MIKE MAULDIN, F. Scott Dueser Chair in Excellence in Banking, Rawls College of Business at Texas Tech University
ARTHUR M. TRAN, John Massey School of Business at Southeastern Oklahoma State University
DREW B. WINTERS, Lucille and Raymond Pickering Chair in Finance, Rawls College of Business at Texas Tech University

The Dodd-Frank Wall Street Reform and Consumer Protection Act (hereafter, Dodd-Frank Act) was created, according to the first paragraph of the act itself: “To promote the financial stability of the United States by improving accountability and transparency in the financial system, end ‘too big to fail,’ protect the American taxpayer by ending bailouts, protect consumers from abusive financial services practices and for other purposes.” However, it is not achieving its objectives. For example, Allen, Cyree, Whitledge and Winters (2018) show that it did not end “Too Big to Fail.” ^[1] Additionally, Cyree (2016) finds an increase in regulatory burden for small banks following the passage of the act. ^[2]

Introduction

On August 26, 2024, Judge Randy Crane of the Southern District of Texas, said that the final rule developed by the Consumer Financial Protection Bureau (CFPB) to implement Dodd-Frank Act section 1071 was within the purview of the CFPB and was not arbitrary and capricious in its scope. The judge further ruled that the bureau had performed an adequate cost-benefit analysis while promulgating the rule.

Section 1071 of the Dodd-Frank Act is part of the effort “to protect consumers from abusive financial services practices.” It amends section 704A of the Equal Credit Opportunity Act by adding section 704B. Section 704B has the following stated purpose:

“The purpose of this section is to facilitate enforcement of fair lending laws and enable communities, governmental entities and creditors to identify business and community development needs and opportunities of women-owned, minority-owned and small businesses.”

Here we will discuss if the CFPB’s final rule will facilitate the enforcement of fair lending laws for small businesses. We will use the results from an academic research paper by Tran and Winters (2024) to discuss the details of the CFPB’s final rule and whether it can be used to facilitate the enforcement of fair lending. After discussing the academic work, we provide a commentary on the CFPB’s final rule.

Details of CFPB Final Rule to Implement Section 1071

2.1: Details on Section 1071

Section 1071 states: “(1) Each financial institution shall compile and maintain, in accordance with regulations of the bureau, a record of the information provided by any loan applicant...” Then the CFPB will make this data available to the public (and regulators).

In their final rule, the CFPB notes: “While these data alone generally will not establish compliance with fair lending laws, regulators, community groups, researchers and financial institutions will be able to use the data to identify potential disparities in small-business lending based on disaggregated categories of race and ethnicity. (page 42) [Emphasis added by Tran and Winters.]

2.2: Data Collected Under Section 1071

Section 1071 details the obligation of the lender to retain information relative to a loan application:

1. the number of the application and the date on which the application was received;
2. the type and purpose of the loan or other credit being applied for;
3. the amount of the credit or credit limit applied for, and the amount of the credit transaction or the credit limit approved for such applicant;
4. the type of action taken with respect to such application, and the date of such action;
5. the census tract in which is located the principal place of business of the women-owned, minority-owned or small-business loan applicant;
6. the gross annual revenue of the business in the last fiscal year of the women-owned, minority-owned or small-business loan applicant preceding the date of the application;
7. the race, sex and ethnicity of the principal owners of the business; and
8. any additional data that the bureau determines would aid in fulfilling the purposes of this section.

Items A through G are required under section 1071 for the lender to compile and maintain for each business loan request it receives. Then, item (H) allows for the inclusion of any additional information the CFPB considers beneficial for fulfilling the purpose of the section, which is compliance with fair lending laws. Items A through G do not include any credit data that the lender would use in making a loan decision. Gross revenue is included because that is how the SBA defines a small business. So, at this point, the data does not provide for any reasonable analysis of compliance with fair lending. Accordingly, we analyze the final rule for the data items to be included under item H for any credit-related variables that would be useful for an appropriate analysis of fair lending.

2.3: Data Collected Under Item H

Tran and Winters (2024) search for and identify the data to be collected under item H. They note that the final rule document is 888 pages without a table of contents or an index. They search for the term “data.” “Data” appears 5,488 times in the document and they review all of these appearances.

Tran and Winters (2024) find that item H includes 74 additional data points for collection bringing the total data items to be collected for each loan to 81. None of the 81 data points comes from the balance sheet. One data point—gross revenue—comes from the income statement and it is collected to determine small-business status. The only data that can remotely be considered a credit quality variable is the age of the business. There is a data item for “denial reason,” but this only reports the reason for the decision. Thirty-three of the data points are for reporting the race and gender of up to four owners.

