A redlining case can be made largely through the use of HMDA, census, mapping, peer, branch, marketing and assessment area data; all of which are readily available in LendingPatterns.™
McLean, VA (PRWEB) October 19, 2015
ComplianceTech announced the availability of the latest 2014 HMDA data in LendingPatterns™, an advanced fair lending and CRA data mining tool used by regulators, enforcement agencies, fair housing groups and hundreds of lenders nationwide. With the new data refresh, LendingPatterns™ contains 11 years of data allowing users to analyze trends and patterns over time.
One example of the kind of findings available to users with access to the LendingPatterns™ data refresh is the surprising development in the growth of subprime-like pricing with regard to FHA lending. HMDA reporters are required to report the spread (difference) between the annual percentage rate (APR) and the applicable average prime offer rate (APOR) if the spread is greater than or equal to 1.5 percentage points for first-lien loans. Historically, this reporting threshold has been a line of demarcation or proxy for determining whether conventional or FHA lending was prime or subprime.
While the percentage of conventional lending meeting the subprime threshold has been relatively constant for each racial group over the past 3 years, subprime FHA lending has skyrocketed for all major racial groups. Thirty-six percent of the FHA 1st lien loans made to non-Hispanic whites in 2014 met the subprime definition compared to only 4% in 2012, a 9-fold increase. Forty-three percent of the FHA 1st lien loans made to African-Americans in 2014 were subprime compared to only 8% in 2012, a 5-fold plus increase. Forty-eight percent of the FHA 1st lien loans made to Hispanics in 2014 were subprime compared to only 5% in 2012, nearly a 10-fold increase. Thirty percent of the FHA 1st lien loans made to Asians in 2014 were subprime compared to only 2% in 2012, a 15-fold increase. This market shift is seismic and bound to pose macro policy issues as well as adding complexity to fair lending monitoring.
Other findings with major policy implications involve the role of Fannie Mae and Freddie Mac (GSE’s). The data reveal a continued pattern of extremely low GSE purchases of conventional mortgage loans of minority borrowers, especially blacks and Hispanics, in America's largest and most diverse metro areas. For example, in the St. Louis metro area the GSE’s bought 13,271 conventional loans in 2014. The racial distribution was white, 12,147 or 91.53%, black, 557 or 4.20%, Hispanic, 162 or 1.22%, Asian, 379 or 2.86%, Native American, 12 or 0.09% and Hawaiian, 14 or 0.11%.Only 1,168 or 8.92% were from minorities, despite the fact that minorities make up 24.98% of the population. This purchase pattern is likely to have a profound impact on the socio-economic vitality of minority communities.
Finally, this latest version of LendingPatterns™ also includes a new statistically-based redlining report. Although there is no well established quantitative redlining test that has been promulgated by the courts or the regulators, the new report in LendingPatterns™ is derived from the evolving parameters set forth in recent U.S. Department of Justice and/or CFPB redlining actions. By quantifying previous redlining actions, users can now compare the lending patterns of Lender A to the patterns of Lender B that has already been sued for redlining. Among other things, the report allows users to select a lender and a pre-defined or customized set of peers/competitors. Relative to those lenders, users can check whether the target lender's share of applications or loans in majority white census tracts is statistically significantly higher than their share of applications or loans in majority minority census tracts.
"Unlike underwriting and pricing issues, redlining is the only fair lending issue that can be advanced by the regulators and enforcement agencies that does not require the lender's proprietary loan origination system data. Thus, a redlining case can be made largely through the use of HMDA, census, mapping, peer, branch, marketing and assessment area data; all of which are readily available in LendingPatterns™," says Maurice Jourdain-Earl, Managing Director and co-founder of ComplianceTech.
ComplianceTech, based in McLean, VA, is a leading provider of fair lending and CRA solutions to the federal government, lending institutions, law firms, community organizations and researchers. The company’s software products include LendingPatterns™, Fair Lending Magic™ 4.0, the Racestimator™, The Premium Pricing Analyzer, and other high tech analytical solutions. ComplianceTech’s products are offered directly or through its reseller Questsoft Corporation.
For more information contact Dana Ginsburg at DanaGinsburg(at)ComplianceTech(dot)com or call her on 202-618-7079.