Full text of Economic Policy Review (Federal Reserve Bank of New York) : Volume 18, Number 2 : Special Issue: The Evolution of Banks and Financial Intermediation

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Nicola Cetorelli, Benjamin H. Mandel, and Lindsay Mollineaux

The Evolution of Banks and
Financial Intermediation:
Framing the Analysis
1. Introduction

The description of the 2007-09 crisis as “the Great Recession” is commonly
attributed to Paul Volcker, who used the term in a speech in April 2009
(http://sitemason.vanderbilt.edu/myvu/news/2009/04/21/paul-volcker-and
-donald-kohn-discuss-the-economic-crisis-at-ogsm-forum.78224). For the
application of this term to earlier recessions, see http://economix.blogs
.nytimes.com/2009/03/11/great-recession-a-brief-etymology/.

intermediation failure that did not necessarily, or at least not
directly, result from bank failures. To be sure, many banks did
indeed fail during the crisis and many more were left with
impaired operations—outcomes that certainly exacerbated the
scale and scope of the crisis. Nevertheless, major disruptions
occurred among segments of financial intermediation activity
that had in recent years been growing rapidly and that did not
seem to revolve around the activity and operations of banks.
For instance, we have learned that the crisis originated as
a run on the liabilities of issuers of asset-backed commercial
paper (ABCP), a short-term funding instrument used to
finance asset portfolios of long-term maturities (see, for
example, Gorton [2008]; Covitz, Liang, and Suarez [2009];
Acharya, Schnabl, and Suarez [forthcoming]; and Kacperczyk
and Schnabl [2010]). In this sense, ABCP issuers (conduits)
perform typical financial intermediation functions, but they
are not banks. Certainly, in many instances banks were the
driving force behind ABCP funding growth, sponsoring
conduit activity and providing the needed liquidity and credit
enhancements. But the main point is that ABCP financing
shifts a component of financial intermediation away from the
traditional location—the bank’s own balance sheet. Similarly,
and concurrently with the ABCP disruptions, financial markets
also witnessed a bank-like run on investors that funded
their balance sheet through repurchase agreement (repo)
transactions, another form of financial intermediation that
grew rapidly but did not take place on bank balance sheets
(Gorton 2008; Gorton and Metrick 2010). Additionally, in the

Nicola Cetorelli is a research officer at the Federal Reserve Bank of New York;
Benjamin H. Mandel and Lindsay Mollineaux are former assistant economists
at the Bank.

The views expressed 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.

hile the term “the Great Recession” has been loosely
applied to almost every economic downturn in the
past twenty years, the crisis of 2007-09 has—more than most
recessions—lived up to that name.1 The crisis has been felt
across virtually all economic sectors and in all parts of the
world. Still, if its effects have been widespread, its origins were
narrower: the crisis had its roots in the financial sector and
manifested itself first through disruptions in the system of
financial intermediation.
This story is in itself not new. Many economic crises in
history have been the result of financial crises, and many
financial crises in turn originated as failures of financial
intermediaries. And in every instance the reference has been to
banks, in their essential role as deposit-taking entities involved
primarily in the business of lending. Thus, Reinhart and Rogoff
(2008) identify some thirty separate instances of banking crises
across many countries and at different points in time during
the last 100 years.
Indeed, the terms bank and financial intermediary have
normally been used interchangeably. However, what was new
in this last crisis is that we witnessed many instances of financial
1

Correspondence: nicola.cetorelli@ny.frb.org

FRBNY Economic Policy Review / July 2012

The Credit Intermediation Chain

Asset flows
Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Step 7

Credit, maturity,
and liquidity
transformation

Credit
transformation
(blending)

Credit, maturity,
and liquidity
transformation

Credit
transformation
(blending)

Credit, maturity,
and liquidity
transformation

Maturity and
liquidity
transformation

Loan
origination

Loan
warehousing

ABS
issuance

ABS
warehousing

ABS CDO
issuance

ABS
intermediation

Wholesale
funding

Loans

ABS

Loans

ABCP

Repo

ABS CDO

ABS

ABCP, repo

CP, repo

ABCP

$1 NAV

ABCP, repo

Funding flows

Source: Pozsar et al. (2010).
Note: ABS is asset-backed security; CDO is collateralized debt obligation; CP is commercial paper; ABCP is asset-backed commercial paper;
NAV is net asset value.

aftermath of Lehman Brothers’ default, money market mutual
funds, yet another class of nonbank entities that serve as
financial intermediaries, experienced a run on their liabilities,
an event that triggered in turn an even bigger run on ABCP
issuers (Acharya, Schnabl, and Suarez, forthcoming).
The crisis has therefore exposed significant instances
of financial intermediation failure but also an apparent
disconnect between financial intermediation activity and
banks. A new narrative has emerged, describing intermediation as a decentralized rather than a bank-centered
system, one in which the matching of the supply of
and demand for funds occurs along an extended credit
intermediation chain, with specialized markets and nonbank
institutions playing a part along the way.
This is the so-called shadow banking model of financial
intermediation, as described, for instance, in Pozsar et al.
(2010).2 The authors characterize the transition from a bankcentered to a decentralized model in this way: “In essence, the
shadow banking system decomposes the simple process of
deposit-funded, hold-to-maturity lending conducted by banks
into a more complex, wholesale-funded, securitization-based
lending process that involves a range of shadow banks” (p. 13).
2

The term shadow banking was apparently coined by McCulley (2007).

The Evolution of Banks and Financial Intermediation

As the authors explain, the “backbone” of the new system is the
credit intermediation chain. The exhibit above, from the
Pozsar et al. paper, depicts the multiple steps in the chain.
Loans are originated, but with a funding approach that involves
a precise sequence of steps, during which they are removed
from the balance sheet of the originator (warehousing), and
then packaged into securities (asset-backed-security [ABS]
issuance). This last step could expand into additional steps that
may involve warehousing of the asset-backed securities
themselves and further repackaging into more complex
securities (for instance, collateralized debt obligations, or ABS
CDO issuances).
This decentralization of activities opens up significant
opportunities for economies of specialization, in which
nonbank firms emerge as organizations that have a narrower
scope than banks but perform an important function in
finalizing securitization activity. In this alternative model,
traditional banks may have a diminished role. Understanding
the extent to which this is the case is important in and of itself,
but it also raises key normative questions. Namely, what are
the consequences of the new reality for the monitoring and
regulation of financial intermediation? The system of controls
that has been in place over time, certainly until the crisis

erupted, assumes that risks, especially in their systemic
component, are mainly concentrated on the balance sheet of
banks. If financial intermediation now occurs somewhere else,
should we rethink the “boundaries” of regulatory control? To
what extent will the new model of financial intermediation and
its associated risks be subject to review and intervention with
a bank-based regulatory approach?
These questions motivate the articles in this special issue
of the Economic Policy Review. The thesis that unites all of the
contributions in the volume is that banks—regulated banking
institutions—have in fact not been bypassed in the modern
process of financial intermediation. Indeed, we argue that
banks have shown a remarkable capacity to adapt to the
evolving system of intermediation, continuing to provide,
albeit in new ways, those services needed to facilitate the
matching of fund supply and demand. Moreover, we contend
that when nonbank intermediation has come into play, banks
have actually supported its growth.
Our thesis unfolds through two complementary
approaches. First, we provide an in-depth analysis of the credit
intermediation chain, focusing on the roles needed for a dollar
of funding to be successfully intermediated through the new
model, centered on asset securitization. Because each role is
performed by a specific entity, this role-based approach allows
us to assess the scale and scope of participation by banks—and
nonbanks—in the process. The approach confirms that banks
have indeed adapted naturally to the changing model of
intermediation, redefining their “production function”
while continuing to provide the type of services needed for
intermediation to occur.
Second, we look at the same issues from the perspective of
the organizational form of the banking firm itself. In particular,
we posit that banks have adapted through a significant
transformation of their organizational structure. If financial
intermediation entails increasing participation by nonbank
entities, then banks can adapt by integrating those nonbank
entities in the same bank holding company (BHC) structure.
This second approach, focusing on entity type, confirms that
BHCs have allotted nonbank subsidiaries an increasingly
important role in their activities, consistent with the view of
adaptation through organizational changes.
Significantly, the structural changes initiated by banks have
clear normative implications, since BHCs and financial
holding companies are regulated by the Federal Reserve. If
entities active in the credit intermediation chain have in fact
been incorporated in BHCs, then we may need to reassess how
much of modern financial intermediation has been overtaken
by “shadow banking” and how much remains open to
regulatory scrutiny.

2. From Bank-Based
to Securitization-Based
Intermediation
As any textbook on money and banking would explain, the
standard problem of external financing—that is, the matching
of agents in possession of funds with those in need of funds—
is resolved in one of two ways: 1) with direct finance, where
fund suppliers support demand through ownership participation (acquisition of equity positions) and/or the acquisition
of debt instruments (for example, bonds) directly issued by the
agents demanding the funds; or 2) with indirect finance, where
fund supply is funneled to “in-between” agents, the financial
intermediaries, which are then responsible for the allocation
to demand.
Direct finance grants agents an immediate participation
in, and control over, investment activities, but it also entails
dealing with a number of well-known informational and
liquidity frictions. For instance, unless the agent seeking funds
has an established track record of performance, selection
requires learning about the agent and its intended use of funds.
But even when a record of satisfactory performance exists, a
supplier still needs to follow the investment project, monitoring
activities throughout its life cycle. Moreover, before the
supplier selects a specific investment opportunity, it must
employ resources to screen available alternatives, evaluating the
many dimensions of risk, return, business, scale, scope, and
geography before making an informed decision. And because
of these informational costs, funding constraints may still limit
the ability of the supplier to diversify risks across a suitably
large portfolio of alternative investment opportunities. Finally,
even if the informational issues are successfully resolved,
the fund supplier needs to factor in its own liquidity
preferences, that is, the need to have funds available before
the investment matures.
The wide range of costs associated with direct finance
justifies the existence of financial intermediaries, traditionally
understood to be centralized agents performing under one roof
the roles of screening, selection, monitoring, and diversification of risk while simultaneously providing credit and
liquidity services to fund suppliers. These services—the credit,
maturity, and liquidity transformations of financial claims—
presuppose all of the roles just described and show the intrinsic
fragility of the intermediary’s activity: Given the nature of its
operations, the financial intermediary never holds sufficient
balances to guarantee full withdrawals, a condition that
exposes it to potential “runs.” And because the investments of
intermediaries are naturally opaque, it is difficult to distinguish
the problems specific to one intermediary from problems
affecting the industry as a whole, with the result that the
observation of distress at one entity could lead to runs on

FRBNY Economic Policy Review / July 2012

others as well. Hence, financial intermediation activity carries a
significant social risk—the potential for systemic disruptions.3
The existence of this risk is one rationale, and perhaps the
major one, for the fact that financial intermediation activity
in modern history has been closely governed by laws and
regulations and, more specifically, restricted to entities that are
able to obtain explicit authorization in the form of a charter. In
the United States, a charter permitting the taking of deposits is
granted exclusively to entities organized as commercial banks
(and similarly to thrifts and credit unions as well).4 Moreover,
because of the potential for systemic risk, the restricted bank
charter also comes with exclusive access to liquidity and credit
support by the taxpayer—made available, in the United States,
through access to the Federal Reserve’s discount window and
the insurance of deposit accounts by the Federal Deposit
Insurance Corporation (FDIC), respectively. The existence
of these official backstops is a significant factor strengthening
investors’ confidence in banks.5
Hence, both the chartering restrictions and the official
liquidity and credit guarantees have been key in making the
traditional system of financial intermediation a bank-centered
system. In this framework, risks reside on banks’ balance
sheets, which is the main justification for a system of regulation
and supervision that is likewise focused on banks.

3. A Role-Based Approach to
Understanding Bank Evolution
As suggested earlier, however, the advent of asset
securitization has broken down the traditional system of
intermediation. The origination of loans is now just the first
step in a longer sequence (recall the exhibit presented above),
and in every subsequent step, specialized entities now
perform specific roles. For instance, warehousing in step 2
is done through dedicated entities (for instance, the ABCP
conduits mentioned earlier) that finance the acquisition of
the long-term assets through the issuance of shorter-term
liabilities. Because of the implied maturity transformation
that this role involves, this stage would typically require
the provision of some form of liquidity and credit
enhancement—for the same reason that banks’ traditional
3

See, for example, Ennis and Keister (2010) for a survey of the theoretical
arguments on financial intermediation fragility.
4
The first bank charter in U.S. history is probably that granted by the
Continental Congress to the Bank of North America in 1781 (Knox 1900),
although some earlier contenders for this distinction exist (for example,
the Massachusetts Land Bank in 1739).
5
“FDIC insurance is backed by the full faith and credit of the United States
government. Since the FDIC was established in 1933, no depositor has ever
lost a single penny of FDIC-insured funds.” See http://www.fdic.gov/deposit/
deposits/dis/index.html.
4

The Evolution of Banks and Financial Intermediation

activity requires both liquidity and credit guarantees.
Following warehousing, the assembly of the loans into
securities and the related sale to investors require the services
of several parties: an issuer, that is, a company that acquires
the assets to be transformed into securities; an underwriter,
the entity in charge of the packaging and sale of the securities;
a trustee, an agent that acts on behalf of and looks after the
interests of the securities buyers; and a servicer, a party that
manages the income streams from the underlying assets and
the related payments to the investors. Finally, along the whole
chain, the process may also require further liquidity and
credit enhancement to boost the quality of the issuances.6
Although these roles are now typically played by separate
specialized entities, they are the same roles performed simultaneously, albeit in implicit form, by a bank in the traditional
centralized model of intermediation: The bank is the loan
originator, but it is also the implicit issuer and underwriter of
the loan portfolio to its own investors, depositors, and equity
holders. Likewise, the bank performs the role of trustee, as
the delegated agent for its investors, and that of servicer, as it
collects the revenue stream from the loan contracts. Finally, it
provides credit enhancement to debt holders, represented by
the existence of equity held on the balance sheet, and liquidity
services, in fact on both sides of the balance sheet, to firms and
depositors.
This continuity in roles is an important qualification,
showing clearly that while the system has become decentralized
and complex, it is still plainly financial intermediation at its
core. Consequently, we can more clearly assess whether banks
have in fact been eclipsed by other players by analyzing who
performs each role along the credit intermediation chain.
We begin with loan origination. Traditionally the amount
of loans found on bank balance sheets would be a reasonable
measure of aggregate lending activity. Yet, the evolution to a
securitized-based model has actually made it more difficult to
quantify precisely how much lending is originated and by
whom. For instance, if loans are increasingly originated to be
sold quickly to feed the asset securitization machine—the socalled originate-to-distribute model of intermediation—then
the balance sheet (given its static nature) could not capture the
richer dynamics of origination and sales taking place in the
background. Hence, the levels and trends in lending amounts
observed in intermittent snapshots—that is, at every point
in time banks are required to file—become increasingly
uninformative about the extent to which banks actively engage
in the new intermediation model.
Regulatory reporting data, such as banks’ quarterly
Consolidated Reports of Condition and Income (“call reports”),
provide a small window into the originate-to-distribute
practice from the observation of banks’ held-for-sale accounts,
6

Steps 4 through 6 in the exhibit represent more complex instances of
resecuritization, but still require essentially the same roles.

Chart 1

Chart 2

Commercial Banks Reporting Loans Held for Sale

Mortgage Originations by Commercial Banks

Percent

35
30

Trillions of dollars

Percent

Share of total loans held by banks
reporting held-for-sale loans
Scale

Share of banks reporting
held-for-sale loans

Scale

2.0
Mortgages held after origination year
Mortgages sold within origination year

1.5

70
1.0

20
60
15
50

0.5

5
1991

0
1990

The call reports (officially designated FFIEC 031/FFIEC 041) provide basic
data on banks’ financial condition; the forms originate with the Federal
Financial Institutions Examination Council and are collected by the Federal
Reserve. Note that the “held-for-sale” designation indicates only the intent to
sell, so the size of this book is likely to depart from actual sales levels. Also, the
held-for-sale books would not capture origination and sale dynamics occurring
at a higher frequency than data reporting (for example, mortgage loans originated and sold all within two consecutive quarters of customary regulatory
reporting). Nevertheless, the comparison of the trend in the size of these books
with that of aggregate growth in securitization activity should give an
indication of the participation of banks—as loan originators—in the process.

Source: Home Mortgage Disclosure Act.

Source: Federal Financial Institutions Examination Council,
Consolidated Reports of Condition and Income.

in which banks place loans that they intend to sell.7 As Chart 1
shows, the fraction of banks reporting held-for-sale loans
(represented by the bars) increased substantially from the early
1990s, even though at the peak of the crisis, still only about one
in four banks did so. However, those banks accounted for
roughly 80 percent of total commercial bank loans (the solid
line) over the same period. This information seems to suggest
that banks increasingly shifted to an originate-to-securitize
model of lending and that they may have done more origination than the balance sheet would suggest.
Still, the amount of loans held for sale at a given point in
time can only offer an indirect view of the underlying dynamics
of origination and sale. Ideally, one would like to see data on
actual origination trends, actual sales, and the purpose of the
sale—information that is not collected in current regulatory
data. Information reported under the Home Mortgage
Disclosure Act (HMDA) provides some detail for at least the
residential mortgage subset of these assets, revealing that actual
loan origination by commercial banks has grown over time
(Chart 2). Moreover, a majority of these loans are sold within
the same calendar year. So, for instance, in the most recent
years, for every one dollar of mortgages originated and held
by banks, nearly four dollars of additional mortgages were
originated and sold.

Chart 3

Mortgages Sold within Origination Year
by Commercial Banks, as a Share of Total Residential
Mortgage-Backed-Securities Issuance
Percent

30
1997 98 99 00 01 02 03

04 05

06 07 08

09 10

Sources: Home Mortgage Disclosure Act; Securities Industry and
Financial Markets Association.

This “churning” activity confirms quite effectively the
increasing inadequacy of balance sheet data to gauge the actual
importance of banks in the role of originator. Indeed, we reach
the same conclusion when we compare the magnitude
of residential mortgages sold in every origination year to the
total new issuance of residential mortgage-backed securities
(RMBS), as reported by the Securities Industry and Financial
Markets Association (SIFMA).8 Residential mortgages originated and subsequently sold by commercial banks account for
between 30 and 50 percent of RMBS issuance in most years,
though this figure was closer to 60 percent in 2006 (Chart 3).
8

SIFMA figures for total RMBS issuance combine agency MBS issuance with
nonagency RMBS issuance.

FRBNY Economic Policy Review / July 2012

Table 1

Chart 4

Banks’ Provision of Support in Structured Finance

Outstanding Principal Balance of Assets Sold
by Commercial Banks with Servicing Retained
or with Recourse or Other Seller-Provided
Credit Enhancements

Top Fifty ABS Deals

Top Fifty ABCP Conduits

Number
of Deals

Amount
(Billions
of Dollars)

Number
of Deals

Amount
(Billions
of Dollars)

229.15

168.52

Nonbank
affiliates

166.57

43.01

Other

60.59

11.47

Banks

Total

272.09

180.12

Source: Moody’s.
Note: ABS is asset-backed security; ABCP is asset-backed
commercial paper.

Moving on to liquidity and credit enhancement, we
consider the extent to which banks have ceded these roles to
other entities. As noted earlier, bank-based intermediation is
made relatively stable, despite its intrinsic fragility, by the
existence of explicit official support from central authorities.
This support takes the form of both liquidity guarantees (for
example, central bank discount window access) and credit
guarantees, that is, the protection of intermediaries’ liabilities
in the event of their default (for example, deposit insurance).
By extension, the new securitized-based system, while shifting
maturity transformation outside of bank balance sheets, could
not thrive without receiving adequate similar support. Lacking
access to official guarantees, the system requires the provision
of such services from within the market itself. While various
types of entities can provide, and have provided, such services,
absorbing liquidity and credit risk for clients is again one of the
defining characteristics of banks’ business model. Moreover,
banks are also natural providers of such services exactly
because their sponsoring services are credible, owing to the
official support they receive in turn.
The evidence seems to support the continuing importance
of banks in these roles. Focusing on the ABCP market, we
note that prior to the crisis, when conduits had expanded to
reach a peak of about $1.2 trillion, banks were the providers
of support in almost 75 percent of the value outstanding
(Acharya, Schnabl, and Suarez, forthcoming). And even after
the crisis, although the volumes in this market have shrunk
considerably (to less than $400 billion in 2010), banks have
maintained a dominant role. For instance, data from Moody’s
concerning the top fifty ABCP issuances in the United States at
year-end 2010—amounting to approximately $180 billion—

The Evolution of Banks and Financial Intermediation

Trillions of dollars

2.5

Assets sold and not securitized by reporting banks
Assets sold and securitized by reporting banks

2.0
1.5
1.0
0.5
0
2002

suggest that banks were the providers of support in forty-seven
of such deals, for a total of $168 billion (Table 1). As the table
shows, banks were also significant providers of support in ABS
issuance, and if we consider the entire holding company
organization (including nonbank subsidiaries), banks figure
even more importantly in the provision of this service.
Hence, banks seem to have been “private central bankers” to
important components of shadow banking activity throughout
the years of its growth. This is another way in which banks have
asserted their renewed importance in the transformed mode of
intermediation: If intermediation has migrated away from
bank balance sheets, its growth still seems largely dependent
on banks’ support.
Further along the credit intermediation chain, to what
extent have banks been engaged in the securitization process as
issuers, underwriters, servicers, and trustees? This question is
difficult to answer, because available regulatory data at best
provide only some indirect evidence and only for the most
recent period. For instance, through additions to the call
reports introduced in 2001, we can derive at least a partial
measure of banks’ participation in asset securitization from
the aggregate amount of assets sold in which banks retained
a servicing role or provided some form of enhancement. As
Chart 4 shows, this amount about doubles from the early 2000s
to a peak in 2009 of about $2 trillion. However, this figure does
not explicitly take into account any of the other roles needed in
asset securitization, and it misses the extent to which banks

Chart 5

Chart 6

Composition of Noninterest Income

Commercial Banks, 1991-2010

Top 1 Percent of Commercial Banks by Assets, 1991-2010
Billions of U.S. dollars

Billions of U.S. dollars

250

300
Category 4
Category 3
Category 2
Category 1

250
200

Category 4
Category 3
Category 2
Category 1

200
150

150
100
100
50

50
0
1991

Note: The categories are defined as follows:
Category 1 = income from fiduciary activities + servicing fees on
deposit accounts
Category 2 = trading revenue + other foreign transaction gains
+ venture capital revenue + insurance commissions and fees
+ investment banking fees
Category 3 = other noninterest income + net gains on asset sales
Category 4 = net servicing fees + net securitization income.

may have performed these roles in securitization activity that
they did not originate. Some additional information can be
gathered from observation of the sources of income reported
by banks. The income statement, also part of the call report and
also revised in 2001, now requires richer detail on the types of
activities performed by banks and the relative contribution of
these activities to bank income flows. In particular, banks have
to report “fees from servicing securitized assets” and income
from “securitizations, securitization conduits, and structured
finance vehicles, including fees for administrative support,
liquidity support, interest rate risk management, credit
enhancement support, and any additional support functions
as an administrative agent, liquidity agent, hedging agent, or
credit enhancement agent.” 9 We report these figures in
aggregate (Chart 5) and separately for banks in the top 1 percent
and bottom 90 percent of assets (Charts 6 and 7, respectively).
The charts do seem to suggest that banks were indeed highly
involved in the many roles needed to complete the process of
intermediation through asset securitization. This finding is
confirmed by the Moody's data on securitization services
(other than credit enhancement) provided by banks in top
ABS and ABCP issuances (Table 2).

0
1991

Federal Financial Institutions Examination Council, Consolidated Reports
of Condition and Income, Reporting Form 031 Instructions, p. 35.

Chart 7

Composition of Noninterest Income
Lowest 90 Percent of Commercial Banks by Assets, 1991-2010
Billions of U.S. dollars

20
Category 4
Category 3
Category 2
Category 1

5
0
1991

Sources: Federal Financial Institutions Examination Council,
Consolidated Reports of Condition and Income; Board of Governors
of the Federal Reserve System, Consolidated Financial Statements
of Bank Holding Companies (FR Y-9C data).
Note: The categories are defined as follows:
Category 1 = income from fiduciary activities + servicing fees on
deposit accounts
Category 2 = trading revenue + other foreign transaction gains
+ venture capital revenue + insurance commissions and fees
+ investment banking fees
Category 3 = other noninterest income + net gains on asset sales
Category 4 = net servicing fees + net securitization income.

FRBNY Economic Policy Review / July 2012

Table 2

Chart 8

Banks’ Other Roles in Structured Finance

Growth in Assets of Bank and Nonbank Subsidiaries
of Bank Holding Companies and of Other
Financial Intermediaries

Top Fifty ABS Deals

Top Fifty ABCP Conduits

Number
of Deals

Amount
(Billions
of Dollars)

Number
of Deals

Amount
(Billions
of Dollars)

250.60

111.44

Banks

18
17

Log of assets (assets in millions of dollars)
Assets of other
financial intermediaries

Nonbank
affiliates

261.95

92.29

Other

78.61

12.41

Total

272.09

180.12

Source: Moody’s.

15
14

Assets of bank subsidiaries
of BHCs
Assets of nonbank
subsidiaries of BHCs

13
12

Note: ABS is asset-backed security; ABCP is asset-backed
commercial paper.

1991

09 10

Sources: Board of Governors of the Federal Reserve System, Flow of Funds
Accounts and Consolidated Financial Statements of Bank Holding
Companies (FR Y-9C data).

4. Organizational Adaptation:
An Entity-Based View
We have suggested that banks have adapted to the modern
decentralized system of intermediation by engaging, to varying
degrees, in the roles that have emerged along the new credit
intermediation chain. This adaptation is also evident in the
changes made by banks to their organizational structure. With
intermediation services provided in a decentralized fashion
and increasingly by nonbank entities, banking firms have
responded by integrating such entities under common
ownership and control. This potential expansion of the
boundaries of the banking firm, in the sense articulated by Coase
(1937), thus suggests shifting the focus of observation from
commercial banks to bank holding companies. Banks’ organizational adaptation occurred somewhat organically over time,
even in the presence of the strict regulatory restrictions
imposed by the Banking Act of 1933 (Glass-Steagall) on the
type of activities allowed by chartered banking institutions,
but it was then officially sanctioned with the passage of the
Financial Modernization Act of 1999 (Gramm-Leach-Bliley)
and the constitution of the financial holding company as the
legal entity allowed to own and control both bank and nonbank
financial entities.
What does financial intermediation look like once we
broaden our scope to consider bank and financial holding
companies as the unit of observation (for brevity, we refer to
both types of holding companies as BHCs)? Chart 8 compares
the asset growth rates of regulated bank entities with those of
“other” financial intermediaries (OFIs), an aggregate aimed at
capturing the evolution outside the world of banks. The OFI

The Evolution of Banks and Financial Intermediation

aggregate is constructed from the Federal Reserve’s Flow of
Funds data as the sum of total assets of funding corporations,
insurance companies, finance companies, closed-end funds,
exchange traded funds, pension funds, mutual funds, real
estate investment trusts, money market mutual funds, brokers
and dealers, and issuers of asset-backed securities. The total
for commercial banks is from call report data. The aggregate
numbers are expressed in natural logarithms, so that the line
trend visualizes the growth rate of each series.
As the chart clearly shows, nonbank entities have grown
substantially over the last thirty years and, most importantly, at
a faster pace than commercial banks. It is also clear, however,
that a significant chunk of the growth in the BHCs actually
came from the nonbank subsidiaries that are consolidated on
the balance sheet of the holding companies. Not surprisingly,
the growth of these subsidiaries picked up in the late 1990s,
with the process of deregulation mentioned earlier. The growth
comparison across categories is also quite remarkable: OFI
assets grew about 1.7 times from 1990 to 2010. Over the same
period, commercial bank assets grew 1.2 times, while assets
of nonbank subsidiaries grew more than 3.0 times.
Another way to assess the expansion in the scope of BHC
activities is to consider the income data discussed earlier.
Commentators have already suggested that the relative decline
in banks’ asset size was probably more a sign that book assets
were becoming increasingly uninformative about banks’
business, rather than an indication of a true decline. In other
words, banks have simply moved into alternative business lines,
relying less on traditional interest-based revenues (which are
reflected directly in asset holdings) and more on fee-based

5. Overview of the Volume

Chart 9

Book Assets versus Adjusted Assets, 1990-2010
Bank Holding Companies
Trillions of dollars

80
Adjusted assets
60

Book assets

0
1990

activities (which are not immediately related to asset size).
In doing so, banks have preserved overall profitability and
prevented their obsolescence. Boyd and Gertler (1994) made
this point quite clear when they introduced the concept of
“adjusted assets” as a way to quantify the importance of these
non-asset-based banking business lines. From the rate of return
on these activities, obtained from banks’ income statements,
they performed the thought experiment of calculating how
many extra units of book assets a bank would need in order to
generate, through traditional interest-based activities, the same
amount of fee-based income. We adapted their approach to
compare the total book assets of BHCs with their computed
adjusted assets. As BHCs expand and increasingly incorporate
nonbank subsidiaries, whose activity is predominantly fee
based, we would expect to see adjusted assets grow faster than
total book assets. This is indeed the case: the gap between
aggregate adjusted assets and aggregate book assets of BHCs has
grown distinctly larger over time (Chart 9). While fee-based
income contributed very little throughout the early part of the
1990s (hence the adjusted assets aggregate is about the same size
as the book asset aggregate), the gap explodes after that. Even if
we exclude the years after Lehman’s collapse, when some of the
largest investment banks acquired BHC status, adjusted assets
grew to be more than twice as large as total book assets.
This section’s focus on changes in entity type suggests that
as the financial intermediation sector was evolving over the last
three decades, “banks”—under the redefined organizational
concept—did adapt, significantly expanding the boundaries
of the traditional banking firm.

