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Will Section 1071 Data Reporting Boost Lending to Underserved Small Businesses or Lead to Consolidation and Reduce Product Choice?

The banking industry is making a vigorous critique of proposed new rules for small business lending data collection. But those arguments are misleading at best — and policymakers should understand the flaws and deceptions built into the industry’s attack on lending transparency.

Myths and Facts About the Banking Industry’s Arguments

Section 1071 of the Dodd Frank Wall Street Reform and Consumer Protection Act of 2010 (Dodd Frank) requires lending institutions to publicly report the race, gender and other characteristics of small business applicants. Congress included this provision in Dodd Frank out of concern that smaller women- and minority-owned businesses seeking affordable credit encountered barriers and in some cases open discrimination from lenders. 

The philosophy behind Section 1071 is that publicly available data on small business lending will hold lending institutions accountable and motivate them to improve upon any weaknesses in their performance as measured against their peers or the demographic composition of small businesses in their community. The idea was borrowed from the Home Mortgage Disclosure Act (HMDA) that Congress passed in 1975 and improved in 1989 to include the demographic characteristics of borrowers. When Congress improved HMDA, lending surged to people of color and low- and moderate-income borrowers in the early to mid-1990s, most likely due to the extra burst of accountability provided by this disclosure law. 

The deliberate and successful boom in home lending in the 1990s stands in stark contrast to the irresponsible, high-cost subprime lending that proliferated in the early to mid-2000s and which was the main driver of the financial crisis. The crisis prodded Congress in Dodd-Frank to mandate disclosure of pricing and loan terms and conditions in HMDA data to serve as an early warning system and prompt stakeholders and policymakers to take action in the future should a surge of abusive lending again threaten families and the economy. Meanwhile, policymakers remembered the lack of data on pricing and loan terms and conditions as a lesson for future small business data disclosure.

Section 1071 states that its statutory purpose “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.” 

To achieve this, the Consumer Financial Protection Bureau (CFPB) last year proposed a comprehensive data collection rule that included demographic characteristics of the small business, pricing and loan terms and conditions. Using its discretionary authority, the agency sought from the outset to create a rigorous database so that the small business marketplace could not only promote access to loans but prevent the abuses and exorbitant pricing that riddled the housing market in the mid 2000s. 

The CFPB received hundreds of letters in response to its request for comments (letters were due on January 6). Community-based organizations extolled the value of the data in promoting an equitable and responsible lending marketplace while banks decried the proposed rule as a restriction on lending. The industry comments implied that instead of promoting the goals of the statute, the proposed regulation, or just about any regulation, would thwart the fair lending and community development purposes of Section 1071 by reducing the number of loans and banks. 

The American Bankers Association (ABA) bemoaned that “unless the Bureau revises the proposed rule, it will impose significant costs on banks — costs that will be felt most acutely by community banks — that will negatively affect their small business customers [….] Over time, the 1071 rule will drive further consolidation, and the gradual loss of community banks. Reduced competition will lead to fewer choices and higher prices for small businesses.” 

The Independent Community Bankers Association (ICBA) lamented that “Complex lending should not be subject to simplified, rigid analysis, which might give rise to unfounded fair lending complaints. For this reason, the proposed rules under Section 1071 will have a chilling effect on community banks’ ability to price for risk, unless the Bureau can properly tailor a rule that excludes community banks from coverage.” 

Let’s unpack these industry myths. 

Myth: The high costs of Section 1071 data collection will cause smaller banks to close, leaving borrowers with higher costs and fewer choices.

The ABA’s letter featured a survey of its member banks that purported to show data collection costs that were more than double the CFPB’s estimates. The ABA explained that the CFPB did not consider the need of smaller banks to hire more staff and that small business data collection is more complex than HMDA data collection due to small business lending being less standardized than home lending. 

Fact: Costs are not as high as the industry asserts.

