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Consumer &
Community Context
A series examining economic and
financial topics affecting consumers
and communities

Access to Financial Services Matters
to Small Businesses
Small businesses are vital to the American economy. While there is no single,
widely accepted definition, the U.S. Small Business Administration generally
classifies businesses with fewer than 500 employees as small.
By this metric, small businesses account for 99.9 percent of all U.S. firms and
nearly half of private-sector employment. At the smaller end of the spectrum,
about 30 million firms (98 percent of small businesses) have fewer than
20 employees or are sole proprietorships.1 Small businesses are remarkably
diverse, producing products or delivering services in virtually every industry
segment and accounting for about 44 percent of the total private-sector output
of the economy.2 Beyond numbers, small businesses are part of the fabric of
their communities, employing local residents and supporting civic causes.
Business owners and entrepreneurs need access to a variety of credit sources.
Short-term credit matters for day-to-day management of cash flow, while
longer-term credit is essential for capital investments. Yet less than half of small
businesses report that their credit needs are met.3

Note: Charlene van Dijk, Barbara Lipman, and PJ Tabit, of the Federal Reserve Board’s Division of
Consumer and Community Affairs, contributed to this introduction.
1. U.S. Small Business Administration, “2018 Small Business Profile,” https://www.sba.gov/
sites/default/files/advocacy/2018-Small-Business-Profiles-US.pdf. For more information on nonemployer firms, see Federal Reserve Banks, 2019 Small Business Credit Survey Report on Nonemployer Firms (August 2019), https://www.fedsmallbusiness.org/medialibrary/fedsmallbusiness/files/
2019/sbcs-nonemployer-firms-report-19.pdf.
2. Kathryn Kobe and Richard Schwinn, Small Business GDP: Update 1998–2014 (Washington:
U.S. Small Business Administration, December 2018), https://s3.amazonaws.com/advocacy-prod
.sba.fun/wp-content/uploads/2018/12/21060437/Small-Business-GDP-1998-2014.pdf.
3. Federal Reserve Banks, Small Business Credit Survey: 2019 Report on Employer Firms
(April 2019), https://www.fedsmallbusiness.org/medialibrary/fedsmallbusiness/files/2019/sbcsemployer-firms-report.pdf.

November 2019 ▪ Vol. 1, No. 2

In This Issue
Access to Financial Services Matters to
Small Businesses

Searching for Small Business Credit Online:
What Prospective Borrowers Encounter on
Fintech Lender Websites

Mind the Gap: Minority-Owned
Small Businesses’ Financing Experiences in
2018

Growing Pains: Examining Small Business
Access to Affordable Credit in Low-Income
Areas

The views expressed here are those of the
authors and do not necessarily reflect the
position of the Federal Reserve Board or
the Federal Reserve System.

Consumer & Community Context

Supporting
Small Businesses
“The Federal Reserve System
helps foster growth in local
and regional communities by
connecting small businesses
to research and networks
through its Community
Development function at the
12 Reserve Banks and the
Board of Governors. These
connections amplify our
understanding of challenges
that small businesses and
startups can face, and underscore that creditworthy small
businesses and startups
need adequate and affordable access to credit in order
to form, grow, and succeed.”
—Federal Reserve Board
Vice Chair for Supervision
Randal K. Quarles

This issue of Consumer & Community Context focuses on small businesses’
access to capital. The first article describes what small business owners
encounter when searching for financing on the websites of online lenders. The
second explores disparities in small business credit approval by race and
ethnicity. The third examines small businesses’ access to financial services in
low- and moderate-income communities.
Thank you for your interest in Consumer & Community Context. To subscribe
to future issues, email CCA-Context@frb.gov. For past issues, visit https://www
.federalreserve.gov/publications/consumer-community-context.htm.

November 2019

Searching for Small Business Credit
Online: What Prospective Borrowers
Encounter on Fintech Lender Websites
by Barbara J. Lipman, Federal Reserve Board Division of Consumer and
Community Affairs, and Ann Marie Wiersch, Federal Reserve Bank of Cleveland
Community Development Department1
A review of online lender websites finds inconsistencies in the disclosure of cost
information, posing difficulties for prospective borrowers.
Nonbank online lenders are a growing source of small-dollar credit for small
businesses. As the Federal Reserve Banks’ Small Business Credit Survey
(SBCS) indicates, nearly one-third (32 percent) of small businesses that applied
for credit in 2018 sought it from an online lender, up from 19 percent and
24 percent in 2016 and 2017, respectively.2
The fintech lending industry consists of various types of online lenders, offering a
variety of products. Some products are lines of credit and term loans structured
much like those from traditional banks, with fixed rates and monthly payments.
Other short-term products have fixed weekly or daily payments. Still others are
merchant cash advance (MCA) products that entail the sale of future receivables
for a set dollar amount, repaid with a set percentage of the business’s daily sales
receipts. For example, a business may be advanced $50,000 and repay
$60,000 through 10 percent automatic draws from its daily credit card receipts.
Some products are a hybrid in which repayment is based on a share of
sales—much like a cash advance product—but regardless of sales, must be
fully repaid within a set period—like a term loan.
What these various credit products have in common is that borrowers apply and
are largely processed, underwritten, and serviced online. Also, it is important to
note that “Truth in Lending” rules that apply to consumer loan and credit

1. The authors thank Scott Colgate and PJ Tabit of the Federal Reserve Board for their assistance with the visitor tracking analysis in this study, as well as Kenny Clark, Carol Evans, Marysol
McGee, and Michael Scherzer, also of the Federal Reserve Board, for their thoughtful comments.
2. The Small Business Credit Survey (SBCS) is an annual survey of employer and nonemployer
small firms administered by the 12 Federal Reserve Banks; see https://www.fedsmallbusiness.org/
about.

Consumer & Community Context

products generally do not apply to business credit, so in practice, lenders have
more flexibility in their disclosures of product costs and features.3

About the Study: Small Businesses’ Challenges with
Online Lenders
According to the SBCS, financing approval rates are higher at online lenders
than at traditional lenders (82 percent at online lenders versus 71 percent at
small banks and 58 percent at large banks). However, satisfaction levels with
online lenders are far lower (net satisfaction of 33 percent at online lenders
versus 73 percent at small banks and 55 percent at large banks).4 In 2018,
63 percent of online lender applicants reported challenges working with their
lender, with more than half saying they experienced high interest rates and
almost a third reporting concerns with unfavorable repayment terms.
In two previous studies, both utilizing online focus groups, we suggest why this
may be the case. The focus group participants—more than 80 small business
owners—completed a “virtual shopping” exercise and compared mock products
based on real online product offerings. These studies found that small business
owners struggle to understand many of the products offered by online lenders
and the unfamiliar terminology that some lenders use in their product
descriptions.5
Augmenting the findings from the SBCS and focus groups, this article
systematically examines the website content of several prominent small
business online lenders.6 It considers