Although this volume is motivated by the notion that financial
intermediation has changed, we do not really investigate the
drivers of innovation. Such an analysis would be a separate
undertaking, and is beyond our scope. However, we would be
remiss if we did not describe the major innovations in banking
operations and in financial intermediation more broadly
over the last thirty years or so. Hence, before presenting the
volume’s main articles, we begin with a survey of the regulatory
and policy decisions that have altered the institutions and
instruments of credit intermediation and helped transform
the role of banks in the process. “Regulation’s Role in Bank
Changes,” by Peter Olson, suggests that government action—
sometimes unintentionally—has spurred the evolution of
financial intermediation.
The five articles that follow explore the idea of bank
adaptation in more depth, presenting arguments and findings
related to the volume’s dual emphasis on intermediation roles
and changes in bank structure. In “The Rise of the Originateto-Distribute Model and the Role of Banks in Financial
Intermediation,” Vitaly Bord and João Santos focus on the role
of loan origination and provide direct evidence of asset
churning by banks. Using supervisory data on corporate loans,
the authors are able to track the life of a loan from origination
to subsequent sales. Equipped with information on the identity
of the originator and the entities that acquire the loan at later
stages, Bord and Santos nail down the actual role of banks in
origination at the start of the modern credit intermediation
chain. Their results confirm that banks play a much more
important part in lending than what the balance sheet suggests.
In addition, the results indicate that bank actions have actually
fed the growth of the shadow bank entities involved in the
subsequent steps of the credit intermediation chain.
The importance of banks in providing credit enhancements is the topic of analysis in “The Role of Bank Credit
Enhancements in Securitization,” by Benjamin Mandel,
Donald Morgan, and Chenyang Wei. The authors focus on the
economics of credit enhancement: Why is it provided and what
functions does it play? One argument, probably the most
natural, is that the extension of such guarantees is a way
to buffer investors—the buyers of loans repackaged as
securities—to reduce their credit risk exposure. At the same
time, enhancement may resolve some of the informational
frictions discussed earlier by providing a signal of the quality of
the underlying security. The two hypotheses imply a specific
relationship between the amount of enhancement afforded and
the ex post performance of the security. Namely, buffering
would lead one to expect higher enhancements among more

FRBNY Economic Policy Review / July 2012

poorly performing securities, while the signaling hypothesis
would imply instead that high enhancements are associated
with high performance. The authors’ econometric analysis
suggests that buffering investors is in fact the main motivation
behind the provision of enhancement in asset securitization,
thus corroborating the underlying argument that banks have
played a fundamental role in supporting the modern
intermediation process.
The article by Nicola Cetorelli and Stavros Peristiani, “The
Role of Banks in Asset Securitization,” completes the analysis
of the roles implicit in the credit intermediation chain.
Parsing a Bloomberg database that includes virtually the
universe of asset-backed securities issued over time, and
drawing on supplementary information from Moody’s, the
authors are able to identify the entities that play the roles of
issuer, underwriter, trustee, and servicer. This “beancounting” approach is necessary to establish the extent to
which financial intermediation is now occurring
“in the shadow”—that is, outside the realm of banks and
beyond the scrutiny of regulators. Significantly, the evidence
suggests that very little securitization-based intermediation
is actually in the shadow, with much of it remaining within
the scope of regulated bank entities.
The last two articles in the volume focus on our second
approach to the thesis of bank adaptation, centered on the
organizational transformation of banks and the expanding
role of BHCs. In “A Structural View of U.S. Bank Holding
Companies,” Dafna Avraham, Patricia Selvaggi, and James
Vickery describe the organizational structure and history of
U.S. bank holding companies. While the literature on this
subject draws heavily on aggregate data on bank holding
companies (obtained from the Federal Reserve’s publicly
available FR Y-9C regulatory reports), the authors of this article
merge information from a number of more obscure regulatory
sources to obtain a very detailed set of stylized facts that
document changes in the size and complexity of BHCs over
time. In particular, the authors demonstrate that while the
number of nonbank subsidiaries is an order of magnitude
larger than in the 1990s, most of the structural expansion
beyond the traditional boundaries of commercial banking
has been limited to the largest organizations—a development
that signifies the existence of important economies of scale
with this form of adaptation. In the final article in the volume,
“Evolution and Heterogeneity among Larger Bank Holding
Companies: 1994 to 2010,” Adam Copeland tracks the
changing activities of bank holding companies by analyzing
data on BHC income streams. Adam shows the rising
importance of fee-based income across the largest BHCs,

The Evolution of Banks and Financial Intermediation

and—consistent with our thesis—the increasing importance
of nonbank subsidiaries as a source of income for the larger
organization.

6. Summary and Normative
Suggestions
Financial intermediation has become very complex, and banks’
balance sheets are now less reflective of actual intermediation
activity. However, when intermediation is distilled down to
its basic components, it is still the same system, with the same
roles needed so that funding can be successfully matched
with demand. The crucial difference is that these roles are
performed in a new way, such that it becomes economically
viable, and perhaps more efficient, for different entities to
specialize in providing different services.10
This observation is important, since it has provided a key
to analyze the evolution of banks. We have shown, through
both a role-based and an entity-based approach, that regulated
banking institutions have remained crucially involved in every
step of the credit intermediation chain. This ability to adapt
has occurred in large part through a significant expansion
of the boundaries of the banking firm, with bank holding
companies becoming increasingly broad in the number of
their subsidiaries and the type of activities they have been
engaged in.
Our findings take us back to the policy questions we raised
earlier: With so many nonbanks involved in modern intermediation, and with systemic risk now spread along the chain,
regulatory agencies around the globe are currently considering
reforms to the principles governing the regulation and
monitoring of financial intermediation.11 These efforts are likely
to lead to an expansion of the boundaries of prudential-based
regulation and supervision to include entities and activities that
contributed heavily to systemic events during the crisis.
However, the biggest challenge facing regulators is not
redesigning current regulatory boundaries but delineating
principles and guidelines for monitoring and identifying future
10

We are aware, however, that this decentralization of roles brings with it
new layers of agency/informational friction (see, for example, Ashcraft
and Schuermann [2008]).
11
For example, in response to an explicit mandate by the Group of Twenty,
the Financial Stability Board (2011) is conducting a cross-jurisdiction exercise
(still in process at the time of this article’s publication) aimed at providing both
monitoring and regulatory recommendations to pursue better governance of
financial intermediation activities (see http://www.financialstabilityboard.org/
publications/r_120420c.pdf).

mutations in the system of intermediation—mutations that,
if history has taught us anything, will at least in part be the
result of the battery of regulatory fixes on the table now.
We believe that the results of our analysis can offer insights
on this issue. The demonstrated ability of regulated banking
institutions to adapt to the changing environment suggests that
there may be much to learn about the future evolution of
intermediation directly from the observation of banks. Risks
are still likely to be concentrated in other parts of the system—

that is, outside of banks’ balance sheets—but there is a good
chance a bank will be involved in new mutations of the
intermediation system, either directly or indirectly. This
observation thus suggests a new role for bank supervisors:
In addition to carrying out their main mandate of monitoring
the health of banking firms, supervisors could contribute to
dynamic and forward-looking oversight of the whole system
of financial intermediation as it continues to evolve.

FRBNY Economic Policy Review / July 2012

References

Acharya, V., P. Schnabl, and G. Suarez. Forthcoming. “Securitization
without Risk Transfer.” Journal of Financial Economics.

Gorton, G. B. 2008. “The Panic of 2007.” NBER Working Paper
no. 14358.

Ashcraft, A., and T. Schuermann. 2008. “Understanding the
Securitization of Subprime Mortgage Credit.” Foundations
and Trends in Finance 2, no. 3 (July): 191-309.

Gorton, G. B., and A. Metrick. 2010. “Securitized Banking and the Run
on Repo.” Yale ICF Working Paper no. 09-14.

Boyd, J., and M. Gertler. 1994. “Are Banks Dead? Or Are the Reports
Greatly Exaggerated?” Federal Reserve Bank of Minneapolis
Quarterly Review 18, no. 3 (summer): 2-23.
Choudry, M. 2007. Bank Asset and Liability Management:
Strategy, Trading, Analysis. Singapore: John Wiley and Sons
(Asia) Pte. Ltd.
Coase, R. H. 1937. “The Nature of the Firm.” Economica 4, no. 16
(November): 386-405.
Covitz, D. M., N. Liang, and G. A. Suarez. 2009. “The Evolution of
a Financial Crisis: Panic in the Asset-Backed Commercial Paper
Market.” Board of Governors of the Federal Reserve System
Finance and Economics Discussion Series, no. 2009-26.
Ennis, H. M., and T. Keister. 2010. “On the Fundamental Reasons for
Bank Fragility.” Federal Reserve Bank of Richmond Economic
Quarterly 96, no. 1 (first quarter): 33-58.

Kacperczyk, M., and P. Schnabl. 2010. “When Safe Proved Risky:
Commercial Paper during the Financial Crisis of 2007-2009.”
Journal of Economic Perspectives 24, no. 1 (winter): 29-50.
Kashyap, A., R. Rajan, and J. Stein. 2002. “Banks as Liquidity Providers:
An Explanation for the Coexistence of Lending and DepositTaking.” Journal of Finance 57, no. 1 (February): 33-73.
Knox, J. J. 1900. A History of Banking in the United States.
New York: Rhodes and Company.
McCulley, P. 2007. “Teton Reflections.” PIMCO Global Central
Bank Focus.
Pozsar, Z., T. Adrian, A. Ashcraft, and H. Boesky. 2010. “Shadow
Banking.” Federal Reserve Bank of New York Staff Reports,
no. 458, July.
Reinhart, C. M., and K. S. Rogoff. 2008. “This Time Is Different:
A Panoramic View of Eight Centuries of Financial Crises.”
NBER Working Paper no. 13882.

Financial Stability Board. 2011. “Progress Report to the G20 on
Strengthening the Oversight and Regulation of Shadow Banking.”
Available at http://www.financialstabilityboard.org/publications/
r_120420c.pdf.

The views expressed 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. The Federal Reserve Bank of New York provides no warranty, express or implied, as to the
accuracy, timeliness, completeness, merchantability, or fitness for any particular purpose of any information contained in
documents produced and provided by the Federal Reserve Bank of New York in any form or manner whatsoever.
12

The Evolution of Banks and Financial Intermediation

Peter Olson

Regulation’s Role
in Bank Changes
1. Introduction

anks are heavily involved in facilitating the modern chain
of market-based financial intermediation. This chain
is long and complex: It involves loans originated to be
securitized, special-purpose vehicles that purchase and bundle
these loans, investors who buy the securities, entities that
provide credit and liquidity enhancement to guarantee assets
and make the corresponding securities more reliable, assetbacked commercial paper conduits that sell commercial paper,
money market mutual funds that purchase that commercial
paper, and the repo market, where highly rated securities have
come to be a form of currency (Gorton and Metrick 2010).
There are also many other steps, players, and processes.
The thesis set forth in the introduction to this volume
(Cetorelli, Mandel, and Mollineaux 2012) is that financial
intermediation technology has evolved in recent years and that
banks have adapted to this evolution. However, the authors
remain agnostic as to the causes of this technological evolution,
focusing instead on documenting the evolving role of banks.
The goal of this article is to acknowledge the importance of the
regulatory environment as a main driver of such developments.
In 1986, Nobel Prize–winning economist Merton Miller
spoke of how government action frequently played a role
in the advent of financial innovation, arguing that the
government provided the “grain of sand in the oyster” that
led to the pearl. In fact, Miller went so far as to declare that
“the major impulses to successful financial innovations over
the past twenty years have come from regulations and taxes.”

Peter Olson, a student at Harvard University, wrote this article while working
as a summer intern at the Federal Reserve Bank of New York.

This article is not an attempt to show that regulation has been
the major impulse to innovation, nor does it reason at length
on the endogeneity of regulatory changes (in some instances,
rules are changed to match an evolving marketplace rather
than the reverse, though even then we can learn much from
the law of unintended consequences).1 Rather, it argues that
government involvement has been a significant factor, and
describes a number of the regulatory, legal, and policy
decisions that have influenced the development of this new
financial intermediation landscape and shaped banks’ roles
within it over the past thirty to forty years.

2. The Emergence of Money Market
Mutual Funds
2.1 Increase in the Federal Funds Rate
and Regulation Q
In January 1978, the federal funds rate was 6.5 percent. By
year’s end it had risen to 10 percent (Federal Reserve Bank of
New York 2011). At the time, the interest rate that commercial
1

Kroszner and Strahan explore the nature of regulatory change in a number
of papers (1999, 2001, forthcoming). They argue that much of the banking
deregulation in recent decades—and its timing—can be attributed to the
power that private interests have in pressing for or stalling regulatory change.

The views expressed are those of the author and do not necessarily reflect
the position of the Federal Reserve Bank of New York or the Federal
Reserve System.
FRBNY Economic Policy Review / July 2012

banks could pay on deposits was capped by the Federal Reserve
Board’s Regulation Q (Gilbert 1986), so the rapid increase in
the fed funds rate to such high levels created great demand for
bank substitutes that were safe yet could deliver a higher yield
than banks were legally permitted. In 1980, Congress passed
the Depository Institutions Deregulation and Monetary
Control Act, which mandated the lifting of Regulation Q.
However, by the time the interest rate ceiling was completely
phased out in 1986, money market mutual funds (MMMFs)
were already flourishing. According to Gorton and Metrick
(2010), MMMFs were created as “a response” to the interest
rate caps on bank deposits.

2.2 Money Market Mutual Funds
and Regulation 2a-7
Money market mutual funds gained a reputation for being
very reliable, in part because their investments were legally
restricted to “high-quality” assets. The creation of MMMFs
dates back to the late 1970s and early 1980s, when certain
mutual funds sought relief from the accounting rules of the
Investment Company Act of 1940, which stipulated that the
funds had to mark-to-market the values of their portfolios
(Securities and Exchange Commission 1983). At first, the
Securities and Exchange Commission granted such accounting
exemptions on a case-by-case basis, but in 1983 it codified
these rules in the form of Regulation 2a-7, which stated that, in
exchange for restrictions on the types of assets in which they
could invest, MMMFs were permitted to value their shares
based on either 1) the amortized value, or 2) the current market
value, but rounded to the nearest penny, with one share
equaling one dollar (Securities and Exchange Commission
1983).
Regulation 2a-7 gave MMMFs a special status within the
mutual fund world. Many investors came to believe that
MMMFs were so thoroughly restricted by regulation that they
had an implicit government guarantee, a viewpoint somewhat
validated when the funds were essentially bailed out in 2008, as
Gorton and Metrick (2010) have observed. These authors add
that MMMFs do not pay insurance premiums to the Federal
Deposit Insurance Corporation (FDIC) for this seeming
guarantee—an advantage that has given them a competitive
edge over commercial banks.

3. The Growth of the Repo Market
3.1 Volatile Interest Rates
The dramatic move in the federal funds rate in 1978 was not an
isolated event. Between 1976 and 1981, the funds rate swung
from a low of 4.75 percent to a high of between 19 and
20 percent, then dropped back, slipping below 6 percent
temporarily in 1986 (Federal Reserve Bank of New York 2011).
According to Garbade (2006), the “rising volatility of interest
rates . . . elevat[ed] the importance of risk management.”
Concerns about risk provided fertile ground for the repo, a
contract with powerful hedging potential. For example, if an
investor holding bonds was worried that those bonds might
decline in value, he or she could short-sell securities and use a
reverse repo to borrow the securities to be delivered against the
short sale. If interest rates went up and the value of bonds in the
marketplace decreased, the investor would lose money on the
bonds he or she was holding long, but gain money off the fact
that, when the repo contract came due, he or she could
purchase securities at a lower price than that obtained on the
short sale and use those securities to close out the reverse repo.
If interest rates went down, the investor would lose money
on the short sale, but that loss would be offset by the increase
in the value of the bonds held long. The volatile interest rate
environment made such hedging tactics more of a priority, and
repo use grew as a result (Garbade 2006).
The repo market was not used solely for hedging purposes,
however. According to Acharya and Oncu (2011), those
wanting to invest large sums on a temporary basis found
repos attractive because 1) funds in the repo market can earn
a higher interest rate than funds in commercial bank deposits,
and 2) funds in the repo market are safe (backed by
collateral), whereas, beyond the FDIC-insurance limit, funds
in commercial banks are not. Consequently, the rise of the
repo market is directly relevant to commercial banks because
the repo market is a substitute for commercial bank deposits.
As Gorton and Metrick (2009) put it, “Repurchase agreements are economically like demand deposits; they play the
same role as demand deposits, but for firms operating in the
capital markets.”

3.2 Bankruptcy-Remote Status for Repos
As repos grew in popularity, a major legislative event secured
the efficacy of the repo contract. For years, ambiguity about
whether the repo contract represented the formal sale of a

Regulation’s Role in Bank Changes

security or merely the lending of a security had served traders
well; clients who did not want to purchase a security could
be told that it was a loan, and vice versa (Stigum 1983). But
there was the presumption that if an investment bank or other
firm dealing a security through a repo contract went bankrupt,
the security would remain firmly in the hands of the counterparty. If this were not the case and repos were subject to the
automatic stay (the restriction that the assets of bankrupt firms
be frozen until the court determines how those assets should
be distributed), the value of the security could potentially
fall in the interim while the counterparty waited to receive
the asset. In short, having repos be subject to bankruptcy
proceedings would dramatically decrease the usefulness of
the repo contract, a mainstay of today’s financial system
(Garbade 2006; Stigum 1983).
In 1982, the issue finally arose in court and it was decided
that repos were merely “secured loans” (Garbade 2006). This
conclusion was worrisome to many, including Federal Reserve
Chairman Paul Volcker. Prompted in part by Chairman
Volcker’s recommendation, Congress passed the Bankruptcy
Amendments and Federal Judgeship Act of 1984, which,
though it did not settle the loan/sale issue, protected repos
involving Treasury and federal agency securities from the
automatic stay (Schroeder 1996; Garbade 2006). Were it not
for this legislation, repos would likely not be the foundational
transaction tool they are today because being subject to the
bankruptcy process would make them a far less sure form
of collateral.

4. Rise and Growth of Securitization
4.1 Government-Sponsored Enterprises’
Involvement in Mortgage-Backed
Securities
As DeYoung (2007) has observed, “Securitization is a story
about government intervention right from the beginning.
Securitization began in the 1960s with the creation of the
Ginnie Mae pass-through and exploded in the 1980s with the
development of the collateralized mortgage obligation.”
In 1968, Congress granted Ginnie Mae (the Government
National Mortgage Association) the right to issue mortgagebacked securities, known as MBS (Oesterle 2010), and
Ginnie Mae did so for the first time in 1970 (McConnell and
Buser 2011). Freddie Mac (the Federal Home Loan Mortgage

Corporation) followed suit in 1971, and Fannie Mae (the
Federal National Mortgage Association) adopted the practice
ten years later (White 2004). Initially, MBS could be issued
only on mortgages guaranteed or insured by the government,
but the Emergency Home Finance Act of 1970 lifted that
restriction for Freddie Mac and Fannie Mae, enabling them
to buy mortgages with no government guarantee (Reiss 2008;
Van Order 2000; Carrozzo 2005). Since then, Freddie Mac and
Fannie Mae have securitized huge numbers of mortgages. As
of 2009, total Freddie Mac and Fannie Mae outstanding MBS
issuance stood at nearly $4 trillion (Dynan and Gayer 2011).

4.2 Creation of the Real Estate Mortgage
Investment Conduit
In 1983, the government-sponsored enterprises once again
found themselves on the cutting edge of securitization practices
when Freddie Mac became the first institution to issue
collateralized mortgage obligations (CMOs), which are multiclass mortgage-backed securities—or, in other words, MBS
with multiple tranches (McConnell and Buser 2011; Roll
1987). Before long, the private sector followed suit (Kolb 2011).
CMOs were useful because they allowed investors to
purchase tranches with varying characteristics. For example,
investors who were concerned about prepayment risk (the risk
that a loan will be paid off early because of a decline in interest
rates, thus leaving the investor in a poor environment for
reinvesting those funds) could purchase securities designed to
mitigate that risk (Hu 2011). A complicating factor facing
multi-class trusts was that their payments were considered
equity dividends, which are not tax deductible, whereas
payments to a traditional nontranched, pass-through security
were considered payments on debt, which are tax deductible
(Fabozzi 2001). This meant that, when money flowed from the
loans to the investors, not only did the investors have to pay
taxes, but the trusts needed to as well. “The resulting double
taxation . . . made the transaction economically impractical,”
notes Fabozzi (2001).
Collateralized mortgage obligations were an innovation
because, as the name suggests, they were structured such that
their payments were debt payments collateralized by
traditional pass-through securities rather than equity
payments, and were thus tax deductible for the trust issuing
them (Fabozzi 2001; Hu 2011). However, the structural
constraints on CMOs were burdensome (residual interests
needed to be held, capital requirements needed to be met, and
so forth), making it difficult to issue the securities efficiently
(Fabozzi 2001).

FRBNY Economic Policy Review / July 2012

In the tax reform of 1986, Congress eliminated the doubletaxation problem by calling for the creation of the real estate
mortgage investment conduit (REMIC), a tax-exempt specialpurpose vehicle specially designated for issuing multi-class
MBS.2 REMICs are “the tax vehicle of choice” in the multi-class
mortgage-backed-securities market today (Peaslee and
Nirenberg 2001).

4.3 Increasing Bank Capital Requirements
In 1981, regulators decided to impose primary capital
requirements equal to 5 percent and 6 percent of total assets
on regional banks and community banks, respectively (Wall
1989). In 1983, capital requirements of 5 percent of total
assets were applied to multinational banks (Wall 1989; Baer
and McElravey 1993). Then, in 1988, the Basel Committee
on Banking Supervision passed a set of stricter capital
requirements that were intended to provide the international
banking community with a consistent capital ratio framework. Basel I, as it is called, was fully phased in by 1992 and
required banks to have capital reserves equal to 8 percent of
their risk-weighted assets (Choudhry 2007).
However, this “stricter” set of requirements disproportionately favored mortgage-backed securities. For instance, cash
had a risk multiplier of zero percent, so holding additional
cash did not require a bank to hold additional capital, and
MBS had a risk-weight of 50 percent, so acquiring an
additional $10,000 of MBS meant that a bank would need
$10,000 x 0.5 x 0.08 = $400 more capital. However, other
“customer loans are 100 percent risk-weighted regardless of
the underlying rating of the borrower or the quality of the
security held” (Choudhry 2007).
It was in part to correct the oversimplified nature of Basel I
that Basel II was developed. Among other changes, it gave
banks the choice between three different capital frameworks.
The “standardized approach” was essentially the same as
Basel I, but it incorporated asset ratings and applied more
risk-weighting gradations between different assets. Meanwhile,
the “foundation and advanced internal ratings-based (IRB)
approaches” allowed banks to use their own, more sophisticated models of risk (Choudhry 2007). It is important to note,
however, that the Basel II standards had not been implemented
in the United States when the financial crisis hit (Elliott 2010).

CMOs essentially disappeared in the early 1990s, so today the term CMO
generally refers to a REMIC structure (Hu 2011).

Regulation’s Role in Bank Changes

The introduction of capital requirements in 1981, and the
various revisions of those requirements in the decades since
then (under the Basel capital rules), has had the significant
unanticipated consequence of motivating banks to move
assets off their balance sheets in order to avoid the regulatory
capital cost. Securitization provided an effective way to
accomplish this. As Kroszner and Strahan (forthcoming) put
it, “Efforts to avoid capital may in part explain the rise in offbalance-sheet banking during the 1980s. Similarly, the 1988
Accord may have encouraged banks to securitize loans in
order to reduce required capital ratios.” Likewise, Choudhry
(2007) argues that “the Basel I rules . . . have been a driving
force behind securitization” and that banks now use securitization “to improve balance sheet capital management.”

4.4 Low Capital Requirements for Banks’
Liquidity Support of Asset-Backed
Commercial Paper
Interpretation 46, issued by the Financial Accounting
Standards Board in 2003, stated that all commercial banks
needed to include information in their financial reports about
the special-purpose vehicles for which they were the primary
beneficiaries. This rule would have meant that banks needed to
include in their capital requirement calculations the assetbacked commercial paper (ABCP) conduits to which they
provided credit and liquidity support. However, in 2004,
the Office of the Comptroller of the Currency, the FDIC, the
Office of Thrift Supervision, and the Federal Reserve made
ABCP conduits exempt from the consolidation rules. Instead,
regulators decided that the liquidity guarantees extended to
ABCP conduits required a capital charge of one-tenth the
capital needed to hold an equivalent dollar value of loans
on the balance sheet, though credit guarantees had capital
requirements similar to on-balance-sheet loans (Acharya,
Schnabl, and Suarez, forthcoming; Gilliam 2005).
According to Acharya, Kulkarni, and Richardson (2011),
banks were able to “exploit a loophole in Basel capital
requirements” and structure their guarantees as “so-called
liquidity enhancements,” which were effectively credit
guarantees but without the more stringent capital requirements. Thus, banks could move loans off their balance sheets,
securitize them, and then provide them with liquidity support.
This strategy would leave banks with one-tenth the capital
charges but the same level of risk they would have had if they
had held the loans on their balance sheets (Acharya, Schnabl,
and Suarez, forthcoming).

5. Changes to Banking Structure
5.1 Laws Promoting Growth of Interstate
Banking and Branching
As documented in the introduction to this volume, banks have
adapted to recent changes in intermediation technology by
expanding into nontraditional banking activities and taking up
the many roles needed in the process of asset securitization.
The existence of important economies of scale in adopting this
different business model made growth in size a necessity; yet
for much of the twentieth century, banks faced expansion
restrictions. As Jayaratne and Strahan (1996) note, bank
holding companies of one state were not allowed to engage in
interstate banking (owning and operating banks in different
states), and most states prohibited individual banks from
intrastate branching (opening new branches within the state).
Moreover, as pointed out by McLaughlin (1995), banks were
prevented from engaging in interstate branching (opening
branches in other states).
In 1978, Maine passed a law allowing bank holding
companies of other states to purchase banks in Maine if those
states would grant Maine’s bank holding companies the same
privilege in return. Other states followed suit, and by 1992—
with the exception of Hawaii—all the states had passed such
legislation (Strahan 2003; Jayaratne and Strahan 1998). The
Office of the Comptroller of the Currency furthered this
movement in the mid-1980s by allowing banks with national
charters to branch into any state that permitted the unrestricted
branching of savings institutions (Strahan 2003). Intrastate
branching was permitted in many states in some form even
before the 1970s, and the percentage of states for which this was
true increased substantially over the subsequent decades. By
1992, statewide branching was permissible in almost all states
(Strahan 2003; Jayaratne and Strahan 1998).
Finally, in 1994, Congress passed the Riegle-Neal Interstate
Banking and Branching Efficiency Act.3 It required complete
interstate banking by 1997 and encouraged states to permit
interstate branching, which all states except Texas and
Montana did (Strahan 2003). The interstate banking and
branching deregulation commenced by the states and
furthered by the federal government contributed to the
consolidation of U.S. commercial banks. Indeed, DeYoung
(2007) writes that, after Riegle-Neal was passed, “the
immediate response was the highest ever five-year run of
3

See http://www.gpo.gov/fdsys/pkg/BILLS-103hr3841enr/pdf/BILLS
-103hr3841enr.pdf.

bank mergers in U.S. history in terms of both the number
and the value” (Berger et al. 2004).

5.2 The Gramm-Leach-Bliley Act
In the wake of the catastrophic bank failures at the beginning
of the Great Depression, legislators passed the Banking Act
of 1933 (also known as the Glass-Steagall Act), which, among
other things, segregated commercial banking activities from
investment banking activities (Cornett, Ors, and Tehranian
2002; Spong 2000). From 1933 to 1963, banks largely adhered
to the provisions of Glass-Steagall, but from 1963 to 1987 they
challenged the restrictions on their ability to underwrite
mortgage-backed securities, municipal bonds, and commercial
paper—and often won in court. Then, with this “de facto
erosion of the Glass-Steagall Act by legal interpretation,” in
1987 the Federal Reserve permitted bank holding companies
to hold both commercial banks and investment banks, as long
as no more than 5 percent of the investment banks’ revenue
was from “ineligible securities activities” (Cornett, Ors, and
Tehranian 2002). This limit was increased to 10 percent in 1989
and to 25 percent in 1996.
This trend toward deregulation continued in subsequent
years. In 1999, Congress passed the Financial Services
Modernization Act (also known as the Gramm-Leach-Bliley
Act), which created the financial holding company structure.
Under this legislation, a financial holding company could have
commercial banks, securities firms, and insurance companies
as subsidiaries (Spong 2000). According to Spong, this act
“[set] the stage for dramatic changes within the financial
industry.” By permitting commercial banks to engage in a wide
variety of fee-based activities such as equity and debt
underwriting, securities brokerage, and insurance products,
the Gramm-Leach-Bliley Act played a part in commercial
banks’ shift away from traditional on-balance-sheet banking
toward off-balance-sheet, noninterest income sources
(DeYoung 2007).

6. Conclusion
The government actions described in this article fall into a few
distinct categories, and these categories reveal much about the
growth of the financial intermediation industry as it relates to
banks. In some cases, the government enacted restrictions that
indirectly encouraged financial innovation by prompting

FRBNY Economic Policy Review / July 2012

banks and other actors to seek ways of circumventing the new
rules. For example, Regulation Q led to the growth of money
market mutual funds, while capital requirements indirectly
promoted securitization and other off-balance-sheet activities.
Sometimes the government explicitly promoted or
protected a particular entity, as it did when it declared
asset-backed-commercial-paper conduits exempt from
Interpretation 46, and again when it created the real estate
mortgage investment conduit. In other instances, the government simply created an environment that proved fertile
ground for innovation. Thus, the volatile interest rates of

Regulation’s Role in Bank Changes

the late 1970s and early 1980s encouraged the growth of
repo contracts. And in the most obvious example of its
involvement, the government put into practice its new
vision of commercial banking by explicitly approving the
consolidation of commercial banks through the Riegle-Neal
Act and by expanding the banks’ stock of permissible
activities with the Gramm-Leach-Bliley Act.
In these and other ways, the guiding hand of policy and
regulation has been influential in altering the institutions,
contracts, and instruments used in financial intermediation
and in reshaping the role that banks play in this process.

References

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Contingent Capital, and Liquidity Requirements.” Regulating
Wall Street, Chap. 6. Hoboken, N.J.: Wiley.
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Market.” Regulating Wall Street, Chap. 11. Hoboken, N.J.:
Wiley.

Elliott, D. 2010. “Basel III, the Banks, and the Economy.” Brookings
Institution paper, July.
Fabozzi, F. 2001. The Handbook of Mortgage-Backed
Securities. New York: McGraw Hill.

Acharya, V., P. Schnabl, and G. Suarez. Forthcoming. “Securitization
without Risk Transfer.” Journal of Financial Economics.

Federal Reserve Bank of New York. 2011. “Historical Changes of the
Target Federal Funds and Discount Rates: 1971 to Present.”
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Baer, H., and J. McElravey. 1993. “Capital Shocks and Bank Growth—
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Garbade, K. 2006. “The Evolution of Repo Contracting Conventions
in the 1980s.” Federal Reserve Bank of New York Economic
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Berger, A., C. Buch, G. DeLong, and R. DeYoung. 2004. “Exporting
Financial Institutions Management via Foreign Direct Investment
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Gilbert, R. 1986. “Requiem for Regulation Q: What It Did and Why
It Passed Away.” Federal Reserve Bank of St. Louis Review,
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Gilliam, L. 2005. “Accounting Consolidation versus Capital
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Emergency Home Finance Act of 1970, Standardization, and
the Secondary Market Revolution.” Real Property, Probate,
and Trust Journal 39, no. 4 (winter).
Cetorelli, N., B. H. Mandel, and L. Mollineaux. 2012. “The Evolution
of Banks and Financial Intermediation: Framing the Analysis.”
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no. 2 (July): 1-12.

Calculation: The Conflict over Asset-Backed Commercial Paper
Programs.” North Carolina Banking Institute Journal 9,
February: 291-315.
Gorton, G., and A. Metrick. 2009. “The Run on Repo and the Panic
of 2007-2008.” Unpublished paper, Yale University.

———. 2010. “Regulating the Shadow Banking System.” Brookings
Papers on Economic Activity, fall.

Choudhry, M. 2007. Bank Asset and Liability Management.
Singapore: Saik Wah Press Pte Ltd.

Hu, J. 2011. Asset Securitization: Theory and Practice.
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Cornett, M., E. Ors, and H. Tehranian. 2002. “Bank Performance
around the Introduction of a Section 20 Subsidiary.” Journal
of Finance 57, no. 1 (February): 501-21.

Jayaratne, J., and P. Strahan. 1996. “The Finance-Growth Nexus:
Evidence from Bank Branch Deregulation.” Quarterly Journal
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DeYoung, R. 2007. “Safety, Soundness, and the Evolution of the U.S.
Banking Industry.” Federal Reserve Bank of Atlanta Economic
Review 92, no. 1-2 (first and second quarters): 41-66.

———. 1998. “Entry Restrictions, Industry Evolution, and Dynamic

Dynan, K., and T. Gayer. 2011. “The Government’s Role in the
Housing Finance System: Where Do We Go from Here?”
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Kolb, R. 2011. The Financial Crisis of Our Time. New York:
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FRBNY Economic Policy Review / July 2012

References (Continued)

Kroszner, R., and P. Strahan. 1999. “What Drives Deregulation?
Economics and Politics of the Relaxation of Bank Branching
Restrictions.” Quarterly Journal of Economics 114, no. 4
(November): 1437-67.

