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EPR

FEDERAL RESERVE BANK OF NEW YORK

ECONOMIC POLICY REVIEW

Complexity in
Large U.S. Banks

Linda Goldberg and April Meehl

Volume 26, Number 2
March 2020

Complexity in Large
U.S. Banks
Linda Goldberg and April Meehl

OVERVIEW

• Bank size and complexity
were identified as determinants
of systemic importance following the global financial crisis.
Research has shown that big
U.S. banks have not shrunk
in size since then. This article
explores the evolution of the
complexity—organizational,
business, and geographic—of
U.S. banking organizations over
the period from 2007 to 2017.
• Organizational complexity,
or the number of legal entities
within a bank holding company
(BHC), has decreased as the
number of entities within the
most complex BHCs has fallen.
• Business complexity,
capturing the scope and concentration of industries across
BHCs, has shifted more than it
has declined, especially within
the financial sector; nonfinancial entities within U.S. BHCs
continue to tilt heavily toward
real estate–related industries.
• Geographic complexity has
decreased as fewer large BHCs
have global affiliates and the
geographic span of the most
complex has declined.

Federal Reserve Bank of New York

n the wake of the global financial crisis, the Dodd-Frank
Wall Street Reform and Consumer Protection Act of
2010 (hereafter called Dodd-Frank) identified bank size and
complexity as determinants of systemic importance, with
both features viewed as contributing to risks to financial
stability. Since Dodd-Frank, big U.S. banks have not shrunk
in size (Cetorelli and Stern 2015; Avraham, Selvaggi,
and Vickery 2012; Goldberg and Meehl 2018). In this article,
we ask if U.S. banking organizations have decreased in
complexity in the decade since the global financial crisis.
This new evidence on the evolving complexity of large
U.S. BHCs compares 2007 with 2017.
As a starting point, we note that the complexity of bank
holding companies (BHCs) cannot be well-captured by a
single metric. The system established to address global
systemically important banks1 views complexity as a combination of balance-sheet and derivatives exposures and the
number of distinct legal entities within the BHC. High levels
of these components are associated with balance-sheet
opacity and greater difficulty in valuing asset portfolios and
exposures when BHCs fail.2 We instead focus exclusively on
U.S. BHC structural complexity, using information on all
legal entities under the umbrella of each BHC conglomerate.
Our work builds on earlier contributions to understanding

Linda Goldberg is a senior vice president and April Meehl a former research analyst at the
Federal Reserve Bank of New York. Email: linda.goldberg@ny.frb.org; aimeehl@wisc.edu.
The views expressed in this article are those of the authors and do not necessarily reflect
the position of the Federal Reserve Bank of New York or the Federal Reserve System.
To view the authors’ disclosure statements, visit https://www.newyorkfed.org/research
/epr/2020/epr_2020_bank-complexity_goldberg.

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Economic Policy Review, 26, no. 2, March 2020

Complexity in Large U.S. Banks

the structure and size of U.S. BHCs by Avraham, Selvaggi, and Vickery (2012) and Cetorelli,
Jacobides, and Stern (2017) and of global organizations by Cetorelli and Goldberg (2014) and
Carmassi and Herring (2010). We consider both existing and new measures that cover organizational, business, and geographic complexity. We also look more in depth at the industries
and geographies of BHC subsidiaries. Our discussion zooms in on the changes that have
occurred in complexity from 2007, just prior to the global financial crisis, to ten years later.
This period encompasses both the crisis and the implementation of reforms such as
Dodd-Frank and guidance around “living wills,” and beyond.
We use the term “organizational complexity” to refer to the number of separate legal
entities within a BHC, relevant for understanding why banks choose to be complex and how
larger numbers contribute to higher resolution and systemic costs if a BHC fails. The term
“business complexity” is used to capture the scope and concentration of businesses and
industries across these legal entities. Finally, the term “geographic complexity” captures the
domestic versus international locations of these entities, using information on their span and
dispersion across countries.3
Comparing measures of organizational, business, and geographic complexity over the
2007-17 period for the largest U.S. BHCs, we conclude that BHCs have seen mixed outcomes when it comes to simplifying their organizations. Large BHCs remain very complex
across organizational, business, and geographic dimensions. Nonetheless, the most organizationally complex have reduced the number of legal entities within their conglomerates
and, in some cases, reduced the number of countries in which they have affiliates. The
number of broad businesses spanned within BHCs has remained similar across time,
while the industries spanned by entities within the BHCs have shifted more than they
have declined, especially with respect to the financial industry breakdown. The nonfinancial entities within U.S. BHCs continue to tilt heavily toward real estate–related industries.
Many of these subsidiaries are vehicles for community housing investments. Research has
also shown that BHC performance tends to improve following expansion into financial
businesses that were not previously the BHCs’ points of focus (Cetorelli, Jacobides, and
Stern 2017).
The number of large U.S. BHCs that have entities in foreign locations declined modestly in
the decade following 2007. For those that remain global, geographic complexity is somewhat
reduced. The large BHCs that have entities in a variety of countries also tend to have a significant share of those affiliates in locations associated with favorable tax regimes. The continued
prominence of countries considered low-tax locations stands in marked contrast to the
reduced prominence of affiliated entities in some emerging markets and informationally
opaque locations. Many of the nonbank foreign subsidiaries of U.S. BHCs are concentrated in
the United Kingdom and the Cayman Islands, while specific industries, such as insurance and
real estate, have higher shares of subsidiaries in other locations.
The measures of BHC organizational, business, and geographic complexity are presented in
Section 1 of this article. Section 2 compares the evolution of complexity across the fifty largest
U.S. BHCs by using observations from 2007 as a pre-crisis snapshot and those from 2017 as a
post-crisis snapshot. In Section 3, we delve more deeply into the business complexity of BHCs
and provide details on the evolution of the scope of those legal entities, specifically within the
financial services and nonfinancial sectors. We present a similar exercise in Section 4, looking
at locations of foreign affiliates and their patterns across advanced economies, emerging
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Complexity in Large U.S. Banks

markets, tax havens, and financial secrecy locations. We also describe the pattern of locations
of subsidiaries operating in specific industries.
Section 5 concludes with observations about the current complexity landscape, noting some
potential drivers of this landscape. Regulators have clearly signaled that complexity should be
reduced (Haldane 2015). The main argument for this view is that greater complexity, all else
equal, can contribute to agency problems and make a failing bank harder to resolve, adding to
systemic risk and the “too complex to fail” problem. Within Dodd-Frank, efforts to reduce
complexity include the requirement that large BHCs periodically submit resolution plans, also
known as living wills. So far, the dominant forms of change have been in the number of legal
entities, without wholesale reductions in scope or dispersion. Yet the overall implications for
types of BHC risk are not well understood, since diverse business lines and activities across
countries can add value, synergies, diversification benefits, and efficiencies. Additional
research is needed to further understand these important consequences of organizational,
business, and geographic complexity.