3. The Truth in Lending Act is implemented through Regulation Z. Regulation Z does impose certain substantive protections applicable to credit card holders, including where the card is issued for
business use. Alternative small business lenders, however, do not typically issue credit cards.
4. In the SBCS, approval rate is the share of firms approved for at least some credit, and net satisfaction is the share of firms satisfied minus the share of firms dissatisfied.
5. See Barbara J. Lipman and Ann Marie Wiersch, Alternative Lending Through the Eyes of
“Mom & Pop” Small Business Owners: Findings from Online Focus Groups (Cleveland, OH: Federal
Reserve Bank of Cleveland, 2015), https://www.clevelandfed.org/newsroom-and-events/
publications/special-reports/sr-20150825-alternative-lending-through-the-eyes-of-mom-and-popsmall-business-owners.aspx; and Barbara J. Lipman and Ann Marie Wiersch Browsing to Borrow:
“Mom & Pop” Small Business Perspectives on Online Lenders (Washington: Board of Governors of
the Federal Reserve System, 2018), https://www.federalreserve.gov/publications/files/2018-smallbusiness-lending.pdf.
6. This study builds on earlier work by the Federal Trade Commission, “A Survey of 15 Marketplace Lenders’ Online Presence,” June 2016, https://www.ftc.gov/system/files/documents/public_
events/944193/a_survey_of_15_marketplace_lenders_online_presence.pdf, and the U.K. Financial
Conduct Authority, Payday Lending Market Investigation, “Review of the Websites of Payday Lenders and Lead Generators,” Appendix 6.4, February 2015, https://assets.publishing.service.gov.uk/
media/5329df8640f0b60a7600032e/140131_review_of_websites_working_paper.pdf.

November 2019

• where and how credit products’ interest rates, fees, repayment and prepayment terms, and other features are disclosed;
• how much product information is made available before website visitors are
asked to supply personal or business information; and
• the extent to which visitors are tracked.
We compiled a list of 10 online lenders by conducting multiple keyword
searches and cross-referencing the results with industry lists and estimates of
lending volumes of some of the most prominent lenders.7 In the course of the
review, some 15 different aspects of the websites’ content were documented,
including the language used and where and how information was displayed.
Finally, the study used a Chrome browser extension to attempt to identify and
quantify the number and types of third-party trackers used by the websites. A
discussion of the takeaways follows.

Websites Vary in Their Degrees of Transparency
Lenders vary significantly in the level of upfront product information they provide
to prospective borrowers. As shown in table 1, of the 10 online lender websites
included in this study, 2 provide costs using an annual interest rate (a third
company does so for its lines of credit only); 3 show product costs using
nonstandard terminology; and 5 provide no cost information about their
products. On some sites, particularly those that offer traditional term loans,
product descriptions are somewhat detailed. Others—often those that provide
MCAs to high-credit-risk borrowers—feature little or no information about the
actual products. Virtually all the sites focus on the ease of applying and
qualifying for funding, the speed at which applications are approved, and the
array of uses for loan proceeds.
Specifically, details that were important to focus group participants—rates, fees,
and repayment information—were absent from several of the websites or hard
to find. Even on websites with relatively detailed information, specifics about the
products were sometimes missing or not readily displayed. For example, one
lender featured in prominent bold print the “as low as” rate for a loan product,
but in a footnote, disclosed a far higher average rate. In some cases, information

7. Note that the websites participants chose to visit in each of the two focus group studies (see
footnote 5) largely overlapped, but did differ somewhat from the websites in the present study. The
websites of five banks and two payment processors also were considered. See report on which this
article is based, Barbara J. Lipman and Ann Marie Wiersch, Uncertain Terms: What Small Business
Borrowers Find When Browsing Online Lender Websites (Washington: Board of Governors,
forthcoming).

Lenders vary significantly
in the level of upfront
product information they
provide to prospective
borrowers. . . . Specifically,
details that were important to
focus group participants—
rates, fees, and repayment
information—were absent from
several of the websites or hard
to find.

Consumer & Community Context

Table 1. Select details from online lender websites
Lender

Location of cost
information

Product cost
description

Additional fees

Company A

On home page in box,
details in footnotes

Rate for business loans
described as a Total
Annualized Rate; fixed
rates ranging from
5.99% to 29.99%

Origination fee: 1.99%
to 8.99% of loan
amount

Company B

On home page in plain
text, details on product
pages in feature text
and in footnotes

Costs shown as simple
interest starting at 9%
for short-term loans and
Annual Interest Rate
(AIR) starting at 9.99%
for long-term loans
(both rates exclude
fees); lines of credit
(LOCs) costs shown as
Annual Percentage Rate
(APR) (starting at
13.99%, weighted
average is 32.6%)

Origination fee: up to
4% of loan amount;
monthly maintenance
fees on LOC

Company C

Not provided

No rates or product
costs are described on
the site

No info

Company D

On Rates and Terms
page in feature text,
details in footnotes

Costs for loans and
LOCs are described
as a monthly fee
determined by the fee
rate, which ranges from
1.5% to 10%

Third-party partners
may charge up to an
additional 1.5% per
month

Company E

Not provided

No rates or product
costs are described on
the site

3% origination fee
(loans), $395 admin fee
(MCAs)

Company F

On product page in
plain text

Working capital loans,
MCAs—factor rates
as low as 1.15;
business expansion
loans—interest rates
starting at 9.99% (not
an APR)

Set-up or underwriting
fee: 2.5% of loan total;
admin. fee up to
$50/month

Company G

On home page in
feature text, details in
tables on Rates and
Fees page

Loan costs shown as
fixed annual interest
rate, ranging from
4.99% to 26.99%

Origination fee: 0.99%
to 6.99%; late payment
fee: 5% of missed
payment

Company H

Not provided

No rates or product
costs are described on
the site

No info

Company I

Not provided

No rates or product
costs are described on
the site

No info

Company J

Not provided

No rates or product
costs are described on
the site

No info

Note: Although all information shown is publicly available, company names have been anonymized, as
this analysis is intended to describe typical practices in the marketplace rather than to single out
practices of individual companies.
Source: Authors’ analysis of company websites, as of May 31, 2019.

November 2019

such as loan terms and repayment terms were found on terms of use pages or
in frequently asked questions (FAQs).
Three of the websites reviewed in the study convey information about product
costs using nonstandard terminology, for example, a “factor rate” or “fee rate” or
“simple interest.” Table 2 presents APR-equivalents for a common scenario in
which $50,000 is repaid in six months according to the terms and rates
promoted on the lenders’ sites.
This variation in the product cost descriptions and terminology is confusing to
some prospective borrowers and a possible source of frustration, as evidenced
by comments from the focus group participants:
• “It is difficult [to compare when] they are using different models and different
terminology.”
• “They don’t like to use the word ‘interest,’ and they dress it up in other ways
to conceal the real cost of the loan.”
• “I don’t know what a ‘factor rate’ is.”
• “Full disclosure, like on credit cards or mortgages… is what is necessary.
They need to state the actual APR.”
Estimating interest rates for purposes of comparing costs of online products
with traditional credit products proved difficult for focus group participants. For
example, when asked to compare a credit card to a short-term loan that was
described using nontraditional language, the majority incorrectly guessed the
Table 2. Estimated APRs for select online products
Rate advertised on website

Product details

Estimated APR equivalent

1.15 factor rate

• Total repayment amount:
$59,000
• Fees: 2.5% set-up fee;
$50/month administrative fee
• Daily payments (assume steady
payments 5 days/week)
• Term: none (assume repaid in
6 months)

Approximately 70% APR

4% fee rate

• Total repayment amount:
$56,500
• Fee rate: 4% (months 1–2),
1.25% (months 3–6)
• Fees: none
• Monthly payments
• Term: 6-month term

Approximately 45% APR

9% simple interest

• Total repayment amount:
$54,500
• Fees: 3% origination fee
• Weekly payments
• Term: 6-month term

Approximately 46% APR

Source: Authors’ calculations, based on product descriptions on company websites.