———. 2001. “Obstacles to Optimal Policy: The Interplay of Politics
and Economics in Shaping Banking Supervision and Regulation
Reforms.” In Frederic S. Mishkin, ed., Prudential Supervision:
What Works and What Doesn’t. Chicago: University of
Chicago Press.

———. Forthcoming. “Regulation and Deregulation of the U.S.
Banking Industry: Causes, Consequences, and Implications for the
Future.” In N. L. Rose, ed., Economic Regulation and Its
Reform: What Have We Learned? NBER conference volume.
Chicago: University of Chicago Press.
McConnell, J., and S. Buser. 2011. “The Origins and Evolution of the
Market for Mortgage-Backed Securities.” Annual Review of
Financial Economics 3, December: 173-92.
McLaughlin, S. 1995. “The Impact of Interstate Banking and
Branching Reform: Evidence from the States.” Federal Reserve
Bank of New York Current Issues in Economics and
Finance 1, no. 2 (May).
Miller, M. 1986. “Financial Innovation: The Last Twenty Years and the
Next.” Journal of Financial and Quantitative Analysis 21,
no. 4 (December): 459-71.
Oesterle, D. 2010. “The Collapse of Fannie Mae and Freddie Mac:
Victims or Villains?” Ohio State Entrepreneurial Business
Law Journal 5, no. 2: 733-60.

Roll, R. 1987. “Collateralized Mortgage Obligations: Characteristics,
History, Analysis.” In F. Fabozzi, ed., Mortgage-Backed
Securities. Chicago: Probus.
Schroeder, J. 1996. “Repo Madness: The Characterization of
Repurchase Agreements under the Bankruptcy Code and
the UCC.” Syracuse Law Review 46: 999-1050.
Securities and Exchange Commission. 1983. “Valuation of Debt
Instruments and Computation of Current Price Per Share by
Certain Open-End Investment Companies (Money Market
Funds).” Federal Register 48, no. 138 (July): 32555-565.
Spong, K. 2000. Banking Regulation: Its Purposes,
Implementation, and Effects. 5th ed. Federal Reserve Bank
of Kansas City.
Stigum, M. 1983. The Money Market. Rev. ed. Homewood, Ill.:
Dow Jones-Irwin.
Strahan, P. 2003. “The Real Effects of U.S. Banking Deregulation.”
Federal Reserve Bank of St. Louis Review 85, no. 4 (July-August):
111-28.
Van Order, R. 2000. “The U.S. Mortgage Market: A Model of Dueling
Charters.” Journal of Housing Research 11, no. 2: 233-55.
Wall, L. 1989. “Capital Requirements for Banks: A Look at the 1981
and 1988 Standards.” Federal Reserve Bank of Atlanta Economic
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True Privatization Is Good Public Policy.” Cato Institute Policy
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Peaslee, J., and D. Nirenberg. 2001. Federal Income Taxation
of Securitization Transactions. 3d ed. New Hope, Penn.:
Frank J. Fabozzi Associates.
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Fannie Mae and Freddie Mac’s Obligations: Uncle Sam Will
Pick Up the Tab.” Georgia Law Review 42: 1019-81.

The views expressed are those of the author and do not necessarily reflect the position of the Federal Reserve Bank of New York
or the Federal Reserve System. The Federal Reserve Bank of New York provides no warranty, express or implied, as to the
accuracy, timeliness, completeness, merchantability, or fitness for any particular purpose of any information contained in
documents produced and provided by the Federal Reserve Bank of New York in any form or manner whatsoever.
20

Regulation’s Role in Bank Changes

Vitaly M. Bord and João A. C. Santos

The Rise of the Originateto-Distribute Model
and the Role of Banks in
Financial Intermediation
1. Introduction
istorically, banks used deposits to fund loans that they
then kept on their balance sheets until maturity. Over
time, however, this model of banking started to change. Banks
began expanding their funding sources to include bond
financing, commercial paper financing, and repurchase
agreement (repo) funding. They also began to replace their
traditional originate-to-hold model of lending with the socalled originate-to-distribute model. Initially, banks limited
the distribution model to mortgages, credit card credits, and
car and student loans, but over time they started to apply it
to corporate loans. This article documents how banks adopted
the originate-to-distribute model in their corporate lending
business and provides evidence of the effect that this shift has
had on the growth of nonbank financial intermediation.
Banks first started “distributing” the corporate loans they
originated by syndicating loans and also by selling them in the
secondary loan market.1 More recently, the growth of the
market for collateralized loan obligations (CLOs) has provided

In loan syndications, the lead bank usually retains a portion of the loan and
places the remaining balance with a number of additional investors, usually
other banks. This arrangement is made in conjunction with, and as part of,
the loan origination process. In contrast, the secondary loan market is a
seasoned market in which a bank, including lead banks and syndicate
participants, can subsequently sell an existing loan (or part of a loan).

Vitaly M. Bord is a former associate economist and João A. C. Santos
a vice president at the Federal Reserve Bank of New York.
Correspondence: joao.santos@ny.frb.org

banks with yet another venue for distributing the loans that
they originate. In principle, banks could create CLOs using the
loans they originated, but it appears they prefer to use collateral
managers—usually investment management companies—that
put together CLOs by acquiring loans, some at the time of
syndication and others in the secondary loan market.2
Banks’ increasing use of the originate-to-distribute model
has been critical to the growth of the syndicated loan market,
of the secondary loan market, and of collateralized loan
obligations in the United States. The syndicated loan market
rose from a mere $339 billion in 1988 to $2.2 trillion in 2007,
the year the market reached its peak. The secondary loan
market, in turn, evolved from a market in which banks
participated occasionally, most often by selling loans to other
banks through individually negotiated deals, to an active,
dealer-driven market where loans are sold and traded much
like other debt securities that trade over the counter. The
volume of loan trading increased from $8 billion in 1991 to
$176 billion in 2005.3 The securitization of corporate loans also
experienced spectacular growth in the years that preceded the
financial crisis. Before 2003, the annual volume of new CLOs
issued in the United States rarely surpassed $20 billion. After
2

According to the Securities Industry and Financial Markets Association,
97 percent of corporate loan CLOs in 2007 were structured by financial
institutions that did not originate the loans.

The authors thank Nicola Cetorelli, Stavros Peristiani, an anonymous reviewer,
and participants at a Federal Reserve Bank of New York seminar for useful
comments. The views expressed 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.

FRBNY Economic Policy Review / July 2012

that, loan securitization grew rapidly, topping $180 billion
in 2007.
Investigating the extent of U.S. banks’ adoption of the
originate-to-distribute model in corporate lending has proved
difficult because of data limitations. Thomson Reuters Loan
Pricing Corporation’s DealScan database, arguably the most
comprehensive data source on the syndicated loan market and
the source used by many researchers in the past, imposes
serious limitations on the investigation of this issue. This
database includes information available only at the time of loan
origination, making it impossible to use it to investigate what
happens to the loan after origination. Furthermore, DealScan
has very limited information on investors’ loan shares at the
time of origination. The information on the credit shares
that each syndicate participant holds is sparse, and even the
information on the share that the lead bank—the bank that sets
the terms of the loan—retains at origination is missing for
71 percent of all DealScan credits.
The Loan Syndication Trading Association database
contains micro information on the loans traded in the
secondary market, but it has no information about the identity
of the seller(s) or buyer(s), ruling out its use to close the
information gaps in DealScan. Financial statements filed with
the Federal Reserve, in turn, contain information only on the
credit that banks keep on their balance sheets and thus cannot
be used to ascertain the volume of credit that banks originate.
These statements contain information on the loans that banks
hold for sale, but, as Cetorelli and Peristiani (2012) explain in
detail elsewhere in this volume, this variable provides limited
information on the extent to which banks have replaced the
originate-to-hold model with the originate-to-distribute
model in their lending business.4
We rely instead on a novel data source, the Shared National
Credit program (SNC) run by the Federal Deposit Insurance
Corporation, the Board of Governors of the Federal Reserve
System, and the Office of the Comptroller of the Currency. Like
DealScan, the SNC program is dominated by syndicated loans.
In contrast to DealScan, however, the SNC program tracks
3

Researchers have suggested several explanations for the development of the
secondary market, including the capital standards introduced with the 1988
Basel Accord (Altman, Gande, and Saunders 2004), the standardization of
loan documentation and settlement procedures that came about with the
establishment of the Loan Syndication Trading Association in 1995 (Hugh and
Wang 2004), and the increase in demand and liquidity resulting from the
increasing involvement of institutional investors (Yago and McCarthy 2004).
See Gorton and Haubrich (1990) for a detailed description of the loan-sales
market in the 1980s.
4
This variable does not distinguish corporate loans from all the other loans
that banks may intend to sell. Further, since there is no information on when
the loans held for sale were originated, ascertaining banks’ relative use of the
originate-to-distribute model based on this variable is difficult. Lastly, the
variable reports only the loans that banks “intend” to sell, not the actual
loans that they sold.

The Rise of the Originate-to-Distribute Model

loans over time, and it has complete information on investors’
loan shares over the life of the credit. We discuss the SNC
database in more detail in the data section.
Our study of the change in banks’ corporate lending model
yields a number of significant findings. Although the data
indicate that lead banks increasingly used the originate-todistribute model from the early 1990s on, we conclude that this
increase was limited to a large extent to term loans; in their
credit-line business with corporations, banks continued to rely
on the traditional originate-to-hold model. Further, we find
that lead banks increasingly “distributed” their term loans by
selling larger portions of them not only at the time of the loan
origination, but also in the years after origination. For example,
in 1988, the first year of our sample, lead banks retained in
aggregate 21 percent of the term loans they originated that year.
In 2007, lead banks retained only 6.7 percent of the term loans
originated in that year. By 2010, lead banks had managed to
further lower their share in the credits they had originated in
2007 to 3.4 percent.
Our investigation into the entities investing in bank loans
confirms that other banks were not quick to step in and take
over as lead banks reduced their stake in the loans they
originated. Instead, we find that new loan investors, including
investment managers and CLOs, increasingly assumed
control of the credit business. In 1993, all together, nonbank
investors acquired 13.2 percent of the term loans originated
that year. In 2007, they acquired 56.3 percent of the term
loans originated in that year, a 327 percentage point increase
from fifteen years earlier.
The trends documented in this article have important
implications. Banks’ increasing use of the originate-todistribute model in their term-lending business will lead to a
transfer of important portions of credit risk out of the banking
system. In the process, however, it will contribute to the growth
of financial intermediation outside the banking system,
including a larger role for unregulated “shadow banking”
institutions.5 It will also, over time, make the credit kept by
banks on their balance sheets less representative of the stillessential role they perform in financial intermediation.
In addition, banks’ increasing use of the originate-todistribute model could lead to some weakening of lending
standards. According to several theories—including those of
Ramakrishnan and Thakor (1984), Diamond (1984), and
Holmström and Tirole (1993)—banks add value because of
their comparative advantage in monitoring borrowers. To
carry out this task properly, banks must hold the loans they
originate until maturity. If they instead anticipate keeping only
a small portion of a loan, their incentives to screen loan
5

See Pozsar et al. (2010) for a detailed account of the growth of shadow
banking in the United States.

applicants properly and to design the terms of the loan contract
will diminish.6 They will also have less incentive to monitor
borrowers during the life of the loan.7 The growth of the
CLO business has likely exacerbated these risks because
CLO investors invest in new securities that depend on the
performance of the “reference portfolio,” which is made up
of many loans, often originated by different banks.8
Banks’ adoption of the originate-to-distribute model may
also hinder the ability of corporate borrowers to renegotiate
their loans after they have been issued.9 This difficulty may
arise not only because the borrower will have to renegotiate
with more investors but also because the universe of investors
acquiring corporate loans is more heterogeneous.
Finally, our evidence that banks continue to use the
traditional originate-to-hold model in the provision of credit
lines supports the argument that banks retain a unique ability
to provide liquidity to corporations, possibly because of their
access to deposit funding.10 Our findings are in line with the
theories advanced by Holmström and Tirole (1998) and
Kashyap, Rajan, and Stein (2002) concerning banks’ liquidity
provision to corporations. Still, as Santos (2012) documents,
banks’ provision of liquidity to depositors and corporations
exposes them to a risk of concurrent runs on both sides of their
balance sheets.
The remainder of our article is organized as follows.
The next section presents our data and methodology and
characterizes our sample. Section 3 documents U.S. banks’
transition from the originate-to-hold model to the originateto-distribute model in corporate lending over the past two
decades. Section 4 identifies the relative role of the various
investors that increasingly buy the credit originated by
banks. Section 5 summarizes our findings and their larger
implications.

See Pennacchi (1988) and Gorton and Pennacchi (1995) for models that
capture these moral hazard problems.
7
Recent studies, including Sufi (2007), Ivashina (2009), and Focarelli, Pozzolo,
and Casolaro (2008), document that lead banks in loan syndicates use the
retained share to align their incentives with those of syndicate participants
and commit to future monitoring.
8
See Bord and Santos (2010) for evidence that the rise of the CLO business
contributed to riskier lending.
9
Borrowers often renegotiate their credits to adjust the terms of their loans
(Roberts and Sufi 2009) or to manage the maturity they have left in their credits
(Mian and Santos 2011).
10
See Gatev, Schuermann, and Strahan (2009) and Gatev and Strahan (2006)
for empirical evidence in support of banks’ dual liquidity role to depositors
and corporations.

2. Data, Methodology, and Sample
Characterization
2.1 Data
Our main data source for this project is the Shared National
Credit program, run by the Federal Deposit Insurance
Corporation, the Federal Reserve Board, and the Office
of the Comptroller of the Currency. At the end of each year,
the SNC program gathers confidential information on all
credits that exceed $20 million and are held by three or more
federally supervised institutions.11
For each credit, the SNC program reports the identity of the
borrower, the type of the credit (term loan or credit line, for
example), purpose (such as working capital, mergers, or
acquisitions), amount, maturity date, and rating. In addition,
the program reports information on the lead arranger and
syndicate participants, including their identities and the share
of the credit they hold.
The SNC data fit nicely with our goal of investigating
the role that banks continue to play in the origination of
corporate credit in the United States and the role they have
played in the growth of financial intermediation outside the
banking system. Since the SNC program gathers information
on each syndicated credit at the end of every year, we can link
credits over time and determine the portion of each credit
that stays in the banking sector and the portion acquired by
nonbank financial institutions both at the time of the credit
origination and in each subsequent year during the life of
the credit. In addition, since we have this information over
the past two decades, we can investigate how the relative
importance of the various players in the syndicated loan
market has evolved over time.
We complement the SNC data with information from the
Moody’s Structured Finance Default Risk Service Database and
from Standard and Poor’s Capital IQ. The Moody’s database
has information on structured finance products, including the
size, origination date, and names. We rely on the Moody’s
database to identify CLOs among the syndicate participants
reported in the SNC program that do not have the letters CLO
in their names. We use the Capital IQ database to identify
private equity firms, hedge funds, and mutual funds among
the syndicate participants.
11

The confidential data were processed solely within the Federal Reserve
for the analysis presented in this article.

FRBNY Economic Policy Review / July 2012

2.2 Methodology
Our investigation into the effect of the originate-to-distribute
model on the importance of banks in financial intermediation
has two parts. We begin by investigating how the rise of that
model affected the portion of each credit that the lead bank
retains during the life of the credit. To this end, for each credit
in the SNC program, we first compute the portion that the lead
bank retains on its balance sheet at origination. Next, because
banks sometimes sell or securitize part of their credits after they
originate them, we compute the portion of the credit that the
lead bank still retains on its balance sheet three years after the
origination year.
In the second part of our investigation, we identify the
buyers of bank credits and how the role of the various buyers
has changed over the past two decades. For each credit, we
compute the portion that the lead bank sells to other banks
and the portion that it sells outside the banking sector,
distinguishing in the latter case whether the acquiring
institution is an insurance company, a finance company, a
pension fund, an investment manager, a private equity firm,
a CLO, or a broker or investment bank. This part of our
investigation allows us to pin down the role that banks have
played in the growth of financial intermediation outside the
banking system in general and their role in the growth of
shadow banking in particular.
Because the nature of the credit contract may affect
the lead bank’s ability to sell or securitize the credit, we
distinguish between term loans and credit lines throughout
our investigation. For a similar reason, we also categorize the
credits according to their purpose: that is, whether they are
to fund mergers and acquisitions or capital expenditures
or whether they are to serve corporate purposes.

2.3 Sample Characterization
Our sample covers the period 1988-2010. On average, we
observe 7,432 credits each year. Of these, 1,758 are new credits
originated in the year, and 5,674 are credits originated in prior
years. Even though the criteria for inclusion of a credit in the
SNC program remained unchanged throughout the sample
period, inflation and growth over the past two decades

The Rise of the Originate-to-Distribute Model

contributed to an upward trend in the number of credits in the
SNC database. In 1989, the SNC database had 5,402 credits, of
which 1,368 were originated in that year. In 2007, at the peak
of the business cycle, it had 8,248 credits, of which 2,114 were
originated in that year.
To get a better sense of the SNC database coverage, we
compare the annual value of credits included in that database
with the annual value of credits in DealScan, the database
mentioned above that has been extensively used for research on
bank corporate lending in recent years.12 Chart 1 reports the
annual value of new credits—that is, credits originated in each
year—in the SNC database and the annual value of credits
reported in DealScan. Since SNC covers only credits above
$20 million, we also report the annual value of credits in
DealScan above that threshold. To make the information from
the two databases even more comparable, we further adjust the
information reported from DealScan by excluding credits that
are classified as “restatements” of previous credits, since this
indicates a renegotiation of an existing credit.13
From Chart 1, it is apparent that both databases pick up the
positive trend in the volume of credit as well as the effect of the
three recessions in the United States during the sample period
(1990-91, 2001, and 2008-09). It is also clear that the main
difference between the two databases is that DealScan reports
information on new credits as well as information on renegotiations of existing credits. The fact that SNC reports only credits
above $20 million while DealScan contains information on
credits above $100,000 does not constitute an important
difference between the two databases. When we adjust the
information reported in DealScan to “match” the credits
reported in the SNC database, the difference between the
two databases becomes very small. On average, each
year the volume of credit reported in the SNC database
is 37.2 percent of that reported in DealScan. When we restrict
the credits in DealScan to those above $20 million, that share
increases to 37.8 percent; when we further drop renegotiations
from DealScan, the share rises to 74.4 percent.

Examples of papers that use DealScan include Dennis and Mullineaux
(2000), Hubbard, Kuttner, and Palia (2002), Santos and Winton (2008, 2010),
Hale and Santos (2009, 2010), Sufi (2007), Bharath et al. (2009), Santos (2011),
Paligorova and Santos (2011), and Bord and Santos (2011).
13
In SNC, renegotiations do not usually give rise to a new credit, while in
DealScan they do.

Chart 1

Loan Volumes Reported in the SNC and DealScan Databases
Billions of U.S. dollars

Billions of U.S. dollars
2,400
2,200

2,400
2,200

SNC Issuance by Year

2,000

1,800

1,600
1,400

1,200

1,000

800

600

400

200
0

200
0
1990

1995

2000

2005

2010

LPC Issuance by Year
All loans

Loans of greater
than $20 million
Loans of greater than
$20 million, excluding
renegotiations

1990

1995

2000

2005

2010

Sources: Shared National Credit (SNC) database, produced jointly by the Federal Deposit Insurance Corporation, Board of Governors of the Federal
Reserve System, and Office of the Comptroller of the Currency; DealScan database, produced by Thomson Reuters Loan Pricing Corporation (LPC).

3. From Originate-to-Hold
to Originate-to-Distribute
In traditional banking, banks originate credits and hold them
on their balance sheet until their maturity. Over time, however,
banks began to replace the originate-to-hold model with the
originate-to-distribute model, whereby they originate a credit
and sell or securitize a portion of it at the time of origination or
later. In this section, we investigate how the adoption of the
originate-to-distribute model reduced the exposure of banks
to the credits they originated over the past two decades.

3.1 Distribution at the Time of Credit
Origination
To investigate the effect of the originate-to-distribute model
on the exposure of banks to the credits they originate, we begin
by looking at the lead banks’ market share of the credits they
originate, at the time of the credit origination.
For our purposes, “banks” are all institutions that are
regulated and that perform the traditional bank roles of
maturity and credit transformation. Thus, the banks discussed
throughout our article refer to all commercial banks, bank
holding companies (BHCs), thrifts and thrift holding
companies, credit unions, and foreign banking organizations,
including their domestic branches. Note that whether an

institution is classified as a bank may vary over time. For
example, Morgan Stanley and Goldman Sachs are classified as
banks only from January 1, 2009, when they became BHCs. For
the period preceding this date, they are not counted as banks
since they were operating as investment banks.
In 1988, the first year of the sample period, lead banks
retained in aggregate a stake of 17.6 percent of the credits they
originated in that year, including term loans and credit lines
(Chart 2).14 Beginning in 1990, when they retained in aggregate
22.2 percent, lead banks started to decrease their share of the
credits they originated, reaching a low of 10.5 percent in 1999.
During the 2000s, the aggregate shares varied with the business
cycle but generally remained steady at around 13 percent.
The market share of the credits that lead banks retain at
origination has clearly fallen, but the representation of this
decline in Chart 2 is skewed by the large number of credit lines
in our sample. As we can see from Chart 3, while banks have
increasingly replaced the originate-to-hold model with the
originate-to-distribute model over the past two decades, this
substitution has been far more pronounced in the origination
of term loans than of credit lines. To be sure, this difference was
not immediately apparent: In 1988, lead banks retained in
aggregate 17.6 percent of the credit lines and 21 percent of the
14

Here, and throughout the rest of the article, we use the terms market share
and aggregate share interchangeably. By lead banks’ market or aggregate share,
we mean the share of all credits that the lead banks, taken together, retain.
It is computed as the sum of all the lead banks’ retained credit amounts
divided by the sum of all new credits they originated that year.

FRBNY Economic Policy Review / July 2012

term loans they extended in that year. These shares declined
to 10.3 percent and 10.0 percent, respectively, by 1999.
However, in the first decade of the 2000s, while lead banks
continued the trend of decreasing their market share of term
loans, they reversed the trend for credit lines. By 2006, the last
year before the data pick up the effects of the most recent

Chart 2

Lead Banks’ Market Share of Syndicated Loans
at Credit Origination
Market share
0.30
0.25
0.20
0.15
0.10
0.05
0
1990

1995

2000

2005

2010

Source: Shared National Credit database, produced jointly by the Federal
Deposit Insurance Corporation, Board of Governors of the Federal
Reserve System, and Office of the Comptroller of the Currency.

financial crisis, lead banks increased their market share of the
credit lines they originated to 14.1 percent but decreased their
market share of the term loans they originated to 8.8 percent.
These aggregate trends are consistent with the trends in the
average share of the credit that the lead bank retains on its
balance sheet. This share was equal to 32 percent for credit
lines in 1988 and 31 percent for term loans in the same
year. By 1999, these shares had declined to 17 percent and
16 percent, respectively. Then, in the first decade of the new
century, the average credit-line share retained by the lead
bank increased to 24 percent by 2006, whereas the average
share retained in term loans increased slightly but essentially
remained stable, at 17 percent, by the same year.
Since average retained shares are much higher than the
aggregate (market) shares, the data indicate that banks tend to
keep smaller shares of the larger credits that they originate.
Recall that the average retained share is a simple average of the
credit shares that banks keep on the balance sheet, while the
aggregate share is a weighted average of these shares, with the
weights defined by the size of the credits.
The disparity between the trends in lead banks’ market
shares of credit lines and term loans shows the effect of banks’
increasing syndication and securitization of term loans. These
trends, though suggestive of these effects, do not reflect the
whole story, since they account only for the role of lead banks
and exclude that of banks that participate in the loan syndicate
(syndicate-participant banks). We discuss this issue further in
a later section.

Chart 3

Lead Banks’ Market Share of Credits at Origination, by Credit Type
Market share

Market share
0.30

0.30

Credit Lines

0.25

0.20

0.15

0.10

0.05

Term Loans

0
1990

1995

2000

2005

2010

1990

1995

2000

2005

2010

Source: Shared National Credit database, produced jointly by the Federal Deposit Insurance Corporation, Board of Governors of the Federal Reserve System,
and Office of the Comptroller of the Currency.

The Rise of the Originate-to-Distribute Model

Even though banks substituted the originate-to-distribute
model for the originate-to-hold model at a faster pace in their
term-loan business, they did not use the former uniformly
across all types of term loans. For instance, they varied their
retention rates depending on the purpose of the loan, as can
be seen in Chart 4. Over time, banks increasingly used the
originate-to-distribute model when they extended loans for

corporate purposes and in particular to fund mergers and
acquisitions, possibly because of the additional risk such
loans tend to carry. In contrast, they continued to use their
traditional originate-to-hold model when they extended
loans for capital expenditures.

3.2 Distribution after the Credit Origination
Chart 4

Lead Banks’ Market Share of Term Loans
at Origination by Credit Purpose
Market share
0.4

Capital expenditures

0.3

0.2

0.1
Corporate purposes

0
1995

1990

2000

Mergers and
acquisitions

2005

2010

The decline in the share of credits that lead banks originate
did not occur only at the time of the credit origination but
continued throughout the life of the credit. To investigate this
effect, we began by selecting cohorts of credits originated each
year that we observed for at least three years. Next, we
computed the market share of the credits that the lead banks
retained at the time of origination and three years later. Both of
these shares are depicted in Chart 5. The left panel shows the
market shares for credit lines, while the right panel shows the
market shares for term loans. To allow us to observe all the
credits for three years, we end the chart with credits originated
in 2007. Recall that our sample ends in 2010.
A quick look at Chart 5 shows two important results. First,
in the years after credit-line origination, lead banks either did
not sell off additional portions of the credit lines or sold off a
very small (aggregate) share. This practice prevailed at the
beginning of our sample period in the late 1980s and continued
throughout the sample period, with the exception of the earlyto-mid-1990s when lead banks seemed to have sold off more
of the credit lines.

Chart 5

Lead Banks’ Market Share of Credits at Origination and Three Years Later
Market share

Market share
0.30

0.30

Credit Lines

0.25

Term Loans

0.25

0.20

0.20
Year 0

0.15

Year 0

Year 3
0.10

0.10

0.05

Year 3

0
1990

1995

2000

2005

2010

1990

1995

2000

2005

2010

Source: Shared National Credit database, produced jointly by the Federal Deposit Insurance Corporation, Board of Governors of the Federal Reserve System,
and Office of the Comptroller of the Currency.

FRBNY Economic Policy Review / July 2012

Second, as the term loans held by lead banks aged, the
banks increasingly reduced their aggregate exposure to them.
In the previous section, we documented that, over time, lead
banks retained at origination a smaller market share of the
term loans they originated. Chart 5 shows that this decline
continued even after the origination year. For example, of the
term loans that banks originated in 1988, they retained in
aggregate 21.4 percent at origination. Three years later, these
banks had, in aggregate, 18.7 percent of these term loans on
their balance sheet. In 2004, lead banks retained in aggregate
8.6 percent of the term loans they originated in that year.
Three years later, the banks’ aggregate exposure to the same
set of term loans had been reduced to 7.1 percent. In 2007, the
last year in our sample for which we conducted this exercise,
lead banks retained a market share of 6.7 percent of their term
loans at the time of origination. By 2010, they had lowered
their market share of these same term loans to 3.4 percent.
We obtain similar results when we track the individual share
of each credit that the lead bank retains on its balance sheet. For
credit lines, lead banks either decreased their average retained
shares very little or not at all. For example, of the credit lines
originated in 1988, on average banks retained 30.5 percent at
origination and 28.5 percent three years later. In 2004, lead
banks retained, on average, 21.6 percent at origination and
21.2 percent three years later. For term loans, however, lead
banks tended to cut back more of their credit exposure. Of the
term loans originated in 1988, banks retained an average of
35.2 percent at origination and 30.7 percent three years later.
In 2004, banks retained on average 19.2 percent at origination
and 18.0 percent three years later.
In sum, the results reported in this section show that over
the past two decades, banks largely continued to use the
traditional originate-to-hold model when they extended credit
lines to corporations but increasingly switched to the originateto-distribute model for term loans. This evidence suggests that
banks have a unique ability to provide liquidity to corporations
by extending credit lines to them. It also highlights the need
to reconsider the measures traditionally used to capture the
importance of banks as providers of credit to corporations.
As banks increasingly adopt the originate-to-distribute model,
conventional measures of bank lending activity, which rely on
the credit kept by banks on their balance sheets, will tend to
understate the role they play in the credit-origination process.
In the next section, we investigate which institutions are buying
the credits that banks originate.

4. Who Buys Bank Credit Lines
and Term Loans?
Given our finding that over time lead banks are retaining a
smaller and smaller portion of the credits they originate
(especially in the case of term loans), a natural question to ask
is, Who buys these credits? Answering this question—and, in
particular, finding out whether banks or other institutional
investors such as pension funds and hedge funds are buying
these credits—is important because these institutions have
quite different monitoring capabilities and incentives for
renegotiating existing credits. Answering this question also
helps us understand the growth of shadow banking in the past
decade and the links of these institutions to the banking sector.

4.1 The Role of Banks as Credit Acquirers
We start by investigating whether, as the lead banks have
lowered the share of credits they retain at origination, other
banks have increased the share of credit they hold as syndicate
participants. The left panel of Chart 6 shows for the total credit
extended under credit lines each year, the portion that lead
banks retained, the portion acquired by banks that are
syndicate participants, and the portion acquired by the
remaining investors. The right panel of the chart reports the
same information for term loans.
As the chart shows, although the market share of credit
lines retained by lead banks decreased through the 1990s and
increased through the 2000s, the total market share held by all
banks (both lead and syndicate-participant banks) remains
fairly stable, at an average of 92 percent during the pre-crisis
sample period. In fact, when lead banks’ market share
decreased in the 1990s, the syndicate-participant banks’
market share increased, and that share increased more than
the lead banks’ share decreased. Similarly, from 2000 to 2010,
syndicate-participant banks’ market share decreased more
than the lead banks’ market share increased. In other words,
credit-line provision continues to be in essence a “bank
business.”
Term loans, however, present a different picture. As we can
see from the right panel of Chart 6, the decline in the lead
banks’ aggregate retained share was accompanied by an even
bigger decline in the share of the term loans acquired by other
banks.15
15

The picture is fairly similar when we consider the average share held by
banks. For credit lines, the average share held by syndicate-participant banks
remained stable at approximately 10 percent throughout the time period.
By contrast, for term loans, the average share held by syndicate-participant
banks decreased from its peak of 14 percent in 1991 (11 percent in 1988) to
6.3 percent in 2006.

The Rise of the Originate-to-Distribute Model

Of the $47 billion in term loans originated in 1988, banks,
including lead banks and syndicate-participant banks, retained
on their balance sheet 88.6 percent of the amount of credit.
Of the $315 billion in term loans originated in 2007, banks
retained on their balance sheet 43.7 percent. Thus, banks (lead
banks and syndicate-participant banks) more than halved their
market share of term loans from 1988 to 2007.

These patterns remain when we consider how the market
share of bank investors changed over the life of the loan. As
Chart 7 shows, syndicate-participant banks did not sell off their
market share of credit lines during the lifetime of the loans but,
apart from short periods in the early 1990s and mid-2000s, they
did decrease their market share of term loans as the loans
matured. In fact, for term loans that we observe for at least

Chart 6

Banks’ Retained Credits at Origination: Lead Banks versus Non-Lead Banks
Market share

Market share

Term Loans

Credit Lines
1.0

1.0

0.8

0.8
Nonbanks
Syndicate-participant banks
Lead banks

0.6

0.4

0.2

0.2
0

0
1990

1995

2000

2005

1990

2010

2000

1995

2005

2010

Source: Shared National Credit database, produced jointly by the Federal Deposit Insurance Corporation, Board of Governors of the Federal Reserve System,
and Office of the Comptroller of the Currency.

