Too Small to Collect Big Data: Financial Inclusion Implications




January 27, 2021
Too Small to Collect Big Data: Financial Inclusion Implications
Congress has demonstrated an ongoing interest in
insured banks and credit unions that originate fewer than
promoting financial inclusion (i.e., increasing the access of
100 closed-end mortgage loans in either of the two
traditionally underserved populations and markets to
preceding calendar years no longer need to report such data
affordable financial services and products). The concept of
effective July 1, 2020. (The previous threshold was set at 25
financial inclusion has evolved to include the adoption of
closed-end loans.) The permanent threshold for reporting
digital technologies, which can enhance the effectiveness of
data about open-end lines of credit was also set at 200
regtech—the use of technology by both regulators and
open-end lines of credit effective January 1, 2022
regulated entities to facilitate compliance with applicable
(following expiration of the temporary higher threshold of
regulations and policy objectives. While regtech can be
500 open-end lines of credit that was increased from 100 in
used to monitor prudential financial (e.g., credit, liquidity,
2018). Going forward, HMDA data are likely to contain
interest rate) risks, it can also be deployed to analyze the
less information about mortgage lending, pricing practices,
circulation of financial products and services, thus
and characteristics of borrowers in rural areas.
monitoring the breadth of inclusiveness. Regtech relies
upon collecting and organizing digital data, which may be
Section 1071: Database for Women- and Minority-
costly for certain institutions—especially those that serve
Owned Small Business Credit
predominantly customers facing appreciable financial
On July 24, 2020, the CFPB released an Advance Notice of
challenges.
Proposed Rulemaking (ANPR) for Section 1071 of the
Dodd-Frank Act. Section 1071 requires financial
Regtech and Financial Risk Reporting
institutions to collect data pertaining to credit applications
U.S. depository institutions (i.e., banks and credit unions)
for women-owned, minority-owned, and small businesses.
have mandatory quarterly data reporting requirements,
The data would then be reported annually to the CFPB, thus
which allow regulators to monitor institutions’ financial
having some similar attributes to the HMDA database. The
health. Every quarter, banks and credit unions submit data
ANPR states that reporting requirements would not apply to
(referred to as call report data) to their primary regulators
small businesses that are not owned by women or
for aggregation and analysis. In September 2014, the Office
minorities, and they would not apply to women- and
of the Comptroller of the Currency (OCC) finalized
minority-owned businesses that do not meet the Small
guidance to heighten standards for the largest U.S. banks,
Business Administration’s definitions of small.
including the data aggregation and reporting capabilities
Consequently, a full understanding of how the experiences
that would be appropriate for their size, complexity, and
of women and minority firms that apply for small business
risk profiles as well as to support supervisory reporting
loans differ from other small firms looks to be more
requirements. Implementation of the necessary information
difficult without the ability to make extensive comparisons.
technology (IT) infrastructures reportedly still remains
The CFPB is also considering collection and reporting
challenging and costly for many large banks.
exemptions based on either a size-based or activity-based
threshold or both. Many small lenders have historically
Some Data Reporting Exemptions
been a primary funding source for small businesses and
For laws designed to monitor financial inclusion,
especially early-stage start-ups. Requiring data reporting
exemptions for data collection exist for certain entities and
from small lenders has challenges, which are discussed in
circumstances, namely depositories that are small or have a
the last section.
small footprint in a particular lending market, discussed in
the examples below.
Community Reinvestment Act (CRA)
The Community Reinvestment Act (CRA; P.L. 95-128) was
Home Mortgage Disclosure Act (HMDA)
enacted to encourage federally insured banks to meet the
The Home Mortgage Disclosure Act of 1975 (HMDA; P.L.
credit needs of the communities in which they accept
94-200) required originators to disclose mortgage
deposits. Since passage, restrictions on interstate banking
information to facilitate the monitoring of lending activity.
and branching were lifted, and online and mobile banking
The 2010 Dodd-Frank Wall Street Reform and Consumer
has increased. Thus, the federal bank regulators have
Protection Act (Dodd-Frank Act, P.L. 111-203) required the
focused on updating the current CRA regulatory framework
collection of credit scores under HMDA. Using its
to incorporate banking activities that occur outside of
discretionary authority to carry out the purposes of HMDA,
geographical boundaries.
the Consumer Financial Protection Bureau (CFPB) also
required some additional data collection. However, the
While federal bank regulators typically engage in joint
2018 Economic Growth, Regulatory Relief, and Consumer
CRA rulemaking, the OCC on May 20, 2020, finalized its
Protection Act (P.L. 115-174) required the CFPB to
updated CRA framework, which aims to provide for more
implement certain statutory reporting thresholds. Federally
timely and transparent CRA-related data collection,
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Too Smal to Col ect Big Data: Financial Inclusion Implications
recordkeeping, and reporting. The OCC reported receiving
costs to collect, manage, and report digital data can be
numerous comments on proposed data collection,
significant given that IT systems can quickly become
recordkeeping, and reporting requirements. In response, the
outdated and require ongoing updating. (Greater reliance on
final rule accounts for the differences among the categories
cloud-based service providers may also be costly.)
of institutions to reduce the burden with regard to data
Moreover, the Federal Reserve Bank of St. Louis reports