Consumer & Community Context

short-term loan to be less expensive. In addition, the estimation of interest rates
is further complicated by added fees for online products. The website analysis
revealed that lenders may charge sizable origination fees—as high as
8.9 percent—and other fees which were excluded from the interest rates
advertised.

Variation in the product cost
descriptions and terminology is
confusing to some prospective
borrowers and a possible source
of frustration.

The impact of early repayment on total costs for products with fixed payback
amounts (such as MCAs) is not addressed on most websites. Without such
information, focus group participants often made the assumption that, as is the
case with traditional credit products, they would save money by repaying faster.
In fact, there is usually no savings associated with early repayment on these
products.8

Lack of Information Prompts Solicitation
All of the lenders’ websites use forms to gather personal and business
information from prospective borrowers. Through these forms, visitors request
product information or initiate an application. As noted earlier, five of the lenders
provide no upfront cost information; rather, visitors must provide their information
to request details on product cost and terms. Many of the focus group
participants who encountered such sites during their virtual shopping exercise
found this frustrating. As one participant noted, “I hoped to see rates, terms,
and what I qualified for,” and observed that the lender she visited, “wouldn’t
provide any information without an email or contact information.”
Moreover, when users enter their information on any of the sites, they give
consent to be contacted via phone, text, or email by the lender or its third-party
affiliates. On some sites, the consent is described explicitly on the form itself. On
others, consent is implicitly given, as described in the site’s privacy policy or
terms of use page.
Participants associated the sharing of their contact or other business information
with aggressive marketing tactics used by some lenders. For example, one
participant stated, “I don’t want to be solicited for the rest of my life just because
I was looking for some information.” More than three-quarters of the focus group
participants reported receiving email, mail, phone calls, or offers from online
lenders. Phone calls were described as the most bothersome, with some
participants reporting they occur “almost every day” or “twice a week” and some
noting, as one participant put it, the callers “won’t take ‘no’ for an answer.”

8. See Lipman and Wiersch, Browsing to Borrow, 19–20.

November 2019

Tracking Website Visitors
Asking visitors to provide business and contact information is one tool lenders
may use to construct profiles of potential small business borrowers. Third-party
trackers are another.
When installed on a lender’s website, trackers collect identifying information
about website visitors and attempt to match them to known businesses or
owners, using data from a variety of sources including Facebook, Amazon,
Twitter, LinkedIn, and other common web platforms.9 The profiles may contain
information like company name, address, and internet activity, as well as more
sensitive data including financial information and owner demographics. So even
when visitors do not share identifying information with the lender, embedded
trackers may collect this information as well as data on how visitors navigate the
lender’s website and other sites they visit. Such details can then be shared with
data aggregators to build a more complete profile.
We used Ghostery, an open source (Chrome) browser extension, to estimate the
numbers of trackers in five distinct tracker categories on each lender’s website
(see figure 1).10 Each of the 10 websites used at least 7 trackers, and most used
several in each category.
Lenders use trackers much the way other companies do—to collect as much
information as possible about each visitor in order to customize visitors’
experiences and reach them through targeted advertising. However, privacy
experts as well as small business advocates have suggested that data collected
surreptitiously through trackers may be used along with the other alternative
data online lenders employ in their underwriting algorithms to underwrite and
price offers of credit.11

9. See, for example, Wolfie Christl, Corporate Surveillance in Everyday Life: How Companies
Collect, Combine, Analyze, Trade, and Use Personal Data on Billions (Vienna: Cracked Labs,
June 2017), https://monoskop.org/images/b/ba/Cracked_Labs_Corporate_Surveillance_in_
Everyday_Life_2017.pdf. See also, Katharine Kemp, “Getting Data Right,” blog post, September 27, 2018, Center for Financial Inclusion at Accion, https://www.centerforfinancialinclusion.org/
getting-data-right.
10. The analysis does not include websites’ use of so-called zero day trackers, which are
designed to be undetectable.
11. See Christl, Corporate Surveillance in Everyday Life, 53.

Consumer & Community Context

Figure 1. Use of trackers on online lender websites
Company 1
Company 2
Company 3
Company 4
Company 5
Company 6
Company 7
Company 8
Company 9
Company 10

Number of trackers

0
Essential

5
Site analytics

10
Customer interaction

15
Social media

20
Advertising

Note: Key identifies bars in order from left to right. Company names have been anonymized and relabeled
to indicate that the order in which they are listed here does not correspond with the order in table 1.
Essential includes tag managers, privacy notices, and technologies that are critical to the functionality of
a website.
Site analytics collects and analyzes data related to site usage and performance.
Customer interaction includes chat, email messaging, customer support, and other interaction.
Social media integrates features related to social media sites.
Advertising provides advertising or advertising-related services such as data collection, behavioral analysis, or retargeting.
Source: Analysis by Scott Colgate, Federal Reserve Board, as of July 16, 2019.

Disclosures for Small Business Online Credit in the
Policy Debate
This analysis finds that some online lenders’ websites lack detailed information
on product costs, and that there is little consistency of information provided
across lender websites. These practices, coupled with relatively low satisfaction
rates shown in the SBCS, raise concerns that some borrowers may be opting
for credit products that are not well-suited for their businesses—in some cases,
putting their businesses at risk.12 Indeed, debate about small business borrower
protections and product disclosures has accelerated recently with California

12. Record of Meeting, Community Advisory Council and the Board of Governors, October 5,
2018, https://www.federalreserve.gov/aboutthefed/files/cac-20181005.pdf, 7: “The Council notes a
growing trend among small business owners getting into trouble with expensive online small business loans, such as merchant cash advances (MCA). Oftentimes, the pricing and structure of these

November 2019

enacting truth in lending legislation covering small business online lenders—an
action under consideration by other states.13
At the national level, legislators, regulators, online lenders, and small business
advocates continue discussions about whether and how to address disclosure
and data concerns in small business lending.14 Meanwhile, industry trade
groups continue efforts to promote standardization of disclosures, including a
revised version of a voluntary disclosure box.15
As part of the focus group studies, participants were shown a stylized disclosure
table and asked their impressions of the content and format. Among the metrics
included in the table were the APR, total cost of capital, the term, payment
frequency, average payment amount, and basic information about prepayment.
Participants reacted favorably to the clear presentation of information
in a standard format, noting it would be very useful for product
comparisons—especially if provided early in the search process rather than at
loan closing. A majority of participants commented that APR was among its
most helpful details.16 However, required disclosure of APR for online products,
especially those without a fixed term, is a point of contention in the industry.17
Small business advocates argue that the clear disclosure of product costs and
terms, including APR, could help these business owners make informed
decisions about the amounts they borrow, managing their cash flow, repaying
early, and repeat borrowing. Standardized disclosures would enable comparison
across not only online lenders’ products but also online and more traditional
products such as home equity lines of credit and credit cards.

loans is deliberately obscured, and small business owners take on debt burdens and fees that they
are not able to sustain.”
13. California SB-1235, “Commercial Financing Disclosures,” was signed into law on September 30, 2018. It has not yet been implemented, as the California Department of Business Oversight
is adopting regulations. The New York and New Jersey legislatures are considering similar bills.
14. See, for example, U.S. House of Representatives, Committee on Small Business, “Financing
through Fintech: Online Lending’s Role in Improving Small Business Capital Access,” hearing held
October 26, 2017, https://www.govinfo.gov/content/pkg/CHRG-115hhrg27255/html/CHRG115hhrg27255.htm.
15. See SMART Box Model Disclosure Initiative, https://innovativelending.org/smart-box/.
16. The total cost of capital, repayment amount, payment frequency, and prepayment penalties
also were cited as important.
17. APR aside, debates are ongoing about whether already-regulated commercial bank lenders
would be subject to disclosure rules, should rules be implemented. See, for example, the Bipartisan
Policy Commission report Main Street Matters: Ideas for Improving Small Business Financing
(August 2018), https://bipartisanpolicy.org/report/main-street-matters-ideas-for-improving-smallbusiness-financing/.