1. Defining and Measuring Complexity
Many BHCs are corporate conglomerates with significant ownership positions or controlling
interests in a range of legal entities (which we alternatively refer to as affiliates or subsidiaries)
that can span bank and nonbank activities. As in the complexity measures of Cetorelli and
Goldberg (2014), we use information on the structure, number, location, and industry type of
bank and nonbank affiliates under each BHC. The core data set for our analysis is a complete
and time-consistent panel of legal entities within all existing U.S. BHCs, created using Federal
Reserve form FR Y-6 and FR Y-10 filings, described in Cetorelli and Stern (2015) and updated
quarterly. (Form FR Y-6 is the means by which BHCs file their annual reports; each contains a
subsidiary organizational chart. Form FR Y-10 is filed when a BHC changes its organizational
structure.) Each affiliate within a BHC is coded with information on its primary industry, captured by one of 203 four-digit North American Industry Classification System (NAICS) codes,4
and its country location.
Respective complexity metrics—organizational, business, and geographic—rely on counts of
legal entities in each BHC. These counts are combined in various ways to explore different business or industry types, international versus U.S. locations of entities, and the dispersion of entities
across the respective component. Implicit in the notation we use for complexity indexes at the
level of the BHC is that an index is both BHC- and time-specific; we only include subscripts to
distinguish the number and characteristics of the legal entities within each BHC.
The most basic measure of complexity and the only measure in the organizational complexity category is the total number of legal entities within the BHC, or Count.
Measures of business complexity use information on the industries and businesses of entities within the ownership structure of each BHC. These measures are alternatively constructed
as counts or as Herfindahl-type indexes normalized and defined to take values between 0 and 1,
and they increase in the dispersion of activities within the BHC. Nonfinancial count share is the
share of legal entities that are not in the more broadly defined financial sector (two-digit
NAICS code 52). CountN is the number of four-digit NAICS industries spanned by the legal
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Complexity in Large U.S. Banks

entities in the BHC. Industry type is indexed by i, or summed over every i for a BHC at a date
and denoted by I. CountB is the total number of business types (maximum six) spanned by
BHC affiliates, where we define business types as Banking, Insurance, Mutual and Pension
Fund, Other Financial, Nonfinancial Management Firms, and Other Nonfinancial.5 The dispersion of affiliate business types within the BHC and across its legal entities is given by a
countb 2
CountB
modified Herfindahl-type index, with BHHI = ________
CountB
(1 -ΣbϵB (_______
Σ count
), where B is
-1
bϵB
b
the set of business types, and countb is the number of a BHC’s subsidiaries that are classified in
accordance with each business type b. These measures take a value of zero if all entities are in
banking and increase as the dispersion of entities across types of businesses rises.
Geographic measures begin with an indicator created to identify banks that hold at least
one foreign-located subsidiary, HasForeign. This metric takes a value of 1 if the BHC has any
affiliates in foreign locations and is 0 otherwise. Geographic location is denoted by country c,
and the sum over all locations is denoted by C, which takes a minimum value of 1 if all affiliates of the BHC are situated within the U.S. Other measures include the count of countries
spanned by the affiliates CountC , and a Herfindahl-Hirschman index of location dispersion
countc
CountC
across countries indicated by CHHI = ________
CountC
(1 - ΣcϵC ( _______
Σ count
)2) where C is the set of
-1
cϵC
c
countries and countc is the count of a BHC’s subsidiaries in each country c. CHHI is 0 when all
of the BHC’s legal entities are within the United States and increases as the dispersion across
countries rises.6

2. Complexity Patterns in the Fifty Largest U.S. BHCs
Asset size and complexity are concentrated within the largest of the thousands of U.S. BHCs.
Accordingly, our exploration of the evidence for complexity begins with the BHCs that have
more than $1 billion in assets7 and have a U.S. top holder.8 The quarterly value of total BHC
assets and the number of U.S. domestic BHCs satisfying these criteria are shown in Chart 1 for
the period from 2007 through 2017. The red line and right scale show the total number of
these BHCs, which gradually increased from about 400 in 2007 to over 500 by 2017. Their
total assets rose from about $10 trillion in 2007 to $14 trillion by 2017 (left scale, upper grey
contour). The assets of the largest fifty of these BHCs in each quarter, shown by the blue
shaded bars, represent over 85 percent of the overall BHC assets. As complexity is also concentrated in the largest BHCs, below we focus solely on the largest fifty BHCs and compare
complexity pre-crisis (2007) with that of a decade later (2017).

2.1 Broad Patterns in BHC Complexity
Patterns in complexity across the fifty largest U.S. BHCs are presented in summary form in
Table 1, which provides the minimum, median, mean, and maximum values of each complexity metric in the second quarter of 2007 and the second quarter of 2017. On balance, compared
to the pre-crisis date, by 2017 the largest U.S. BHCs tended to simplify in organizational, business, and geographic complexity while nonetheless increasing in size. While average BHC
assets increased from 2007 to 2017, this increase in size was driven mainly by the largest of the
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Complexity in Large U.S. Banks
Chart 1

Total Assets and Number of BHCs Larger Than $1 Billion: 2007:Q2 to 2017:Q2
Assets of U.S. BHCs > $1 billion (left scale)
Assets of fifty largest U.S. BHCs (left scale)
Number of BHCs in sample (right scale)
Trillions of dollars

Number of BHCs

550

500

12
450

10
400
2007:Q1

2009:Q3

2012:Q1

2014:Q3

2017:Q1

Source: Federal Reserve Board, Consolidated Financial Statements of Bank Holding Companies (FR Y-9C
data).
Notes: Figures are based on FR Y-9C filings of U.S.-owned BHCs with assets over $1 billion. Asset totals and
BHC counts exclude Goldman Sachs, Morgan Stanley, American Express, CIT Group, Ally Financial, Discover
Financial Services, and MetLife.

large BHCs. The average number of legal entities within a BHC declined from 232 to 189,
demonstrating a clear decline in organizational complexity despite increases in BHC assets.
The changes in organizational, business, and geographic complexity between 2007 and 2017
are spread more broadly across the fifty largest BHCs.
Declines in business and geographic complexity are less pronounced than those observed
for organizational complexity. On average, the fifty largest BHCs maintained five of the six
business types, and marginally reduced the number of NAICS industries spanned by their
affiliated entities (by two). The average share of nonfinancial subsidiaries increased only
slightly between 2007 and 2017, from 38 percent to 40 percent. The share of BHCs with any
foreign affiliates declined from 58 percent to 54 percent, implying that twenty-seven instead
of twenty-nine of the fifty largest BHCs had affiliates in foreign locations. The average
number of country locations spanned by these affiliates remained between seven and eight
with a dispersion rate near 18 percent.
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Complexity in Large U.S. Banks
Table 1