Chart 7

Syndicate-Participant Banks’ Market Share of Credits at Origination and Three Years Later
Market share

Market share
0.9

0.9

Credit Lines

Year 0

0.7

Term Loans

0.8

Year 0

0.7

Year 3

0.6

0.5

0.4

0.3

0.2

0.1

Year 3

0
1990

1995

2000

2005

2010

1990

1995

2000

2005

2010

Source: Shared National Credit database, produced jointly by the Federal Deposit Insurance Corporation, Board of Governors of the Federal Reserve System,
and Office of the Comptroller of the Currency.

FRBNY Economic Policy Review / July 2012

Chart 8

Nonbank Investors’ Market Share by Credit Type
Market share

Market share
0.6

Credit Lines

Foreign nonbank organizations
Other
Finance companies
Pension funds
Private equity firms
Investment management firms
Brokers and investment banks
Collateralized loan obligations
Insurance companies

0.5
0.4
0.3
0.2

Term Loans
1.0
0.8
0.6
0.4
0.2

0.1

0
1990

1995

2000

2005

1990

2010

1995

2000

2005

2010

Source: Shared National Credit database, produced jointly by the Federal Deposit Insurance Corporation, Board of Governors of the Federal Reserve System,
and Office of the Comptroller of the Currency.

three years, of the $17 billion of such loans originated in 1988,
banks (both lead and syndicate-participant banks) kept on
their balance sheets 90.2 percent in 1988 but only 86.9 percent
three years later. Similarly, of the $17 billion in term loans
issued in 2007, banks kept on their balance sheets 42.1 percent
at origination but only 32.8 percent three years later.
Thus, for credit lines, syndicate-participant banks tended to
offset the actions of the lead banks at origination, and they
tended to hold the credit lines to maturity (or at least for three
years). For term loans, in contrast, syndicate-participant banks,
like lead banks, have been decreasing the market share they
retain at origination and over the years after origination.16

4.2 The Role of Nonbank Financial
Institutions
Given the decline in the portion of term loans retained in the
banking sector, the next question to ask is, Who are the
investors that have been increasing their presence in this
market? To address this question, we report in Chart 8 the
market shares at the time of credit origination in the creditline market (left panel) and the term-loan market (right
16

Interestingly, the average shares for syndicate-participant banks did not
change much over the life of the credit, for both credit lines and term loans.
With the exception of loans originated during the recessions of 1990 and 2001
(for which the average participant bank share decreased over the loans’
lifetime), on average, syndicate-participant banks retained the same share
at origination as three years later.

The Rise of the Originate-to-Distribute Model

panel) of the main nonbank investors in these markets:
insurance companies, investment management firms, finance
companies, collateralized loan obligation managers, private
equity firms, brokers and investment banks, pension funds,
and foreign nonbank organizations.17
Looking at the information on credit lines, we see that the
market share of nonbank investors in credit lines is very small,
less than 10 percent in each year. This finding was expected,
given our previous evidence that banks continue to play a
dominant role in the provision of liquidity to corporations
through credit lines. The nonbank entities that have the highest
market share are finance companies, pension plans, investment
managers, and “other.”18 Finance companies first appear in
our credit-line data in 1992, when they held a market share
of 0.2 percent. They reached their peak market share in 2002
with 3.2 percent of all credit lines originated.
17

The different categories are identified in a variety of ways: by keyword;
by information from the National Information Center run by the Federal
Reserve System, which identifies banks, bank holding companies, foreign
banking organizations, finance companies, insurance companies, and so on;
by matching to the Moody’s Structured Finance Database, which allows us
to identify CLOs; and by matching to Capital IQ to identify investment
management firms and private equity firms. Investment management firms
are identified as hedge funds, mutual funds, or asset managers. Note that
institutions may shift across categories over time. For example, for most of
our sample, Goldman Sachs and Morgan Stanley are identified as investment
banks. However, after they officially converted their status to BHCs in the
first quarter of 2009, they are classified as BHCs. Finally, note that for the
remaining analysis, we exclude nonbank entities that are part of banking
entities—for example, finance companies that are part of BHCs. (Including
them does not substantially change our analysis.)

Turning our attention to term loans, we see from the right
panel of Chart 8 that finance companies, CLOs, brokers, and
investment managers have been increasing their share in the
market for term loans and that nonbank investors—
particularly, investment managers and CLOs—play a much
bigger role in this market than in the credit-line market.
Investment managers first appear in our data in 1992, when
they acquired 2 percent of the term loans originated that year.
Similarly, CLOs first appear in our data in 1994, when they held
0.3 percent of the term loans originated in that year. By 2007,
these investors had acquired 13.6 percent and 15.5 percent,
respectively, of the term loans issued in that year. Again, note
that all of these numbers underestimate the true presence of
each category in the market since the “other” grouping
contains institutions that could not be accurately matched to
any of the categories from our sources; nonetheless, most of
these institutions probably do fall into one of these categories.
Finance companies first appear in the term-loan data in 1989,
when they acquired 0.03 percent of the term loans issued that
year; at their peak in 1998, they held 7.3 percent of the term
loans issued that year. Private equity firms currently represent
a small share of the market (0.8 percent in 2010), but they have
been steadily building their presence in this market, from
0.4 percent in 1996 to 3 percent in 2007. In contrast, insurance
companies continue to play a minor role: the share of the term
loans held by insurance companies increased from 0.2 percent
in 1988 to 1.0 percent in 2007.

share of the term-loan business. These investors have been
buying larger portions of the credits at the time of their
origination, and they continue to increase such investments
in the years after origination. From 2000 to 2007, on average,
CLOs acquired 12.6 percent of the term loans originated in
each year, while investment managers acquired on average

Chart 9

Role of Finance Companies
Market share
0.30
0.25
0.20
0.15
0.10
Year 3

0.05

Year 0
0
1990

1995

2000

2005

2010

Chart 10

4.3 Nonbank Investors’ Shares
after Loan Origination

Role of Investment Managers
Market share

We documented earlier that both lead banks and syndicateparticipant banks continue to reduce the share of their term
loans in the years following origination. In Charts 9 through
11, we examine the market shares of the top three nonbank
investors in the syndicated loan market at the time of the credit
origination and three years later. Because these nonbank
investors invest mainly in term loans, we limit our analysis
to the term-loan market.
Finance companies kept their share of the term-loan market
more or less constant over the past decade. In contrast, CLOs
and investment managers have been increasing their market

0.30
Year 3

0.25
0.20
0.15
0.10

Year 0
0.05
0
1990

1995

2000

2005

2010

The majority of the institutions in the “other” category were not clearly
identified by our sources as belonging to one of the categories discussed above.
Because much of the identification was done through name matching,
institutions for which the quality of the match was in question were also placed
in the “other” category. Finally, the category also contains a very small number
of Article XII New York investment companies, data processing servicers,
individuals, and foundations.

FRBNY Economic Policy Review / July 2012

Chart 11

Role of Collateralized Loan Obligations
Market share
0.30
0.25
0.20
Year 3
0.15
Year 0

0.10
0.05
0
1990

1995

2000

2005

2010

8.7 percent of this market. Three years later, such institutions
held 18.2 percent and 12.9 percent of these loans, respectively.
This evidence shows that over the past two decades, as banks
have increasingly opted to retain on their balance sheet a
smaller portion of the term loans they originated, they have
been fueling the growth of nonbank institutions, in particular
CLOs and investment managers.

5. Final Remarks
Our analysis of banks’ role in financial intermediation reveals
that beginning in the early 1990s, lead banks increasingly used
the originate-to-distribute model in their corporate lending
business. This increase, however, was largely limited to term
loans. In general, banks continued to rely on the traditional
originate-to-hold model in the credit-line business. Further,
we find that more and more lead banks “distributed” their
term loans by selling larger portions of them, not only at
the time of the loan origination but also in the years after
origination.

The Rise of the Originate-to-Distribute Model

Our investigation into the investors that bought the bank
loans shows that traditional institutional investors and, in
particular, new loan investors—including investment managers
and CLOs—began taking over more of the credit business.
Our findings have several important implications for the
theme of this volume. They show that in evaluating the
importance of banks in financial intermediation, analysts must
use measures of the credit that banks originate, as opposed to
measures of the credit they retain on their balance sheets.
Indeed, our findings confirm that measures of the importance
of banks that rely on the credit held by banks on their balance
sheets will increasingly understate the essential role that banks
play in financial intermediation. Our findings also show that
banks have been an important contributor to the so-called
shadow banking system.19 For example, in 1993, of the
$22.7 billion in term loans originated, banks sold $2.2 billion to
the shadow banking system. By comparison, in 2007, of the
$315 billion in term loans originated, they sold $125 billion to
the shadow banking system. In about two decades, the annual
volume of term loans that banks supplied to nonaffiliated
shadow-banking institutions increased by $123 billion.
Lastly, our findings suggest some interesting questions
for future research. Does the increasing presence of nonbank
financial institutions in loan syndicates affect lending terms or
hinder borrowers’ ability to renegotiate their credits? Does the
decline in a lead bank’s retained share of the credits it originates
affect the nature of its relationship with borrowers? What are
the implications of the decline in a bank’s retained share for its
incentives to assess the creditworthiness of loan applicants or
to track the viability of loans? Researchers have been using the
share of a credit held by the lead bank at the time of origination
as a proxy for the bank’s monitoring incentives. As our
evidence shows, however, this share may be a biased proxy
for the bank’s exposure during the life of a loan. It would be
interesting to investigate the implications of the decline in the
bank’s credit share for its monitoring incentives during the life
of the credit.

For these computations, “shadow banking institutions” are defined as CLOs,
brokers and investment banks, investment managers, private equity firms,
finance companies, and foreign nonbank institutions.

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(March): 335-49.
Gatev, E., and P. Strahan. 2006. “Banks’ Advantage in Hedging
Liquidity Risk: Theory and Evidence from the Commercial Paper
Market.” Journal of Finance 61, no. 2 (April): 867-92.
Gatev, E., T. Schuermann, and P. E. Strahan. 2009. “Managing Bank
Liquidity Risk: How Deposit-Loan Synergies Vary with Market
Conditions.” Review of Financial Studies 22, no. 3 (March):
995-1020.

Gorton, G. B., and G. G. Pennacchi. 1995. “Banks and Loan Sales:
Marketing Nonmarketable Assets.” Journal of Monetary
Economics 35, no. 3 (June): 389-411.
Hale, G. B., and J. A. C. Santos. 2009. “Do Banks Price Their
Informational Monopoly?” Journal of Financial
Economics 93, no. 2 (August): 185-206.
———. 2010. “Do Banks Propagate Debt Market Shocks?”
Unpublished paper, Federal Reserve Bank of New York, February.
Holmström, B. R., and J. Tirole. 1993. “Market Liquidity and
Performance Monitoring.” Journal of Political Economy 101,
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———. 1998. “Private and Public Supply of Liquidity.” Journal
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Effects in Borrowers’ Costs of Funds? Evidence from a Matched
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Loan and Junk Bond Markets.” Journal of Banking and
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300-19.
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Providers: An Explanation for the Coexistence of Lending and
Deposit-Taking.” Journal of Finance 57, no. 1 (February):
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Management over the Credit Cycle.” Unpublished paper, Federal
Reserve Bank of New York.
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Risky Firms to Borrow? Evidence from the Bank Risk-Taking
Channel of Monetary Policy.” Unpublished paper, Federal Reserve
Bank of New York.

Gorton, G. B., and J. G. Haubrich. 1990. “The Loan Sales Market.”
Research in Financial Services 2: 85-135.

FRBNY Economic Policy Review / July 2012

References (Continued)

Pennacchi, G. G. 1988. “Loan Sales and the Cost of Bank Capital.”
Journal of Finance 43, no. 2 (March-April): 375-96.
Pozsar, Z., T. Adrian, A. Ashcraft, and H. Boesky. 2010. “Shadow
Banking.” Federal Reverse Bank of New York Staff Reports,
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Reliability and a Theory of Financial Intermediation.” Review
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Crisis.” Review of Financial Studies 24, no. 6 (June): 1916-43.

———. 2012. “Banks’ Liquidity Insurance Provision to Firms and
Depositors and the Risk of Cìoncurrent Runs on Their Assets
and Liabilities.” Unpublished paper, Federal Reserve Bank
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———. 2010. “Bank Capital, Borrower Power, and Loan Rates.”
Unpublished paper, Federal Reserve Bank of New York.
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A Primer.” Milken Institute, October.

The Rise of the Originate-to-Distribute Model

Benjamin H. Mandel, Donald Morgan, and Chenyang Wei

The Role of Bank Credit
Enhancements
in Securitization
1. Introduction

oes the advance of securitization—a key element in the
evolution from banking to “shadow banking” (Pozsar et al.
2010)1—signal the decline of traditional banking? Not
necessarily, for banks play a vital role in the securitization
process at a number of stages, including the provision of credit
enhancements.2 Credit enhancements are protection, in the
form of financial support, to cover losses on securitized assets
in adverse conditions (Standard and Poor’s 2008). They are
in effect the “magic elixir” that enables bankers to convert
pools of even poorly rated loans or mortgages into highly rated
securities. Some enhancements, such as standby letters of
credit, are very much in the spirit of traditional banking and
are thus far from the world of shadow banking.
This article looks at enhancements provided by banks in the
securitization market. We start with a set of new facts on the
evolution of enhancement volume provided by U.S. bank
holding companies (BHCs). We highlight the importance of
bank-provided enhancements in the securitization market by
comparing their market share with that of financial guaranties
sold by insurance companies, one of the main sellers of credit
protection in the securitization market. Contrary to the notion
1

According to Federal Reserve Chairman Bernanke (2012), “Examples of
important components of the shadow banking system include securitization
vehicles.”
2
See Cetorelli and Peristiani (2012) for analysis of banks’ role in other steps
in the securitization process.

Benjamin H. Mandel is a former assistant economist and Donald Morgan an
assistant vice president at the Federal Reserve Bank of New York; Chenyang
Wei is a senior economist at the Federal Reserve Bank of Philadelphia.
Correspondence: don.morgan@ny.frb.org

that banks were being eclipsed by other institutions in the
shadow banking system, we find that banks have held their
own against insurance firms in the enhancement business.
In fact, insurers are forthright about the competition they
face from banks:
Our financial guaranty insurance and reinsurance
businesses also compete with other forms of credit
enhancement, including letters of credit, guaranties and
credit default swaps provided, in most cases, by banks,
derivative products companies, and other financial
institutions or governmental agencies, some of which have
greater financial resources than we do, may not be facing
the same market perceptions regarding their stability that
we are facing and/or have been assigned the highest credit
ratings awarded by one or more of the major rating agencies
(Radian Groups 2007, form 10-K, p. 46).
Given the steady presence of bank-provided enhancements in the securitization market, we next study exactly
what role enhancements play in banks’ securitization process.
The level of credit enhancements necessary to achieve a given
rating is determined by a fairly mechanical procedure that
reflects the rater’s estimated loss function on the underlying
collateral in the securitization (Ashcraft and Schuermann
2008). If estimated losses are high, then—all else equal—
more enhancements are called for to achieve a given rating.
Those mechanics suggest a negative relationship between

The authors thank Nicola Cetorelli, Ken Garbade, Stavros Peristiani, and
James Vickery for helpful comments and Peter Hull for outstanding research
assistance. The views expressed 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.

FRBNY Economic Policy Review / July 2012

the level of enhancements on a deal and the performance of
securitized assets. Note that in this scenario, enhancements
serve as a buffer against observable risk (as embodied in the
estimated loss function).
We are interested in the idea that enhancements might also
be used to solve part of the asymmetric information problems
that may plague the securitization process. If banks are better
informed than outside investors about the quality of the assets
they are securitizing, as they almost certainly are, banks that are
securitizing higher-quality assets may use enhancements as a
signal of their quality. In other words, by their willingness to
keep “skin in the game” to retain some risk, banks can signal
their faith in the quality of their assets. Such signaling implies
a positive relationship between the level of enhancements and
the performance of securitized assets, just the opposite of the
buffer explanation. Obviously, enhancements could, and
probably do, serve both as a buffer against observable risk
and a signal against unobservable (to outsiders) quality.
However, since the buffer role is almost self-evidently true,
we are interested in whether we can detect any evidence for
the role of securitization enhancements as a signal.
Others have also considered the hypothesis that
enhancements might play a signaling role. Downing, Jaffee,
and Wallace (2009) observe that asymmetric information
about prepayment risk in the government-sponsoredenterprise (GSE) mortgage-backed-security market should
motivate the use of signaling devices.3 Albertazzi et al. (2011)
note the potential centrality of asymmetric information to
the securitization process and conjecture that a securitizing
sponsor can keep a junior (equity) tranche “as a signaling”
device of its (unobservable) quality or as an expression of a
commitment to continue monitoring. James (2010) comments
that if asset-backed securities include a moral hazard (or
“lemons”) discount due to asymmetric information, issuers
have an incentive to retain some risk “as a way of
demonstrating higher underwriting standards.” 4
A variant of the question we are asking about credit
enhancements showed up in earlier literature on the role
of collateral in traditional (on-the-books) bank lending.
A theoretical literature in the 1980s predicted that in the
context of asymmetric information, safer borrowers were more
likely to pledge collateral to distinguish themselves from riskier
ones (Besanko and Thakor 1987; Chan and Kanatas 1985).
However, an empirical study by Berger and Udell (1990) found
strong evidence against the signaling hypothesis: that is,
3

Because the mortgage-backed securities that the authors study are
guaranteed, prepayment risk is the only risk investors need to worry about.
4
In a paper that is somewhat related to ours, Erel, Nadauld, and Stulz (2011,
p. 37) investigate why banks hold highly rated tranches of securitizations,
and conclude that their doing so may partly serve as “a credible signal of deal
quality to potential investors.”

The Role of Bank Credit Enhancements in Securitization

collateral was associated with riskier borrowers and loans.
In other words, when it comes to loans on the books, collateral
seems to serve more as a buffer against observable risk than
as a signal of unobservable quality.
We found only one other paper that looks at the relationship
between enhancements and the performance of securitized
assets. Using loan-level data, Ashcraft, Vickery, and
Goldsmith-Pinkham (2010) find that delinquency on
underlying subprime and Alt-A mortgage pools is positively
associated with the amount of AAA subordination.5 Those
results are consistent with the hypothesis that subordination is
used as a buffer against observable credit risk. Interestingly,
however, the authors find that BBB subordination is negatively
associated with mortgage performance on Alt-A deals, which
they consider more opaque (hard to rate). The latter result
seems consistent with the signaling hypothesis: the issuer of an
opaque security submits to a high degree of subordination to
signal its confidence in the quality of the assets it is selling.
We investigate our question from two angles. First, we look
directly at the relationship between the performance of
securitized assets and total enhancements in a panel analysis
where we regress the fraction of securitized assets that are
severely delinquent (delinquent for ninety or more days or
charged off) on total enhancements per unit of securitized
assets. We estimate the regression for seven categories of credit:
residential real estate loans, home equity loans, credit card
loans, auto loans, other consumer loans, all other loans, and
total securitizations. We are not able to detect any evidence
for the signaling hypothesis; when we find a significant
relationship between delinquency on securitized assets and
enhancements, the relationship is positive, consistent with
the buffer hypothesis.
In the second part of our article, we test the hypotheses
from the perspective of market participants. Specifically,
we investigate how stock investors and the option market
reacted when BHCs detailed for the first time their
securitization activity in their 2001:Q2 regulatory reports,
which include enhancements and aggregate loan performance
(delinquencies) of the assets that BHCs securitized. We
calculate the cumulative abnormal stock return around that
date for each BHC that had positive securitization activity.
We find first that abnormal returns are highly positively
correlated with the extent of securitization activity at a
BHC. That comes as no surprise, since securitization was
presumably viewed at the time as positive net-present-value
(NPV) activity. More interestingly, we find that the
relationship between total credit enhancements and
5

The amount of subordination at a given rating is the fraction of bonds that
absorb losses before the bond in question. If 90 percent of the bonds in a deal
are senior AAA bonds and 10 percent are junior, subordination of the AAA
bonds is 10 percent.

cumulative abnormal returns depends on the delinquency rate
on securitized assets; when the rate is below some threshold,
cumulative abnormal returns are positively correlated with
total credit enhancements. This result suggests that when the
delinquency rate is relatively low, enhancements serve as a
signal of quality (hence, the high cumulative abnormal
return). However, when the rate is above that threshold,
the relationship between enhancements and cumulative
abnormal returns becomes negative. This finding suggests
that when the delinquency rate is relatively high—meaning
that securitized assets are demonstrably risky—enhancements
serve as a buffer against observable risk.
We also examine how securitization activity and
enhancements are related to BHC risk, as measured by
the implied volatility of BHC stock prices. We find that
securitization activity is positively correlated with implied
volatility, suggesting that markets view securitization as a risky
activity. We also find that total enhancements are positively
related to implied volatility. This result implies that just as
traditional originate-and-hold banking exposed bank
shareholders to risk, so does banks’ provision of credit
enhancements.

2. Background on Bank-Provided
Credit Enhancements
While credit enhancements can take many forms, Schedule
HC-S, on which BHCs report on their securitization activity,
includes fields for three types of enhancements.6 The first is
credit-enhancing, interest-only strips. Schedule HC-S
instructions define these strips as:
an on-balance-sheet asset that, in form or in substance,
1) represents the contractual right to receive some or
all of the interest due on the transferred assets; and
2) exposes the bank to credit risk that exceeds its pro-rata
share claim on the underlying assets whether through
subordination provisions or other credit-enhancing
techniques.
Elsewhere, the HC-S instructions note that the field for
credit-enhancing, interest-only strips can include excess spread
accounts.7 Excess spread is the monthly revenue remaining on
6

To be clear, our article focuses on the three types of enhancements reported
by bank holding companies on Schedule HC-S. For a more general discussion
of enhancements, see Ashcraft and Schuermann (2008).
7
Levitin (2011, p. 16) asserts that, in the context of credit card securitization,
excess spread accounts are also referred to as credit-enhancing, interest-only
strips.

a securitization after all payments to investors, servicing fees,
and charge-offs. As such, excess spread—a measure of how
profitable the securitization is—provides assurance to
investors in the deal that they will be paid as promised. Excess
spread accounts are the first line of defense against losses to
investors, as the accounts must be exhausted before even the
most subordinated investors incur losses.
The second class of enhancements, subordinated securities
and other residual interest, is a standard-form credit
enhancement. By holding a subordinated or junior claim, the
bank that securitized the assets is in the position of being a firstloss bearer, thereby providing protection to more senior
claimants. In that sense, subordination serves basically as a
buffer or collateral. However, in the asymmetric information
context, holding a subordinate claim gives the bank the stake
that can motivate it to screen the loans carefully before it
securitizes them and to continue monitoring the loans after it
securitizes them. The bank’s willingness to keep some risk may
serve as a signal that it has screened loans adequately and plans
to monitor diligently.
The third class of enhancements, standby letters of credit,
obligates the bank to provide funding to a securitization
structure to ensure that investors receive timely payment on
the issued securities (for example, by smoothing timing
differences in the receipt of interest and principal payments) or
to ensure that investors receive payment in the event of market
disruptions. The facility is counted as an enhancement if and
only if advances through the facility are subordinate to other
claims on the cash flow from the securitized assets.8
Although not technically classified as an enhancement, a
fourth item on Schedule HC-S that we consider is unused
commitments to provide liquidity. Unused commitments
represent the undrawn balance on previous commitments.
We include this variable simply as a control; we do not venture
a hypothesis about how it will enter any of our regressions.
It is important to note that the HC-S data we study,
particularly subordination, are measures of risk retention by
BHCs and not necessarily a total credit enhancement for a
securitization deal. For example, a deal could have 20 percent
subordination (say, a $1 billion mortgage pool divided into an
$800 million senior bond and a $200 million junior bond)
without the BHC holding (retaining) any of the subordinated
piece. In that case, the enhancement would not show up in our
data. Our basic question, however, remains: Is risk retention
important because it is a buffer against observable risk or
because it is a signal of unobservable quality? Indeed, Title 9
of the Dodd-Frank Act requires federal regulators to set
8

Note that banks also provide enhancements in the form of representation
and warranties that obligate the issuer to take back the loan if it defaults early
in its life.

FRBNY Economic Policy Review / July 2012

Chart 1

Chart 2

Total Credit Enhancements
by Bank Holding Companies

Credit Card Enhancements
by Bank Holding Companies

Billions of U.S. dollars

Percent

Billions of U.S. dollars

Percent

180

160

140

120

100

140
120

Enhancements as share
of outstanding securitizations

100

Scale

80
60

40
Scale

0
2001

mandatory retention standards for sponsors of asset-backed
securities, suggesting that some policymakers believe that
enhancements in the form of retentions can ameliorate the
incentive and information problems endemic to securitization.
Because the enhancement data in Schedule HC-S have not,
to our knowledge, been studied publicly before, we briefly
examine the data in graphic form to get a sense of the size,
trends, and volatility of enhancements by BHCs. The data run
from 2001:Q2, when BHCs were first required to disclose
securitization activity, to 2009:Q4, when BHCs were required,
per Financial Accounting Standards Board ruling 167,9 to bring
securitized assets back on their balance sheets (and thus ceased
to report most enhancements).
Chart 1 plots total enhancements in billions of dollars and
as a percentage of outstanding securitizations. Measured per
securitized asset, enhancements were more or less stable at
between 2 and 3 percent until 2009:Q1, although there is a
slight upward trend in the series to that point. In dollar terms,
total enhancements trended upward from about $25 billion
in 2001:Q2 to about $70 billion in 2009:Q1. In the following
quarter, total enhancements more than doubled, to
$164 billion, and enhancements per securitized asset rose
to about 6 percent.
Chart 2 shows that the abrupt increase in total enhancements in 2009 came about almost entirely because of a rise in
enhancements on securitized credit card loans. The increase
in credit card enhancements, in turn, came about because of
increased enhancements at two BHCs: Bank of America and
See http://www.fasb.org/cs/ContentServer?c=FASBContent_C&pagename
=FASB/FASBContent_C/NewsPage&cid=1176156240834.

The Role of Bank Credit Enhancements in Securitization

0
02

Source: Federal Reserve System, Form FR Y-9C, Schedule HC-S.

JPMorgan Chase (JPMC). The increase at Bank of America
followed purchases of new securitization trusts after it acquired
Merrill Lynch in 2009. More interestingly, perhaps, the
increase in enhancements at JPMC in 2009 occurred primarily
because several classes of notes issued by Chase Issuance Trust,
one of its master trusts of securitized credit card assets, were
placed on credit watch and one class of notes was downgraded.10 That case illustrates how enhancements are used
to maintain a given rating level, whether by providing
a buffer against collateral losses, a signal of faith in the quality
of the assets, or both.
For completeness, Chart 3 plots the enhancements, both
by level and per securitized asset, for non–credit card
enhancements. The only feature of note is the downward trend
in non–credit card enhancements per securitized non–credit
card asset. That finding implies that the upward trend in overall
enhancements per securitized asset evident in Chart 1 results
from the upward trend in credit card enhancements per
securitized asset evident in Chart 2.
Chart 4 breaks out total enhancements into enhancements
of the BHCs’ own securitized assets (“self-enhancements”) and
enhancements provided to third parties (“third-party
enhancements”). Apart from the beginning and the end of the
sample period, self-enhancements were roughly stable at
between $30 billion and $40 billion. By contrast, third-party
enhancements began trending upward in about 2004:Q4 to
reach a peak of about $25 billion in 2008:Q2. Third-party
10

1
2001

Source: Federal Reserve System, Form FR Y-9C, Schedule HC-S.

Scale

Total enhancements

Scale

Enhancements as
share of outstanding
credit card securitizations

Total enhancements

See “Fitch: Chase Increases Credit Enhancement in Credit Card Issuance
Trust (CHAIT),” http://www.reuters.com/article/2009/05/12/
idUS260368+12-May-2009+BW20090512.

Chart 3

Chart 4

Non–Credit Card Enhancements

Self-Enhancements and Third-Party Enhancements

Billions of U.S. dollars
50

Percent

Billions of U.S. dollars

Total enhancements
Scale

160

40
35

Self-enhancements

140
120

100

25
10

Third-party
enhancements

Enhancements as share
of outstanding non–credit
card enhancements

5
0

2001

40
20

Scale

5
0

Source: Federal Reserve System, Form FR Y-9C, Schedule HC-S.

enhancements dropped noticeably during the financial crisis,
presumably because BHCs’ own solvency and liquidity came
into question.
While Charts 1-4 tell us something about trends in
enhancements within the banking industry, we were also
interested in how enhancements by bank holding companies
compared with those by financial institutions in the shadow
banking system, namely, insurance companies. Insurance
companies provide enhancements to structured finance
products through guaranties and credit default swaps (CDS).
As there is no central source of data on enhancements provided
by insurance companies, we turned to their 10-K forms for
data. Starting with the nineteen publicly traded insurance
companies, we determined that only six or seven (depending
on the year) provided guaranties for asset-backed securities.
These included firms such as Ambac, MBIA, and Radian.11
While the companies usually provided a reasonable breakdown
of guarantee coverage—such as residential and consumer loans
and the like—the classifications were not uniform across
companies. Thus, for each company we summed guaranties
across categories and then summed across companies to obtain
the aggregate level of guaranties by publicly traded insurance
companies in a given year.
11

180

The sample excludes American International Group, Inc. AIG was a
prominent seller of CDS protections on collateralized debt obligations (CDOs)
through one of its subsidiaries, AIG Financial Products. AIG experienced a
severe liquidity crisis due to its rating downgrade in late 2008, and the
subsequent bailout resulted in a substantial decline in outstanding net notional
amount of AIG’s CDS portfolio written on CDO products. Including AIG in
our analysis would therefore cause a more significant downward trend in
insurance companies’ presence in the financial guarantee market for the
sample period. We exclude AIG to make a conservative comparison of the
aggregate volumes of protection provided by banks and insurance firms in the
securitization market.

0
2001

Source: Federal Reserve System, Form FR Y-9C, Schedule HC-S.

Chart 5 plots the ratio of guaranties by insurance companies
to total enhancements provided by bank holding companies.
The level of guaranties provided by insurance companies
clearly swamps the level of enhancements provided by bank
holding companies; at its peak in 2004:Q4, the ratio was more
than ten to one. However, apart from some notable
fluctuations, including a drop in 2009 because of the increase
in credit card enhancements at JPMC and Bank of America, the
ratio has been fairly trendless, indicating that banks have
maintained (or perhaps increased) their share of the credit
enhancement business.
As noted in the introduction, we found that insurers would
often cite (in their 10-Ks) competition from banks for
enhancement business. Here is another example:
Financial guarantee insurance also competes with other
forms of credit enhancement, including senior-subordinated
structures, credit derivatives, letters of credit and guarantees
(for example, mortgage guarantees where pools of mortgages
secure debt service payments) provided by banks and other
financial institutions, some of which are governmental
agencies. Letters of credit are most often issued for periods
of less than 10 years, although there is no legal restriction
on the issuance of letters of credit having longer terms. Thus,
financial institutions and banks issuing letters of credit
compete directly with our Insurers to guarantee short-term
notes and bonds with a maturity of less than 10 years. To the
extent that banks providing credit enhancement may begin
to issue letters of credit with commitments longer than
10 years, the competitive position of financial guarantee
insurers could be adversely affected (MBIA Inc. 2008,
form 10-K, p. 24).