Standardized disclosures would
enable comparison across not
only online lenders’ products but
also online and more traditional
products such as home equity
lines of credit and credit cards.

Consumer & Community Context

Unanswered Questions and Future Research
This study includes only the content of lender websites and does not compare
formal credit offers and loan agreements with terms advertised on the sites. It
also does not address the extent to which data collected by trackers may be
used in lenders’ credit decisions. Future research could consider the impact of
standardized disclosures on satisfaction with online lenders, as well as whether
they lead to borrowing decisions that help small businesses thrive and grow.

November 2019

Mind the Gap: Minority-Owned
Small Businesses’ Financing
Experiences in 2018
by Mels de Zeeuw, Federal Reserve Bank of Atlanta Community and Economic
Development Department, and Brett Barkley, Federal Reserve Bank of
Cleveland Supervision and Regulation Department
Black-owned firms are less likely than white-owned firms to be approved for
financing at banks, even taking into account firm characteristics.
U.S. Census estimates project that by 2060, racial minorities will comprise some
56 percent of the U.S. population, compared with about 39 percent in 2017.
However, business ownership rates among most minority groups continue to lag
those of non-Hispanic whites.1 Increasing minority-business ownership can
benefit not just individual entrepreneurs and their households—such as through
wealth-building—but also communities and the U.S. economy as a
whole—such as through job creation and innovation, and it could alleviate
economic disparities.
A critical component of many small businesses’ success is adequate,
accessible, and affordable financing. In a previous paper, using data from the
Federal Reserve’s 2016 Small Business Credit Survey (SBCS), we found
evidence that black-owned firms are less likely than white-owned firms to
receive approval for financing and are more likely to be discouraged from
applying for financing.2 We also found that Hispanic- and black-owned firms are

1. For instance, in 2016, 81.6 percent of small employer firms classifiable by the race and ethnicity of the owner(s) were owned by non-Hispanic whites, though this group made up 60.7 percent of
the U.S. population that year. In contrast, blacks represented 2.2 percent of small employer firms,
compared to 12.5 percent of the population, and Hispanics made up 5 percent of small business
owners, compared to their 18.1 percent share of the U.S. population. See U.S. Census Bureau’s
Population Estimates Program: July 1, 2016 and U.S. Census Bureau’s 2016 American Survey of
Entrepreneurs.
2. See Alicia Robb, Brett Barkley, and Mels de Zeeuw, “Mind the Gap: How Do Credit Market
Experiences and Borrowing Patterns Differ for Minority-Owned Firms?” Community and Economic
Development Discussion Paper 03-18 (Atlanta: Federal Reserve Bank of Atlanta, September 2018),
https://www.frbatlanta.org/-/media/documents/community-development/publications/discussionpapers/2018/03-mind-the-gap-how-do-credit-market-experiences-and-borrowing-patterns-differfor-minority-owned-firms-2018-09-14.pdf. For more information on the Small Business Credit Survey (SBCS), visit fedsmallbusiness.org.

Consumer & Community Context

more likely than white-owned firms to seek financing at nonbank online lenders
such as OnDeck Capital, CAN Capital, and Kabbage.3
This article revisits that analysis, using 2018 SBCS data.4 First, we describe the
profiles of minority-owned firms and consider their need for, and access to,
credit. We then compare application patterns and approval rates by race and
ethnicity of a business’s ownership across lender types.
We find differences in the financing experiences of minority-owned firms
compared with white-owned firms in several respects:
• First, black-owned firms are less likely overall to be approved for financing, or
to be approved at large or small banks, compared with white-owned firms.
• Second, a relatively large share of minority-owned firms face potentially large
unmet financing needs, as black-, Asian-, and Hispanic-owned firms are less
likely than white-owned firms to report having sufficient levels of financing in
place.
• Finally, black- and Hispanic-owned firms are less likely to turn to small banks
and, contrary to previous analysis of 2016 SBCS data, are just as likely to
turn to online lenders compared with white-owned firms after controlling for
other firm characteristics—likely driven by the growth of online lender applicants among white-owned firms.

Why Increasing Minority Small Business Ownership Matters
Closing the gap in minority small business ownership presents opportunities for
policymakers to expand the benefits of economic growth and economic mobility
to a broader cross-section of the U.S. population who, historically, have faced
barriers to fully participating in the country’s prosperity. For example, increased
3. The survey questionnaire asks about a range of nonbank online providers, including retail/
payments processors, peer-to-peer lenders, merchant cash advance lenders, and direct lenders.
For purposes of this article, nonbank online lenders are grouped into one category, “online lenders.”
4. The SBCS contains self-reported data on firm characteristics, credit application, approval,
and other experiences in the market for small business financing. The SBCS yielded 6,614
responses from small employer firms in 2018 with race/ethnicity of the owner identified. The sample
size will vary from question to question based on how many firms responded to a given question
(for instance, firms that did not apply for financing will not answer questions on financing approval).
While the survey is based on a convenience sample of respondents, the data are weighted by the
race and/or ethnicity of firm ownership, gender of the firm’s owner(s), geographic location (census
division, and rural or urban location), firm size, firm age, and industry to attempt to ensure it is representative of the U.S. small employer firm population. In places where we reference estimates
based on all three years of SBCS survey data from 2016 to 2018, estimates are based on a sample
of 24,651 small employer firms, allowing for some overlap in firms responding from year to year.
Also note that the primary SBCS reports (https://www.fedsmallbusiness.org/survey) adopted a
name change in 2019. While previous reports were titled for the year the survey was conducted,
starting in 2019, the report title reflects the calendar year the report is released.

November 2019

minority-business ownership could help alleviate certain economic disparities
that exist along racial lines; research suggests there is a relationship between the
race or ethnicity of a business owner—or an individual with hiring authority—and
the race or ethnicity of employees hired. Therefore, an increased share of
black-owned businesses could contribute to narrowing the differential in
unemployment rates that exists between blacks and whites.5
Increased minority-business ownership could also lead to a reduction in wealth
gaps that exist between white and black households and white and Hispanic
households. An analysis of the 2008 Survey of Income and Program
Participation data show that the wealth gap between black and white business
owners shrinks to a factor of 3, from a factor of 13, between white and black
households overall.6
However, a lack of wealth or startup capital contributes to lower rates of small
business ownership among minorities, in turn enabling the racial wealth gap to
persist. Black and Hispanic entrepreneurs, in particular, tend to rely
disproportionately on external sources of capital due to their lower personal
wealth levels.7
The small business financing environment, therefore, is critically important to
their success and ultimately to the long-term health of the U.S. economy.8

Firms’ General Traits and Performance
Basic characteristics and performance (age, revenue size, profitability, and so
on) of minority- and nonminority-owned firms have remained largely consistent
with the dynamics discussed in our previous research and in the 2016 Small
Business Credit Survey: Report on Minority-Owned Firms.9 In general, blackand Hispanic-owned firms tend to be younger, smaller, and less profitable. They
also have lower credit scores than white- and Asian-owned firms.