Summary Statistics of Complexity Variables
2007:Q2
Min

Median

Min

Median

11.61

37.41

178.19 2,220.87

19.53

34.10

251.94 2,563.17

5.00

59.50

231.68 2,834.00

4.00

39.00

189.48 1,258.00

Nonfinancial count share

0.05

0.36

0.38

0.92

0.05

0.38

0.40

0.97

CountB

4.00

5.00

5.14

6.00

3.00

5.00

4.88

6.00

BHHI

0.24

0.86

0.83

0.99

0.09

0.83

0.77

1.00

CountN

5.00

13.00

13.56

33.00

4.00

10.00

11.52

29.00

Has foreign

0.00

1.00

0.58

1.00

0.00

1.00

0.54

1.00

CountC

1.00

2.00

7.94

80.00

1.00

2.00

7.42

69.00

CHHI

0.00

0.06

0.18

0.84

0.00

0.03

0.17

0.81

BHC assets (billions of dollars)

Mean

2017:Q2
Max

Mean

Max

Organizational
Count
Business

Geographic

Sources: Authors’ calculations based on Federal Reserve Board, Consolidated Financial Statements of Bank
Holding Companies (FR Y-9C data), Annual Report of Holding Companies (FR Y-6 data), and Report of
Changes in Organizational Structure (FR Y-10 data).
Notes: Units are as follows: Count is the total number of legal entities in the BHC; Nonfinancial count share
and Has Foreign are share of legal entities; CountB is the total number of business types; BHHI (dispersion
of business types) and CHHI (dispersion across countries) use a scale of 0-1; CountN is the total number of
four-digit NAICS codes; CountC is the total number of countries.

The two most organizationally complex BHCs in 2007 held 2,834 and 1,900 subsidiaries,
respectively.9 By contrast, the most complex BHC in 2017 held 1,258 subsidiaries. The number of
subsidiaries within the top ten BHCs contrasts sharply with counts in the bottom forty. Business
complexity patterns are less differentiated. The count of unique four-digit NAICS codes by BHC
size rank shows a generally decreasing pattern as asset size declines. The number of NAICS codes
within BHCs tended to decline from 2007 to 2017, especially among the largest BHCs.
Asset size and complexity are correlated but not comparable statistics across U.S. BHCs.10
Chart 2 shows the relationship between BHC total affiliate count and assets in 2007 (blue dots)
and in 2017 (red dots). The positive slopes of the solid fitted lines show that larger BHCs tend
to have more legal entities within their organizations. The rightward shift of the line over data
for the second quarter of 2017 shows that BHC assets are larger post-crisis and entity counts are
smaller, given BHC asset size, in 2017 compared with 2007. Every vertical slice of this chart,
regardless of whether we use information from 2007 or 2017, shows the substantial diversity in
organizational complexity as represented by numbers of legal entities and conditional on size.
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Complexity in Large U.S. Banks
Chart 2

Organizational Complexity versus Assets for the Fifty Largest BHCs: 2007 and 2017

2007:Q2
Log total affiliate count

2017:Q2

Total affiliate count

2,980

403

2
16 [8,886]

18 [65,659]

20 [485,165]

22 [3,584,912]

Log assets (thousands of dollars)

Only some forms of complexity are highly correlated with BHC size or with each other, as
shown by the Pearson correlations presented in Table 2. The broad patterns by size are further
illustrated in Chart 3. At each date, BHCs are sorted into quintiles by size, with quintile 1
capturing the ten largest BHCs and quintile 5 the ten smallest BHCs among this top fifty
group. The panels provide box-and-whisker representations of the distribution of the complexity variable within the sample of BHCs and across dates. The larger BHCs tend to have more
affiliates that span more industries and more countries. However, size is not strongly correlated
with the dispersion of these affiliates across businesses or across locations. When the number
of businesses expands, the dispersion of businesses tends to fall. The dispersion of business
types, BHHI, is negatively correlated with all other complexity variables. There is little correlation between Nonfinancial count share and numbers of businesses and countries of affiliates.
When a BHC adds more nonfinancial subsidiaries, these tend to be either domestic or in
existing foreign locations, business types, and industries. Comparing pre- and post-crisis, the
declines in counts of industries spanned and country locations were particularly concentrated
in the largest quintiles of U.S. BHCs.
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Complexity in Large U.S. Banks
Table 2

Pearson Correlation of Complexity Metrics of Largest U.S. BHCs, 2017

Complexity Metric
BHC assets

BHC
assets

Count

Nonfin
count
Has
share CountB BHHI CountN foreign CountC CHHI

Organizational
Count

0.76

Nonfinancial count share

0.03

0.27

CountB

0.49

0.53

0.24

BHHI

-0.22

-0.59

-0.30

-0.27

CountN

0.81

0.74

0.21

0.75

-0.34

Has foreign

0.36

0.47

0.15

0.40

-0.43

0.50

CountC

0.84

0.78

-0.02

0.56

-0.23

0.83

0.47

CHHI

0.44

0.41

-0.20

0.47

-0.18

0.54

0.69

Business

Geographic

3. Business Complexity and BHC Affiliate Scope
BHCs have long operated in sectors outside of banking, including other financial and
nonfinancial industries. Drivers and consequences of the decision to expand into or
leave these industries are a ripe topic for research. For example, Cetorelli and Wang (2016)
emphasize that growth of the BHCs’ community housing affiliates has occurred to
support obtaining Community Reinvestment Act credits and Low-Income Housing Tax
Credits, and Cetorelli, Jacobides, and Stern (2017) find that BHCs saw improved performance on average when they altered their scope to resemble that of the modal BHC.
Some BHCs may have first expanded into particular industries in order to seize opportunities to reallocate capital, bring production in-house, or create synergies from
combining activities, for example. Other BHCs then diversified similarly to replicate the
new modal structure.
Below, we highlight the key changes BHCs have made in their industrial composition
from 2007 to 2017, looking separately at financial and nonfinancial affiliates. We document
both trends and differences across BHCs. We observe that most BHCs have not decreased
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Complexity in Large U.S. Banks
Chart 3

Complexity of the Fifty Largest BHCs by Asset Size Quintile in 2007 and 2017
2007:Q1
(Log) Assets

2017:Q2

Count

BHC Assets

3,000

2,000

1,000

Affiliate Count

Asset quintile
CountC
80

Asset quintile
Country Count

CountN
40

NAICS Code Count

0
1

3
4
Asset quintile

Sources: Authors’ calculations based on Federal Reserve Board, Consolidated Financial Statements of Bank
Holding Companies (FR Y-9C data), Annual Report of Holding Companies (FR Y-6 data), and Report of
Changes in Organizational Structure (FR Y-10 data).
Notes: Box-and-whisker plots represent the distribution of the complexity metric for BHCs falling into each
quintile of the size distribution of the largest fifty BHCs as determined by BHC assets. Asset quintile 1
represents the ten largest BHCs. The upper and lower whisker values represent 1.5 times the interquartile
range above and below the 75th and 25th percentile, respectively. Values outside of the upper and lower
whiskers are shown with dots. Count is the total number of legal entities in the BHC. CountC is the count of
countries spanned by the affiliates; CountN is the number of four-digit NAICS industries spanned by the legal
entities in the BHC.

their industry scope since 2007; instead, they have shifted their concentration across
industries. Correa and Goldberg (2019) show that BHCs’ idiosyncratic and liquidity risk
exposures decrease with organizational complexity and geographic scope, which may also
be providing diversification gains.