FRBNY Economic Policy Review / July 2012

Chart 5

Table 1

Guaranties to Asset-Backed Securities Provided
by Insurance Companies/Credit Enhancements
Provided by Bank Holding Companies

Summary Statistics

Ratio

Mean

Standard
Deviation

Severe delinquency ratio
Residential real estate
Home equity
Credit card
Auto
Other consumer
Commercial and industrial
All other
Total

3,394
536
703
686
444
717
968
4,589

0.006
0.012
0.012
0.005
0.027
0.003
0.002
0.005

0.025
0.024
0.018
0.011
0.032
0.008
0.008
0.017

Total enhancements (ratio)b
Residential real estate
Home equity
Credit card
Auto
Other consumer
Commercial and industrial
All other
Total

3,394
536
703
686
444
717
968
4,589

0.037
0.062
0.024
0.060
0.063
0.037
0.062
0.041

0.150
0.108
0.071
0.104
0.095
0.124
0.170
0.150

12
10

4
2
2001

Observations

Variable

Sources: Federal Reserve System, Form FR Y-9C, Schedule HC-S;
insurance companies’ 10-K forms.

Source: Federal Reserve System, Form FR Y-9C, Schedule HC-S.

3. Panel Regression Results
In this section, we investigate the relationship between the
performance of securitized assets and the extent of credit
enhancements. According to the buffer hypothesis, where
enhancements are a buffer against observable risks, one would
expect a negative relationship between enhancements and
performance. Under the signaling hypothesis, where
enhancements are a signal of unobserved quality, we would
expect a positive relationship between enhancements and
performance.
To investigate that question, we estimate the following
fixed-effect regression models:
(1) Severe Delinquency Rateit =  i +  t +  Total Enhancementsit
+   Controls +  it .

For each loan category (mortgages, credit card loans, and the
like), the dependent variable is the sum of securitized assets
ninety or more days past due and loans charged off, divided by
total securitized assets outstanding at BHC i in quarter t. The
main independent variable, TotalEnhancements, is the sum of
the three types of credit enhancements discussed earlier scaled
by total outstanding securitizations for each BHC in each
quarter.12 The controls are unused commitments divided by
total loans in each category, the log of on balance sheet assets,
leverage (total common equity divided by total balance sheet

The Role of Bank Credit Enhancements in Securitization

Severe delinquency ratio = securitized loans ninety days past due plus
charge-offs divided by total loans in that category.

Total enhancements = sum of credit-enhancing, interest-only strips
and excess spread accounts, subordinated securities, and other residual
interest; standby letters of credit; and other enhancements divided by
total loans in that category.

assets), ROA (quarterly net income divided by total balance
sheet assets), and risk-weighted assets divided by total balance
sheet assets (a measure of risk). All the variables in this and
subsequent regressions are defined in the appendix. The BHC
and time-fixed (quarter-year) effects control for constant
differences in performance across BHCs and time. We report
Huber-White robust standard errors for all quarter-BHC
observations with nonmissing, nonzero outstanding
securitization. The standard errors are clustered by BHCs. The
equation is estimated from 2001:Q2 to 2007:Q2 , that is, up to
but not including the financial crisis. A BHC is included in the
regression if it had nonzero securitization for a given loan type.
12

Besides the aggregate enhancement, Schedule HC-S reports disaggregated
numbers cross several categories, including retained interest-only strips,
standby letters of credit, subordinated securities, and other enhancements,
as discussed earlier. We focus on the aggregate amount, as discussions with
professionals in this business sector suggest that the overall amount of
enhancements is the most relevant term in the deal-making process.

Table 2

Panel Regression Results
Dependent Variable: Severely Delinquent Loans / Total Securitized Loans
Pre-Crisis (2001:Q2 to 2007:Q2)
Residential
Real Estate

Home
Equity

Credit Card

Auto

Other
Consumer

Commercial
and Industrial

All Other

Total

Total enhancements

0.017
[2.54]**

0.09
[4.49]***

0.044
[1.07]

0.027
[2.38]**

0.037
[1.34]

0.003
[0.29]

-0.007
[0.86]

0.015
[2.40]**

Unused commitments

-0.083
[1.85]*

-0.015
[1.22]

3.714
[1.92]*

-0.009
[1.05]

-0.034
[1.44]

-0.004
1.05]

-0.002
[0.85]

-0.001
[0.17]

Leverage

-0.047
[1.61]

0.015
[0.07]

-0.125
[3.35]***

0.001
[0.11]

0.218
[1.18]

0.026
[0.55]

-0.094
[3.64]***

-0.04
[1.08]

Return on assets

0.226
[1.09]

-0.11
[0.20]

-0.52
[8.58]***

0.011
[1.26]

0.009
[0.03]

0.029
[0.17]

-0.131
[1.39]

-0.042
[0.49]

Risk-weighted assets/total assets

-0.017
[1.75]*

0.006
[0.20]

0.01
[0.39]

0.028
[3.63]***

-0.003
[0.05]

-0.013
[0.83]

0.002
[0.24]

0.008
[0.91]

Log asset size

0.002
[0.92]

0.013
[1.36]

0.009
[1.36]

-0.002
[0.88]

0.022
[1.15]

0.004
[1.49]

-0.002
[0.71]

0.004
[1.36]

Observations

3,358

532

703

685

444

706

960

4,543

166

225

0.04

0.18

0.36

0.17

0.05

0.06

Number of entities
R

0.2

Source: Authors’ calculations.
Notes: Robust t-statistics appear in brackets. Time dummies are not reported. Variables are defined in the appendix.
***Statistically significant at the 1 percent level.
***Statistically significant at the 5 percent level.
***Statistically significant at the 10 percent level.

Summary statistics are reported in Table 1, and the
regression results are in Table 2. In the regressions, the point
estimates on total enhancements are positive in every loan
category but the residual “all other” and are significantly
different from zero in four of the eight categories: residential
real estate, home equity, auto, and total. Thus, we find no
evidence for the signaling hypothesis and some evidence for
the hypothesis that enhancements serve as a buffer against
observable risk. It is possible that enhancements serve as both
a buffer and a signal but the buffering role dominates.
Although we do not claim that the relationship between
delinquency and enhancements is causal, it is still interesting to
gauge the magnitude of the relationship between the two. To

do so, we calculate how much delinquency rates rise relative to
the average when total enhancements increase by one standard
deviation. Specifically, we calculate the product of the point
estimate for each loan category and the standard deviation
of total enhancements for that category; we then scale that
product by the mean delinquency rate for that category. The
result yields the estimated percentage change in delinquency
(relative to the mean delinquency rate) per standard deviation
change in total enhancements. The results imply a fairly stable
relationship between total enhancements and delinquency
rates in cases where the relationship was statistically significant:
residential real estate (0.43), home equity (0.81), auto (0.56),
and total (0.45).

FRBNY Economic Policy Review / July 2012

4. Event Studies: What Do Stock
Price Reactions and Implied
Volatility Tell Us about
the Role of Enhancements?
We next investigate the role of credit enhancements in
securitization by looking at market reactions to the new
disclosure requirement adopted in 2001:Q2 on BHCs’
securitizations. Beginning in that quarter, BHCs started
including in the quarterly “Reports of Condition and Income”
a new schedule that detailed their securitization activities.
The new schedule requires BHCs to disclose comprehensive
information on the volume and performance13 of seven
categories of securitized assets (the same categories we study
in the panel analysis above). Significantly, BHCs are required
to report the maximum amount of credit exposure they face
through the credit enhancements described above. This new
information first became public after BHCs’ reports for
2001:Q2 were disclosed in August and September 2001. This
event provides a unique opportunity for assessing how banks’
securitization and the associated credit exposure through
enhancements affect shareholders.
We focus on the valuation and risk implications of the newly
disclosed securitization activities. First, we conduct a standard
event study on a sample of 267 BHCs. A one-factor market
model is estimated for each firm using monthly return data
from July 1996 to June 2001, with the S&P 500 index being the
factor. Monthly abnormal returns are calculated for August
and September 2001 and then summed to reach a two-month
cumulative abnormal return (CAR) for each bank.
To see how the newly disclosed securitization activities and
credit enhancements affect valuation, we relate the CARs to
several securitization-related variables through the following
regression:
(2) CARi =  +  1 Securitizationi   2 Total_Enhancementsi
  3 Total_Enhancementsi Delinquencyi   4 Delinquencyi
  5 Unused Commitmentsi   6 Stock Volatilityi   i 
The dependent variable CARi is the two-month cumulative
abnormal return for bank i. All independent variables are
constructed using data from the Federal Reserve Y-9C reports,
which bank holding companies filed as of 2001:Q2 under
the revised reporting rules. Securitizationi represents the
outstanding principal balance of assets sold and securitized by
bank i, with servicing retained or with recourse or other sellerprovided credit enhancements, and is normalized by the bank’s
total outstanding loans on the balance sheet. This measure
13

The performance metrics include past-due amounts, charge-offs, and
recoveries on assets sold and securitized.

The Role of Bank Credit Enhancements in Securitization

reflects the extent to which bank i has moved its loans off the
balance sheet through securitization. Total_Enhancementsi
and Unused Commitmentsi are defined in Section 3 (and the
appendix). While the scale of securitization activities is
captured by Securitizationi , Total_Enhancementsi reflects the
extent to which bank i could still be “on the hook” should the
securitized assets perform poorly. We measure performance by
Delinquencyi , defined as the sum of past-due loan amounts and
year-to-date net charge-offs divided by the total outstanding
securitized assets. Last, to control for a BHC’s risk, we include
the stock volatility estimated using the daily returns in the
252 trading days prior to the disclosure period.
Equation 2 also includes an interaction between
Total_Enhancementsi and Delinquencyi . Per our earlier
discussion, we postulated two hypotheses on the role of
enhancements. Under the signaling hypothesis, keeping risk
through enhancements signals bank i’s private knowledge of
good loan quality, implying a positive relationship between
high enhancements and CAR. Under the buffer hypothesis,
banks securitizing riskier collateral need more enhancements
to meet rating agencies’ criteria. In this case, high enhancements
are associated with observably riskier deals, implying a negative
valuation impact. If loan performance is a reasonable proxy
for the observable riskiness of the securitized assets, we expect
the signaling effect to dominate among relatively betterperforming (lower-delinquency) deals, where observable risk
is less a concern, resulting in an overall positive relationship
between Total Enhancements and CAR. When deals are
performing poorly (high delinquency), however, concerns
over “observable risk” would heighten and the buffer role
of enhancements would dominate, leading to a negative
relationship between Total Enhancements and CAR. As a result,
we expect a positive coefficient for Total Enhancements (  2 )
and a negative coefficient for the interaction Total
Enhancements  Delinquency (  3 ).
Table 3 presents the least-squares regression coefficient
estimates with Huber-White robust standard errors. Each
model estimated includes one of two versions of the
Delinquencyi variable. Models 1 and 2 use a delinquency
measure based on all past-due loans, while models 3 and 4
use one that includes severe delinquencies only. The crosssection variation of the CARs appears to be significantly
associated with the securitization-related variables. The
impact of Securitization is significantly positive in all
specifications, suggesting that more favorable market
reactions are associated with larger-scale securitizations as
first disclosed by banks in 2001. This finding is consistent
with the notion that securitization transactions were
generally viewed as positive-NPV (that is, profitable)
projects in 2001 and that the market reacted more favorably

Table 3

Regression Analysis of Cumulative Abnormal
Equity Returns
Dependent Variable: Cumulative Abnormal Equity Returns,
August 2001-September 2001
(1)

(2)

(3)

(4)

Constant

-0.002
[0.34]

-0.0034
[0.57]

-0.0016
[0.28]

-0.0027
[0.0059]

Securitization

0.04
[3.48]***

0.032
[2.62]***

0.042
[3.88]***

0.036
[2.99]***

Total enhancements

0.047
[0.58]

0.295
[4.40]***

0.06
[0.82]

0.168
[3.45]***

Delinquencies (all)

-0.106
[0.46]

0.499
[1.59]

-0.337
[0.78]

0.759
[1.50]

Delinquencies (all) 
total enhancements

-10.933
[3.06]***

Delinquencies
(severe)
Delinquencies
(severe)  total
enhancements

-15.567
[3.32]***

Unused commitments

0.014
[0.20]

-0.122
[2.31]**

0.005
[0.08]

-0.041
[0.83]

Stock volatility

-1.498
[1.53]

-1.33
[1.36]

-1.496
[1.53]

-1.374
[1.41]

267

Observations
2

R (percent)

Source: Authors’ calculations.
Notes: Robust t-statistics appear in brackets. Variables are defined
in the appendix.
***Statistically significant at the 1 percent level.
***Statistically significant at the 5 percent level.
***Statistically significant at the 10 percent level.

interplay between enhancement and loan performance in
determining which of the two hypotheses dominates. Using
model 4 as an example, we can compare the relationship
between the market reaction (CAR) and enhancements at
different levels of severe loan delinquencies off the balance
sheet. For example, with no severe delinquency (Delinquency =
0 percent), the overall effect of Total Enhancements is
0.168 + (-15.567)  0 = 0.168, a positive wealth effect of
enhancements consistent with the signaling hypothesis.
As the severe delinquency ratio rises, however, the effect of
Total Enhancements weakens monotonically but remains
positive until severe delinquency reaches 0.168/15.567 =
1.08 percent.14 Once the delinquency rate exceeds
1.08 percent, the net effect of Total Enhancements on CAR
becomes increasingly negative as delinquency further rises.
For example, when severe delinquency is 1.18 percent,15
the net effect of Total Enhancements on CAR becomes
0.168 + (-15.567)  1.18 percent = -1.6 percent. This negative
relationship is consistent with the notion that investors
become increasingly concerned when a bank with poorly
performing securitized assets discloses a high level of credit
enhancements, just as the buffer hypothesis would predict.
We next focus on the risk implications of banks’
securitization activities. Specifically, we examine changes in
option-implied volatilities around the event period. For
fifty-one banks in our sample, we obtained data from the
OptionMetrics Ivy database, which features implied volatilities
calculated using the Cox, Ross, and Rubinstein (1979)
binomial model adjusted for dividends. Because some banks
have numerous exchange-traded options, we impose a number
of widely used sample restrictions.16 We calculate weightedaverage implied volatilities at the firm level, using each option’s
vega as the weight (Latané and Rendleman 1976). We then run
the following regression:
(3)  [log (implied_voli)]
=  +  1 Securitizationi +  2 Total_Enhancementsi

when banks reported that a higher portion of their assets
was being securitized.
In columns 1 and 3 of Table 3, Total_Enhancements,
Delinquency, Unused Commitments, and Stock Volatility are all
statistically insignificant. Securitization is the only significant
variable in those models.
Models 2 and 4 suggest that the insignificance of Total
Enhancements in models 1 and 3 is likely due to the omitted
interaction between enhancements and loan performance. In
both models 2 and 4, Total Enhancements alone is significantly
positive and has a strongly negative interaction effect with loan
performance, Total Enhancements  Delinquency. A simple
numerical exercise further illustrates the importance of the

+  3 Total_Enhancementsi Delinquencyi
  4 Delinquencyi   5 Unused Commitmentsi
  6 Stock Volatilityi   i 
14

This number corresponds to the 90th percentile of the severe delinquency
ratio in our sample.
15
This number corresponds to the 92nd percentile of the severe delinquency
ratio in our sample.
16
Specifically, several studies (see, for example, Patell and Wolfson [1981])
report that implied volatility estimates behave erratically during the last two
to four weeks before expiration and also that options with a very long time to
expiration are less sensitive to volatility changes). We therefore study only
those options with expiration dates between 28 and 100 days away from the
event day, with the latter criterion due to Deng and Julio (2005). Last, we
require each option to have nonzero trading volume in the event window.

FRBNY Economic Policy Review / July 2012

Table 4

Regression Analysis of Changes in Implied Volatility
Dependent Variable: [log( Implied Volatility )]
(1)

(2)

(3)

(4)

Constant

0.414
[5.12]***

0.404
[4.95]***

0.418
[5.37]***

0.41
[5.25]***

Securitization

0.045
[2.21]**

0.043
[1.80]*

0.049
[2.39]**

0.047
[2.12]**

Total enhancements

0.279
[2.64]**

0.367
[2.06]**

0.289
[2.62]**

0.316
[2.64]**

Delinquencies (all)

-0.137
[0.27]

0.15
[0.15]

-0.538
[0.71]

-0.125
[0.08]

Delinquencies (all) 
total enhancements

-4.744
[0.44]

Delinquencies (severe)

5. Conclusion

Delinquencies (severe) 
total enhancements
Unused commitments
One-year lagging
daily stock return
standard deviation
Observations
2

R (percent)

-5.53
[0.38]
0.187
[2.32]**

0.145
[1.53]

0.177
[2.10]**

0.172
[1.92]*

-10.945
[3.46]***

-10.626
[3.39]***

-10.952
[3.55]***

-10.726
[3.48]***

The dependent variable [log(implied_voli)] measures the
change in log(implied_voli) from the beginning of August 2001
to the end of September 2001. All the independent variables
remain the same as in equation 2.17
Overall, the significantly positive coefficient estimates for
Securitization suggest that higher securitization activities are
associated with higher risk as perceived in the forward-looking
option market (Table 4). This result, coupled with the positive
valuation effect of securitization just noted, suggests that
securitization was generally viewed as increasing both
shareholder value and risk. Unused commitments were also
17

We cannot control for market movement in the current regression setup.
As an alternative, we define excess implied volatility as the difference between
each option’s implied volatility and market volatility and use it to calculate the
dependent variable. The results are quantitatively similar to those in Table 4.

associated with higher risk, despite the lack of valuation
effect (see Table 2). Total Enhancements are always positive
and significant, which is sensible given that enhancements
represent exposure to the securitizing bank. Unlike the analysis
of valuation impact, we do not observe any significant
interaction effect between Total Enhancements and
Delinquency in the risk effect of credit enhancements. Overall,
the evidence suggests that both securitization activities and the
associated credit enhancements are perceived to add risk to the
securitizing bank, even though underlying assets have been
moved off the balance sheet.

The Role of Bank Credit Enhancements in Securitization

This article focuses on credit enhancements provided by banks
in the U.S. securitization market. Contrary to the impression
that banks have been surpassed by other financial institutions
in the shadow banking system, we show that banks have held
their own relative to monoline insurance companies in the
business of providing credit enhancements.
Having shown that banks are still important in providing
enhancements, we also investigate the role of bank enhancements in the securitization process. Enhancements obviously
serve as a buffer against observable risk, but we are interested
in the hypothesis, commonly advanced by academics, that
enhancements also serve as a signal of unobservable quality.
By keeping “skin in the game,” banks offering enhancements
may signal to investors or raters that the assets being securitized
are of high quality.
Our event study of banks’ first-time disclosure in 2001 of
their securitization activities finds evidence that the buffer
effect and the signal hypothesis could both be at play, with the
dominant effect depending on the riskiness of the securitized
assets. Specifically, we find that stock prices reacted favorably
to high enhancement provisioning among banks with betterperforming (lower-delinquency) securitizations, consistent
with the signaling hypothesis. Among banks with poorly
performing securitizations (high delinquency), however, stock
prices reacted negatively to higher levels of enhancements,
suggesting that the buffer role of enhancements dominates
under observably risky securitizations.
Evidence from cross-sectional regressions favors the buffer
hypothesis of enhancements. There we find a positive
relationship between delinquency rates on banks’ securitized
assets and credit enhancements, contrary to what the signaling
hypothesis suggests. Of course, it could be that enhancements
do serve a signaling role, but that role is dwarfed by the
buffering role.

Appendix: Variable Definitions

Delinquencies (All): Securitized loans thirty or more days past
due plus charge-offs divided by total securitized loans in the
category.
Delinquencies (All)  (Total Enhancements): Delinquencies
(all) times total credit enhancements.
Delinquencies (Severe): Securitized loans ninety days past due
plus charge-offs divided by total securitized loans in the
category.
Delinquencies (Severe)  (Total Enhancements): Delinquencies
(severe) times total credit enhancements.
Leverage: Total common equity divided by total balance sheet
assets.

ROA: Quarterly net income divided by total balance sheet
assets.
Securitization: Total securitized loans divided by total balance
sheet loans.
Severely Delinquent Loans/Total Securitized Loans: Securitized
loans ninety days past due plus charge-offs divided by total
securitized loans in the category.
Stock Volatility: One-year lagging daily stock return standard
deviation.
Total (Credit) Enhancements: Sum of interest-only strips,
subordinated securities, and other residual interest; standby
letters of credit; and other enhancements divided by total loans
in the category.

Log Asset Size: Natural log of total balance sheet assets.
Risk-Weighted Assets/Total Assets: Total risk-weighted assets
divided by total balance sheet assets.

Unused Commitments: Unused commitments to provide
liquidity divided by total loans in the category.

FRBNY Economic Policy Review / July 2012

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The Role of Bank Credit Enhancements in Securitization

Nicola Cetorelli and Stavros Peristiani

The Role of Banks in Asset
Securitization
1. Introduction

t is probably safe to assume that Frank Capra’s intentions
in his classic film It’s a Wonderful Life were to exalt the
fundamental virtues of the human character and to caution us
against the perils of material temptations. And yet, almost
seventy years later, his film remains one of the best portrayals
in Hollywood cinematic history of the role and importance
of banks in the real economy. This film could easily be used
in a classroom to describe a traditional model of financial
intermediation centered on banks, defined here as deposittaking institutions predominantly engaged in lending.1
The typical bank of the 1940s is embodied in the film’s
Bailey Building and Loan Association, a thrift institution that
takes deposits and invests them in construction loans that
allow the local residents to disentangle themselves from the
clutches of the greedy monopolist, Henry F. Potter. We also
see a bank run developing, and we learn of banks’ intrinsic
fragility when George Bailey, the film’s main character and
the manager of the thrift, explains to panicked clients
demanding withdrawals that their money is not in a safe on
the premises, but rather is, figuratively speaking, “in Joe’s
house . . . that’s right next to yours.”
The film debuted in 1946, but Bailey’s bank has remained
the dominant model of banking throughout the decades that
1

See, for example, the Council of Economic Education article, “It’s a Not So
Wonderful Life,” http://www.econedlink.org/lessons/index.php?lid=698
&type=student.

Nicola Cetorelli is a research officer and Stavros Peristiani an assistant
vice president at the Federal Reserve Bank of New York.
Correspondence: nicola.cetorelli@ny.frb.org; steve.peristiani@ny.frb.org

followed. Indeed, it is by and large the model that has inspired
the supervisory and regulatory approach to financial
intermediation, at least until recent times. Because of the
significant social externalities associated with banks’
activities, close monitoring of the banks’ books is warranted
in order to minimize the risk of systemic events (there is
indeed even room for a bank examiner in the film!).
However, if we were to remake the film and fit it into the
current context, many of the events would need significant
adaptation. For instance, we could still have the bank, but it
would be an anachronism to retain the idea that depositors’
money is in their neighbors’ houses. Most likely, the modern
George Bailey would have taken the loans and passed them
through a “whole alphabet soup of levered-up nonbank
investment conduits, vehicles, and structures,” as McCulley
(2007) incisively puts it when describing financial intermediation’s evolution to a system now centered around the
securitization of assets.
Under the securitization model, lending constitutes not the
end point in the allocation of funds, but the beginning of a
complex process in which loans are sold into legally separate
entities, only to be aggregated and packaged into multiple
securities with different characteristics of risk and return that
will appeal to broad investor classes. And those same securities
can then become the inputs of further securitization activities.
The funding dynamics of such activities diverge from the
traditional, deposit-based model in several ways. Securitization structures develop the potential for separate funding
The views expressed 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.

FRBNY Economic Policy Review / July 2012

mechanisms, such as issuance of commercial paper backed by
the securitized assets. And the creation of these new classes of
securities fuels the growth of other nonbank-centered, secured
intermediation transactions, such as repurchase agreements
and securities lending, in need of what Gorton (2010) calls
“informationally insensitive” collateral.
Under such a complex configuration, traditional banks may
no longer be needed, as we witness the rise of what McCulley—
apparently the first to do so—calls “shadow banks.” The goal
of our article is to delve more deeply into the analysis of asset
securitization activity in order to address the following
fundamental question: Have regulated bank entities become
increasingly marginalized as intermediation has moved off
the banks’ balance sheets and into the shadows? Aside from
the insights gained, furthering our understanding of the
evolution of financial intermediation has first-order normative
implications: If regulated banks are less central to intermediation and if intermediation is a potential source of
systemic risk, then a diminished bank-based system would
require a significant rethinking of both the monitoring and
regulatory fields.
This study provides, for the first time, a complete
quantitative mapping of the markets and entities involved in the
many steps of asset securitization. Our findings indicate that
regulated banks—here defined at the level of the entire bank
holding company—have in fact played a dominant role in the
emergence and growth of asset-backed securitization and that,
once their roles are explicitly acknowledged, a considerable
segment of modern financial intermediation appears more
under the regulatory lamppost than previously thought.
Using micro data from Bloomberg, we perform an
exhaustive census of virtually the entire universe of nonagency
asset-backed-securitization activity from 1978 to 2008. For
each asset-backed security (ABS), we focus on the primary roles
in securitization: issuer, underwriter, trustee, and servicer.
These four roles are critical in the life of an asset-backed
security, extending from issuance through maturity, and
therefore are also critical for the existence of a securitizationbased system of intermediation.
We show that the degree of bank domination varies according
to product type and securitization role. Banks are inherently
better suited to compete for the data-intensive trustee business,
capturing in most cases more than 90 percent of these services.
Having a strong role in securities underwriting, banks are able to
exploit their expertise to capture a significant fraction of assetbacked underwriting as well. Naturally, in issuing and servicing
the different segments of the securitization market, banks face
competition from nonbank mortgage lenders and consumer
finance companies. Nevertheless, we show that banks were
able to retain a significant and growing share of issuance and

The Role of Banks in Asset Securitization

servicing rights as well. Despite the greater complexity of a
system of intermediation based on asset securitization, which
appears to have migrated and proliferated outside of the
traditional boundaries of banking, our findings suggest that
banks maintained a significant footprint in much of this
activity through time.
Our article is organized as follows: In the next section, we
outline the principal roles in securitization. Section 3 describes
our sources of information for the vast number of asset-backed
securities. In Section 4, we briefly review the explosive growth
and evolving nature of the securitization market. Section 5
documents the dominant role of commercial banks and
investment banks in securitization. Section 6 concludes.

2. Primary Roles in Asset
Securitization
The securitization process redistributes a bank’s traditional
role into several specialized functions (see the appendix for
details on the evolution of asset securitization and for basic
terminology). The exhibit highlights the key roles in the
securitization process: issuer, underwriter, rating agency,
servicer, and trustee.2 The issuer (sometimes referred to as
sponsor or originator) brings together the collateral assets for
the asset-backed security. Issuers are often the loan originators
of the portfolio of securitized assets because structured finance
offers a convenient outlet for financial firms like banks, finance
companies, and mortgage companies to sell their assets.
In the basic example of securitization represented in the
exhibit, all of these assets are pooled together and sold to an
external legal entity, often referred to as a special-purpose
vehicle. The SPV buys the assets from the issuer with funds
raised from the buyers of the security tranches issued by
the SPV. The transfer of the assets to the SPV has the legal
implication of obtaining a true sale opinion that removes issuer
ownership and insulates asset-backed investors in the event of
an issuer bankruptcy. The SPV often transfers the assets to
another special-purpose entity—typically a trust. This second
entity actually issues the security shares backed by those assets
2

The lines connecting the different roles (boxes) in the exhibit represent
transaction flows of securities, assets, payments, information, and other
services. Sometimes these flows are two-way. For example, investors buy
security notes issued by the special-purpose vehicle (SPV) in lieu of cash.
Admittedly, the securitization example presented is fairly generic, depicting a
representative structure of the securitization process. This basic exhibit often
varies according to the type of collateral or the complexity of the security. Some
asset-backed securities can be more exotic, involving very complex interactions
among the involved parties. Even intricate securities—such as synthetic
collateralized debt obligations, in which the role of originator is blurrier—
rely on an SPV/trust structure.

A Representative Securitization Deal
Borrower
Lender
portfolio

Servicer

Trustee

SeniorAAA

Issuer
Specialpurpose
vehicle
Rating
agency

Noteholders

Subordinate
Residual

Underwriter
Ancillary support
Credit enhancement
Swap counterparty
Liquidity support

under GAAP sale rules outlined in the Financial Accounting
Standards Board’s Statement No. 125.
Another important role in the securitization process is
performed by the servicer, the party responsible for processing
payments and interacting with borrowers, implementing the
collection measures prescribed by the pooling and servicing
agreements and, if needed, liquidating the collateral in the
event of default. In cases in which the issuer is also the lender
of the underlying assets, there is a greater likelihood that the
issuer would retain these servicing rights.
In addition to managing payment flows, servicers are
expected to provide administrative help to the trustee. The
trustee is an independent firm with the fiduciary responsibility
for managing the SPV/trust and representing the rights of the
investors (that is, the noteholders). The primary role of the
trustee is to disperse payments to investors and to oversee the
security on behalf of the investors by collecting information
from the servicer and issuer while validating the performance
of the underlying collateral.
The role of underwriters in structured finance is similar to
that in other methods of securities issuance. Asset-backedsecurity underwriters fulfill traditional arranger roles of
representing the issuer (here, the SPV or trust). The primary
job of the underwriter is to analyze investor demand and design
the structure of the security tranches accordingly. Consistent
with traditional, negotiated cash-offer practices, underwriters
of asset-backed bonds would buy at a discount a specified
amount of the offer before reselling to investors. In addition to

marketing and selling these securities, underwriters provide
liquidity support in the secondary trading market. Because
asset-backed securities trade in over-the-counter markets, the
willingness of underwriters to participate as broker-dealers by
maintaining an inventory and making a market enhances the
issuance process.
Working closely with the rating agencies, the underwriter
helps design the tranche structure of the SPV to accommodate
investors’ risk preferences. Under the guidance of rating
agencies, the expected cash flows from securitized assets are
redirected by the underwriter into multiple tranches. The
rating agencies played a critical role in the rapid growth of
structured finance in the United States over the past two
decades. Rating agencies provide certification services to
investors who need to carry out a due-diligence investigation of
the underlying assets and evaluate the structure of the security.
Ratings are necessary because many large institutional
investors and regulated financial firms are required to hold
mostly investment-grade assets.
Although asset-backed-security ratings of subordination
structures vary across product types, most of them rely on a
common blueprint. These securities are typically structured
notes, meaning that the collateral cash flows are distributed
into several separate tranches. Asset-backed tranches usually
have different risk ratings and different maturities derived
from the same pool of assets. The diversity in tranches makes
them more appealing to a heterogeneous pool of investors with
various risk preferences and investment objectives. The core
components of each security include a number of senior
tranches rated AAA, a class of subordinate tranches with a
rating below AAA, and an unrated residual equity tranche.
The senior tranches receive overcollateralization protection,
meaning that credit losses would initially be absorbed by these
subordinate classes. Sometimes junior (mezzanine) belowAAA classes that are subordinate to senior classes may also have
a buffer of protection from the residual tranche or receive other
credit enhancements. The remaining cash flows are distributed
to the residual (equity) certificateholders. The residual
investors receive any leftover cash flows, but have no claim
on the collateral until all obligations to the more senior classes
of securities are fully met.
In addition to overcollateralization cushions, several other
ancillary enhancements are put in place to further protect
investors from default and other risks (such as liquidity risk,
currency fluctuation risk, and interest rate risk). In contrast to
overcollateralization buffers that are built into the security
internally, these credit enhancements are provided for a fee
from a third party. For example, it was a common practice in
the early years of nonagency mortgage securitization to buy
credit bond insurance (often referred to as a wrap) from

FRBNY Economic Policy Review / July 2012

independent insurance providers. Foreign exchange and
interest rate swaps are sometimes used to improve the overall
risk profile of the security, making it more attractive and easier
to price for investors. In addition, the SPV may lower risk
exposures by obtaining a letter of credit or an asset-swap
agreement.
Focusing on this taxonomy of roles allows us to better
understand the “shadowy” financial system of securitization.
Essentially, we argue that structured finance retains all the
unique facets of financial intermediation. Leaving aside rating
agencies, we show that securitization requires the primary
services of issuer, trustee, underwriter, risk enhancer, and
servicer. At the same time, banks perform exactly the same
roles in the traditional model of intermediation: They are loan
issuers and implicitly underwrite the loan portfolio to investors
(the depositors and equityholders). They serve in the role of
trustee as the delegated agent for their depositors and provide
credit enhancement, represented by the existence of equity held
on their balance sheets. They provide liquidity services, on both
sides of the balance sheet, to firms and depositors. And they act
as a servicer, collecting loan payments and paying interest to
depositors.
Although a bank in the traditional model of intermediation
performs all these roles, its compensation is determined
implicitly by the asset-liability contracts. With asset securitization, however, the same roles can be played by multiple
entities, each compensated separately for its services. This
proliferation of markets and entities involved in the securitization process is perhaps the main reason why the modern
system of intermediation seems so hard to decipher. We
hope this study contributes to enhanced understanding of
its main dynamics.