collection and data integrity requirements. For example,
that underserved or higher-risk borrowers, typically located
banks with less than $2.5 billion in assets are generally
in areas with few financial institutions or branches, are
exempted from being evaluated under the newly adopted
likely to depend upon lenders already facing greater
CRA performance standards but may opt in. On September
liquidity and funding disadvantages due to lower
21, 2020, the Federal Reserve released an ANPR to obtain
transaction volumes or scale. In other words, financially
feedback on its tentative plans to update the CRA
weaker customers are more likely to be served by
framework for the entities it supervises. The Federal
institutions already facing cost disadvantages. Hence, if
Reserve also proposes to exempt small banks from certain
digitization is generally costly for large financial (and non-
new data collection requirements.
financial) firms, then it is likely very expensive for small
institutions with thinner profit margins.
Soft Information in a Regtech Age
Hard information refers to quantitative, standardized
Despite costs, the trend to use digital data by regulators and
information that is easier to collect and transmit and is
depository institutions to promote financial inclusion is
frequently summarized in the form of numerical metrics .
likely to continue given the overall net benefits. For
Hard information is generally conducive for automated or
example, regtech can be used to conduct CRA and fair
algorithmic machine underwriting, using computerized
lending compliance examinations. (Fair lending
scoring methods to evaluate and set loan prices for higher-
examinations are used to enforce compliance with the
credit-quality borrowers. For depositories with business
nondiscriminatory requirements of the 1974 Equal Credit
models that already rely on digital technologies and hard
Opportunity Act [P.L. 94-239] and the 1968 Fair Housing
information, compliance with regtech data reporting
Act [P.L. 90-284]). Larger banking institutions also have
requirements is less costly.
the resources to adopt third-party software designed to
identify and reduce the risk of CRA or fair lending
By contrast, soft information is qualitative in nature and
violations. These technologies can efficiently reduce
usually compiled for manual underwriting, which is a labor-
compliance costs for both depositories and their regulators.
intensive method used to evaluate and set loan prices,
In addition, more data fields reported under HMDA along
typically for customers with weak or non-existent credit
with data collected by the U.S. Census Bureau and the
histories. The inability to convert applicants’ financial
Social Security Administration allow the federal depository
histories into digital credit scores increases the difficulty to
regulators to use geocoding techniques to better identify
predict comparable loan repayment behaviors. Hence, when
banking deserts, which typically refers to areas with no
consumer or business credit applicants lack numeric credit
physical financial institutions such as a credit union, bank,
scores (i.e., credit invisible), lenders must take more time
or branches. The NSCB reports that electronic data
and effort to verify and document the financial information.
submissions of loan data to regulators can increase the
For small businesses that accept only cash rather than
efficiency of examinations by allowing more pre-
electronic or digital forms of payment when conducting
examination work to be conducted off site, which saves
transactions with their local customers, prospective lenders
time and has grown in importance in the Coronavirus
may require in-person interviews with applicants to gather
Disease 2019 (COVID-19) pandemic.
specific details about their extenuating circumstances.
These businesses might also require assistance with
If underserved populations, small depositories, or both are
recordkeeping and providing accurate financial statements,
more likely to generate soft information when participating
thus becoming an even more labor- and paper-intensive
in financial transactions, then some options may be possible
process for prospective lenders. In these situations, lenders
to support these data collection efforts. For example,
use soft information and their personal assessments to make
multiple regulators may coordinate their data requests for
lending decisions rather than automated technologies.
multiple purposes such as for both Section 1071 and CRA
reporting. Small depositories could send soft information to
Data reporting exemptions for small banks and credit
their primary regulators, which may have the resources to
unions do not eliminate the need for them to collect
convert into digital form. Regulators may consider
information. Soft information still provides informative
encouraging larger depositories to form partnerships with
insights, even though it is not in digital format and takes
small depositories to digitize their data. Even if digital
more time to collect and disseminate to regulators during
reporting improvements are made for some regulated
on-site examinations. According to the National Survey of
depositories, data gaps may still persist if non-depository
Community Banks (NSCB), small bankers still place value
firms have data that are not submitted to prudential
on having examiners on site, which can help better convey
regulators or the CFPB. New questions and market
idiosyncrasies unique to the operating environments where
developments will emerge no matter the amount of reported
their banks provide financial services.
hard information. Soft data collected in non-digital forms
(e.g., interviews, surveys, and focus groups), therefore, will
Despite taking greater time and effort to make frequently
remain necessary to gain insights into ongoing efforts to
riskier and smaller loans, the use of soft information is still
support financial inclusion.
a less costly and more viable option for small lenders. The
Darryl E. Getter, Specialist in Financial Economics
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Too Smal to Col ect Big Data: Financial Inclusion Implications

IF11742


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