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Complexity in Large U.S. Banks
Chart 4

Share of Commercial Banks in Total Financial Affiliates by BHC Asset Size Quintile
2007:Q2

2017:Q2

Share of commercial banks

0.8

0.6

0.4

0.2

0
1

Asset quintile

Sources: Authors’ calculations based on Federal Reserve Board, Consolidated Financial Statements of Bank
Holding Companies (FR Y-9C data), Annual Report of Holding Companies (FR Y-6 data), and Report of
Changes in Organizational Structure (FR Y-10 data).
Notes: Box-and-whisker plots represent the distribution of the share of commercial banks for BHCs falling
into each quintile of the size distribution of the fifty largest BHCs as determined by BHC assets. Asset quintile
1 represents the ten largest BHCs. The upper and lower whisker values represent 1.5 times the interquartile
range above and below the 75th and 25th percentile, respectively. Values outside of the upper and lower
whiskers are shown with dots.

3.1 Financial Entities
Only a small fraction of the legal entities within BHCs are commercial banks, even if these
entities account for a large share of BHC total assets. The share of commercial banks in the
financial entities of BHCs ranges from less than 1 percent to around 20 percent, both pre- and
post-crisis. As shown in Chart 4, which depicts the top fifty BHCs sorted by size into quintiles
at 2007 and again at 2017, that share changed in idiosyncratic ways across BHCs. The majority
of their subsidiaries fall into the category of “Other Financials” (Table A1).
In the past decade, large U.S. BHCs have shifted the composition of their financial subsidiaries away from bank intermediaries (Chart 5). There has been a large increase in subsidiaries
classified as portfolio management, with three large BHCs more than tripling their share of
affiliates in portfolio management from 2007 to 2017. The largest five BHCs’ average share
of portfolio management affiliates is over 40 percent. Also increasing was the share of
financial subsidiaries involved in “other securities activities,” defined as the catch-all for
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Chart 5

Share of Type of Financial Affiliates in Total Financial Affiliates by BHC Asset
Size Quintile
2007:Q2
Share

0.8

Broker-Dealers

0.6

0.4

0.2

Mutual and Pension Funds

0
1

Asset quintile

Share
0.8

2017:Q2

Other Portfolio Management

Other Securities Activities

0.8

0.6

0.4

0.2

0
1

3
4
Asset quintile

0.8

Insurance

0.6

0.4

0.2

3
4
Asset quintile

Other Intermediaries

0
1

3
4
Asset quintile

Sources: Authors’ calculations based on Federal Reserve Board, Consolidated Financial Statements of Bank
Holding Companies (FR Y-9C data), Annual Report of Holding Companies (FR Y-6 data), and Report of
Changes in Organizational Structure (FR Y-10 data).
Notes: Box-and-whisker plots represent the distribution of the complexity metric for BHCs falling into each
quintile of the size distribution of the fifty largest BHCs as determined by BHC assets. Asset quintile 1
represents the ten largest BHCs. The upper and lower whisker values represent 1.5 times the interquartile
range above and below the 75th and 25th percentile, respectively. Values outside of the upper and lower
whiskers are shown with dots.

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Complexity in Large U.S. Banks

other financial investment activities but excluding activity categorized as relating to securities and commodity exchanges, portfolio management, and trust and custody activities.
The change in this share of BHC entities in “other portfolio management” is particularly
pronounced: One large BHC had a share greater than 50 percent in 2007 compared with
four BHCs in 2017 (Table A2). The decline in the share of other types of financial intermediaries is also clear: Five BHCs had shares of over 30 percent in 2007 compared with only
one in 2017. Insurance companies make up a greater proportion of financial affiliates for
the smaller BHCs both in 2007 and 2017.

3.2 Nonfinancial Entities
All of the large U.S. BHCs have nonfinancial subsidiaries. The biggest categories of nonfinancial subsidiaries tend to fall within the industries for housing, real estate, and
management companies (Table A3). The total share of nonfinancial entities within these
three categories rose significantly from 2007 to 2017, with considerable differences across
the BHCs. Management companies are the most popular nonfinancial affiliate type, with the
five largest BHCs holding an average share of all nonfinancial entities of around 30 percent
in both 2007 and 2017. Among the largest quintile of BHCs, the minimum share of housing
subsidiaries rose from 10 percent in 2007 to 25 percent in 2017. In terms of NAICS codes,
some housing entities (code 62422) replaced real estate–related entities (code 53), as the
average share of the latter decreased from 20 percent in 2007 to 13 percent in 2017.

4. Geographic Complexity
Comparing pre-crisis with post-crisis dates, two fewer BHCs among the fifty largest have
any foreign-located subsidiaries. The relationship between BHC size and the share of foreign
affiliates is positive, as geographic complexity is more prevalent in larger BHCs but still
highly differentiated even within size buckets among these large BHCs (Chart 6). While the
ten largest BHCs in 2017 had a greater foreign share in total entity counts than the ten
largest in 2007, some of this change stems from the larger reduction in domestically located
entities within BHCs, consistent with the BHCs’ broader decline in organizational complexity.
Many of the largest U.S. BHCs operated in fewer countries in 2017 than in 2007, another
sign of reduced geographic complexity. In 2017, 45 percent of bank entities were outside the
United States, up from 34 percent in 2007 (Table 3). Substantially higher shares of mutual
and pension funds, and a lower share of insurance entities, are now located outside the
United States.
The locational choices of the foreign banking subsidiaries and branches of global banks
have long been the subject of academic research and debate.11 These choices have been linked
to international trade in goods and services, country and institution growth rates, and comparative advantage in bank and country productivity rates. The post-crisis period has seen
noteworthy waves of contraction in cross-border bank lending volumes, especially in
bank-to-bank transactions (Milesi-Ferreti and Tille 2011). Overall, global activities have also
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Complexity in Large U.S. Banks
Chart 6

Share of Foreign Affiliates versus Assets for the Fifty Largest BHCs: 2007 and 2017
Sources: Authors’ calculations based on Federal Reserve Board, Consolidated Financial Statements of Bank

