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Why Protecting Banks Against Regulators’ Disparate Impact Theory in Discriminatory Lending Cases is Practically Impossible
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Why Protecting Banks Against Regulators’ Disparate Impact Theory in Discriminatory Lending Cases is Practically Impossible

In our last article, we highlighted the Justice Department’s unofficial war on banks as seen in the spike in discriminatory lending lawsuits in the last three years.  In most of those cases, Justice claims certain banks’ lending policies have had a disparate impact on protected classes of borrowers.[1]

In this article, we will take a look at the ambiguity that arises when prosecutors attempt to apply the disparate impact theory in a discriminatory lending context.

The body of law defining disparate impact, its assessment, and whether it can be adequately justified by a defendant grew out of employment discrimination issues.  The law is clear only as to what must be proved to support or defend an employment related disparate impact claim, such as whether employee screenings are job-related and consistent with business necessity, and whether less discriminatory alternatives are available to meet the business necessity.

On the other hand, disparate impact in a lending context is not clearly defined by statutory law or case law.  It is ephemeral — the ten-dollar legal phrase for such ill-defined legal standards is “unconstitutionally vague.”  (The reason vague and ambiguous laws are unconstitutional is because it is not fair to hold someone accountable to a standard when one can’t reasonably know what the heck the standard is, or how to comply with it.)

The dangers of this ambiguity are compounded exponentially by the fact that the disparate impact theory allows prosecutors to effectively avoid the need to show any actual intent to discriminate on the bank’s part.  Instead, a bank’s intent to discriminate, or failure to avoid inadvertent discrimination, can be shown by statistical evidence — the alleged disparate impact. 

So how can banks avoid inadvertently creating a disparate impact?  What econometric formula do regulators use to support a disparate impact claim?

No one knows.  In fact, regulators’ methodology for establishing a statistical disparate impact is as enigmatic as Area 51, and nearly as well protected, according to a recent article reporting that bankers who settle out of court are being required to sign nondisclosure agreements barring them from talking about the methods prosecutors used to formulate the alleged disparate impacts.  Such reports are almost too incredible to believe.  Almost.

At the time of this writing, there is no published method recommended by Justice, the CFPB, or anyone else we know of for lenders to perform self-assessments to ensure they are not at risk of running statistically afoul of the Equal Credit Opportunity Act (ECOA) or the Fair Housing Act (FHA) by inadvertently causing a disparate impact. 

Depending on which statistics prosecutors measure and how they are weighted, prosecutors can support a claim against virtually any bank at any time, regardless of the bank’s intent.

Although banks are hard pressed to manage the uncertainty presented by the Justice Department’s actions under the disparate impact theory, we are watching the issue closely and working to find a legal solution.  Check back soon to read more about the flaws in the disparate impact theory, and other challenges currently facing the banking industry. 

If you are a bank or another business facing compliance issues, consult with legal counsel to ensure compliance and help you develop a sound legal strategy.  The attorneys at Glass & Goldberg provide high quality, cost-effective legal services and advice for clients in all aspects of business litigation and transactional law.  Call us at (818) 888-2220, email us at info@glassgoldberg.com, or visit us on the web at www.glassgoldberg.com to learn more about the firm and to sign up for future newsletters.


[1] “Disparate impact” is the statistical summary prosecutors point to in support of claims that banks must have behaved in a discriminatory manner, because the purported statistical outcome shows Group A received fewer loans or less favorable loan terms than Group B.

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