5. Michael A. Stoll, Steven Raphael, and Harry J. Holzer, “Why Are Black Employers More Likely
Than White Employers to Hire Blacks?” Institute for Research on Poverty, Discussion Paper 123601, https://www.irp.wisc.edu/publications/dps/pdfs/dp123601.pdf.
6. Association for Enterprise Opportunity, The Tapestry of Black Business Ownership in America:
Untapped Opportunities for Success (Washington: Association for Enterprise Opportunity, 2017),
https://www.aeoworks.org/wp-content/uploads/2019/03/AEO_Black_Owned_Business_Report_
02_16_17_FOR_WEB.pdf.
7. Robert W. Fairlie and Alicia Robb, Race and Entrepreneurial Success: Black- Asian- and
White-Owned Businesses in the United States (Cambridge, MA: MIT Press, 2008).
8. See the discussion in Robb et al., “Mind the Gap.”
9. Federal Reserve Banks, 2016 Small Business Credit Survey: Report on Minority-Owned Firms
(November 2017), https://www.fedsmallbusiness.org/survey/2017/report-on-minority-owned-firms.

Consumer & Community Context

Black-Owned Firms Face Greater Challenges
Raising Capital

Creditworthy black-owned
firms experience greater
challenges raising capital than
creditworthy white-owned firms.
[Even controlling] for firm
characteristics and performance
. . . approval rates for
black-owned firms still remain
lower.

Our analysis finds that creditworthy black-owned firms experience greater
challenges raising capital than creditworthy white-owned firms.
According to 2018 SBCS data, only 64 percent and 65 percent of black- and
Hispanic-owned applicant firms, respectively, were approved for some financing,
compared with 80 percent and 76 percent among white- and Asian-owned
firms, respectively (estimates without controls not shown in figures).
However, it is important to control for firm characteristics and performance when
comparing approval rates of firms across race and ethnicity of the owner. When
doing so, approval rates for black-owned firms still remain lower, consistent with
our previous analysis of 2016 survey data. Compared with similar white-owned
firms in terms of profitability, credit risk, and other factors, black-owned
businesses that applied for financing were 7 percent less likely to obtain credit
overall, and they were 20 percent and 17 percent less likely to do so at large
and small banks, respectively (see figure 1).10
This indicates that even creditworthy black-owned firms experience relatively
large challenges raising capital. Notably, compared with their experience at
traditional institutions, black-owned firms appear to have a better chance at
approval from online lenders.11 While there is some evidence to suggest
Hispanic-owned firms also face relatively large challenges obtaining approval for
financing in the small business credit market, results are much less definitive
than estimates for black-owned firms.12
The results on financing approval are consistent with recent research on
discrimination in mortgage lending markets using millions of loan records, which
suggests that while online lenders have not eliminated discrimination for black
and Hispanic borrowers, they may have reduced it compared with traditional
lenders through a combination of competition and more impersonal application

10. The results hold when estimating on all years of survey data (2016, 2017, and 2018) at
99 percent confidence intervals. The likelihood of approval overall refers to approval at any lender
source for all types of credit. The likelihood of approval at each respective lender refers to approval
only for loan or line-of-credit products.
11. While point estimates show black-owned firms are still around 3 percent less likely to be
approved than white-owned firms at an online lender, this result is not statistically significant.
12. For Hispanic-owned firms, a robustness check using 2016 through 2018 data shows
a -5 percent difference in overall approval rates and a -6 percent difference in large bank approval
rates between Hispanic- and white-owned firms at the 95 percent and 90 percent significance
level, respectively; the likelihood of approval between Hispanic- and white-owned firms at small
banks and online lenders is statistically similar.

November 2019

Figure 1. Likelihood of approval for at least some financing at lending
source, by race/ethnicity of firm ownership (2018)

83.0

84.6

58.8**

64.8

67.0

75.9

78.0

74.4**

Percent

81.7

100

44.8***

60
50
40
30
20
10
0

Overall
Non-Hispanic white

Large banks

Small banks

Non-Hispanic black

Online lenders
Hispanic

Note: Key identifies bars in order from left to right. The likelihood of approval overall refers to approval at
any lender source for all types of credit. The likelihood of approval at each respective lending source
refers to approval only for loan or line-of-credit products. Results are from a series of logistic regressions
controlling for revenue size, credit score, profitability, urban/rural location, age, industry, state, veteranowned, woman-owned, and employee size. Estimates are displayed as average adjusted predictions.
Results for Asian-owned firms, and for Hispanic-owned firms that applied at small banks or online lenders, have been omitted from this figure due to a limited number of observations. Asterisks on minorityowned firm estimates denote statistical differences from white-owned firms: *** p<0.01, ** p<0.05, * p<0.1
Source: The authors’ analysis based on 2018 Small Business Credit Survey (SBCS) data.

processes.13 However, both small business applicants and debt holders at
online lenders are significantly more likely to report encountering high interest
rates or less favorable repayment terms than they are at small or large banks.14

13. Robert Bartlett, Adair Morse, Richard Stanton, and Nancy Wallace, “Consumer-Lending Discrimination in the FinTech Era,” University of California Berkeley Working Paper (presented at the
FDIC-Duke Financial Technology Conference, February 2019), https://www.fdic.gov/bank/
analytical/fintech/papers/stanton-paper.pdf. For analysis of personal consumer loans, see Julapa
Jagtiani and Catharine Lemieux, “The Roles of Alternative Data and Machine Learning in Fintech
Lending: Evidence from the LendingClub Consumer Platform,” Federal Reserve Bank of Philadelphia Working Paper 18-15 (January 2019), https://philadelphiafed.org/-/media/research-and-data/
publications/working-papers/2018/wp18-15r.pdf. While not accounting for race/ethnicity specifically, findings suggest that LendingClub’s use of alternative data has enabled some consumers to
obtain lower-priced credit than would otherwise be possible based on a traditional credit score
used by brick-and-mortar banks.
14. Federal Reserve Banks, Small Business Credit Survey: 2019 Report on Employer Firms
(April 2019), https://www.fedsmallbusiness.org/medialibrary/fedsmallbusiness/files/2019/sbcsemployer-firms-report.pdf. Fifty-three percent of small business applicants to online lenders report

Consumer & Community Context

Given the above results, this could indicate that a relatively large share of
minority-owned businesses face higher borrowing costs, on average, which
could offset the benefits of obtaining credit in the first place. Analysis on larger
data sets is recommended. Additional due diligence by policymakers would be
beneficial in order to better evaluate the potential positive and negative
consequences associated with online small business credit products and the
alternative underwriting models sometimes associated with them.15