2007:Q2

2017:Q2

Share of foreign affiliates
0.8

0.6

0.4

0.2

0
16 [8,886]

18 [65,659]

20 [485,165]

22 [3,584,912]

Log assets (thousands of dollars)
Holding Companies (FR Y-9C data), Annual Report of Holding Companies (FR Y-6 data), and Report of
Changes in Organizational Structure (FR Y-10 data).
Notes: Observations represent the fifty largest BHCs by assets in 2007 and 2017. The values in brackets are
the total assets equivalent of log assets in U.S. dollars. The solid lines are linear regressions fitted by date.

been rebalanced toward banking systems that are better capitalized and toward nonbank
market-based financing (Avdjiev, Gambacorta, Goldberg, and Schiaffi, forthcoming). The
share of U.S. banks has risen around the world, even as fewer U.S. BHCs are involved.
Less attention has been paid to the other nonbank affiliates of these financial conglomerates, which dominate the absolute numbers of foreign affiliates within BHC conglomerates.
Location choices could be driven by factors similar to those for the bank affiliates. Additionally, the development of institutions and the size and depth of financial markets could
matter, along with potentially favorable tax treatment and the degree of opacity or secrecy
locally. Know-your-customer (KYC), anti-money laundering (AML), and compliance costs
for combating the financing of terrorism could also play a role, as such concerns have been
associated with the derisking of global banks and reduced activity in some foreign markets
(Erbenova et al. 2016).
We highlight some of these considerations by sorting the foreign affiliates of U.S. BHCs
according to location. The sort has two dimensions. First, it distinguishes between affiliates
within advanced economies (AEs) and those within emerging markets (EMs). Second, it
distinguishes locations that have low-tax jurisdictions or weak transparency/high secrecy,
using two indicators from the Financial Secrecy Index (FSI) of the Tax Justice Network:
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Complexity in Large U.S. Banks

Table 3

Share of Foreign Affiliates by Business Type
2007:Q2

2017:Q2

Banks

.34

.45

Insurance

.16

.10

Mutual and Pension Funds

.34

.54

Other Financial

.26

.29

Nonfinancial Management Firms

.33

.36

Other Nonfinancial

.07

.05

Sources: Authors’ calculations based on Federal Reserve Board, Annual Report of Holding Companies
(FR Y-6 data) and Report of Changes in Organizational Structure (FR Y-10 data).
Note: The table presents the share of foreign affiliates for each business type across all of the fifty largest
BHCs in 2007 and 2017.

Secrecy Score and Tax Credits.12 The secrecy score is calculated based on the average of
twenty different indicators. The score is equal to a percentage between 0 and 100, with 100
representing the greatest amount of secrecy (least transparency). The FSI metric of tax credits,
one of the twenty indicators used to create the secrecy score, focuses specifically on a country’s
level of promotion of tax evasion based on the existence of unilateral tax credits.13 The secrecy
score should capture at least some of the KYC and AML locations that have been the focus of
international bank derisking discussions.14
Table 4 provides a breakdown of the number of BHCs that have affiliates in foreign locations, in low-tax jurisdictions, and in high financial secrecy locations by BHC size quintile.
This table also illustrates the stark positive relationship between size and involvement in
low-tax and high financial secrecy locations. The number of BHCs in the top quintiles with
affiliates in low-tax jurisdictions was unchanged from 2007 to 2017, while the next quintile
registered a decrease. This second quintile also had fewer BHCs in high financial secrecy
locations. The shares of total foreign affiliates in these locations also changed. In 2007, the
median share of foreign affiliates in low-tax jurisdictions for BHCs in quintile 1 was 50 percent,
compared with 40 percent in 2017. For quintile 2, these shares were 42 percent and 27 percent,
respectively. Of the few BHCs with affiliates located in high financial secrecy locations, these
affiliates make up a very small share of their total foreign affiliates. In quintile 1, the median
share of foreign affiliates in these locations was 0.8 percent in 2007 and 0.6 percent in 2017.
Out of all BHCs in the top fifty, the maximum share of foreign affiliates in high financial
secrecy locations was 100 percent in 2007 and 50 percent in 2017.
Tables 5 and 6 provide a more detailed look at the evolution of affiliate locations, also considering the numbers in low-tax jurisdictions or high financial secrecy locations. In each table,
the upper panel provides the total count of BHCs out of the fifty largest BHCs with at least one
subsidiary located in advanced economies (AE) or emerging markets (EM). The lower panel
provides the count of all affiliates out of the total sample of affiliates held by the fifty largest
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Complexity in Large U.S. Banks

Table 4

Number of BHCs with Affiliates in High Financial Secrecy Countries and Low-Tax
Jurisdictions, by Asset Size Quintile

Quintile

2007:Q2

2017:Q2

High
Foreign
Low-Tax Financial
Affiliates Jurisdiction Secrecy

Sources: Authors’ calculations based on Federal Reserve Board, Annual Report of Holding Companies
(FR Y-6 data) and Report of Changes in Organizational Structure (FR Y-10 data).
Notes: The table presents the number of BHCs that have foreign affiliates in low-tax jurisdictions and high
financial secrecy countries, by asset quintile. The maximum number of BHCs in each quintile is ten.

BHCs that are located in advanced economies or emerging markets. Each panel further enumerates those entities in low-tax or high financial secrecy jurisdictions. Table 5 focuses on all
foreign affiliates, banks, and total nonbanks. Table 6 presents the disaggregation by nonbank
business type.
In the past decade, the fifty largest BHCs have shifted the balance of locations of their
foreign subsidiaries slightly toward advanced economies over emerging markets. Total counts
of foreign entities under large U.S. BHCs declined from 2007 to 2017. Bank affiliates significantly contracted in both AE and EM locations (Table 5). The total number of BHCs with
banking affiliates in AE locations declined from eleven to eight, while those in EMs remained
at only six BHCs out of the fifty largest. Within AEs, these declines were not only in the financial secrecy locations that have received attention around derisking. Indeed, the banking
affiliate declines were more substantial in low-tax jurisdictions than in jurisdictions with high
financial secrecy ratings. Among EMs, the Cayman Islands remain the most popular secretive
location for subsidiaries of large U.S. BHCs.
Among the foreign nonbank entities within U.S. BHCs, the number of BHCs declined in
both AE and EM locations, with declines in each type of EM location (Table 5). The number
of entities in AE low-tax jurisdictions increased from 291 to 300, but spanned a smaller
number of BHCs. Affiliates in secrecy locations remained stable. Entities in EM low-tax jurisdictions are far more prevalent than those associated with financial secrecy, but they still
declined substantially from 2007 to 2017. The largest share of nonbank affiliates is in “Other
Financial,” which covers activities such as other portfolio managers, broker-dealers, other
intermediaries, and other securities activities (Table A6). Foreign nonfinancial management
companies, which perform activities such as financial planning, billing, and recordkeeping,
and physical distribution, declined substantially in both AEs and EMs, outside of the secrecy
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Complexity in Large U.S. Banks