3. Data
To analyze the full extent of the securitization market, we
combine several databases that provide extensive information
on the SPV structure. The primary source for this securityspecific information is Bloomberg L.P. Recall that tranches
represent the basic building blocks of the SPV. Most assetbacked securities are sold as separate tranches with different
risks and corresponding prices. To accommodate this feature
of asset-backed securities, CUSIP identifiers are assigned at the
tranche level.3 The Bloomberg database tracks around 153,000
nonagency asset-backed tranches issued globally between 1983
3

This coding system was implemented in 1964 by the Committee on Uniform
Security Identification Procedures (CUSIP) to promote more efficient clearing
and settlement of U.S. and Canadian securities.

The Role of Banks in Asset Securitization

and 2008, corresponding to roughly 19,600 asset pools of SPVs.
Similarly, the Bloomberg database traces the issuance of about
130,000 private-label tranches between 1978 and 2008,
corresponding to roughly 10,300 multiclass pools.
The Bloomberg mortgage and asset-backed information
modules include an array of variables describing the characteristics of the issue (including face value, interest rate, maturity,
and ratings at issuance). The database also provides a snapshot
of the outstanding balance of the security (for example,
amount outstanding, tranche prepayment-rate history, and
defaults); however, it offers limited historical information on
the performance of the various security tranches. To fill some
of the historical performance gaps, our analysis uses the
Moody’s database of asset-backed securities. The information
from Moody’s focuses primarily on the securities it rates and
therefore does not span the entire population of asset-backed
securities available in Bloomberg.
More important for our analysis, the Bloomberg and
Moody’s databases offer extensive information on the primary
institutional parties outlined in our earlier exhibit. Information
on these parties allows us to determine the importance of
banks as well as other financial intermediaries in the securitization market. Most of the information available on issuers,
underwriters, and other parties to the transaction is collected
from the prospectus (or related documents). Typically, the
prospectus summarizes the underlying structure of the assetbacked security and the parties involved.
In contrast to the traditional bond or equity offerings, in
which the corporate issuer is a well-defined entity, the
identity of the issuer in asset-backed offerings is often
concealed behind the name of the SPV or trust that is legally
assigned this role. Thus, while the Bloomberg and Moody’s
information on underwriter, servicer, and trustee roles is
fairly accurate, the true identity of the issuer is masked by
the SPV/trust legal name. For instance, throughout the
period of our study, Lehman Brothers issued about 4,000
securities identified under the name of about seventy-five
sponsoring SPVs or trusts. At times, these issuing programs
revealed their Lehman Brothers affiliation (for example,
Lehman XS Trust or Lehman ABS Corp); however, the
majority of these issuers did not have a recognizable
association to Lehman Brothers.
A major task of our empirical analysis was to identify
the true issuer of the asset-backed securities. Much of this
information was obtained manually using various sources.
The detailed information compiled from Bloomberg,
Moody’s, and other sources allows us essentially to perform
an exact quantitative mapping of the asset-backed-securities
universe and the types of institutions involved.

4. The Emergence of Nonagency
Structured Finance
Structured finance (agency and nonagency securities combined)
was one of the most important sources of debt financing in the
United States over the last decade, representing about 30 percent
of the aggregate U.S. debt outstanding. Chart 1 shows the
explosive growth in the nonagency securitization market over
this period. The pace of securitization was particularly strong for
mortgage-backed securities (MBS) and home equity products
(HELOANs and HELOCs), retail asset-backed securities, and
collateralized debt obligations (CDOs), which collectively surged
from around $400 billion in 1998 to nearly $1.7 trillion in 2006.
(See the appendix for formal terminology of the different
categories of asset-backed securities.) However, the implosion
of the subprime mortgage market in 2008 not only caused the
collapse of nonagency MBS, it also adversely affected all other
security products.
Chart 2 offers a breakdown of issuance by product for
subprime MBS and home equity products, retail ABS, and
CDOs. It traces the share of each category from 1987 to 2008,
excluding the earlier low-volume and more erratic 1983-86
period. The “Other ABS” category includes some of the more
unusual cash flow securities (such as equipment leasing,
aircraft leasing, trade receivables, royalties, and small-business
loans). Notably, in the early years of nonagency securitization,
most of the growth came from retail ABS products, particularly
auto loans and credit card receivables. This initial trend
indicates a pent-up need to securitize outside the mortgage
sector, especially in consumer lending. The slower securitization in nonagency MBS was also partly dictated by supply
factors, as most originated loans in this earlier period were
conforming or prime mortgages and therefore fell under the
jurisdiction of the government-sponsored enterprises or the
private-label market.
By the mid-2000s, however, subprime MBS, home equity
securities, commercial mortgage-backed securities (CMBS),
and CDOs became the dominant outlet in securitization. At the
peak of the securitization market in 2006, subprime MBS and
home-equity-related products represented 26 percent of total
nonagency issuance, and CMBS amounted to about 30 percent
of the market issuance.4 The most striking rise in activity was

experienced in CDO products, where volume reached
$500 billion in 2007, roughly doubling from 2006. The surge
in CDO issuance was in part spurred by a sharp rise in global

Chart 1

Nonagency Asset-Backed Issuance by Type
of Collateral, 1982-2008
Billions of dollars
1,800
1,600
1,400
1,200
1,000

Card/Student
Loansloan
Credit card/student
Other ABS
MBS/HELOANs/HELOCs
CMBS
CDOs
Auto

800
600
400
200

0
1982 84 86 88 90 92 94 96 98 00 02 04 06 08
Sources: Bloomberg L.P.; authors’ calculations.
Notes: The chart shows nonagency asset-backed issuances for the
major securitization products. It does not include originations in the
private-label market. ABS are asset-backed securities; MBS are
mortgage-backed securities; HELOANs are home equity loans;
HELOCs are home equity lines of credit; CMBS are commercial
mortgage-backed securities; CDOs are collateralized debt
obligations.

Chart 2

Share of Nonagency Asset-Backed Market
Issuance by Type of Collateral, 1987-2007
Percent
100
90

Credit card/student loan

Other ABS

70
MBS/HELOANs/HELOCs

60
50

CMBS

40
30

CDOs

20
4

Admittedly, comparing the aggregate dollar volume of issuance across the
different categories of structured products sometimes yields misleading results.
For instance, securities backed by credit card receivables require the issuer to
maintain a large pool of reserves. Most credit card ABS are structured as standalone or master trust SPVs. In the late 1980s, securitization was done mostly by
the stand-alone method, which directs cash flow from receivables to a trust
representing a single security. Today, the most preferred method is the master
trust structure, which allows the issuer to channel cash flow to multiple
securities from the same trust. Because of the fluid nature of credit card
receivables, the issue manager is expected to maintain a large pool of
receivables and is obligated to replenish the trust with new collateral.

Auto

10
0
1987

Sources: Bloomberg L.P.; authors’ calculations.
Notes: The chart shows nonagency asset-backed issuances for the major
securitization products. It does not include originations in the
private-label market. ABS are asset-backed securities; MBS are
mortgage-backed securities; HELOANs are home equity loans; HELOCs
are home equity lines of credit; CMBS are commercial mortgagebacked securities; CDOs are collateralized debt obligations.

FRBNY Economic Policy Review / July 2012

Chart 3

Table 1

Share of Nonagency Asset-Backed Issues
Offered Offshore or Placed Privately, 1990-2007

Volume of Asset-Backed Issuance by Country,
1983-2008

Percent
40
Country

Rule 144a issues

United States
Cayman Islands
Ireland
Netherlands
Great Britain
Italy
Spain
Luxembourg
Other
Total

30
Reg S issues
20

0
1988

Notes: The chart shows the share of nonagency securitizations offered
under Rule 144a (private offerings) and Regulation S (off-shore security
issues). It does not include private-label originations.

Depending on investor demand, the underwriter may decide
on a public offering or opt for a Rule 144a private issue
directed exclusively to qualified institutional buyers. The
asset-backed bond can also be sold under Regulation S to
investors outside the United States (a so-called offshore
transaction).
Chart 3 reveals that the fraction of asset-backed securities
falling under Rule144a and Regulation S has gradually
increased over the past three decades. By the end of 2008,
34 percent of asset-backed bonds were offered privately to
qualified institutional buyers; about one in four securities were
sold offshore. Table 1 reveals that much of the growth in
overseas securitization issuance (representing issuers
domiciled outside the United States) took place in the Cayman
Islands. To be sure, a large fraction of the Cayman Islands
issuance stems from the growth of CDOs, especially synthetic

The Role of Banks in Asset Securitization

73.1
12.7
3.1
2.6
2.1
1.7
1.7
0.8
2.2

Notes: The table summarizes total nonagency issuance by country
of issuer. The aggregates represent the volume of originations for
all securities with a specified country of origin.

Sources: Bloomberg L.P.; authors’ calculations.

4.1 Offering Structure of Nonagency
Securities

7,089
1,227
304
254
198
167
165
79
213
9,697

Share
(Percent)

Sources: Bloomberg L.P.; authors’ calculations.

buyout activities that reemerged over this period. Most
leveraged buyout transactions were financed by leveraged
syndicated loans that were eventually packaged into CDOs.
The reported value probably represents a lower bound of CDO
volume because it does not include private CDO deals arranged
between banks and other counterparties.

Volume
(Billions of Dollars)

transactions, which were often sponsored by U.S. financial
institutions. Together, the United States and the Cayman
Islands accounted for more than 85 percent of the assetbacked-issuance volume.
A goal of Rule 144a and Regulation S is to allow companies
to raise funds quickly without having to go through the public
registration process mandated by the Securities and Exchange
Commission (SEC). While Rule 144a and Regulation S issues
are exempt from SEC registration rules, the issuer still needs
to provide information to potential investors through a
prospectus document; nevertheless, given the heterogeneity
in these informal filings, private or Regulation S offerings are
generally less transparent.

4.2 Private-Label Securities
Recall that the private-label market was a significant
component of nonagency structured finance during this
period. In a way, the private-label market can be viewed as
the complement of the subprime MBS market in nonagency
securitizations, encompassing all prime nonconforming and
Alt-A mortgage-based products.5 The main building block of
5

Alternative-A (Alt-A) mortgages are an intermediate category of loans falling
between the prime and subprime classes. Although Alt-A borrowers typically
have fairly good credit histories, their income may not be fully documented.
Furthermore, Alt-A loans are characterized by riskier loan-to-value and debtto-equity ratios, and the borrowers have lower credit scores.

Table 2

Issuance in Private-Label Mortgage Market

Year
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Total (1978-08)

Number of Tranches,
Non-U.S.

Number of Tranches,
U.S.

Volume, Non-U.S.
(Billions of Dollars)

Volume, U.S.
(Billions of Dollars)

Share, U.S.
(Percent)

23
45
135
186
251
384
414
489
958
1,067
1,284
1,918
1,970
850
10,033

1,567
2,187
2,636
5,086
3,939
3,060
5,833
7,462
9,638
10,377
14,476
14,286
12,391
1,209
105,462

22.5
5.4
17.6
21.9
43.1
71.8
97
134.7
290.9
315.1
369
555.9
739.7
880.3
3,569.90

28.9
37.6
55
140.1
98.5
78.4
168.6
247.2
333.4
420
645.9
641.9
701.7
64.2
3,909.60

56.2
87.4
75.8
86.5
69.6
52.2
63.5
64.7
53.4
57.1
63.6
53.6
48.7
6.8

Sources: Bloomberg L.P.; authors’ calculations.
Notes: The private-label market includes prime and Alt-A nonagency securities. The table summarizes private-label originations between 1995 and 2008.
The bottom row presents total originations since the inception of the private-label market in 1978. The aggregates represent only the number and volume
of originations for securities with a specified country of origin.

private-label MBS is the so-called jumbo loan, which is a loan
with an original balance greater than the upper bound of the
conforming mortgage limit for government-sponsored
enterprises. Although private-label MBS were first issued in the
late 1970s, the market remained fairly small compared with the
agency-sponsored market. With the robust rise in housing
prices in the United States over the last few decades, however,
nonconforming jumbo loans became a critical segment in
housing finance.
Table 2 depicts the growth and increasing importance of
the private-label market in the period from the mid-1990s
through the end of 2008. Like nonagency MBS, private-label
securities are offered overseas. But in contrast to nonagency
MBS, which are offered primarily in the United States, privatelabel MBS have a strong foothold overseas, especially in the
United Kingdom. In fact, total private-label activity between
1995 and 2008 is more or less evenly split between U.S. and
overseas issues. One striking difference highlighted by the
table is that the structure of prime MBS offered overseas is
significantly more concentrated: The average overseas tranche
is about ten times the size of the comparable U.S. tranche.

4.3 Security Summary Statistics
at the Tranche Level
The various categories of securities in Table 3 indicate that
credit card receivable ABS tranches are generally larger,
reflecting the shorter average life of the underlying cash flow
assets. The average tranche size for MBS is about $62 million,
relatively similar to the average for private-label MBS. The
minimum tranche size of zero often indicates the presence
of a more complex subordination payment structure, such as
residual tranches or excess spread tranches that typically have
zero balances at the time of issuance.
The significant difference between the mean and median
statistics suggests that the face value of issuance is skewed to the
right. The degree of skewness is particularly evident in privatelabel MBS, where the maximum offering is greater than
$40 billion, in contrast to a relatively tiny $8 million median
offering. Many of these gigantic tranches were originated in
Europe. For instance, a $40.7 billion floating-rate tranche was
issued in the Netherlands by Rabobank, and it consisted of
roughly 198,000 mortgages.

FRBNY Economic Policy Review / July 2012

Table 3

Tranche-Level Summary Statistics by Type of Security
Variable
Auto ABS
Face value
Maturity
Weighted average life
Weighted average maturity
Weighted average coupon
Credit card ABS
Face value
Maturity
Weighted average life
Weighted average maturity
Weighted average coupon
Student loan ABS
Face value
Maturity
Weighted average life
Weighted average maturity
Weighted average coupon
Other ABS
Face value
Maturity
Weighted average life
Weighted average maturity
Weighted average coupon
Collateralized debt obligations
Face value
Maturity
Weighted average life
Weighted average maturity
Weighted average coupon
Commercial MBS
Face value
Maturity
Weighted average life
Weighted average maturity
Weighted average coupon
MBS/HELOCs/HELOANs
Face value
Maturity
Weighted average life
Weighted average maturity
Weighted average coupon
Private-label MBS
Face value
Maturity
Weighted average life
Weighted average maturity
Weighted average coupon

Mean

Median

Minimum

Maximum

198.3
63.6
26.2
59.7
11.3

110.0
60.9
24.0
55.0
10.2

0.0
1.9
0.8
4.0
1.0

5,519.0
415.7
270.6
660.0
30.2

345.5
96.3
56.1
56.6
10.3

165.8
89.6
59.3
57.0
9.6

0.0
5.1
4.8
6.0
3.9

4,504.0
450.4
239.4
110.0
19.6

138.9
301.2
91.3
151.1
7.2

82.0
334.4
84.0
140.0
7.3

0.0
12.2
6.1
65.0
3.8

2,910.0
495.2
337.4
278.0
20.7

132.7
162.1
52.9
96.0
8.8

52.7
121.3
42.0
56.0
8.3

0.0
1.0
1.0
2.0
2.8

5,064.8
1137.3
383.4
550.0
20.0

90.2
269.6
90.7
142.2
6.5

27.0
182.6
93.4
98.0
5.8

0.0
2.9
1.2
1.0
1.9

16,600.0
1205.3
604.8
405.0
29.9

156.0
283.6
75.3
118.4
6.8

64.0
304.5
69.8
109.0
6.4

0.0
1.8
0.6
0.0
0.0

4,199.0
751.9
387.6
443.0
68.0

62.2
355.6
54.5
320.6
8.6

19.4
366.0
56.9
349.0
8.2

0.0
0.9
0.2
1.0
2.7

8,882.0
698.7
706.6
477.0
18.5

66.1
359.3
75.6
329.2
6.7

8.3
367.1
63.6
357.0
6.6

0.0
1.8
0.1
4.0
0.0

40,720.6
1,145.3
420.0
792.0
22.5

Sources: Bloomberg L.P.; authors’ calculations.
Notes: The table presents summary statistics for asset-backed securities (ABS)
at the tranche level. Tranche face value is measured in millions of dollars;
weighted average life and maturity are measured in months; weighted average
coupon is measured in percent. MBS are mortgage-backed securities; HELOCs
are home equity lines of credit; HELOANs are home equity loans.

The Role of Banks in Asset Securitization

5. The Role of Financial Institutions
in Securitization
This section investigates the primary functions of asset-backed
securitization: issuer, underwriter, servicer, and trustee.
Because of limited data availability, we are unable to examine
the various ancillary services in structured finance (institutions
providing credit, currency, and liquidity risk enhancements).
While the rating process is very important in the asset-backed
transaction, this role is confined to a handful of independent,
specialized credit-rating agencies and is therefore outside the
scope of this article.

5.1 Asset-Backed-Security Issuers
The first step in the securitization process is issuance, the
process of assembling the underlying collateral creating
the asset-backed security. The issuer is closely linked with
the lender, and sometimes these two functions overlap.
The structure therefore depends on the type of collateral.
Consumer auto finance lenders and large retail banks would
be expected to dominate auto securitizations, while banks,
nonbank mortgage lenders, and thrifts would compete more
effectively in the private-label and MBS sectors.
These concentrations in securitization activities are evident
in Table 4, which presents the distribution of asset-backed
issuance by type of financial institution. Consistent with our
expectations, auto loan issuances are dominated by consumer
finance companies, especially captive auto finance companies
(Ford Motor Credit, for example) and, to a lesser degree, by
retail commercial banks. Over the entire sample period 19832008, consumer finance companies accounted for 68.4 percent
of auto loan securitizations. Most of the remaining auto loan
securities were originated by banks.
Turning to credit card receivables, we find that this segment
is mostly under the control of banks, which are responsible
for 93.9 percent of the issuance, corresponding to about an
88.3 percent Herfindahl-Hirschman Index (HHI) of market
concentration. Not surprising, student loan securities are
issued primarily by government-sponsored agencies, such
as Sallie Mae, and banks participating in government studentlending programs. The residual category “Other ABS”
represents an assortment of assets, ranging from trade and
leasing receivables to small-business loans. The largest issuers
in this heterogeneous category of securitizations are consumer
finance companies, insurance firms, nonfinancial firms (for
example, computer and airline companies), and banks.

Table 4

Distribution of Asset Securitizations by Type of Issuer, 1983-2008

Auto ABS
Credit card ABS
Student loan ABS
MBS/HELOCs/HELOANs
CMBS
CDOs
Other ABS
Private-label

Banks

Investment Banks

Mortgage Brokers

Hedge Funds

Consumer
Finance

Government

Total

HHI

409.1
(29.4)
1,095.0
(93.9)
54.3
(22.8)
1,134.3
(39.0)
740.4
(53.5)
772.4
(38.9)
228.5
(29.9)
5,077.6
(66.8)

14.4
(1.0)
10.1
(0.9)
0
(0.0)
651.9
(22.4)
415.7
(30.0)
119.8
(6.0)
36
(4.7)
837.7
(11.0)

15.1
(1.1)
0.8
(0.1)
0
(0.0)
758.5
(26.1)
84.7
(6.1)
61.8
(3.1)
44.9
(5.9)
824.2
(10.9)

2.3
(0.2)
6.9
(0.6)
0
(0.0)
64.2
(2.2)
37.5
(2.7)
927.3
(46.7)
39.6
(5.2)
85.0
(1.1)

952.8
(68.4)
53.9
(4.6)
33.7
(14.1)
296.8
(10.2)
80.2
(5.8)
103.5
(5.2)
323.8
(42.4)
604.8
(8.0)

0
(0.0)
0
(0.0)
150.4
(63.1)
2.9
(0.1)
25.8
(1.9)
2.4
(0.1)
91.2
(11.9)
167.5
(2.2)

1,393.6

55.4

1,166.6

88.3

238.4

47.0

2,908.6

38.4

1,384.4

37.6

1,987.2

28.1

764.1

29.2

7,596.6

46.5

Sources: Bloomberg L.P.; authors’ calculations.
Notes: The table presents a cross-tabulation of asset-backed securities (ABS) by product type and issuer type. Numbers in parentheses represent market
shares, measured in percent. The variable HHI denotes the Herfindahl-Hirschman market concentration index. The HHI can take a value of between 0 and
100, with 100 representing a market dominated by a single firm. MBS are mortgage-backed securities; HELOCs are home equity lines of credit; HELOANs
are home equity loans; CMBS are commercial mortgage-backed securities; CDOs are collateralized debt obligations.

Commercial banks, investment banks, and mortgage
lenders have sponsored most MBS and home equity issuances,
which represent the largest consumer retail segment. In particular, commercial banks and investment banks are responsible
for close to 62 percent of the volume, while most of the
remaining issuances were initiated by mortgage lenders and
consumer finance companies. MBS issuances are moderately
concentrated, with a 38.4 percent HHI, dominated by a small
group of financial institutions led by Countrywide, Lehman
Brothers, and Morgan Stanley, which collectively accounted
for 25 percent of the overall volume.
Interestingly, much of the MBS issuance among consumer
finance companies can be attributed to GMAC, the finance arm
of the world’s largest automaker, General Motors. GMAC was
the third-largest issuer, with roughly $215 billion of MBS
during 1983-2008. Most of GMAC’s MBS securitization
activities were done by its subsidiary Residential Capital LLC
(ResCap). Like most other large issuers of MBS, this mortgage
unit was eventually overwhelmed by the collapse of subprime
mortgages, further contributing to GMAC’s financial
difficulties.

5.2 The Issuance Structure in CMBS
The securitization methods used in CMBS are similar to those
employed in MBS, but with the difference that the underlying
collateral consists of commercial mortgages that derive their
principal and interest cash flows from property assets. However,
there are some distinct operational and structural features in
CMBS. For one, CMBS do not burden the investor with
significant interest rate risks because commercial mortgages do
not generally have a prepayment feature. Commercial real estate
lending is dominated by banks and life insurance companies.
Banks typically lend shorter-term financing; in comparison, life
insurance firms, motivated by the long-dated structure of their
liabilities, prefer to provide longer-term real estate loans.
Although investment banks are not typically large providers of
commercial real estate credit, they are important in the credit
intermediation process of real estate finance as lead underwriters
in the syndicated loan market.
Considering the importance of commercial and investment
banks in lending and arranging commercial real estate
credit, it is not surprising that these institutions dominate
CMBS issuances with a combined market share of more
than 83 percent. Although life insurers are significant credit

FRBNY Economic Policy Review / July 2012

providers in real estate, they typically prefer not to securitize
these loans, leaving this responsibility to the commercial and
investment banks that have the financial expertise to sponsor
a wide variety of asset-backed securities.
The HHI for CMBS issuances is around 37.6 percent, very
similar to the level of concentration achieved in the MBS
sector. The largest issuer of CMBS during 1983-2008 was
Credit Suisse (with close to a 13 percent market share),
followed by Lehman Brothers (9.2 percent) and JPMorgan
Chase (8.3 percent). The remaining list of top issuers is
dominated by large global banks.

5.3 CDO Issuers
Arguably, CDO securities represent some of the most unique
and intricate securitization structures. The typical MBS derives
its cash flow from a large pool of homogenous mortgage loans.
In contrast, the most basic CDO comprises a small number of
corporate debt obligations. The CDO collateral may include
business loans (leveraged loans, revolving credit facilities, and
term loans), corporate bonds, and even other asset-backed
securities.6 In addition to the usual benefits of securitization
outlined previously, CDO sponsors may be motivated by
arbitrage incentives, aiming to profit from purchasing and
securitizing corporate debt or other assets at favorable prices.7
Most of the earlier CDOs were static, meaning that the
underlying collateral was held over the life of the security.
Concerned by the rise in corporate distress during the 2000s,
some investors preferred a managed CDO structure, in which
the issuer was more proactive in managing credit exposure.
Another important innovation in structured finance is the
synthetic CDO, in which the cash flows stem from a credit default
swap (CDS) derivative contract written on a reference portfolio of
corporate bonds, loans, and CDS indexes. The role of the issuing
SPV in a synthetic CDO is very different. In contrast to the more
traditional asset-backed structure, in which the SPV draws cash
flows from a pool of underlying assets, in a synthetic CDO the
entity sells protection on the reference portfolio.8 The SPV and its
investors derive cash flows from the premiums paid by the CDS
protection buyers (typically a commercial or investment bank),
but are liable for all credit events.
6

Often, the CDO collateral consists of other existing CDO securities. If a
substantial fraction of the underlying asset portfolio stems from existing
CDOs, these deals are referred to as CDO2 or “CDO squared.”
7
Such a CDO security is typically referred to as an arbitrage CDO. If the
originator securitizes its own assets (corporate loans, bonds, and other large
receivables), then the CDO is known as a balance sheet CDO. For a more
detailed discussion of CDO securities, see Bond Market Association (2004).
8
For a more detailed discussion, see Adelson and Whetten (2004).

The Role of Banks in Asset Securitization

These more complex managed or synthetic CDO structures
are more demanding on issuers. Managed CDOs require
expertise in corporate debt markets in order to deal with credit
exposures. Issuers of synthetic CDOs need to properly price the
CDS protection of the reference portfolio. In light of these
additional responsibilities, the role of the issuer in CDOs is
typically referred to as collateral manager.
Table 4 shows that banks were responsible for close to
39 percent of CDO securitizations, sponsoring $772 billion
of securities during 1983-2008. It is evident that large sophisticated banks with a large footprint in syndicated lending and
bond underwriting are well suited to be CDO collateral
managers. The table also reveals that hedge funds accounted for
more than half of the CDO issuances. Hedge funds are natural
candidates for the role of collateral manager because they often
have experience trading corporate securities and CDS
derivative contracts. In the case of arbitrage CDOs, the
responsibilities of collateral managers are very similar to those
of hedge fund managers, whose trades seek to take advantage of
relative value opportunities.
In general, the CDO issuance market is relatively less
concentrated than other markets, having an HHI of close to
28 percent. Hedge funds have been able to compete successfully in this segment, originating nearly half of the CDOs.
However, most of the top-tier positions in the league CDO
tables are occupied by large and sophisticated bank holding
companies and investment banks, such as Goldman Sachs,
Credit Suisse, Deutsche Bank, and Société Générale-TCW.

5.4 The Role of Servicer
Throughout the life-span of the structured securities, the servicer
has several fiduciary responsibilities: 1) to collect payments
generated from the underlying assets, 2) to transfer payments to
accounts managed by the trustee, and 3) to manage deposits and
investments of the revenue streams on behalf of the trustee.9 This
specialized role requires the servicer to retain all loan or securityspecific information in order to collect and divert cash flows as
well as track performance. These duties are therefore easier to
perform for an entity associated with the lender of the assetbacked-security collateral.
The close links between servicing, issuing, and lending
suggest that these roles are often combined. Thus, consumer
finance companies not only were the dominant issuers of
9

In addition to the traditional servicer function (sometimes referred to as
primary or master servicer), some ABS transactions may involve variations of
these responsibilities. Sometimes the primary or master servicer responsibility
may be transferred to a special or backup servicer if the loan or other asset in
the security defaults.

Table 5

Distribution of Asset Securitizations by Type of Servicer, 1983-2008

Auto ABS
Credit card ABS
Student loan ABS
MBS/HELOCs/HELOANs
CMBS
CDOs
Other ABS
Private-label

Banks

Investment
Banks

Mortgage Lenders

Hedge Funds

Consumer Finance

Government

HHI

26.6
88.6
13.0
54.2
48.8
71.8
21.1
79.6

1.1
0.0
0.0
2.0
0.2
0.9
0.0
0.3

0.8
0.2
0.0
22.2
45.3
11.4
13.2
14.7

1.2
0.4
0.0
5.3
1.5
10.3
5.6
1.2

70.3
10.8
3.0
16.3
4.2
5.6
52.0
3.2

0.0
0.0
84.0
0.0
0.0
0.0
8.1
1.0

56.5
79.8
72.4
37.3
44.6
54.2
34.2
40.9

Sources: Bloomberg L.P.; authors’ calculations.
Notes: The table presents a cross-tabulation of asset-backed securities (ABS) by product type and servicer type. Market shares are measured in percent.
The variable HHI denotes the Herfindahl-Hirschman market concentration index. The HHI can take a value of between 0 and 100, with 100 representing
a market dominated by a single firm. MBS are mortgage-backed securities; HELOCs are home equity lines of credit; HELOANs are home equity loans;
CMBS are commercial mortgage-backed securities; CDOs are collateralized debt obligations.

auto ABS; they also serviced 70.3 percent of these securities
(Table 5). Being the largest lenders of revolving credit card
debt, banks were able to capture close to 88.7 percent of the
credit card ABS servicing (resulting in a 79.8 percent HHI for
this class of asset-backed securities).
The data-intensive specialty link between lending and
servicing is further evident in real estate securitizations. Large
bank lenders are dominant in MBS, CMBS, and CDO servicing,
having market shares of 54.2 percent, 48.8 percent, and
71.7 percent, respectively. Although investment banks and
hedge funds are also significant issuers in these segments,
their capacity to serve as servicer is more limited because they
have to build the information infrastructure to compete for
these services.

5.5 Underwriters of Asset-Backed Securities
The underwriter is the entity that assumes responsibility for
structuring the asset-backed security (for example, designing
the composition of tranches, and the size and type of credit
and liquidity enhancements) based on the characteristics of
the collateral and existing market conditions. Underwriters
are also in charge of the actual securities sales, typically
acquiring the securities from the special-purpose entities and
therefore bearing some of the initial risks associated with
the transactions.

Investment banks have traditionally fulfilled this role in
bond and equity financing, arranging and selling the offering
for issuing firms. Commercial banks bring an additional
dimension to the underwriting process by enhancing certification stemming from joint-production informational
advantages (gathered primarily from screening and monitoring borrowers) that can be shared with investors. These
certification benefits also are present in asset-backed securities
such as CMBS or collateralized loan obligations, where the
bank has private information on the credit quality of the
borrower. Essentially, a bank is an information specialist that
can bridge the certification gap between issuers and investors.
The importance of expertise in securities underwriting is
quite evident in asset-backed securitization, where commercial
and investment banks dominate. Table 6 shows that, together,
commercial and investment banks were responsible for nearly
all of the underwriting in retail ABS. Because of their significant
presence across many of the securitization product segments,
banks were better placed to retain a larger share of the
underwriting. For instance, banks were able to attract
69.5 percent of the underwriting business in auto ABS, a
market in which security issuance was attributable mostly to
consumer finance companies. Although investment banks
have a very small presence in mortgage lending, they managed
to capture a considerable fraction of MBS underwriting.