Minority-Owned Firms Are Equally Likely to Be Discouraged
from Applying for Credit; Less Likely to Have Sufficient
Funding in Place
Although minority-owned firms that did not apply for financing were 10 to
15 percentage points more likely to report discouragement (that is, they did not
apply because they expected to be turned down) than white-owned firms in
2018, the differences—with the exception of Asian-owned firms—largely
disappear after controlling for firm characteristics like age, revenue size,
profitability, and credit score, among other variables (see figure 2).16 This finding
diverges from our analysis of the 2016 data, in which we found black-owned
firms were significantly more likely to report “discouragement.”
Combined with a drop of the share of black-owned firms that report
discouragement between 2016 and 2018, from 37 to 27 percent, this could
indicate that racial bias against black business owners has decreased. A more
cautious interpretation is that business sentiment measures like
“discouragement” could be prone to more variation than more objective
measures focused on business performance and credit outcomes.
In contrast to findings on firm discouragement, black-, Hispanic-, and
Asian-owned firms that did not apply for credit were each less likely to report
that their firms have sufficient financing compared with white-owned firms (see

high interest rates as a challenge, compared to 19 percent at large banks and 14 percent at small
banks. Additionally, 32 percent of applicants to online lenders report facing unfavorable repayment
terms, compared to just 12 percent of applicants at large banks and 7 percent at small banks.
15. Such due diligence could perhaps be similar to the Consumer Financial Protection Bureau’s
recent No-Action Letter (NAL) to Upstart Network, Inc. (https://www.consumerfinance.gov/aboutus/blog/update-credit-access-and-no-action-letter/), which reported positive results in terms of the
ability of alternative credit models employed by some online lenders to expand credit access and
reduce discriminatory pricing. The NAL with Upstart was focused on consumer lending, but similar
evaluations could be beneficial for small business lending.
16. The differences between Asian- and white-owned firms based on all years of survey data
(2016, 2017, and 2018) are consistent with previously reported results, albeit at smaller magnitudes. Asian-owned firms did not report statistically different levels of discouragement compared
with white-owned firms.

November 2019

Figure 2. Likelihood of reporting reason for not submitting credit application,
by race/ethnicity of firm ownership (2018)
60

Percent

55.9

46.6**

46.4**

45.3***

18.1*

20
12.4

12.9

12.6

0
Discouraged from applying
Non-Hispanic white

Sufficient financing in place
Non-Hispanic black

Asian

Hispanic

Note: Key identifies bars in order from left to right. The results are from a series of logistic regressions
controlling for revenue size, credit score, profitability, urban/rural location, age, industry, state, veteranowned, woman-owned, and employee size. Estimates are displayed as average adjusted predictions.
Asterisks on minority-owned firm estimates denote statistical differences from white-owned firms:
*** p<0.01, ** p<0.05, * p<0.1
Source: The authors’ analysis based on 2018 SBCS data.

figure 2). These firms were around 10 percent less likely to say they had
sufficient financing in place compared with white-owned firms. The dynamics are
largely consistent with our original analysis of 2016 survey data. Among firms
that did file applications for financing and were approved, a significantly larger
share of minority-owned firms received less than half the financing they applied
for compared to white-owned firms.17 Taken together, these findings indicate
that minority-owned firms in particular are facing potentially large unmet
financing needs.

17. Among approved applicants, 62 percent of white-owned firms were approved for all the
financing they sought, compared to 49 percent of black-owned, 51 percent of Asian-owned, and
52 percent of Hispanic-owned firms. Inversely, just 23 percent of white-owned firms were approved
for less than half of the financing amount they applied for, compared to 37 percent of black-owned,
31 percent of Asian-owned, and 32 percent of Hispanic-owned firms.

Consumer & Community Context

Minority-Owned Firms Less Likely to Apply to Small Banks,
Equally Likely to Apply to Online Lenders

Black-, Hispanic-, and
Asian-owned firms that did not
apply for credit were each less
likely to report that their firms
have sufficient financing
compared with white-owned
firms.

Online lenders continue to experience strong growth among small business
credit applicants. According to the Small Business Credit Survey: 2019 Report
on Employer Firms, the share of all applicants applying for credit from an
online lender has increased from 19 percent in 2016 to 32 percent in
2018—growth driven primarily by white-owned firms (estimates not shown in
figures).18 In contrast to our previous analysis of 2016 survey data, black- and
Hispanic-owned firms now appear no more likely to turn to online lenders
compared with white-owned firms when controlling for other firm characteristics
(see figure 3).19
Large banks remain the most common source of credit across all races and
ethnicities. Small banks are also an important source of credit, especially for
white- and Asian-owned firms, but significantly less so for black- and
Hispanic-owned firms. Community development financial institutions (CDFIs),20
on the other hand, are particularly important to black-owned firms, which are
16 percent more likely to turn to these lenders than white-owned firms (see
figure 3).21
Taken together, these dynamics suggest that online lenders are gaining currency
with a wider cross-section of borrowers, which could eventually pose a strategic
risk to traditional lenders in the small business credit market. Notwithstanding
these trends, however, online lenders still appear to inhabit a somewhat niche
market, with a focus on credit applicants that have traditionally been
underserved by banks, such as firms with little or no credit history.

18. Federal Reserve Banks, Small Business Credit Survey: 2019 Report on Employer Firms. The
share of black- and Hispanic-owned businesses applying to an online lender increased by around 7
and 11 percentage points, respectively, from 2016 to 2018 (from 34 percent to 41 percent, and
from 31 percent to 43 percent, respectively) whereas the share of white-owned businesses applying to an online lender increased by around 15 percentage points (from 17 percent to 32 percent).
As noted in footnote 4, starting in 2019, Small Business Credit Survey report titles reflect the calendar year in which a report is released, rather than the year the survey was conducted. Therefore,
the 2019 report is based on the 2018 data, which is the primary dataset used in this article.
19. To be clear, a larger share of black- and Hispanic-owned firms still report applying to an
online lender compared with white-owned firms; but when estimating the likelihood that a given firm
will apply to an online lender, the race/ethnicity of the owner is not a significant predictor. Our estimates show that having a poor credit score and low profitability are the strongest predictors for
applying to an online lender.
20. Community development financial institutions (CDFIs) are financial institutions that provide
credit and financial services to underserved markets and populations. CDFIs are certified by the
CDFI Fund at the U.S. Department of the Treasury.
21. The sample size of CDFI applicants is insufficient to report estimates for financial approval,
which is why we did not include it in figure 1.

November 2019

47.3

47.4

48.2

47.0

33.6

31.0

6.2

4.9

8.1

15.9***

27.6

28.9

32.8***

36.6***

44.8

43.1

44.6

48.1

Percent
53.3

55.4

Figure 3. Likelihood of applying at lending source, by race/ethnicity of
firm ownership (2018)

0
Overall

Large banks
Non-Hispanic white

Small banks
Non-Hispanic black

Online lenders
Asian

CDFIs

Hispanic

Note: Key identifies bars in order from left to right. Results are from a series of logistic regressions controlling for revenue size, credit score, profitability, urban/rural location, age, industry, state, veteranowned, woman-owned, and employee size. Estimates are displayed as average adjusted predictions.
Asterisks on minority-owned firm estimates denote statistical differences from white-owned firms:
*** p<0.01, ** p<0.05, * p<0.1
CDFIs Community development financial institutions.
Source: The authors’ analysis based on 2018 SBCS data.

Conclusion
Overall, our analysis finds that minority-owned firms—particularly black-owned
firms—experience greater challenges obtaining or accessing financing and have
potentially large, unmet financing needs. Although it is beyond the scope of this
analysis to identify underlying causal factors, we have provided updated insight
on how the different financing experiences of minority-owned firms continue to
evolve. Such understanding, informed by ongoing data collection efforts, will
continue to be important to inform efforts that promote small business formation
and economic growth and mobility more broadly, as well as to reduce economic
inequalities where they persist.