The CFPB carefully developed cost estimates and shared its estimates with industry for feedback and adjustment. The agency also surveyed the industry. Most lenders who responded to the CFPB’s survey, including smaller ones located in rural areas, stated that they were not likely to exit the marketplace. The ABA maintained that banks would not want to admit that on a CFPB survey. However, the ABA wants policymakers to believe that its own hurried 60-day survey during the comment period provided more accurate information than the CFPB’s survey, which occurred over a year. This is implausible. 

The CFPB stated that lenders would be likely to pass variable costs onto borrowers and estimated these costs per application would range from $7 for larger banks with more technological capabilities to $28 for smaller banks. If we use the ABA’s cost estimates, these variable costs could be two or three times as high and would range from $14 to $21 on the low end to $56 to $84 on the high end. Let’s assume that the true costs are perhaps somewhere in between the agency’s estimates and the trade associations’, meaning that fees faced by borrowers might range from $14 for the larger banks to $56 for the smaller banks. Would the higher costs put the smaller banks at such a disadvantage that they might close? It is unlikely because the modestly higher fees for smaller banks are unlikely to cause competitive disadvantages. Smaller banks offer long established personal relationships, flexibilities in underwriting and repayments and other advantages that larger banks do not offer. The volume of business these relationships generate for such banks, combined with the result that the ABA’s exaggerated estimated costs amount to a rounding error on the loan amounts, further debunks the industry’s fear mongering. 

Another way to examine the impacts of data collection is historical evidence. From 1996 through 2004, smaller banks with assets under $1 billion were required under the Community Reinvestment Act (CRA) to report lending data. If the trade agencies are correct that data collection would drive banks out of business, one would expect the number of small banks to plummet a few years after 1996 when the agencies mandated data collection. 

But look at the number of banks under $1 billion in assets reporting data: In 1998, about 1,400 smaller banks reported the data; in 2000, 1,456 did; in 2003, 1,577 did. The numbers of reporting banks did not plummet because the data reporting did not cause widespread closures. 

The industry may reply that the CRA data does not contain as many data points and is therefore not as complex as the proposed Section 1071 data. However, the experience under HMDA is similar regarding the number of reporters from year to year. The historical evidence of CRA data reporting from 1996 through 2004 is more supportive of the findings of the CFPB survey than the hasty ABA survey. A robust Section 1071 database will not drive small banks out of business; instead it will promote fair lending and community reinvestment.

Myth: Section 1071 can achieve its purpose without data from small banks.

The CFPB proposed to cover lenders that make 25 or more loans. The ABA proposed a threshold level of 500 loans while the ICBA sought to use a threshold level of $1.3 billion in assets that corresponds to small banks that do not currently submit CRA data. The trade associations reasoned that these proposed exemptions will save their members from significant costs while still creating a robust database that covers most lending activity. 

Fact: Exempting most smaller banks would interfere directly with the statutory purposes of Section 1071.

The industry’s preferred exemption threshold would interfere with the fair lending and community needs purpose of Section 1071. Smaller banks are indeed important lenders for less populated areas including smaller cities and rural counties. If their loans are omitted from the Section 1071 database, a significant portion of lending in these smaller areas will be missed, rendering it impossible to determine if lenders are meeting community needs for credit in significant areas of the country. Furthermore, the fair lending purpose of Section 1071 is thwarted if lenders making up to 500 loans, as recommended by the ABA, are not required to report. It would be very hard if not impossible to hold them accountable for serving the needs of women- and minority-owned small businesses if the public does not have access to their data. 

The ABA wanted to expand the data reporting requirements to other types of non-depository lenders including merchant cash advance (MCA) lenders and merchants that offer trade credit to small businesses. NCRC agrees with expanding Section 1071 broadly throughout the industry. But the trade industry position is inconsistent. The ABA is effectively saying, “Cover the other guy but not me!

Myth: Discretionary variables are costly and not useful.

Section 1071 provides discretionary authority for the CFPB to add more data points that could further explain ease or difficulty of access to credit. For example, “time in business” is an important variable since start-ups have greater difficulty acquiring loans because of the inexperience of the owners or the lack of collateral. A data user would want to control for factors like time in business when comparing the ability of minority- or women-owned small businesses to their White or male counterparts in accessing credit. 