FRBNY Economic Policy Review / July 2012

Table 6

Table 7

Distribution of Asset Securitizations by Type
of Lead Underwriter, 1983-2008

Distribution of Asset Securitizations by Type
of Trustee, 1983-2008

Auto ABS
Credit card ABS
Student loan ABS
MBS/HELOCs/
HELOANs
CMBS
CDOs
Other ABS
Private-label

Banks

Investment
Banks

All Others

69.4
65.7
88.6

29.7
32.9
10.4

0.9
1.4
1.0

57.1
54.0
79.5

56.1
55.2
63.7
60.8
71.8

41.4
41.1
32.4
35.7
24.9

2.5
3.7
3.9
3.5
3.3

48.7
47.4
51.1
49.8
57.8

HHI

Sources: Bloomberg L.P.; authors’ calculations.
Notes: The table presents a cross-tabulation of asset-backed securities
(ABS) by product type and lead underwriter type. Market shares are measured in percent. The variable HHI denotes the Herfindahl-Hirschman
market concentration index. The HHI can take a value of between 0 and
100, with 100 representing a market dominated by a single firm. MBS are
mortgage-backed securities; HELOCs are home equity lines of credit;
HELOANs are home equity loans; CMBS are commercial mortgagebacked securities; CDOs are collateralized debt obligations.

5.6 Trustee Services
The transactions of the special-purpose entity that buys the
loans are typically handled by a trustee. The trustee guarantees
that the transactions are administered in accordance with
the related documentation and, in a cost-effective manner,
takes care of the physical delivery of the securities, follows
compliance and performance-related matters, and handles
cash and information processing for the noteholders.
Significantly, a trustee must work closely with the issuer and
servicer to protect the welfare of the investors. In contrast
to the roles of issuer or servicer, which can be combined, a
trustee should be an independent entity whose sole purpose is
to represent the investor and thus eliminate any conflict-ofinterest problems.
Given the administrative nature of the trustee business, this
service is best suited to large custodian banks with a costeffective back-office infrastructure to process the information.
Table 7 demonstrates the importance of custodian banks across
all types of asset-backed securities. The high market concentration measures (the HHI is over 80 percent for most product
types) indicate that a handful of banks are responsible for the
securitization trustee business. Although not evident from the
table, the hierarchy of bank trustees differs across the various
types of asset-backed products, reflecting the heterogeneous
character of the collateral and its payment infrastructure.

The Role of Banks in Asset Securitization

Auto ABS
Credit card ABS
Student loan ABS
MBS/HELOCs/HELOANs
CMBS
CDOs
Other ABS
Private-label

Banks

All Others

HHI

97.9
98.0
98.7
96.7
99.3
93.2
92.1
83.5

2.1
2.0
1.3
3.3
0.7
6.8
7.9
16.5

95.9
96.0
97.5
93.5
98.6
87.2
85.3
71.6

Sources: Bloomberg L.P.; authors’ calculations.
Notes: The table presents a cross-tabulation of asset-backed securities
(ABS) by product type and trustee type. Market shares are measured in
percent. The variable HHI denotes the Herfindahl-Hirschman market
concentration index. The HHI can take a value of between 0 and 100,
with 100 representing a market dominated by a single firm. MBS are
mortgage-backed securities; HELOCs are home equity lines of credit;
HELOANs are home equity loans; CMBS are commercial mortgagebacked securities; CDOs are collateralized debt obligations.

The top four trustees in MBS and home equity products are
BNY Mellon, Deutsche Bank Trust, U.S. Bank National
Association, and Wells Fargo. BNY Mellon remains the largest
trustee for CDO securities, achieving close to a 38 percent
market share. However, BNY Mellon is not very active in the
CMBS market, which is dominated by LaSalle National Bank
and Wells Fargo.

5.7 A Historical Overview of the
Securitization Role of Banks
Our findings to this point indicate that banks are by far the
predominant force in the securitization market. To further
explore the importance of banks, we examine more closely the
evolution of their market shares for the principal functions of
securitization. We have already highlighted the fact that trustee
business in securitization is dominated by a small group of
custodian banks. Throughout the entire 1990-2008 period,
banks’ market share remained well over 90 percent. These
trustee banks are best suited to processing information and
acting on behalf of investors.
We also find that, typically, banks have issued about half of
the nonagency asset-backed securities. Banks were therefore a
significant force in these shadow banking segments related to
securitization all along. Although banks had to compete with
nonbank institutions throughout the different phases of

Chart 4

Chart 5

Nonagency Asset-Backed Securities: Bank Share
of Primary Roles, 1990-2008

Share of Banks in the Private-Label Mortgage
Market

Percent

100

100
Trustee

Trustee

Underwriter

Underwriter
60

Servicer

Issuer

Servicer

Issuer

0
1990

Sources: Bloomberg L.P.; authors’ calculations.
Note: The chart shows the market share of banks for the four primary
securitization functions in the nonagency securitization market.

securitization, they remained formidable players. In contrast to
the asset-backed-issuance business, in which they managed to
retain a constant market share, banks were more aggressive in
expanding servicing and underwriting, increasing their market
shares from the early 1980s to the peak of the securitization
market in 2007 (Chart 4).
Much of the banks’ success in underwriting can be attributed
to the Gramm-Leach-Bliley Act (1999), which formally removed
many of the legal barriers put in place by the Glass-Steagall Act
(1933); Glass-Steagall had prohibited commercial banks from
participating in equity and bond underwriting. Actually, the
Federal Reserve authorized banks, through their Section 20
subsidiaries, to have limited participation in these underwriting
and other ineligible securities activities starting in the late 1980s.
After the enactment of Gramm-Leach-Bliley, large banks made
a concerted push to expand their securities underwriting
business, raising their asset securitization market shares to
nearly 70 percent.
Banks also gradually increased their presence in servicing
from less than 10 percent in the early 1990s to around
60 percent by the end of 2008. The stronger presence in
servicing stems from the changing character of the securitization market, which shifted from retail ABS products to
CMBS, MBS, and CDO products in which the underlying
collateral and information are primarily originated and kept
by bank lenders.
In addition to dominating these key segments of the
nonagency asset-backed markets, banks also managed to retain
significant trustee business in the private-label market (Chart 5).

1984 86

Sources: Bloomberg L.P.; authors’ calculations.
Note: The chart shows the market share of banks for the four primary
securitization functions in the private-label market.

Relying on their Section 20 subsidiaries, banks expanded their
underwriting activities aggressively in this sector starting in the
early 1990s to achieve a market share of over 80 percent by the
end of 2008. In addition, banks raised their market share of
issuance from 20 percent in the early 1990s to 75 percent in
2008. The success of banks in competing and dominating most
services in the private-label market can be attributed to their
ability to effectively dominate lending in the nonconforming
prime mortgage sector.

6. Conclusion
Financial intermediation has grown increasingly complex in
recent decades. The system of financial intermediation, which
traditionally had centered on banks simultaneously playing
the many roles needed to guarantee an efficient match between
supply and demand for funds, has become decentralized,
and those roles can be played separately by more specialized
entities. This transformation in intermediation raises
legitimate questions about the role of banks and the role of
bank-based supervision and regulation, as systemic risk may be
migrating out of the reach of regulators and policymakers.
The thesis here, however, is that a proper assessment of
financial intermediation’s evolution and its now more complex
characterization needs to be done through a proper quantification of the main roles—and thus potential new markets and
entity types—involved in the process.

FRBNY Economic Policy Review / July 2012

We took our thesis to the data and analyzed in detail the
system of asset securitization, which represents the core of the
modern system of financial intermediation. For the first time,
we have a true quantitative mapping of which party does what
along the crucial steps in the credit intermediation chain.
Our analysis has focused on four principal functions of
securitization: issuer, underwriter, servicer, and trustee.
We demonstrate that large bank holding companies—and,
to a lesser extent, investment banks—have been significant
contributors to all phases of this process. Although much of the
securitization activity appears to have been done outside the

The Role of Banks in Asset Securitization

regulatory boundaries of banking, we find strong evidence to
the contrary.
The modern system of financial intermediation appears
less complex than it did at first glance. Despite the multiple
steps needed for a dollar of funding to reach its destination,
the system still requires the same set of basic intermediation
functions. And when looked at closely, banking firms—
identified according to their broader organizational
structure—are still playing a central role. These considerations should be relevant in any future assessments of the
role of financial system supervision and regulation.

Appendix: The Evolution of Asset Securitization

The Securitization Market
Securitization is a financial innovation with a long history in
U.S. capital markets and in several economies overseas. It
involves the issuance of securities that derive their cash flow
from underlying assets. The most common asset-backed
structure sells shares in this securitized pool to investors. The
novelty of asset securitization is that the performance of the
security is determined by the cash flow of the pledged collateral
and in theory should not depend on the financial strength of
the asset issuer.

Agency Mortgage-Backed Securities
Structured finance techniques were the foundation of the
agency mortgage market, which began in the early 1970s when
the Government National Mortgage Association (Ginnie Mae)
used these techniques to pool government-sponsored
mortgage loans. These structures were later embraced by the
Federal Home Loan Mortgage Corporation (Freddie Mac)
and the Federal National Mortgage Association (Fannie Mae).
The key mechanism in the agency securitization market was
the pass-through mortgage-backed security, which facilitated
the seamless transfer of cash flows from mortgage lenders to
investors.
Another important phase of asset securitization in the
United States emerged in the mid-1980s and was aimed at
satisfying investors looking for more diverse mortgage
securities with different maturities and different interest rate
characteristics. Initially, securitization products, such as
collateralized mortgage obligations and multiclass structures,
were used to transform and resecuritize existing agency
mortgage-backed securities. The resecuritization of agency
securities greatly expanded the role of Freddie Mac and Fannie
Mae, which were chartered by Congress with the mandate of

supporting the secondary market in mortgage debt and
enhancing credit availability in the housing finance market
(Fabozzi and Dunlevy 2001).

Nonagency Asset-Backed Securities
The traditional agency securitization structures offered a
mechanism for the creation of a nonagency securitization
market that began to flourish in tandem with the agency
market in the mid-1980s. A key catalyst in this process was the
Tax Reform Act of 1986, which enabled the creation of real
estate mortgage investment conduits (REMICs). The
authorization of REMICs was a watershed event in the agency
resecuritization and nonagency market. This accounting
vehicle essentially allows the transfer of assets into a
bankruptcy-remote trust that is insulated from the
performance of the asset issuer.a
The REMIC spurred the explosive growth in the securitization of nonconforming mortgage-backed securities using
alternative credit enhancement structures. The nonconforming mortgage market, more commonly referred to as
the private-label securities market, consists of loans that
are too large to meet the agencies’ size limits. In 1995, the
longstanding Community Reinvestment Act was modified
to encourage the securitization of lower-credit-quality
loans. An environment of lower interest rates also made
homeownership affordable, allowing borrowers to refinance
and consolidate their debt.
Technological innovations and advanced credit-scoring
systems also played a critical role in automating underwriting
procedures and lowering borrowing costs. These financial
innovations and lower underwriting standards spurred the
rapid growth of the subprime mortgage market, which surged
from roughly $65 billion in 1995 to about $1.3 trillion in 2007,
according to Inside Mortgage Finance.

The Tax Reform Act of 1986 required income from REMICs to be treated as
regular interest and specified several rules concerning the taxation of the
residual payments from REMIC investments.

FRBNY Economic Policy Review / July 2012

Appendix: The Evolution of Asset Securitization (Continued)

A key requirement in a REMIC is that the underlying
collateral must be static—that is, a real property or a real
property derivative. The REMIC structure cannot be applied to
a large subset of cash-flow-producing assets, such as car loans,
revolving credit card receivables, lease receivables, student
loans, corporate debt, and commercial real estate loans. To fill
this gap, asset securitization has relied on several alternative
bankruptcy-remote structures. The primary mechanisms for
securitizing nonmortgage assets are provided by a variety of
common-law trusts and revolving special-purpose entities such
as master trusts and commercial paper conduits.b

Classification of Nonagency
Securities
This study follows the Securities Industry and Financial
Markets Association (SIFMA) classification and terminology
for nonagency asset-backed securities. While it is true that the
term asset-backed security (ABS) is sometimes used to describe
any structured security that is backed by an asset’s cash flows,
SIFMA uses this definition more narrowly to refer to any asset
receivables other than direct mortgage loans. According to this
designation, the ABS class represents a wide variety of
consumer finance assets (automobile loans, credit card

Static trusts are typically created as grantor trusts or as statutory entities
referred to as owner trusts. In many ways, a grantor trust is similar to a passthrough security in that it facilitates the transfer of income from the underlying
asset (for example, automobile interest rate payments and principal) to
investors. A grantor trust must be passive, with no management responsibilities
for the investors, and limited in the number of asset classes. In comparison, an
owner trust sells certificates to investors, allowing for a more complex structure
of ownership between senior and subordinate investors and sequential
payment distributions according to the maturity of the different tranches.
Revolving structures are often very useful for credit card and home equity line
asset-backed securities. In a revolving master trust, the principal and interest
cash flows are distributed in phases (initially a revolving and subsequently an
amortization phase).

The Role of Banks in Asset Securitization

receivables, student loans, consumer loans, and other, more
exotic, lease financing receivable structures). The ABS class also
encompasses home equity loan (HELOAN) and home equity
lines of credit (HELOC) products. Securities backed by
mortgages are commonly described as mortgage-backed
securities, or MBS (sometimes known as RMBS, for residential
MBS).
Recall that there are two large subgroups of MBS: privatelabel MBS (based on prime or Alt-A nonagency mortgage
products) and subprime MBS (derived from subprime
mortgages). Because subprime MBS, HELOAN, and HELOC
securities are all inherently collateralized by the value of a
home, our analysis lumps these asset classes together. Finally,
structures backed by commercial real estate loans are referred
to as commercial mortgage-backed securities (CMBS).
Another important asset-backed class is the collateralized
debt obligation (CDO), which includes securities backed by
debt instruments. In particular, CDOs backed by corporate
loans or bonds are referred to as collateralized loan obligations
(CLOs) or collateralized bond obligations (CBOs), respectively.
Many of the recent and complex multiclass CDO securities that
were based on existing nonagency MBS are often referred to as
“CDO squared.” Over the last few years, an important category
to emerge is synthetic CDOs. This class of CDOs relies on credit
derivatives (typically, credit default swaps) to transfer asset
risks and cash flow payments between investors and issuers.

References

Adelson, M., and M. Whetten. 2004. “CDOs in Plain English:
A Summer Intern’s Letter Home.” Nomura Fixed Income
Research, September 13. Available at http://www.vinodkothari
.com/Nomura_cdo_plainenglish.pdf.
Bond Market Association. 2004. CDO Primer. Available at http://
www.public.asu.edu/~chliu1/recapmarkets_dese/readings/
16_CDO_Primer_BondMarketAssn.pdf.

Fabozzi, F. J., and J. N. Dunlevy. 2001. Real Estate–Backed
Securities. Hoboken, N.J.: Wiley.
Gorton, G. B. 2010. Slapped by the Invisible Hand: The Panic
of 2007. New York: Oxford University Press.
McCulley, P. 2007. “Teton Reflections.” PIMCO Global Central
Bank Focus, September.

Dafna Avraham, Patricia Selvaggi, and James Vickery

A Structural View of U.S.
Bank Holding Companies
1. Introduction

arge banking organizations in the United States are
generally organized according to a bank holding company
(BHC) structure. In this article, we describe the organizational
structure of large U.S. bank holding companies and present
summary statistics that document the increasing size,
complexity, and diversity of these organizations. We also
outline the different types of regulatory data filed with the
Federal Reserve by U.S. bank holding companies and describe
the strengths and weaknesses of these data, as a source for
researchers and others interested in these organizations.
A BHC is simply a corporation that controls one or more
banks. Typically, a large U.S. parent BHC owns a number of
domestic bank subsidiaries engaged in lending, deposit-taking,
and other activities, as well as nonbanking and foreign
subsidiaries engaged in a broader range of business activities,
which may include securities dealing and underwriting,
insurance, real estate, private equity, leasing and trust services,
asset management, and so on.
Chart 1 illustrates the rapid growth in the size and scope
of BHCs over the past twenty years. As shown in the chart,
nearly all U.S. banking assets are controlled by bank holding
companies, and U.S. BHCs as a group (inclusive of firms whose
ultimate parent is a foreign banking organization) control well
over $15 trillion in total assets, representing a fivefold increase
since 1991.1 By comparison, nominal GDP increased by only
around 150 percent over the same period.

Dafna Avraham is an assistant economist, Patricia Selvaggi an assistant
vice president, and James Vickery a senior economist at the Federal Reserve
Bank of New York.
Correspondence: dafna.avraham@ny.frb.org; patricia.selvaggi@ny.frb.org;
james.vickery@ny.frb.org

Notably, assets held in nonbanking subsidiaries or directly
by the BHC parent account for a progressively larger share
of total BHC assets over time (the gray area in Chart 1,
panel A). This trend reflects a significant broadening in the
types of commercial activities engaged in by BHCs and a shift
in revenue generation toward fee income, trading, and other
noninterest activities (Stiroh 2004). These trends are
attributable in part to important changes in the regulatory
environment, as discussed in Section 2.
Partly the result of a wave of mergers, the share of BHC
assets controlled by the ten largest firms has more than doubled
over the past two decades, from less than 30 percent to more
than 60 percent (see Chart 1, panel B). The total number
of firms organized as BHCs has declined from 5,860 in 1991
to 4,660 as of fourth-quarter 2011, also reflecting industry
consolidation. See Copeland (2012) for a further discussion
of trends in banking consolidation and income generation.
Chart 2 provides a window into the organizational
complexity of large BHCs. One simple measure of complexity
1
Recent growth in industry assets plotted in Chart 1 in part reflects the
conversion of several firms to a BHC organizational form (for example,
Goldman Sachs, Morgan Stanley, Ally Financial, American Express) as well
as out-of-industry acquisitions by BHCs (for example, JPMorgan Chase’s
acquisition of Bear Stearns, an investment bank, and Bank of America’s
acquisitions of Merrill Lynch and Countrywide Financial, an investment bank
and savings bank, respectively). The sizable increase in total assets and nonbank
subsidiary assets in first-quarter 2009 reflects the fact that this is the quarter in
which Goldman Sachs and Morgan Stanley first file BHC regulatory reports. The
bulk of the assets of these two firms are held outside their bank subsidiaries.

The authors thank Nicola Cetorelli, Adam Copeland, and Ken Lamar for
helpful comments, and members of the New York Fed’s Statistics Function
for invaluable assistance with data analysis and institutional details. The views
expressed 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.

FRBNY Economic Policy Review / July 2012

Chart 1

Chart 2

Trends in Number and Total Size
of U.S. Bank Holding Companies

Organizational Complexity and International Reach
of Large U.S. Bank Holding Companies
Number of subsidiaries

Trillions of U.S. dollars

4,000

Panel A: Growth in Commercial Banking
Industry Assets over Time

1990

3,000

Banks not part of BHC
Small BHCs
Large BHCs: Outside of
commercial bank subsidiaries
Large BHCs: Commercial
bank subsidiaries

2,000

1,000

0
1

Gramm-Leach-Bliley Act

0
1991

10
8,000
7,000

80
60

6,000

Number of BHCs

Scale

5,000

Top ten BHCs’ share
of total assets
Scale

4,000

3,000

0
1

2,000

20
10
0
1991

100

BHC count

Panel B: Evolution of Size and Number
of BHCs over Time

Rank of BHC

Number of countries

Percent

2012

Rank of BHC

1,000

Sources: National Information Center; FR Y-10.

Note: Data are as of February 20, 2012, and December 31, 1990,
and include the top fifty bank holding companies (BHCs) at each
of these dates. See the online appendix for more details.

Sources: National Information Center; FR Y-9C; FFIEC 031; FFIEC 041.
Notes: The chart presents financial data up to fourth-quarter 2011. A large
bank holding company (BHC) is defined as a top-tier BHC that files a
Y-9C report (in recent years, this report has been required of BHCs with
at least $500 million in total assets). Commercial bank assets of large BHCs
in panel A are measured as the sum of consolidated assets reported by each
banking subsidiary in its Call Report filing. It is a slight overestimate because
of double-counting of any related party exposures between banks controlled
by the same BHC. Nonbank assets of large BHCs are the difference between
total assets as reported in the Y-9C and commercial bank assets as defined
above. Assets of small BHCs reflect only their commercial bank subsidiaries
(which is, however, likely to be a good approximation of BHC assets for
this class of firms). In panel B, the number of BHCs is a count of Y-9C
filers plus the number of distinct high holders of commercial banks filing
a Call Report, exclusive of banks that are their own high holder or have
a Y-9C filer high holder. See the online appendix for more details.

in this context is the number of separate legal entities in the
BHC. This variable is plotted in the top panel, sorted in rank
order across firms. Today, the four most complex firms
measured on this dimension each have more than 2,000
subsidiaries, and two have more than 3,000 subsidiaries.

A Structural View of U.S. Bank Holding Companies

In contrast, only one firm exceeded 500 subsidiaries in 1991.
BHCs have also expanded their geographic reach; each of the
seven most internationally active banks controls subsidiaries
in at least forty countries.
Building on these stylized facts, in Section 2 we describe the
origins of the BHC organizational form and discuss several key
pieces of legislation that have shaped the scope and size of the
U.S. commercial banking industry. Section 3 outlines the
typical organizational structure of large BHCs and presents
a primer on the types of regulatory data filed by these firms.
Making use of these data, Section 4 presents additional stylized
facts about the organizational complexity and scope of large
BHCs. Section 4 also includes preliminary statistical analysis
of the determinants of organizational complexity, proxied
by the log number of subsidiaries. The analysis suggests that
complexity is positively related to BHC size and weakly
positively related to the diversity of the BHC’s activities.
Section 5 concludes.

2. How Did We Get Here?
Changes in the legislative and regulatory environment have
been a key driver of the trends toward greater BHC size,
scope, and industry consolidation documented in Charts 1
and 2. The evolution of U.S. financial legislation in turn
reflects a long-running public debate about the appropriate
size and scope of banking organizations. As discussed in detail
below, there has been a secular trend in recent decades toward
enlarging the allowable scope of BHC activities. However,
recent legislation represents something of a reversal of this
trend; most prominently, the “Volcker rule” provisions of the
Dodd-Frank Wall Street Reform and Consumer Protection
Act (Dodd-Frank Act) prohibit BHCs from engaging in
proprietary trading and limit their investments in hedge
funds, private equity, and related vehicles.
The primary legislation defining the allowable scope of BHC
activities is the Bank Holding Company Act of 1956 (BHCA,
12 U.S.C. § 1841). The Act establishes conditions under which
a corporation may own a U.S. commercial bank and invests
responsibility for supervising and regulating BHCs with the
Federal Reserve.2
A key original goal of the BHCA was to limit the comingling of banking and commerce, that is, to restrict the
extent to which BHCs or their subsidiaries could engage in
nonfinancial activities (more details and historical background
are found in Omarova and Tahyar, forthcoming; Santos 1998;
Aharony and Swary 1981; and Klebaner 1958). This separation
is intended to prevent self-dealing and monopoly power
through lending to nonfinancial affiliates and to prevent
situations where risk-taking by nonbanking affiliates erodes the
stability of the bank’s core financial activities, such as lending
and deposit-taking (Kroszner and Rajan 1994; Klebaner 1958).
To further enhance stability, BHCs are also required to
maintain minimum capital ratios and to act as a “source of
strength” to their banking subsidiaries, that is, to provide
financial assistance to banking subsidiaries in distress.3
2

Ownership of banks by nonbanks was lightly regulated under the earlier 1933
Banking Act. The Glass-Steagall Act also prohibited firms principally engaged
in investment banking from affiliating with member banks. The original 1956
BHC Act addressed only multibank holding companies, that is, corporations
controlling 25 percent or more of the voting shares of at least two commercial
banks. The 1970 amendment to the BHCA extended the Federal Reserve’s
authority to single-bank holding companies.
3
The BHCA (§ 225.28) defines source of financial strength to mean, “the
ability of a company that directly or indirectly owns or controls an insured
depository institution to provide financial assistance to such insured depository institution in the event of the financial distress of the insured depository
institution.” Ashcraft (2008) presents evidence that affiliation with a multibank
holding company reduces a bank’s probability of financial distress, consistent
with the view that the source of strength doctrine improves financial stability.
Regulation Y sets out the procedural rules that apply to BHCs to ensure they
act as a source of strength.

BHCs today engage in a significantly broader range of
activities than the narrow limits set out in the 1956 BHCA,
enabled through subsequent amendments to the Act.4 For
example, in 1970 the BHCA was amended to allow multibank
holding companies to engage either directly or indirectly
through subsidiaries in activities that are “closely related to
banking” (Aharony and Swary 1981).5,6 BHCs may invest in
nonfinancial firms, although their stake cannot generally
exceed 5 percent of the company’s outstanding voting stock.
The passage of the Gramm-Leach-Bliley Act (GLBA) of
1999 further amended the BHCA to enable a BHC to register as
a financial holding company (FHC), thereby allowing the firm
to engage in a broad range of financial activities, including
securities underwriting and dealing, insurance underwriting,
and merchant banking activities.7 Today, virtually all large
BHCs are registered as FHCs. While it is difficult to prove
causality, it is notable that the striking growth in the size and
importance of nonbank BHC subsidiaries dates almost entirely
to the period after the passage of the GLBA (see Chart 1,
panel A).
The Federal Reserve holds regulatory responsibility for
umbrella supervision of FHCs, as it does for other BHCs.
However, the GLBA provides for functional regulation of a
FHC’s nonbank financial subsidiaries. For example, brokerdealer subsidiaries of a financial holding company are
primarily regulated by the Securities and Exchange
Commission (SEC), and insurance subsidiaries by state
insurance regulators.
Most recently, the passage of the Dodd-Frank Act represents
a significant shift toward strengthening regulations governing
financial service providers and restricting the scope of activities
that BHCs may engage in. Most notably, the “Volcker Rule”
provisions of the Act (§619) introduce two key types of
restrictions: 1) banks are prohibited from engaging in
proprietary trading (that is, short term trading on the bank’s
own account) on many types of financial instruments; and
4

Omarova and Tahyar (forthcoming) offer a detailed discussion of the
evolution of the BHCA, particularly the changes in the statutory definition
of a “bank” within the Act.
5
As defined in Subpart C of Regulation Y (§225.28), this list of permissible related
activities includes mortgage banking, consumer and commercial finance, loan
servicing, leasing, collection agency, asset management, trust company services,
real estate appraisal, and financial and investment advisory activities.
6
While expanding the range of permissible activities for multibank holding
companies, the 1970 amendment to the BHCA had the opposite effect of
constraining the scope of activities for single bank holding companies, since
these firms were not subject to the BHCA until the passage of the 1970
amendment. As discussed in Omarova and Tahyar (forthcoming), this
difference in regulatory treatment had led to a rapid growth in single bank
holding companies after the original passage of the BHCA in 1956.
7
In order to register as an FHC, the holding company as well as all subsidiary
depository institutions must be well-managed and well-capitalized, and be in
compliance with the Community Reinvestment Act, among other requirements (see Regulation Y (§225.84)).

FRBNY Economic Policy Review / July 2012

Stylized Structure of a Large Bank Holding Company

Top-tier
financial holding
company
(FR Y-9C)
(FR Y-9LP)

Bank holding
company
(FR Y-9C)
(FR Y-9LP / SP)

Foreign bank
(FR 2314)

Nonbank holding
company

Commercial bank

(FR Y-11 / 2314)

(FFIEC 031 / 041)

U.S. nonbank
subsidiary

Foreign nonbank
subsidiary

Nonbank
subsidiary

(FR Y-11)

(FR 2314)

(FR Y-11 / 2314)

2) limits are placed on banks’ ownership or sponsorship of
private equity firms, hedge funds, venture capital funds, and
certain other privately offered funds and pooled investment
vehicles.8
Another ongoing debate about BHC scope concerns firms’
commodity trading operations. The BHCA restricts holding
companies’ ability to own or trade physical commodities,
or to own hard assets related to commodity trading such as
storage tanks, shipping containers, and warehouses. But a
“grandfathering” exemption in the GLBA allows an investment bank that converted to holding company status after
1999 to continue to trade or own physical assets if it did
so before September 1997. This exemption has allowed a
number of the largest BHCs to operate large, profitable
commodity trading businesses. However, the legal scope of
the exemption is widely seen as ambiguous. For example, it is
unclear to what extent it allows firm to purchase new hard
assets related to an existing commodities business, or to expand
into new commodities markets. Many speculate that the
Federal Reserve may tighten its treatment of the exemption.9
These recent developments represent a notable reversal
of the trend over the past several decades toward expanding
the range of permissible activities for U.S. BHCs. They also
emphasize that concerns about the separation between banking
8

Specifically, the Act restricts the bank from owning more than 3 percent of the
fund, places an overall limit of 3 percent of the bank’s Tier 1 capital invested in
private funds, and introduces other limitations relating to the name of the fund
and affiliated transactions.
9
For a detailed discussion, see David Sheppard, Jonathan Leff, and Josephine
Mason, “Insight: Wall Street, Fed Face Off over Physical Commodities,” Reuters
newswire, March 2, 2012, available at http://www.reuters.com/article/2012/03/02/
us-fed-banks-commodities-idUSTRE8211CC20120302 (accessed April 9, 2012).

A Structural View of U.S. Bank Holding Companies

Foreign branch
(FFIEC 030)

and commerce, and debates about the appropriate scope
of BHC activities, remain as active as ever. In addition,
restrictions on the scope of large banking organizations are
being considered in other countries in the wake of the financial
crisis. For example, in the United Kingdom, the Independent
Commission on Banking has recommended “ring-fencing”
retail banking activities inside separately capitalized subsidiaries (see Independent Commission on Banking 2011).

3. Structure and Data Sources
Chart 2 illustrates that, as well as increasing in size, the largest
BHCs have become significantly more organizationally
complex over the past two decades, at least as measured by the
number of separate legal entities within each firm and the
geographic reach of these organizations. This section sheds
some light on the organizational structures of large BHCs and
describes key types of regulatory data available regarding
different entities within the BHC, to serve as a guide for
researchers and other analysts.
The exhibit above presents a stylized picture of the
organizational structure of a typical large BHC, including
both banking and nonbanking subsidiaries. It also lists (in
parentheses) the key regulatory reports filed by different
legal entities within the structure. A more detailed table
summarizing regulatory data filed by BHCs and their
subsidiaries is compiled in Appendix A to this article.
The exhibit is simplified by necessity, because in practice the
most complex BHCs control up to several thousand separate

subsidiaries. A snapshot of the organizational structure of each
BHC is reported annually as part of the FR Y-6 Annual Report
of Bank Holding Companies; this report requires BHCs to file an
organizational chart, intercompany ownership and control
relationships, and data on domestic branches, among other
information. In addition, on the FR Y-10 Report of Changes in
Organizational Structure, top-tier BHCs report, as they occur,
any changes to the firm’s worldwide organizational structure
including mergers, acquisitions, or transfers of interests in
other entities, internal reorganizations, commencements
of new activities, and openings, closings or relocations of
branches or subsidiaries.10 By combining these two reports,
it is possible to generate at any point in time an updated picture
of the organizational structure of the firm. Data from these
two reports are publicly available through the National
Information Center repository.11
In determining the set of entities controlled by the ultimate
parent BHC, banking regulations use a definition of control
which differs from that used for financial reporting purposes
under U.S. Generally Accepted Accounting Principles
(GAAP).12 Thus, regulatory reports vary in terms of which
definition of control is used. For example, the FR Y-6 and Y-10
reports require firms to use the supervisory definition of
control when determining the set of subsidiaries controlled
by the BHC. However, the consolidated financial statements
of the BHC are prepared based on U.S. GAAP consolidation
definitions. (See the “Consolidation Rule” column of
Appendix A.) End users should bear these differences in mind
when interpreting regulatory data.
The key source of consolidated financial data on U.S. BHCs
is the FR Y-9C Consolidated Report of Condition and Income,
which is completed on a quarterly basis by each BHC with at
least $500 million in total assets. The Y-9C provides data on the
financial condition of the firm, based on U.S. GAAP
consolidation rules, as well as the capital position of the
consolidated entity. The balance sheet and income data include
items similar to those contained in SEC filings; however, the
Y-9C also contains a rich set of additional information,
including data on regulatory capital and risk-weighted assets,
off-balance sheet exposures, securitization activities, delinquency statistics on different types of loans, and so on. Since
comparability across firms is important for regulatory
purposes, the Y-9C and other reporting forms tend to be more
prescriptive about the way financial data is measured and
reported than U.S. GAAP-based reporting.