Research Findings

Tran and Winters (2024) use Tran’s (2023) approach to examine the possible fair lending results from the analysis of section 1071 data. They use the data from the 2017 Small Business Credit Survey (SBCS) conducted by the Federal Reserve System. SBCS is a nationwide survey on small-business borrowing, so it is a reasonable and relatively recent sample for this research. The authors employ a regression analysis to understand how a loan applicant’s race and gender influence the proportion of the loan amount that is approved. In their analysis, Tran and Winters take into account the business’ total income, amount of the loan they received and state and industry fixed effects. This helps ensure that the observed effects are not influenced by business size, loan size or regional and industry-specific factors. With this model, they examine if minority- or female-owned small businesses received smaller loans than white-owned businesses.

Tran and Winters’ (2024) first set of results indicates that minorities received a smaller percentage of the loan requested compared to white applicants. The second set of regressions, which includes business age and a credit risk score—available in the SBCS survey data, but not collected under the CFPB’s final rule—also shows that minorities received a smaller percentage of the loan requested. The third set of regressions, using a sample limited to community banks and estimated without the credit risk score, again finds that minorities received a smaller percentage of the loan requested. Finally, the fourth set of regressions, using a sample of community banks and including the credit risk score, reveals that minorities received the same percentage approved as white applicants in nearly all cases after controlling for credit risk. The one exception is only significant at the 10 percent level, which is typically considered not statistically meaningful in academic research. These results suggest that when credit risk is accounted for, minority-owned businesses receive the same percentage of credit requested as white-owned businesses when loan requests are made to community banks.

This analysis shows that the data collected under the CFPB’s final rule always indicates that minorities receive less of the requested loan amount than white applicants. However, this data does not provide for any credit risk analysis. When a single simple credit risk variable is included, the differences in approved loan amounts between minority and white applicants disappear at community banks.

Commentary

The CFPB’s final 1071 rule was created to represent a significant step toward greater transparency in small-business lending. By mandating the collection of comprehensive data on loan applications, the rule aimed to identify and address disparities in lending practices. However, like so many other laws and rules, Section 1071 is full of negative unintended consequences.

Tran and Winters’ research highlights a crucial aspect of this limitation: While the CFPB’s data-collection efforts reveal disparities in loan amounts by race and gender, these disparities often disappear when accounting for credit risk. This suggests that the CFPB’s final rule, in its current form, will not fully address the underlying factors influencing loan approval decisions. Yet, the factors for credit risk are currently available to fair lending compliance examination regulators during the examination process.

Tran and Winters’ research illustrates that the absence of credit quality indicators from the mandated data collection limits the ability to fully analyze fair lending compliance. As mentioned above, these indicators are already currently available and used by compliance and safety and soundness bank regulators to determine overall fair lending compliance, making the need for additional data collection unnecessary and, simply put, frustrating for customers who will be required to gather and provide this information during the application process.

Cybercrime is escalating. People, organizations and companies are being attacked every second of every day for their information. Section 1071 data collection requirements will be a cybercriminal’s dream. The unnecessary collection of up to 81 different data fields of information will make identity theft an even greater risk than what it is today. Even though the name is not associated with the collection, published data available will allow one to determine certain companies just through intuitive reasoning. In addition to cybercrime fears, information regarding companies will be available to their competitors.

In summary, although CFPB’s final rule was intended to be a positive development in promoting fair lending, Tran and Winters’ research clearly reveals that it will not serve its original purpose, making Section 1071 strictly onerous for both institutions and customers alike. One can expect the unintended consequences of an acceleration of the continued traditional/community banks consolidation, as many of the relationship lenders will not have the resources to comply and stay in business. Access to credit, especially in rural areas and to small businesses, will be reduced. Both bodies of Congress realized this when they recently passed a bill to remove the CFPB Section 1071 Small Business Lending Rule, only to see it vetoed by President Biden on December 19, 2023.

^[1] Tran, A.M., and Winters, D.B. (2024). The Implementation of Section 1071 of the Dodd-Frank Act: The Legal Exposure of Banking, Texas Tech University working paper.

^[2] Tran, A.M. (2023). Two essays on “Understanding Commercial Banks.” Unpublished doctoral dissertation, Texas Tech University. The data and methods are also used in: Tran, A.M. and Winters, D.B, (2024). “Lending Discrimination and the Role of Community Banks,” Journal of Financial Research. DOI: 10.1111/jfir.12435