Consumer & Community Context

Growing Pains: Examining Small
Business Access to Affordable Credit
in Low-Income Areas
by Claire Kramer Mills, Jessica Battisto, and Scott Lieberman, Federal Reserve
Bank of New York Outreach & Education Function
Since the end of the last recession, low-income neighborhoods have experienced larger declines in the number of banks and larger increases in the number of
alternative financial services companies compared to higher-income areas.
The Great Recession hit small businesses especially hard, resulting in sizable
numbers of business closures and accompanying job losses.1 Businesses in
low- and moderate-income (LMI) areas continue to face challenges, as bank
consolidation and the growth of costly alternative financial services (AFS) have
reduced the number of affordable credit providers.2 Several studies find that
bank consolidation negatively affects small business access to capital,
specifically through the cost of bank loans.3 Additionally, lenders in less
competitive loan markets offer less favorable loan terms to borrowers than those
in competitive markets.4 Researchers also find that “areas in which large banks
acquire small banks subsequently experience faster growth in [high cost]
nonbank financial services such as check-cashing facilities.”5

1. See Aysegul Sahin, Sgiri Kitao, Anna Cororaton, and Sergiu Laiu, “Why Small Businesses
Were Hit Harder by the Recent Recession,” Current Issues in Economics and Finance 17, no. 4.
2. As defined by the Federal Financial Institutions Examination Council (FFIEC), low- and
moderate-income areas correspond to census tracts where the median family income is less than
80 percent of the median family income in the associated metropolitan statistical area.
The banking landscape has changed considerably in recent decades. Between 1990 and
March 2019, the number of institutions insured by the Federal Deposit Insurance Corporation fell
precipitously, with a loss of nearly 10,000 institutions, or 65 percent. This pace increased after the
most recent recession and shows little sign of abating.
3. See, for example, G. Steven Craig and Pauline Hardee, “The Impact of Bank Consolidation
on Small Business Credit Availability,” Journal of Banking and Finance 31, no. 4 (2007): 1237–63;
James H. Rauch and Jill M. Hendrickson, “Does Bank Consolidation Hurt the Small Business Borrower?” Small Business Economics 23, no. 3 (2004): 219–26; Robert B. Avery and Katherine A.
Samolyk, “Bank Consolidation and Small Business Lending: The Role of Community Banks,” Journal of Financial Services Research 25, no. 2-3 (2004): 291–325; and Andrew C. Chang, “Banking
Consolidation and Small Firm Financing for Research and Development,” Finance and Economics
Discussion Series 2016-029 (Washington: Board of Governors of the Federal Reserve System),
http://dx.doi.org/10.17016/FEDS.2016.029.
4. See Yili Lian, “Bank Competition and the Cost of Bank Loans,” Review of Quantitative Finance
and Accounting 51, no. 1 (2018): 253–82.
5. Vitaly M. Bord, “Bank Consolidation and Financial Inclusion: The Adverse Effects of Bank
Mergers on Depositors” (Cambridge, MA: Harvard University, December 1, 2018), https://scholar
.harvard.edu/files/vbord/files/vbord_-_bank_consolidation_and_financial_inclusion_full.pdf.

November 2019

In this article, we examine shifts in small businesses’ proximity to banks, credit
unions, and AFS, as well as levels of bank-originated small business loans in LMI
areas. Alternative financial service providers are defined by NAICS codes
522390 and 522298, which encompass check cashing, payday lending, loan
services, money order/transmission, and pawnshops. Small business loans are
defined here as business loans under $1 million, as reported by the Federal
Financial Institutions Examination Council (FFIEC) Community Reinvestment Act
lending data.
Drawing on data from several financial regulators and the U.S. Census Bureau,
we find that since the last recession, the number of banks operating in
lower-income neighborhoods declined the most and stands at the lowest level
among neighborhood income quartiles. At the same time, the number of costlier
AFS providers in lower-income areas has grown and is large relative to business
density.6 We also find that small business loan volumes in LMI communities,
though proportionate to the number of small businesses, remain a fraction of
loan volumes in upper-income areas.
These figures also likely underplay the relatively higher need for external capital in
low-income areas, as businesses in these communities may have limited
personal savings and “friends and family” networks with savings to invest in the
business; a low or nonexistent credit score; and/or insufficient collateral, such as
limited guarantors, limited real estate, or limited personal property equity.7

Small Businesses’ Financial Needs
Because of their size, many small businesses closely resemble consumers in
their financing needs and behaviors, seeking small loans and relying heavily on
personal credit scores and collateral to obtain financing. These firms are also
likely to have personal and business financing intertwined.8 This is particularly
true of small businesses in LMI areas, which tend to be smaller than firms in

6. Based on the growth in business establishments providing these services.
7. See Martin Hahn, “Business Loans to Low-Income Entrepreneurs,” Communities & Banking
(March 2014).
8. See Federal Reserve Banks, 2018 Small Business Credit Survey Report on Nonemployer
Firms (December 2018), https://www.fedsmallbusiness.org/survey/2018/report-on-nonemployerfirms; 70 percent of nonemployers use their personal credit score exclusively, while 65 percent use
a personal guarantee or personal collateral to secure financing. Nearly half of nonemployer firms
that applied for credit (46 percent) sought less than $25,000.

Small business loan volumes in
LMI communities, though
proportionate to the number of
small businesses, remain a
fraction of loan volumes in
upper-income areas.

Consumer & Community Context

higher-income areas.9 Although small businesses often seek small-dollar loans,
banks may be less willing to make such loans due to their typically higher
underwriting costs.10 As a result, when rejected from traditional sources of
credit, small businesses often turn to consumer AFS providers, such as payday
lenders and check cashers, which offer small loans with minimal underwriting.11
AFS can be attractive to firms seeking relatively small and quickly disbursed
credit, but AFS credit is more expensive than the credit offered by traditional
lenders and can often lead to a pernicious cycle of small businesses taking out
debt to fulfill payments on additional debt.12 Recent studies find average APRs
on payday loans in the range of 300 percent to 600 percent.13
While banks generally have stricter underwriting standards, they offer more
favorable interest rates than AFS providers. For a bank loan, the average annual
interest rate charged is between 4 percent and 6 percent.14

Bank Consolidation and Financial Services in Low-Income
Communities
Banks are a common source of small business financing.15 Yet, recent data
show that the number of bank branches is declining in low-income areas, likely
due to bank branch consolidation.