Table 5

Location of U.S. BHC Foreign Entities, by BHCs and Counts of Entities
A. By BHCs
Total Entities

Banking Entities

Nonbank Entities

2007

2017

2007

2017

2007

2017

All locations

Low-tax jurisdiction

High financial secrecy

All locations

Low-tax jurisdiction

High financial secrecy

In advanced economies

In emerging markets

B. By Affiliate Count
In advanced economies
All locations

1,378

1,222

1,338

1,196

Low-tax jurisdiction

302

307

291

300

High financial secrecy

All locations

884

741

824

698

Low-tax jurisdiction

531

442

514

432

High financial secrecy

In emerging markets

Sources: Authors’ calculations based on Federal Reserve Board, Annual Report of Holding Companies
(FR Y-6 data) and Report of Changes in Organizational Structure (FR Y-10 data).
Notes: The table presents the locational breakdown of U.S. BHCs and their affiliates. Table A7 lists the
countries in the low-tax jurisdiction and high financial secrecy categories.

locations of AEs and primarily declining in the EM low-tax locations. The rebalancing of
activity away from insurance affiliates and toward pension and mutual funds is again reflected
here, with the rise in mutual and pension funds largely occurring through affiliates in low-tax
jurisdictions in the decade after the financial crisis.

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Complexity in Large U.S. Banks

Table 6

Location of U.S. BHC Foreign Entities by Affiliate Type, by BHCs and Counts of Entities
A. By BHCs
Mutual Fund

Insurance

Other
Financial

Nonfinancial
Management

Other
Nonfinancial

2007

2017

2007

2017

2007

2017

2007

2017

2007

2017

All locations

Low-tax jurisdiction

High financial secrecy

All locations

Low-tax jurisdiction

High financial secrecy

In advanced economies

In emerging markets

B. By Affiliate Count
In advanced economies
All locations

885

793

239

220

165

Low-tax jurisdiction

205

193

High financial secrecy

All locations

448

445

153

115

162

Low-tax jurisdiction

271

277

109

High financial secrecy

In emerging markets

Sources: Authors’ calculations based on Federal Reserve Board, Annual Report of Holding Companies
(FR Y-6 data) and Report of Changes in Organizational Structure (FR Y-10 data).
Notes: The table presents the locational breakdown of U.S. BHCs and their affiliates. Table A7 lists the
countries in the low-tax jurisdiction and high financial secrecy categories.

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Complexity in Large U.S. Banks

5. Conclusion
The largest U.S. BHCs entered the global financial crisis with substantial organizational, business, and geographic complexity. We provide metrics of these forms of complexity for U.S. BHCs
covering pre-crisis and post-crisis dates. Organizational complexity, captured by the count of
legal entities within respective U.S. BHCs, tends to be higher for larger BHCs (as measured by
assets), with considerable variation by BHC size. Some of the largest BHCs had significant
declines in affiliate counts in the decade after the financial crisis, and the majority of the
rationalized affiliates were located within the United States. While the largest BHCs hold a
substantial number of subsidiaries in foreign locations, only about half of the top fifty BHCs
have even one foreign subsidiary. The number of countries in which a BHC has subsidiaries
has tended to decline, especially in locations associated with financial secrecy. Low-tax locations remain popular among the geographically complex large U.S. BHCs.
Business complexity, measured using information on the industries of entities within BHCs,
has tended to transform more than simplify. Most large BHCs have entities that span banking,
fund management, insurance, and nonfinancial activities, even if they differ substantially in
the finer sub-industry composition. The nonfinancial share of entities within BHCs remains
large, while the number of industries spanned by these entities is somewhat smaller than it was
pre-crisis. Within the financial industries, BHCs shifted toward less traditional financial subsidiaries such as portfolio management firms and other securities activities, resulting in
reduced shares of commercial banks, insurance firms, and other intermediaries.
Simplification of bank complexity was one of the policy priorities of the post-crisis period.
Regulatory frameworks continue to focus on limiting the risk of failure by improving banks’
ability to absorb risk and on improving resolution mechanisms for these BHCs in the event of
failure (Stiroh 2018). The concept of optimal complexity in U.S. BHCs still warrants additional
analysis. Further research is needed on the implications of complexity for the full bank holding
company, for the specific entities within the BHCs, and for financial stability more broadly.
Research could establish which forms of business and geographic complexity support diversification, efficiencies, and risk sharing, adding value by increasing performance and potentially
enhancing institutional robustness. These positive attributes would contrast with the negative
contributions of bank complexity to agency problems and moral hazard, and the systemic
externalities that motivated strengthening bank recovery and resolution initiatives. While
reducing the costs of bank failure has been targeted by policy initiatives, this additional analysis will better inform the evolving consequences of the different forms of complexity during
the lives of these large financial conglomerates.

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Complexity in Large U.S. Banks

Appendix
Table A1

Breakdown of Business Types by Asset Size Quintile

Banks

Mutual
and Pension
Funds

Insurance

Other
Financial

Nonfinancial
Management
Firms

Other
Nonfinancial

Quintile 2007:Q2 2017:Q2 2007:Q2 2017:Q2 2007:Q2 2017:Q2 2007:Q2 2017:Q2 2007:Q2 2017:Q2 2007:Q2 2017:Q2
1

.015

.012

.038

.015

.008

.035

.453

.504

.109

.103

.377

.330

.018

.010

.029

.026

.013

.004

.369

.203

.072

.048

.499

.708

.101

.033

.067

.060

.009

.007

.399

.394

.136

.253

.288

.253

.093

.115

.098

.081

.000

.498

.488

.149

.115

.163

.201

.131

.041

.093

.033

.000

.455

.631

.076

.047

.245

.248

Sources: Authors’ calculations based on Federal Reserve Board, Annual Report of Holding Companies
(FR Y-6 data) and Report of Changes in Organizational Structure (FR Y-10 data).
Note: The table presents the breakdown of business types by share for the fifty largest BHCs ranked by
assets.

