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Creditors Must Explain Denials

Creditors Must Explain Denials

Creditors must explain denialsCreditors Must Explain Denials

The Consumer Financial Protection Bureau (CFPB) has ruled that creditors must explain credit denials to consumers, even if they’re using “black-box” algorithms. The agency says that if lenders are using an alternative, complex technology to underwrite applications, the stipulations under the Equal Credit Opportunity Act (ECOA) require that a creditor provide an adverse action notice upon denial.

The ECOA also requires lenders to keep you informed of their decisions and to be specific about their reasons for turning down a loan application or charging you a higher interest rate than the best one available at the time your application is accepted.

The CFPB believes that black-box algorithms may make it more difficult for consumers to understand why they were denied. The federal agency is also concerned that black-box algorithms could disproportionately impact certain groups of people, such as minorities and women.

In a CFPB advisory, Director Rohit Chopra said, “The law gives every applicant the right to a specific explanation if their application for credit was denied, and that right is not diminished simply because a company uses a complex algorithm that it doesn’t understand.” This new guidance is important because it provides clarity for consumers who may be denied credit and ensures that they are allowed to correct any errors in their application.

Chopra also stated separately that “Companies are not absolved of their legal responsibilities when they let a black-box model make lending decisions. Now those companies will have to take responsibility for their use of these opaque systems and show that their practices comply with federal law.

What is a Black-Box Credit Algorithm?

A black-box credit algorithm is decision-making software that creates outputs without showing the intermediate calculations or decision-making rules or criteria. These algorithms are designed to make automated decisions about creditworthiness and are often used by creditors to make decisions about loan approvals. Because black-box algorithms are complex and not transparent, it can be difficult for consumers to understand why they were denied credit.

Why Do Creditors Use Black-Box Algorithms?

Algorithms are most frequently used in the financial sector to assess credit risk and accept or reject loan applications. Creditors use black-box algorithms because many say they can provide a more objective way to assess personal credit.

This artificial intelligence is vital to creditors. Machine learning is based on providing a great deal of data to the machines so that they can learn, resulting in the creation of more sophisticated algorithms that may be applied to any new data the machine has never seen before. There are other concerns as well, specifically with data anonymization. A black-box algorithm with that data could have a disparate impact on certain regional groups of people.

Companies use AI to make faster judgments and allow a creditor to handle more applications with the aid of machine learning algorithms. Decisions can be made in seconds and without any human interaction, so they are particularly used most for issuing small-ticket loans like Buy Now – Pay Later purchases.

National Consumer Advocates Are Watching

Ed Mierzwinski U.S PIRG

Ed Mierzwinski, Senior Director of the Federal Consumer Program at the U.S. Public Interest Research Group (PIRG) expressed his opinion with Finn Law Group and said,

“An explanation that simply lists “secret artificial intelligence algorithm” as a main reason you were denied won’t be good enough. Companies that tell the CFPB – “I can read it to you but I can’t understand it for you” will fail. Companies will need to explain to the CFPB that they understand how their algorithm works and prove that it’s not a proxy for discrimination and, then, give consumers a clear, specific plain language reason why they were denied.”

What Can Consumers Expect To Happen Now?

CFPB Black Box Machine Learning

The CFPB’s ruling is a victory for consumers. It provides clarity and transparency in the credit approval process and ensures that consumers have the right to an explanation if their application is denied.

The bureau’s new guidance is a warning to those who might take advantage of consumers with black-box algorithms and also puts pressure on companies that use those algorithms to make sure their practices comply with federal law.

Here is a short list of things you can do yourself to protect your credit

-Order a free credit report from

-Educate yourself about how AI credit scoring works.

-If you’re denied credit, ask the creditor for an explanation.

-Check your credit report regularly to make sure there are no errors.

-If you find an error on your credit report, dispute it with the credit bureau.

Take Action To Protect Your Consumer Rights

You can file a complaint with the CFPB if feel you were wrongly denied credit as a result of a black-box algorithm. The CFPB will investigate the complaint and take appropriate action if they find that the creditor has violated the ECOA. You may also be entitled to damages if you’ve suffered financial harm as a result of the credit denial. The ECOA Act also gives applicants a private right of action, allowing them to bring suits for violations of Regulation B.

Under Regulation B, a lender may not request information about an applicant’s sex, national origin, color, or other information not related to creditworthiness. Consult with an attorney to learn more about your legal rights and options. Remember, that if you’re denied credit, the creditor must send you an adverse action notice and provide you with information about where to get free credit reports.


This article is not intended to be legal advice or create an attorney-client relationship. Led by attorneys Michael D. Finn and J. Andrew Meyer with over 75 years of experience. The Finn Law Group is a consumer protection firm dedicated to protecting the rights of consumers. Follow us on Twitter.


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