9. Maude Toussaint-Comeau, Robin Newberger, and Mark O’Dell, “Small Business Performance
in Industries after the Great Recession,” Profitwise News and Views no. 3 (2019), https://www
.chicagofed.org/publications/profitwise-news-and-views/2019/small-business-performance-inindustries-in-lmi-neighborhoods-after-the-great-recession.
10. Federal Reserve Banks, Small Business Credit Survey: 2019 Report on Employer Firms
(April 2019), https://www.fedsmallbusiness.org/medialibrary/fedsmallbusiness/files/2018/sbcsemployer-firms-report.pdf.
11. The Center for Financial Services Innovation found that “limited availability of bank
microloans means that many…seek credit from alternative sources, such as the quickly growing
Marketplace Loan segment or Merchant Cash Advances. Others turn to sources of credit intended
for personal use.” In addition, 49 percent of small business owners used personal credit cards for
business purposes. See the “2016 Financially Underserved Market Size Study,” https://www
.finhealthnetwork.org/wp-content/uploads/2016/11/2016-Financially-Underserved-Market-SizeStudy_Center-for-Financial-Services-Innovation.pdf.
12. See https://www.bloomberg.com/graphics/2018-confessions-of-judgment/ and https://
www.urban.org/sites/default/files/alfresco/publication-pdfs/410935-Analysis-of-Alternative-Financial
-Service-Providers.pdf.
13. See “Banking and Poverty: Why the Poor Turn to Alternative Financial Services,” Berkeley
Economic Review (April 15, 2019), https://econreview.berkeley.edu/banking-and-poverty-why-thepoor-turn-to-alternative-financial-services/.
14. See “Average Small Business Loan Interest Rates in 2019: Comparing Top Lenders,”
ValuePenguin (web page), https://www.valuepenguin.com/average-small-business-loan-interestrates.
15. Federal Reserve Banks, Small Business Credit Survey: 2019 Report on Employer Firms.

November 2019

Figure 1. Average number of financial service providers by income level of
zip code
5.0

Banks

AFS providers

Credit unions

4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5

Upper
Upper-middle
Lower-middle
Lowest

0.0
2008 2010 2012 2014 2016 2018

2008 2010 2012 2014 2016 2018

Note: “Average number of financial institutions” includes main and branch locations. Only zip codes with
an associated geographic area are included in the analysis.
Source: Federal Deposit Insurance Corporation, Summary of Deposits, Branch Office Deposits for June
of given year; National Credit Union Administration, Call Report Quarterly Data for June of given year
except 2010 and 2013, where September data were used due to data unavailability; U.S. Census Bureau,
2007 through 2016 County Business Patterns Complete ZIP Code Industry Detail Files; and U.S. Census
Bureau, 2013–17 American Community Survey 5-Year Estimates, Table S1901.

To examine the impact of bank consolidation on local access to financing, we
segment zip codes into quartiles based on their median household income.16
We find differences in banking access between low- and upper-income
communities post-2008, a continuation of differences that existed in 2008.
Low-income zip codes continue to have the fewest number of bank branches
and greatest number of AFS providers, on average, among income groups.
Figure 1 illustrates that the average lower-income zip code had 2.0 banks in
2018 (down from 2.3 banks in 2007), the fewest among the income quartiles.
Lower-income zip codes also had 1.2 AFS providers on average in 2016, the
greatest among income quartiles, and 0.5 credit unions in 2018. In contrast, the

16. Zip code median household income retrieved from U.S. Census Bureau, 2013–17 American
Community Survey 5-Year Estimates, Table S1901. Only zip codes in the 50 U.S. states and the
District of Columbia were included in the quartiles.
The lowest income quartile includes all zip codes with at most $41,563 in median household
income; the lower-middle-income quartile includes all zip codes with between $41,564 and
$51,964 in median household income; the upper-middle-income quartile includes all zip codes with
between $51,965 and $65,981 in median household income; and the upper-income quartile
includes all zip codes with at least $65,982 in median household income. It is important to note that
the quartiles are not analogous to the FFIEC’s classifications of neighborhoods by income—low,
moderate, middle, and upper—which are calculated as a comparison between the census tract
and associated metropolitan area. Quartiles presented here are also not weighted by population.

Consumer & Community Context

average upper-income zip code had 4.3 banks in 2018 (down from 4.5 banks in
2007 and 4.6 banks in 2009), the greatest bank average among income
quartiles. Upper-income zip codes also had, on average, 0.7 AFS providers in
2016, the fewest among income quartiles, and 0.7 credit unions in 2018.

Both lower- and upper-income
zip codes had similar
per-business bank densities.
However . . . lower-income zip
codes have a higher ratio of
costly AFS providers to small
businesses than upper-income
zip codes.

While these differences are notable, it is important to consider bank and AFS
densities in proportion to the density of small businesses located in
low-/moderate- and middle-/upper-income areas. Considered from this
perspective, we find that each zip code income quartile has 0.01 banks per
small business. That is, both lower- and upper-income zip codes had similar
per-business bank densities. However, it is equally important to highlight that
lower-income zip codes have a higher ratio of costly AFS providers to small
businesses than upper-income zip codes. As previously mentioned, small
businesses often turn to potentially higher cost, alternate providers if they are
turned down by traditional sources for financing.
The zip codes in the lowest income quartile have 0.007 AFS per small business,
whereas the zip codes in the upper-income quartile have 0.002.17 Over time, the
ratio of banks to AFS providers in low-income areas has declined and is the
lowest among income quartiles. In real terms, this means that low-income areas
have experienced relative growth in more expensive financing channels.

Bank Loans under $1 Million to Businesses, by Business
Location
LMI areas accounted for just 23 percent of bank small business loans in 2017;
this figure is proportionate to the number of small businesses in those areas. As
shown in figure 2, small business loan volumes across income categories have
grown since 2010, the low point for small business lending. In fact, the growth
rate in business loans under $1 million, a proxy for small business lending,
between 2010 and 2017 was highest in LMI areas—165 percent in low-income
areas and 90 percent in moderate-income areas, compared to 34 percent in
middle-income areas and 61 percent in upper-income areas.18

17. The ratio of AFS providers to small businesses by zip code income quartile are: 0.007 for
lowest-income zip codes, 0.005 for lower-middle-income zip codes, 0.003 for upper-middleincome zip codes, and 0.002 for upper-income zip codes. Number of small businesses by zip code
sourced from U.S. Census Bureau, 2016 County Business Patterns Complete Zip Code Industry
Detail File. Only zip codes with an associated geographic area are included in the analysis.
18. Loans under $1 million are a useful proxy for small business lending, since this characterizes
the majority of small business loan demand; see Federal Reserve Banks, Small Business Credit
Survey: 2019 Report on Employer Firms. Growth rate is computed as the change between 2010
and 2017 and is not annualized.

November 2019

Figure 2. Number of small loans to businesses by FFIEC income designation
of business’s census tract (Loans under $1M)
8

Millions

7
6
Upper

5
4
3
Middle

2
1
0

Moderate
Low

2009

2010

2011

2012

2013

2014

2015

2016

2017

Source: Federal Financial Institutions Examination Council (FFIEC) Community Reinvestment Act lending
data, National Aggregate Reports.

Though possibly surprising, this is likely because low- and moderate-income
areas began the period with such a low level of loans that a similar investment
level as that in higher-income areas is a larger percentage. These results may
also reflect gentrification trends in lower-income areas.

Areas for Future Research
These findings shed light on the challenges that small businesses in
lower-income areas face in accessing affordable financial services. Bank branch
consolidation as well as the growth of costlier AFS providers and their sizeable
presence relative to business density are trends that, on average, could raise
borrowing costs for small businesses. While this article focuses on proximity to
different brick-and-mortar financial services, we do not examine the extent to
which capital availability is matched with the amount or type of capital that
businesses are seeking. Future research should examine how these supply
factors interact with business-specific demand factors to influence loan access
and affordability in low-income communities.

Board of Governors of the Federal Reserve System
www.federalreserve.gov
1119

Full text of Consumer and Community Context : Vol. 1, No. 2

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