However, according to the ABA, “the eight discretionary data points unduly increase the burden on reporting financial institutions and create more opportunities for errors, even with reasonably adapted procedures to avoid errors.” The ICBA agrees, saying that some proposed data points like number of workers would be hard to gather since the CFPB is asking for too much detail. For example, the number of workers “would include contractors and others that are not necessarily employed by the applicant.” 

Fact: Lenders are already collecting similar discretionary variables. 

The bank trade associations are portraying the data collection as monumentally difficult when in fact lenders are already collecting similar data when offering government-backed loans through the Small Business Administration (SBA) and by Community Development Financial Institutions (CDFIs) as required by the Department of Treasury. If necessary, the CFPB can and probably will refine and clarify instructions for collecting some of the discretionary data points before it issues its final rule. 

Myth: The proposed pricing information will be misinterpreted.

The banking industry vehemently opposes the proposed collection of pricing information, including interest rates and fees. Based on their rhetoric, however, it seems as though their vehemence is less about the cost of collection and more to do with perceived threats to their reputation. The ABA stated, “Advocates will also view the public data set as showing discrimination in pricing. As with HMDA, the data will drive media reports alleging discrimination in pricing, based only on the data, causing unwarranted damage to banks’ reputations.” 

This canard implies that any attempt to shine sunlight on banking practices and ensure that no discrimination is present is counterproductive and will only sully the reputation of reputable businesses. However,  a large body of academic research documents the likelihood of ongoing discrimination. In addition, over the last few years, NCRC has engaged in several mystery shopping tests in which more qualified people of color testers experience statistically significant less-favorable treatment than their White counterparts.

Fact: The public knows how to use the data. 

The industry’s distrust of the advocacy community is unjustified. The advocacy community is careful not to allege discrimination carelessly. We understand that pricing in small business lending is quite different and less standardized than pricing in home lending. Instead of blindly calling foul, advocates will identify pricing trends that appear to be outliers when comparing a lender against its peers or when comparing prices received by similarly situated applicants (which is why the discretionary variables are important). In cases when egregious pricing appears present, quiet negotiations or referrals to government agencies usually proceed media stories. 

In most cases, observations of questionable pricing trends are made in the hopes of encouraging more affordable lending rather than litigious approaches. Lenders have survived HMDA disclosure for decades because the HMDA data has not been misused and has been used to prompt voluntary efforts to do better. 

Lastly, we agree with the CFPB that the discretionary data the agency proposed to collect can help explain disparities and help stakeholders focus on cases where stark disparities remain even after controlling for characteristics of the business. Often, the lender trade associations will cry foul when a lack of explanatory variables are present in the analysis. This usually occurs, however, when the trade associations succeeded in the past to limit data collection. 

We agree with the Responsible Business Lending Coalition (RBLC), a coalition of financial technology lenders and CDFIs, which stated, “[W]ithout pricing data, section 1071 may have the perverse effect of increasing discrimination in lending, rather than reducing it. If blind to pricing, section 1071 would create the incentive for reporting financial institutions to boost the appearance of service to minority-owned and small businesses in the easiest way possible—simply by charging high rates or using other potentially extractive practices. The practices that led to the subprime mortgage crisis illustrate the folly of considering financial inclusion based on access to capital alone, without regard for the price and terms of the capital being accessed.” 

The American Fintech Council, a coalition of financial technology companies, also supported collecting pricing data in order to determine pricing trends associated with diverse commercial financial products and how those products serve small businesses. 

Myth: The proposed rule poses a huge threat to privacy.

The ABA and ICBA claim that data users seeking to exploit small businesses would be able to use the Section 1071 database and match it with other databases to identify particular small business applicants and either embarrass them or pitch abusive products to them. The ICBA uses an example of an antique store in a small town in Ohio to prove its assertion that a database that has loan level information and information about the sector of the business would be easily abused to identify particular businesses. 

Fact: Privacy risks are manageable and should not be used as an excuse to dilute the Section 1071 database.

