officer told her that the deal wasn\u2019t going to happen, she refused to give up.<\/p>\n<p>With the help of their real estate agent, and multiple emails from her employer on her behalf, she and her husband Eskias pushed back against the denial.<\/p>\n<p>At around 8 p.m. on the night before the original closing date, Crystal Marie got an email from the lender: \u201cYou\u2019re cleared to close.\u201d<\/p>\n<p>She still doesn\u2019t understand how the lender went from a no to a yes, but she was relieved and elated.<\/p>\n<p>\u201cIt means so much to me, as a Black person, to own property in a place where not that many generations ago you were property,\u201d said Crystal Marie, who said she is descended from slaves in neighboring South Carolina.<\/p>\n<p>She said her family has always had a fraught relationship with money. Some relatives were so mistrustful of banks that they\u2019d insisted on dealing only in cash, she said, making it impossible to build up credit or wealth for future generations.<\/p>\n<p>\u201cIt\u2019s meant so much,\u201d she said, \u201cthat we were able to go through this process and finally, eventually, be successful.\u201d<\/p>\n<p><em>This article was <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/themarkup.org\/denied\/2021\/08\/25\/the-secret-bias-hidden-in-mortgage-approval-algorithms\">originally published on The Markup<\/a> by Emmanuel Martinez\u00a0and Lauren Kirchner was republished under the <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/\">Creative Commons Attribution-NonCommercial-NoDerivatives<\/a><a rel=\"nofollow noopener\" target=\"_blank\"> license.<\/a><\/em><\/p>\n<\/div>\n<blockquote><p><strong><span style=\"color: #ff6600;\">If you liked the article, do not forget to share it with your friends. Follow us on\u00a0<span style=\"color: #ff0000;\"><a style=\"color: #ff0000;\" href=\"https:\/\/news.google.com\/publications\/CAAqBwgKMLG0nwswvr63Aw\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Google News<\/a><\/span>\u00a0too, click on the star and choose us from your favorites.<\/span><\/strong><\/p><\/blockquote>\n<blockquote>\n<p style=\"text-align: center;\">For forums sites go to <span style=\"color: #ff9900;\"><a style=\"color: #ff9900;\" href=\"https:\/\/forum.buradabiliyorum.com\/\" target=\"_blank\" rel=\"noopener\">Forum.BuradaBiliyorum.Com<\/a><\/span><\/strong>\n<\/p><\/blockquote>\n<blockquote>\n<p style=\"text-align: center;\"><strong>If you want to read more like this article, you can visit our <span style=\"color: #ff9900;\"><a style=\"color: #ff9900;\" href=\"https:\/\/en.buradabiliyorum.com\/technology\/\" target=\"_blank\" rel=\"noopener\">Technology category.<\/a><\/span><\/strong><\/p>\n<\/blockquote>\n<p><span style=\"color: black;\"><a style=\"color: #ff9900;\" href=\"https:\/\/thenextweb.com\/news\/secret-bias-mortgage-approval-algorithms-syndication\" target=\"_blank\" rel=\"noopener\">Source<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>&#8220;#The secret bias hidden in mortgage-approval algorithms&#8221; The new four-bedroom house in Charlotte, N.C., was Crystal Marie and Eskias McDaniels\u2019s personal American dream, the reason they had moved to this Southern town from pricey Los Angeles a few years ago. A lush, long lawn, 2,700 square feet of living space, a neighborhood pool and playground&#8230;<\/p>\n","protected":false},"author":1,"featured_media":332763,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/img-cdn.tnwcdn.com\/image\/neural?filter_last=1&fit=1280,640&url=https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/08\/MortageHed.jpg&signature=37f503caa43c939be3f903a8f67f4738","fifu_image_alt":"","footnotes":""},"categories":[18],"tags":[],"class_list":["post-332762","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/332762","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/comments?post=332762"}],"version-history":[{"count":0,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/332762\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media\/332763"}],"wp:attachment":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media?parent=332762"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/categories?post=332762"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/tags?post=332762"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}