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Complexity in Large U.S. Banks

Appendix (Continued)
Table A2

Breakdown of Financial Entities by Asset Size Quintile
Commercial Banks

Other Intermediaries

Broker-Dealers

Other Portfolio
Management

Quintile

2007:Q2

2017:Q2

2007:Q2

2017:Q2

2007:Q2

2017:Q2

2007:Q2

2017:Q2

.032

.022

.360

.122

.067

.050

.235

.430

.047

.045

.175

.262

.069

.060

.278

.214

.201

.074

.253

.137

.064

.095

.186

.253

.159

.180

.206

.180

.063

.068

.254

.346

.201

.063

.206

.158

.053

.150

.354

.333

Other Securities
Activities

Insurance

Mutual and
Pension Funds

Quintile

2007:Q2

2017:Q2

2007:Q2

2017:Q2

2007:Q2

2017:Q2

.211

.283

.078

.028

.017

.064

.324

.286

.076

.114

.032

.018

.143

.295

.134

.132

.018

.016

.151

.098

.167

.128

.000

.042

.246

.143

.050

.000

Sources: Authors’ calculations based on Federal Reserve Board, Annual Report of Holding Companies
(FR Y-6 data) and Report of Changes in Organizational Structure (FR Y-10 data).
Notes: The table presents the breakdown of financial affiliates by share for the fifty largest BHCs ranked by
assets. Four-digit NAICS codes are used to sort the financial firms into the seven categories shown.

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Complexity in Large U.S. Banks

Appendix (Continued)
Table A3

Breakdown of Nonfinancial Entities by Asset Size Quintile
Utilities and
Construction

Housing

Manufacturing and
Wholesale Trade

Quintile

2007:Q2

2017:Q2

2007:Q2

2017:Q2

2007:Q2

2017:Q2

.193

.318

.012

.001

.000

.324

.424

.001

.000

.001

.000

.056

.024

.016

.017

.002

.009

.067

.106

.000

.022

.117

.000

Nonfinancial
Management Firms

Other

Real Estate

Quintile

2007:Q2

2017:Q2

2007:Q2

2017:Q2

2007:Q2

2017:Q2

.112

.119

.050

.031

.132

.031

.063

.032

.051

.021

.059

.023

.160

.250

.162

.052

.104

.149

.239

.182

.104

.023

.090

.189

.118

.079

.210

.136

.151

.168

Sources: Authors’ calculations based on Federal Reserve Board, Annual Report of Holding Companies
(FR Y-6 data) and Report of Changes in Organizational Structure (FR Y-10 data).
Notes: The table presents the breakdown of nonfinancial affiliates by share for the fifty largest BHCs ranked by
assets. Two-digit NAICS codes are used to sort the nonfinancial firms into the six categories shown.

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Complexity in Large U.S. Banks

Appendix (Continued)
Table A4

The Fifty Largest BHCs in 2007 and 2017 (1-25)
2007:Q2

Rank

2017:Q2
Highholder
Assets
(Billions of
Dollars)

Highholder Name

Highholder
Assets
(Billions of
Dollars)

CITIGROUP

2,220.87

JPMORGAN CHASE & CO

2,563.17

BANK OF AMER CORP

1,535.68

BANK OF AMER CORP

2,256.10

JPMORGAN CHASE & CO

1,458.04

WELLS FARGO & CO

1,930.87

WACHOVIA CORP

719.92

CITIGROUP

1,864.06

WELLS FARGO & CO

539.87

U S BC

463.84

U S BC

222.53

PNC FNCL SVC GROUP

372.36

SUNTRUST BK

180.31

BANK OF NY MELLON CORP

354.82

CAPITAL ONE FC

145.94

CAPITAL ONE FC

350.59

NATIONAL CITY CORP

140.65

STATE STREET CORP

238.28

REGIONS FC

137.62

BB&T CORP

221.19

BB&T CORP

127.58

SUNTRUST BK

207.32

BANK OF NY CO

126.46

FIFTH THIRD BC

141.07

PNC FNCL SVC GROUP

125.74

KEYCORP

136.36

STATE STREET CORP

112.35

NORTHERN TR CORP

125.61

FIFTH THIRD BC

101.39

REGIONS FC

124.78

KEYCORP

93.49

M&T BK CORP

120.90

NORTHERN TR CORP

59.61

HUNTINGTON BSHRS

101.41

COMERICA

58.95

COMERICA

71.63

MARSHALL & ILSLEY CORP

58.33

ZIONS BC

65.45

CHARLES SCHWAB CORP

49.00

SVB FNCL GRP

48.44

ZIONS BC

48.70

NEW YORK CMNTY BC

48.34

COMMERCE BC

48.23

PEOPLES UNITED FNCL INC

43.02

POPULAR

46.99

POPULAR

41.24

MELLON FNCL CORP

43.39

EAST WEST BC

35.93

FIRST HORIZON NAT CORP

38.40

FIRST CITIZENS BSHRS

34.77

Source: Federal Reserve Board, Annual Report of Holding Companies (FR Y-6 data).

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Complexity in Large U.S. Banks

Appendix (Continued)
Table A5

The Fifty Largest BHCs in 2007 and 2017 (26-50)
2007:Q2

Rank

2017:Q2
Highholder
Assets
(Billions of
Dollars)

Highholder Name

Highholder
Assets
(Billions of
Dollars)

HUNTINGTON BSHRS

36.42

RAYMOND JAMES FNCL

33.43

COMPASS BSHRS

34.94

BOK FC

32.52

SYNOVUS FC

33.30

FNB CORP

30.75

NEW YORK CMNTY BC

29.64

SYNOVUS FC

30.69

COLONIAL BANCGROUP

23.82

CULLEN/FROST BKR

30.23

ASSOCIATED BANC CORP

20.85

ASSOCIATED BANC-CORP

29.77

BOK FC

19.36

FIRST HORIZON NAT CORP

29.37

W HOLD CO

17.83

BANKUNITED

28.99

FIRST BC

17.61

WINTRUST FC

26.93

INVESTORS FNCL SVC CORP

17.06

HANCOCK HC

26.64

WEBSTER FNCL CORP

16.97

WEBSTER FNCL CORP

26.19

SKY FNCL GROUP

16.81

UMPQUA HC

25.26

FIRST CITIZENS BSHRS

16.01

COMMERCE BSHRS

25.10

CITY NAT CORP

15.81

INVESTORS BC

24.33

COMMERCE BSHRS

15.53

VALLEY NAT BC

23.45

NEW YORK PRIV B&TR CORP

15.10

TEXAS CAP BSHRS

23.12

FULTON FNCL CORP

15.08

PROSPERITY BSHRS

22.30

TCF FC

15.07

PACWEST BC

22.25

FBOP CORP

14.38

TCF FC

22.07

SOUTH FNCL GROUP

14.14

IBERIABANK CORP

21.79

CITIZENS REPUBLIC BC

13.28

PINNACLE FNCL PTNR

20.89

BANCORPSOUTH

13.21

UMB FC

20.35

CULLEN/FROST BKR

13.09

MB FNCL

19.97

VALLEY NAT BC

12.32

FULTON FNCL CORP

19.57

R&G FNCL CORP

11.61

STIFEL FNCL CORP

19.53

Source: Federal Reserve Board, Annual Report of Holding Companies (FR Y-6 data).