The ICBA used an exception to prove a rule. In other words, it found a census tract that would be likely to have a smaller number of loans and a small number of businesses that are relatively easy to identify. However, if the Section 1071 database contained a large number of loans for most census tracts, this type of reverse engineering becomes more difficult. NCRC’s comment illustrated how the Section 1071 database could have as many loans as HMDA, which has not been used to identify specific homebuyers or homeowners in more than 40 years of use. 

The CFPB will be exploring privacy risks carefully and can take preventative action if it deems necessary. For example, for some census tracts with smaller numbers of loans, the publicly available data could reveal less information such as not indicating the sector of the business or not providing loan level information for tracts with few loans. Instead, the database could report information such as total loans applied for and received by race and gender for those tracts. Still another technique is called data swapping, in which particular loan records are switched from one tract to another in such a way as to not significantly decrease the overall accuracy of the data. The Census Bureau uses data swapping. 

In other words, privacy risks are not likely to be great and the CFPB has techniques it can employ to create a Section 1071 database that is still considerably more detailed than the current and limited CRA data on small business and farm lending.

Myth: Borrowers do not want to divulge their race and other demographic information.

The CFPB proposed to report racial and ethnic subcategories such as Chinese in addition to Asian, or Cuban in addition to Hispanic. The ABA and ICBA replied that borrowers would not want to report detailed subcategories of race or ethnicity based on low response rates to demographic information collected by the Paycheck Protection Program (PPP), a small business loan program during the pandemic. 

Fact: Borrowers provide detail on their race and ethnicity.

HMDA allows loan applicants to voluntarily report racial and ethnic subcategories. NCRC’s recent analysis of HMDA data has found that about 60% of applicants of color report this data. The bank trade associations used an emergency loan program during the pandemic to prove that applicants will not supply this information when in fact the applicants were filling out applications under duress with their small business’ survival at stake. In this rushed and harried environment, collection of race and ethnicity data is a lower priority than in the normal course of applying for a home loan or a small business loan. Decades of HMDA data collected in good times and bad is a more reliable gauge of borrower behavior than the brief, recent, and crisis-driven Paycheck Protection Program.

Conclusion

Data collection entails costs. On that level, we can agree with the bank trade associations. However, the more than four decades of HMDA experience shows that the overall benefits of increasing equity and efficiency in the lending marketplace massively outweigh these costs. Moreover, the history of bank data reporting under HMDA and  CRA reveals that the costs are manageable and have not caused a massive exodus of banks from the industry. 

The bank trade associations throw up so many objections to the proposed Section 1071 rule that just about any regulation implementing this important legislation would appear to thwart the statutory goals of fair lending and community reinvestment. Do not buy these arguments. They have been trotted out for decades while the data has helped stakeholders make progress against discrimination and disinvestment. 

The CFPB can and must implement a robust final rule creating a comprehensive database. Former Supreme Court Justice Louis Brandeis, the grandfather of data disclosure as a tool for socially-responsible public and private sector activities, had it right: Sunshine is the best disinfectant.

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Redlining and Neighborhood Health

Before the pandemic devastated minority communities, banks and government officials starved them of capital.

Lower-income and minority neighborhoods that were intentionally cut off from lending and investment decades ago today suffer not only from reduced wealth and greater poverty, but from lower life expectancy and higher prevalence of chronic diseases that are risk factors for poor outcomes from COVID-19, a new study shows.

The new study, from the National Community Reinvestment Coalition (NCRC) with researchers from the University of Wisconsin–Milwaukee Joseph J. Zilber School of Public Health and the University of Richmond’s Digital Scholarship Lab, compared 1930’s maps of government-sanctioned lending discrimination zones with current census and public health data.

Table of Content

  • Executive Summary
  • Introduction
  • Redlining, the HOLC Maps and Segregation
  • Segregation, Public Health and COVID-19
  • Methods
  • Results
  • Discussion
  • Conclusion and Policy Recommendations
  • Citations
  • Appendix

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