According to this article in the Wall Street Journal, the government regulators who rely on disparate impact theory to bring discrimination claims against businesses may themselves be liable for disparate impact discrimination.
In 2010, Congress created yet another government agency, the Consumer Financial Protection Bureau (CFPB), when it passed the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010. The CFPB quickly announced that it would use all available legal avenues, including disparate impact theory, to pursue lenders whose practices discriminate against consumers.
To bring a disparate impact claim, the CFPB need not allege, nor even prove, that businesses treat consumers differently because of their race. Instead, the CFPB may rely on statistics to show that a neutral lending practice has a disproportionate effect – that is, a disparate impact – on some racial group. Proof of discriminatory motive is unnecessary. To this end, the CFPB monitors mortgages, credit cards, student loans, and auto loans for evidence that a lender’s practices have an adverse disproportionate effect on different racial groups. When the government finds a disparate impact, it sues the lender for large sums of money. The result is usually a huge settlement.
The CFPB believes that a statistical showing of disparate impact is equal to discrimination. But if that is true, then CFPB has some explaining to do. It turns out that statistics on CFPB’s own employment practices show a disparate impact against Blacks and Hispanics. The problem, according to the article, is that personnel of the CFPB are the epitome of political correctness. In all of government, the CFPB, like the EEOC, is one of the last places where one would expect to find bigoted supervisors and discriminatory employment practices.
But the statistics don’t lie. Or do they? In International Brotherhood of Teamsters v. United States, the Supreme Court warned that
statistics are not irrefutable; they come in infinite variety and, like any other kind of evidence, they may be rebutted. In short, their usefulness depends on all of the surrounding facts and circumstances.
PLF attorneys have filed briefs arguing against the disparate impact doctrine and the sole use of statistics to prove discrimination. As noted in this blog post, the mere attempt by a lender to implement policies specifically to avoid a disparate impact may lead to absurd results. Is the CFPB likely to see the folly of using statistics alone to prove discrimination, especially when its own employment numbers would support a lawsuit against it for disparate impact discrimination? Don’t hold you breath.