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Complexity in Large U.S. Banks

Appendix (Continued)
Table A6

Classification of Affiliate Types
Business Type
Financial affiliates

Affiliate Type

Commercial Banks

5221

Mutual and Pension
Funds

Mutual and Pension Funds

52511, 52591

Insurance

5242, 5241

Other Financial

Other Portfolio Managers

52599, 52392, 52590,
52519, 52592

Broker-Dealers
Other Intermediaries
Other Securities Activities
Nonfinancial affiliates

NAICS Codes

5231, 5232
5222, 5223
5239

Nonfinancial
Management Firms

(Nonfinancial) Management
Companies

Other Nonfinancial

Real Estate

Housing

62422

Utilities and Construction

21, 22, 23

Manufacturing and
Wholesale Trade

31, 32, 33, 42, 45

Other

11, 48, 49, 51, 54, 56, 61,
62 (no 62422), 71, 72, 81

Notes: The table presents the authors’ classification for business types, broken down into financial and
nonfinancial entities, and the associated NAICS codes. The classification uses four-digit NAICS codes for
all financial entities and two-digit NAICS codes for all nonfinancial entities. To further break down portfolio
management, the classification uses six-digit NAICS codes to differentiate between mutual and pension funds
and other portfolio management. In other nonfinancial entities, NAICS code 62422 is community housing, so it
is listed in its own category.

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Complexity in Large U.S. Banks

Appendix (Continued)
Table A7

List of Countries by Low-Tax Jurisdiction and High Financial Secrecy (2018)
Low-Tax Jurisdiction
Aruba
Bahamas
Bahrain
Barbados
Bermuda
Bolivia
British Virgin Islands
Brunei
Cayman Islands
Costa Rica
Czech Republic
France
Gibraltar
Guatemala
Hong Kong
Ireland
Kenya
Liberia
Liechtenstein
Malta
Mauritius
Mexico
Netherlands
New Zealand
Paraguay
Philippines
Russia
Saint Lucia
Seychelles
Singapore
Switzerland
Thailand
Turks and Caicos Islands
Ukraine
United Arab Emirates
Uruguay
Vanuatu

High Financial Secrecy
Aruba
Bahamas
Bahrain
Bolivia
Brunei
Kenya
Liberia
Liechtenstein
Monaco
Panama
Paraguay
Saint Lucia
Seychelles
Switzerland
Taiwan
Thailand
Turks and Caicos Islands
United Arab Emirates
Vanuatu

None
Australia
Austria
Belgium
Botswana
Brazil
Bulgaria
Canada
Chile
China
Cook Islands
Cyprus
Denmark
Dominican Republic
Finland
Germany
Greece
Hungary
Iceland
India
Indonesia
Israel
Italy
Japan
Lebanon
Luxembourg
Macao
Malaysia
Marshall Islands
Norway
Poland
Portugal
Romania
Saudi Arabia
South Africa
South Korea
Spain
Sweden
Tanzania
Turkey
United Kingdom
United States
Venezuela

Source: Tax Justice Network, Financial Secrecy Index.
Notes: The table shows the countries with low-tax jurisdictions (tax credit score below 10), high financial secrecy
(secrecy score above 75), or neither (high-tax jurisdiction or low financial secrecy) based on 2018 scores.

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Complexity in Large U.S. Banks

Notes
Acknowledgments: The authors thank Nicola Cetorelli, João Santos, and Anna Kovner for helpful comments and insights.
Kevin Lai provided excellent research assistance.
1

The classification of these banks and the criteria used can be found at https://www.bis.org/bcbs/publ/d445.htm.

Demsetz and Strahan (1997) and Chernobai, Ozdagli, and Wang (2018) evaluate complexity using balance-sheet
measures such as nonbank assets and noninterest income in order to capture the effects on operational and
firm-specific risk, respectively.
3

Herring and Carmassi (2010) and Carmassi and Herring (2016) focus on shares of the total number of entities
that fall into categories such as foreign-located, size larger than $10 billion in assets or $1 billion in operating
income, or within a given financial industry. Cetorelli and Goldberg (2014) create metrics for the count of
nonbank entities to bank entities and of general business types, including nonfinancial industries, while Cetorelli,
Jacobides, and Stern (2017) count the number of NAICS codes that a bank’s subsidiaries span. Avraham, Selvaggi,
and Vickery (2012) generate a measure of the number of countries and the regions of the world in which a bank
has subsidiaries.
4

See https://www.naics.com/business-lists/counts-by-naics-code/?#countsByNAICS.

Business types are defined according to four-digit NAICS codes as follows: (1) Bank: NAICS code =
5221; (2) Insurance: NAICS code = 5241, 5242; (3) Mutual and Pension Fund: NAICS code = 52511, 52591;
(4) Other Financial: two-digit NAICS code 52, but subsidiary does not fall into the categories of Bank, Insurance,
or Mutual and Pension Fund; (5) Nonfinancial Management Firms: NAICS code = 5511; (6) Other Nonfinancial:
two-digit NAICS code is not 52 and four-digit NAICS code is not 5511.
6

These measures of geographic complexity do not address the concept of dispersion of branch locations or
businesses within the United States, a topic considered in some research on the consequences of the historic
elimination of interstate banking restrictions through the 1980s and with the Riegle-Neal Act in 1994.
7

All analysis in this article excludes the seven large BHCs that were designated as BHCs after 2008: Goldman Sachs,
Morgan Stanley, American Express, CIT Group, Ally Financial, Discover Financial Services, and MetLife.
8

Banking regulatory micro data reference manuals have specific details on the distinctions between BHC top holder
and regulatory top holder. See https://www.federalreserve.gov/data/mdrm.htm.
9

Box plots illustrate how complexity measures differ throughout the distribution of the fifty largest BHCs (Chart 3).
BHC rank at each date is determined using BHC assets. The decline in the mean subsidiary count, previously shown
in Table 1, is further elaborated in Panel B of the chart.
10

Cetorelli and Goldberg (2014) reached a similar conclusion for large non-U.S. global banks.

See, for example, Berger et al. (2003), Buch (2005), Claessens and Van Horen (2014), Claessens, Hassib, and Van
Horen (2017), Russ and Valderrama (2012), and Niepmann (2015).
12

The tax jurisdictions and secrecy scores using 2018 data from the Tax Justice Network are located at
https://www.financialsecrecyindex.com/introduction/fsi-2018-results.
13

We define a country as a secrecy location if its secrecy score is greater than or equal to 75 and as a low-tax
jurisdiction if its tax credits score is less than or equal to 10.
14

Financial Stability Board (2017) provides statistics and related discussion of the status of international
correspondent banking activity. Table A7 provides the country sorting for financial secrecy and low-tax jurisdictions.

Federal Reserve Bank of New York

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Economic Policy Review, 26, no. 2, March 2020

Complexity in Large U.S. Banks

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Complexity in Large U.S. Banks

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