The top-tier BHC, shown at the top of the exhibit, also
submits a separate quarterly report known as the FR Y-9LP,
prepared on an unconsolidated basis. Note that the parent
BHC depicted in the exhibit is also registered as a financial
holding company (FHC). As we discussed in Section 2, this
FHC status allows the firm to control entities engaged in a
broader range of financial activities.
Each domestic commercial bank, like the one depicted on
the right side of the exhibit, files a detailed set of quarterly
financial reports commonly known as “Call Reports”
(FFIEC 031, if the bank has both foreign and domestic offices,
or FFIEC 041, if it has only domestic offices). Like the Y-9C,
Call Reports are prepared on a consolidated basis, but at the
level of the bank, rather than the BHC. Many similarities exist
between the structure of the Y-9C and Call Reports, although
the set of information reported does differ between the two
reporting forms in important ways. For example, the Call
Report provides additional information on core banking
activities, such as the composition of deposit liabilities.
Conversely, the Y-9C provides additional information on
broader financial activities, such as insurance and reinsurance.
Foreign bank subsidiaries, such as the one depicted at the far
bottom left of the exhibit, also report regulatory data on their
activities, but on a standalone rather than a consolidated
basis.13 Large foreign subsidiaries, whether banks or nonbanks,
report balance sheet and income data through the FR 2314
report, while smaller subsidiaries (those below a set of
reporting thresholds) report a small number of data items in
the FR 2314S. Foreign bank branches not incorporated into a
separate subsidiary (as depicted at bottom right of the exhibit)
file the FFIEC 030 report.
A BHC’s banking subsidiaries are “special” in a number of
ways relative to nonbanks; for example, they are able to raise
insured deposits and can borrow at the Federal Reserve's
discount window. However, these entities are also bound by
separate capital requirements and face additional regulation.
Furthermore, although the GLBA has expanded the activities
that BHCs may engage in, many of these activities, such as
underwriting, commodities dealing, and insurance, must
generally occur outside of the BHC’s commercial bank(s) or
their subsidiaries, a factor contributing to the organizational
complexity of BHCs.
Financial information on each large nonbank subsidiary is
filed in the FR Y-11 report (if a domestic subsidiary), or the
FR 2314 (if a foreign subsidiary).14 An exception is made,

13
In this context, “standalone” means that the accounts of the firm are
based only on the entity itself, without consolidating the assets and
liabilities of any subsidiaries.

A top-tier BHC is the ultimate domestic parent organization (that is, a BHC
that is not controlled by another domestic BHC).

See http://www.ffiec.gov/nicpubweb/nicweb/NicHome.aspx.
For example, U.S. GAAP determines that control has been established if the
parent owns more than 50 percent of the voting stock of the firm, while for
supervisory purposes, this limit is only 25 percent.

Smaller subsidiaries instead file an FR Y11S (if domestic) or 2314S (if
foreign), based on size thresholds. See Appendix A for more details. Note that
the FR 2314/2314S is the same report filed by foreign banking subsidiaries.

FRBNY Economic Policy Review / July 2012

however, for securities and insurance affiliates facing separate
functional regulation; such subsidiaries are exempt from
filing the FR Y-11 and instead file reports on their activities and
financial position with their functional regulator.
Another way to examine the foreign activities of U.S. BHCs
is to study their exposure to foreign individuals, firms, and
governments, instead of studying the country in which each
subsidiary is domiciled. This approach is relevant because a
BHC’s domestic subsidiaries may engage in significant foreign
lending. Cross-border exposures of bank holding companies
are reported on the FFIEC 009, Country Exposure Report.
This report presents a consolidated view of the distribution
by country of claims (including derivative exposures) on
foreigners, including foreign subsidiaries of the BHC. As an
application of these data, Cetorelli and Goldberg (2011) use
FFIEC 009 reports to analyze liquidity management and
internal capital markets among internationally active U.S.
banks during the Great Recession. A second instrument, the
Treasury International Capital (TIC) reports, provides data on
the foreign portfolio exposures of the BHC’s U.S. subsidiaries.
These data reflect the geographic location of the exposure itself,
rather than the location of the legal entity holding the security.
Together these two reports provide a global picture of the
BHC’s activities and exposures.
To summarize, while BHCs are organizationally complex,
a range of detailed data is available to regulators, researchers,
and other analysts to help analyze the scope, size, complexity,
and global reach of these organizations. This section has
presented a (nonexhaustive) list of many of these data sources.
We now make use of these reporting data to construct simple
summary statistics on the structure and characteristics of large
U.S. BHCs.

and many are foreign firms. These subsidiaries have been
created for a variety of purposes: 1) for regulatory reasons, for
example, because separate subsidiaries are required in each
country in which the firm operates, or for particular activities;
2) to limit taxation, for example, by shifting certain activities
into lower-tax jurisdictions; 3) to manage the regulatory
burden of the firm, for example, to avoid burdensome laws or
regulatory regimes; 4) to secure or limit the position of
different claimholders on the firm in the case of bankruptcy.
(See Section 4.4 for further discussion.)
While BHCs control a large number of nonbank subsidiaries, most assets are generally held in a small number
(between one and five) of domestic commercial banks. For
example, the largest BHC by total assets, JPMorgan Chase,
controls 3,391 subsidiaries; of the 2,940 subsidiaries that are
domestically domiciled, only four are domestic commercial
banks. These banks and their subsidiaries do, however, hold
86 percent of the firm’s total assets.16
The fraction of total assets held within the BHC’s banking
subsidiaries varies significantly across firms. For smaller
BHCs, this fraction is close to 100 percent. For MetLife,
Goldman Sachs, and Morgan Stanley, which engage in
relatively little traditional lending and deposit-taking, banking
subsidiaries contain a strikingly small fraction of the firm’s
assets (3.2 percent, 11.2 percent, and 10.5 percent, respectively).
For the other largest BHCs, which have large retail banking
operations but also engage in securities dealing and underwriting, insurance, and so on, the fraction of bank assets falls
between these two extremes, varying between 69 percent and
93 percent of firm assets among the four largest firms.

4.1 Industry Breakdown

4. Stylized Facts
We focus on the fifty largest BHCs, which together make up
a large fraction of total industry assets. Our intention is to
present stylized facts on the organizational complexity and
structure of these organizations and to illustrate some of the
many ways in which regulatory reporting data can be used to
shed light on the activities of bank holding companies. All the
statistics are based on the most updated information, reported
as of February 20, 2012.15
Table 1 presents some simple summary statistics on a
sample of large BHCs, sorted in order of total assets and
combining several of the regulatory reports discussed above.
Six of the seven largest BHCs control more than a thousand
subsidiaries; nearly all of these subsidiaries are nonbanks,

A Structural View of U.S. Bank Holding Companies

Charts 3 and 4 present an industry breakdown of the activities
of the subsidiaries of large BHCs. Appropriate regulation of the
15

Each firm’s organizational structure as reported in the 2011 FR Y-6 was
updated for any structural changes that occurred up to February 20, 2012.
(Recall that each change in structure must be reported by the BHC through an
FRY-10 filing.) Financial data are reported quarterly and thus reflects each
firm’s financial position as of December 31, 2011. Note that two large firms,
Taunus Corporation and RBC USA Holding Corporation, lost their BHC
status in early 2012. Even though both firms were among the top fifty BHCs
as of December 2011, they were not BHCs as of February 20, 2012, and thus
are not included in our statistics.
16
These estimates of commercial banking assets are calculated by simply
summing total assets, as reported in the Call Reports of each commercial
banking subsidiary. From a consolidated BHC perspective, this calculation
will overstate commercial bank assets in cases where there are related party
exposures among commercial banks within the same BHC (since these should
in principle be “netted out” from a consolidated perspective). However, we
believe this overstatement will generally be small in practice.

Table 1

Number and Distribution of Subsidiaries: Selected Top Fifty Bank Holding Companies
Number

Asset Value

Domestic

BHC
Rank
1
2
3
4
5
6
7
10
20
30
40
50
Total

Name
JPMorgan Chase & Company
Bank of America Corporation
Citigroup Incorporated
Wells Fargo & Company
Goldman Sachs Group, Incorporated
MetLife, Inc.
Morgan Stanley
The Bank Of New York Mellon Corporation
Regions Financial Corporation
Comerica Incorporated
First Horizon National Corporation
Webster Financial Corporation

Consolidated Total
Assets (Y-9C)
(Billions of
U.S. Dollars)

Commercial
Bank

Other

Foreign

Total

Domestic Commercial
Bank (Percentage
of Y-9C Assets)

4
5
2
5
1
1
2
3
1
2
1
1

2,936
1,541
935
1,270
1,444
39
1,593
211
35
72
35
21

451
473
708
91
1,670
123
1,289
146
4
2
1
0

3,391
2,019
1,645
1,366
3,115
163
2,884
360
40
76
37
22

86.1
77.9
68.8
92.5
11.2
3.2
10.5
83.2
97.1
99.8
99.1
99.8

2,265.8
2,136.6
1,873.9
1,313.9
923.7
799.6
749.9
325.8
127.0
61.1
24.8
18.7

13,670

5,847

19,603

70.4

14,359.1

Sources: National Information Center; FR Y-9C; FR Y-10; FR Y-11; FR 2314; FFIEC 031; FFIEC 041.
Notes: Structure data are as of February 20, 2012. Financial data are as of fourth-quarter 2011. The number of subsidiaries of each bank holding company
(BHC) is determined based on the Regulation Y definition of control. Asset data include approximately 3,700 of the more than 19,600 subsidiaries belonging
to the top fifty BHCs that meet particular reporting threshold criteria. See the online appendix for more details.

scope of BHCs’ activities has been an important and prominent
public policy issue for many decades, as discussed in Section 2.
These figures are based on combining structural data from the
FR Y-10 and financial data from the FR Y-11, FR 2314, and
FFIEC 031 and 041 reports. Industry is classified according to
the North American Industry Classification System (NAICS).17
Based on raw counts (Chart 3), the most common industry
categories are “Funds, Trusts, and Other Financial Vehicles”
and “Securities, Commodity Contracts, and Other.” Weighted
by assets, however, the most important category is “Credit
Intermediation and Related Activities.” This breakdown is
consistent with Table 1. Large BHCs have a large number of
subsidiaries for managing trusts and investment funds as well
as many other purposes; however, the majority of BHC assets
relate to “traditional” credit intermediation activities.
Again, these two charts illustrate enormous variation in
industry composition across firms. For example, perhaps
unsurprisingly, Morgan Stanley and Goldman Sachs, which
focus more heavily on investment banking activities, have a
17

NAICS codes are used to classify firms by their primary economic activity.
The codes range from two to six digits in length, in which two-digit codes
represent the broadest categories and six-digit codes represent the most specific
categories. We use two-digit NAICS codes, except for the finance and insurance
industry, which we break out further using three-digit NAICS codes.

large volume of subsidiaries in the “Funds, Trusts, and Other
Financial Vehicles” category and have a smaller fraction of
assets held in subsidiaries engaged in credit intermediation.
In addition, few assets are reported for MetLife, since a large
fraction of firm assets are held in insurance subsidiaries that
do not submit FR Y-11 reports.
Also notable is a “tail” of BHC subsidiaries engaged in
activities that are not obviously closely related to banking.
For example, BHCs own a number of subsidiaries engaged
in “Health Care and Social Assistance” and “Professional,
Scientific, and Technical Services.” Ownership of such
subsidiaries can arise in a number of ways; for example, a bank
may acquire a firm that it has lent to as the outcome of
bankruptcy proceedings. In general, these nonfinancial
subsidiaries do not make up a significant share of total firm
assets. (Note: Information on the industry distribution of BHC
subsidiaries is also tabulated in Appendix B.)
As an illustration of the richness of these regulatory data
when compared with other data sources, we have constructed
similar industry figures using Capital IQ, a widely-used data
vendor that compiles data from firm’s SEC filings and other
sources. The number of subsidiaries captured in Capital IQ is
significantly smaller than that from the regulatory data. For

FRBNY Economic Policy Review / July 2012

Chart 3

Industry Breakdown of Subsidiaries
Number of subsidiaries
6,000
Remaining top fifty BHCs
MetLife
Morgan Stanley
Goldman Sachs
Wells Fargo
Citigroup
JPMorgan Chase
Bank of America

5,000
4,000
3,000
2,000
1,000

ities

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Sources: National Information Center; FR Y-10.
Notes: Data are for the top fifty bank holding companies and are as of February 20, 2012. See the online appendix for more details.

example, for the seven largest BHCs, 3,890 subsidiaries are
recorded in Capital IQ, of which asset data are reported for
only 53. In contrast, for the same seven firms, 14,583 subsidiaries are recorded in BHC regulatory filings, and asset data are
available for 2,981 subsidiaries. A table in the online appendix
also shows that the sum of subsidiary assets reported in
Capital IQ significantly understates the corresponding sum
from regulatory reports for six of the seven largest BHCs.18

4.2 Geographic Breakdown
Another important dimension of BHC scope is the geographic
reach of firms’ activities. Chart 2, panel B showed that
the most internationally active BHCs control subsidiaries in
18

The exception is MetLife, for which the sum of subsidiary assets is actually
larger in Capital IQ than in their regulatory filings. The reason is that, as
mentioned above, MetLife has large insurance subsidiaries that do not file a
Y-11 report of their financial position because they are functionally regulated
by state insurance regulators (see the discussion in Section 3). For the other
six largest BHCs, the sum of reported subsidiary assets in Capital IQ are only
4 percent to 77 percent as large as in the same firm’s regulatory filings.

A Structural View of U.S. Bank Holding Companies

forty-to-eighty separate countries. Data on the geographic
composition of these subsidiaries are reported in Table 2,
panel A (based on the FR Y-10), which reports geographic data
at the country level. For exposition, we have grouped countries
by geographic region.
A large majority of total BHC assets, 75.82 percent, are
held in the United States. Perhaps unsurprisingly, the fraction
of foreign assets and subsidiaries is significantly higher for
the largest BHCs than for smaller firms. Europe is the most
important location for foreign-held BHC assets (making
up 15.40 percent of assets), followed by the Caribbean
(3.15 percent of assets), Asia (2.79 percent of assets), and
Latin America (1.55 percent of assets).
Table 2, panel B, reports aggregate foreign exposures of
U.S. BHCs, based on data originally reported in the FFIEC 009
report. Note that foreign exposures may differ significantly
from the fraction of assets domiciled overseas, for example,
because domestic BHC subsidiaries may lend to or engage in
derivatives transactions with foreign organizations. Indeed, the
table shows that 62 percent of all foreign exposures are held
within domestic BHC subsidiaries.

Table 2

Geographic Distribution of Bank Holding Company Assets and Exposures
Panel A: Geographic Location of U.S. BHC Subsidiaries
Top Seven BHCs
Region

Total

Assets
(Percent of Total)

Top Fifty BHCs

Assets
(Percent of Total)

Number

9,761
1,828
1,518
593
377
227
153
126

70.92
18.47
3.42
3.80
2.04
0.58
0.26
0.52

3,954
526
164
154
67
47
13
95

89.12
7.08
2.41
0.07
0.25
0.32
0.00
0.75

13,715
2,354
1,682
747
444
274
166
221

75.82
15.40
3.15
2.79
1.55
0.51
0.19
0.58

14,583

100.00

5,020

100.00

19,603

100.00

Number

United States
Europe
Caribbean
Asia
Latin America
Australia
Africa
Canada

Remaining Top Fifty BHCs
Number

Assets
(Percent of Total)

Panel B: Foreign Exposures of U.S. BHCs
Exposures by Subsidiary Type (Percent of World Total)
Region
Europe
Asia
Latin America
Caribbean
Canada
Australia
Africa
International organizations
World Total

Total (Billions
of U.S. Dollars)

Domestic

Foreign

2,017.2
970.3
349.4
205.6
163.5
147.7
26.3
5.1

35.73
11.22
4.19
5.16
2.53
2.28
0.34
0.13

16.19
13.75
4.81
0.13
1.68
1.52
0.34
0.00

51.92
24.98
8.99
5.29
4.21
3.80
0.68
0.13

3,885.1

61.58

38.42

100.00

Total

Sources: National Information Center; FR Y-10; FR Y-11; FR 2314; FFIEC 031; FFIEC 041; E.16.
Notes: Structure data are as of February 20, 2012. Financial data are as of fourth-quarter 2011. Asset data in panel A reflect approximately 3,700 of the more
than 19,600 subsidiaries controlled by the top fifty bank holding companies (BHCs), which meet particular reporting threshold criteria. Aggregate data in
panel B are drawn from the E.16 Country Exposure Lending Survey and Country Exposure Information Report, which in turn is based on data from
FFIEC 009. See the online appendix for more details.

4.3 Caveats and Limitations
When interpreting the above statistics on industrial and
geographic scope, it is worth reiterating some limitations of
the underlying regulatory data:
1.

Assets for each nonbank subsidiary reported in the
FR Y-11/FR 2314 are based on treating the subsidiary in
question as a standalone entity. Given this treatment, asset
and liability positions with related entities (for example,
a loan to or equity position in a subsidiary) will be
included as part of the subsidiary’s balance sheet, even
though such positions net out to zero from a consolidated
BHC perspective. For this reason, summing up reported

assets for each subsidiary will tend to overstate the total
assets of the firm as a whole—particularly in a highly
tiered structure. It is not possible to fully correct this
double-counting.19
2.

As described in Section 3, some (potentially large) U.S.
nonbank subsidiaries do not file a Y-11 because they
instead report separately to their U.S. functional regulator. This practice is primarily relevant for securities and
insurance subsidiaries, which are significant in size for

Balances with related entities are disclosed in the FR Y-11/FR 2314. However, the
item “Claims on related entities” includes related entities whether or not they are
consolidated by the ultimate parent under U.S. GAAP. Therefore, using this line
item to offset related party holdings may generate an overadjustment.

FRBNY Economic Policy Review / July 2012

Chart 4

Industry Breakdown by Assets
Total assets (trillions of U.S. dollars)
14
Remaining top fifty BHCs
MetLife
Morgan Stanley
Goldman Sachs
Wells Fargo
Citigroup
JPMorgan Chase
Bank of America

12
10
8
6
4
2

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Sources: National Information Center; FR Y-10; FR Y-11; FR 2314; FFIEC 031; FFIEC 041.
Notes: Data are for the top fifty bank holding companies (BHCs). Structure data are as of February 20, 2012. Financial data are as of fourth-quarter 2011.
Asset data include approximately 3,700 of the more than 19,600 subsidiaries belonging to the top fifty BHCs that meet size thresholds and other
requirements for reporting asset data. See the online appendix for more details.

some BHCs. These separate filings are in general not
available to analysts outside the functional regulator.20
3.

Small subsidiaries that are below reporting thresholds are
not required to file asset data.

These data limitations are likely to introduce some bias into the
asset-weighted statistics reported in Chart 4 and Table 2, panel A.

4.4 Causes and Consequences of Complexity
Earlier in this section, we posited a number of drivers of BHC
organizational complexity: regulation (and regulatory
arbitrage), tax management, and the determination of control
rights and priority of claims in bankruptcy. A full examination
of each of these drivers is outside the scope of this article.
However, as a first step, below we present a simple crosssectional regression analysis of the correlates of BHC
complexity, as proxied by the total number of subsidiaries.21
20

For example, broker-dealer subsidiaries of BHCs are required to file balance
sheet and income data with the SEC, their primary regulator, in the form of
a FOCUS (Financial and Operational Combined Uniform Single) report.
Information in these FOCUS reports is not publicly available, however,
unless voluntarily disclosed by the broker-dealer.

A Structural View of U.S. Bank Holding Companies

Specifically, we regress the log of the number of subsidiaries
controlled by each of the top fifty BHCs on measures of size (total
assets and log total assets) and the concentration of activities: the
fraction of commercial bank assets and indexes measuring the
industry and geographic concentration of the firm’s assets. Our
expectation is that larger BHCs, as well as those engaged in a more
diversified range of activities, are likely to be more organizationally
complex. We estimate a simple linear model using least squares,
using robust standard errors to account for heteroskedasticity.
The results are presented in Table 3.
The number of subsidiaries is strongly positively and
statistically significantly related to BHC size. The coefficient on
log assets is consistently less than unity, however, implying
that a given percentage increase in BHC size is associated with
a smaller-than-proportionate increase in the number of
subsidiaries. In other words, larger BHCs, on average, have
larger individual subsidiaries.

We readily acknowledge that the number of subsidiaries is likely to be a
noisy measure of organizational complexity, and that it only measures one
dimension of the complexity of BHCs. Studying other dimensions (for
example, the complexity of the firm’s assets or derivatives positions) would be
a fascinating topic for future research, but is outside the scope of this article.

Table 3

Determinants of Bank Holding Company Complexity
Dependent Variable: Log Number of Subsidiaries
Independent Variables

Total assets (trillions of U.S. dollars)
Log total assets
Industry concentration index (three-digit NAICS)

0.889***
[0.097]
-0.895
[0.74]

Geographic concentration index (region)

0.861***
[0.087]

0.851***
[0.085]

0.912***
[0.075]

-1.23
[0.97]

Geographic concentration index (country)

0.333
[0.26]
0.751***
[0.13]
-0.18
[0.81]
-0.786
[1.18]

0.33
[0.26]
0.741***
[0.12]
-0.158
[0.79]

-1.232
[0.86]

Percent of domestic commercial bank assets

Observations

-11.03***
[2.26]
50

-10.18***
[2.28]
50

-9.999***
[2.14]
50

-0.752
[0.66]
-11.54***
[1.72]
50

Adjusted R2

0.77

0.78

0.77

Constant

-0.333
[0.86]
-8.193***
[2.68]
50

-0.969
[1.05]
-0.194
[0.87]
-7.995***
[2.60]
50

0.77

Source: Authors’ calculations.
Notes: The table reports estimates from linear regression models of the correlates of bank holding company (BHC) complexity, measured by the log of the
number of total subsidiaries. Data are for the top fifty BHCs and are as of February 20, 2012. Linear regression, heteroskedasticity-consistent standard errors
are presented. The dependent variable is the natural logarithm of the number of subsidiaries. Robust standard errors are in brackets.
***p<0.01
***p<0.05
***p<0.1

Indexes measuring industry and geographic concentration
are constructed similarly to a Herfindahl-Hirschman Index.
To create the industry concentration index, we identify
the subset of subsidiaries for which total assets are reported;
we then compute the share of these assets related to each
industry i (measured at the three-digit NAICS level), and
calculate the index as the sum of the squared industry shares
2
. A high index value (close to 1) means that the
i si
subsidiaries are highly concentrated in one industry,
whereas a low value (close to 0) means that the subsidiary
assets are spread across many different industries. The same
approach is used to construct the two geographic concentration indexes, one based on world region weights and
another on country weights.
The coefficients on all three concentration indexes are
consistently negative in each column of results. However, they
are not statistically significant at the 10 percent level. Similarly,
a smaller share of BHC assets located in “traditional” banking
subsidiaries is also associated with greater complexity,
although again the coefficient is not statistically significant.22



Together, these results may be interpreted as some evidence,
albeit weak, that organizational complexity is positively related
to the diversity of the BHC’s activities, across both industrial
sectors and geographic locations. In future research, it would
be interesting to analyze this question in more depth, making
use of a larger sample of firms as well as time-series variation in
organizational structure, rather than just a single cross section.
Outside the scope of this article are important questions
regarding the consequences of BHC organizational complexity.
For example: To what extent is organizational structure largely
irrelevant, conditional on the asset and liability structure of the
consolidated entity? Would simplifying the organizational
22
We have also estimated a range of other specifications; for example, using
the total number of subsidiaries, rather than its log value, as the dependent
variable. Our findings are generally similar. One disadvantage of our
benchmark approach is that asset data are not available for all subsidiaries.
We also experimented with constructing concentration indexes based on the
number of subsidiaries (rather than using asset shares). However, this approach
generally does not seem reliable; for example, it dramatically underweights the
activity share of commercial banking, because the average commercial banking
subsidiary is much larger in size than average nonbank subsidiaries.

FRBNY Economic Policy Review / July 2012

structure of BHCs make these firms easier to reorganize in
bankruptcy? Are any costs and benefits associated with BHC
complexity internalized (so that the BHC is “optimally”
complex), or do they generate externalities for counterparties
or others?
One interesting paper related to these questions is Goetz,
Laeven, and Levine (2011), which studies frictions associated
with BHC geographic scope, one dimension of complexity.
Goetz et al. find that greater geographic reach has a negative
effect on BHC valuations. The authors’ preferred interpretation is
that geographic diffusion makes the firm more difficult to
monitor, thus weakening corporate governance. Another relevant
contribution is Morgan (2002), which argues that banks are more
opaque than other types of firms. In future research, it would be
interesting to use the data described above to understand whether
opacity and organizational complexity are related.

A Structural View of U.S. Bank Holding Companies

5. Conclusion
The size, scope, and complexity of large U.S. bank holding
companies have grown significantly in recent decades, shaped
by consolidation, legislative changes, and growth in the overall
size of the financial system. In this article, we have described the
typical structure of large BHCs, as well as many of the main
types of regulatory data they file. As we have illustrated by way
of some simple summary statistics, these data can be used to
provide a rich picture of the financial condition, composition,
and organizational structure of BHCs and represent a valuable
resource for researchers and others interested in these
important firms.

Appendix A: Regulatory Reportsa

This appendix provides information, including a brief
description, unit of observation, filing frequency, rules
of consolidation (U.S. GAAP or statutory rules), and public
availability, for the bank holding company (BHC) reports
listed below. Links to the forms are available at http://
www.newyorkfed.org/banking/reportingforms/index.html.

Foreign Exposures of U.S. BHCs
and Their Subsidiaries
FFIEC 009/9a, Country Exposure Report/Country Exposure
Information Report
Treasury International Capital (TIC) Data

Financial Data on BHCs
and Their Subsidiaries
FR Y-9C, Consolidated Financial Statements of Bank
Holding Companies
FR Y-9LP, Parent Company Only Financial Statements
for Large Bank Holding Companies
FR Y-9SP, Parent Company Only Financial Statements
for Small Bank Holding Companies
FFIEC 031, Consolidated Reports of Condition and Income
for a Bank with Domestic and Foreign Offices
FFIEC 041, Consolidated Reports of Condition and Income
for a Bank with Domestic Offices Only

U.S. Entities Controlled by Foreign
Banking Organizations outside
a U.S. BHC Structure
FR Y-7Q, The Capital and Asset Report for Foreign Banking
Organizations
FR Y-7N/S, Financial Statements of U.S. Nonbank Subsidiaries
Held by Foreign Banking Organizations
FFIEC 002, Report of Assets and Liabilities of U.S. Branches
and Agencies of Foreign Banks
FFIEC 002S, Report of Assets and Liabilities of Non-U.S.
Branches Managed or Controlled by U.S. Branch or Agency
of Foreign Bank (based on U.S. GAAP)

FR Y-11/FR Y-11S, Financial Statements of U.S. Nonbank
Subsidiaries of U.S. Bank Holding Companies
FR 2314/S, Financial Statements of Foreign Subsidiaries
of U.S. Banking Organizations
FFIEC 030/030S, Foreign Branch Report of Condition/
Abbreviated Foreign Branch Report of Condition

Miscellaneous
FFIEC 101, Risk-Based Capital Reporting for Institutions Subject
to the Advanced Capital Adequacy Framework
FR 2436, Semiannual Report of Derivatives Activity

Organizational Structure
and Attributes
FR Y-6, Annual Report of Bank Holding Companies
FR Y-10, Report of Changes in Organizational Structure

This appendix provides a high-level overview of each reporting form. For
more granular information on the description, unit of observation, frequency,
rules of consolidation, and public availability of each form, refer to the form
instructions. To access publicly available forms, visit the following sites: NIC
(http://www.ffiec.gov/nicpubweb/nicweb/nichome.aspx), FFIEC (https://
cdr.ffiec.gov/public/Default.aspx), and FOIA (http://www.federalreserve.gov/
generalinfo/foia/request.cfm).

FRBNY Economic Policy Review / July 2012

Appendix A: Regulatory Reportsa (Continued)

U.S. Bank Holding Companies and Their Subsidiaries
Panel A
Name of Report

Description

Unit of Observation

Frequency

Consolidation Rule

Data
Availability

Financial Data on BHCs and Their Subsidiaries
FR Y-9C

Balance sheet, income, and other financial data
on a consolidated basis for domestic BHCs,
incorporating both domestic and foreign
subsidiaries. Reporting threshold for filing:
$500 million in assets ($150 million pre-2006).

Consolidated top-tier
domestic BHCs

Quarterly

Consolidated
(GAAP basis)

Public

FR Y-9LP, FR Y-9SP

Balance sheet, income, and other financial data
information for large domestic BHCs (those
with less than $500 million in assets) on
parent-only basis. FR Y-9SP collects balance
sheet and income statement information for
small domestic BHCs (more than $500 million
in assets) on parent-only basis.

FR Y-9LP: Parent
company of large
BHCs
FR Y-9SP: Parent
company of small
BHCs

FR Y-9LP:
Quarterly

Unconsolidated

Public

FFIEC 031,
FFIEC 041

Commonly known as the “Call Reports.” FFIEC
031 collects balance sheet, income, and other
financial data on consolidated basis for
commercial banks with domestic and foreign
offices. FFIEC 041 includes the same data but is
filed by banks with domestic offices only.

FFIEC 031:
Quarterly
Commercial banks
with domestic/foreign
offices
FFIEC 041:
Commercial banks
with domestic offices
only

Consolidated at
bank level
(GAAP basis)

Public

FR Y-11, FR Y-11S

Balance sheet, income, and other financial data Large U.S. nonbank
for certain large U.S. nonbank subsidiaries of
subsidiaries of
domestic BHCs (for example, if subsidiary assets domestic BHCs
exceed $1 billion). FR Y-11S collects four financial data items for certain smaller subsidiaries
and is required only if parent files a Y-9C.

FR Y-11: Quarterly

Unconsolidated,
by legal entity

Public

FR 2314, FR2314S

Balance sheet, income, and other financial data
for direct or indirect foreign subsidiaries of
U.S. BHCs or other U.S. banking organizations.
FR 2314S collects four financial data items
for smaller, less complex subsidiaries.

Foreign subsidiaries
of U.S. banking
organizations

Quarterly or
annually (based
on reporting
thresholds)

Unconsolidated,
by legal entity

Public

FFIEC 030,
FFIEC 030S

Data on the structure and geographic
distribution of foreign branch assets, liabilities,
derivatives, and OBS items. 030S collects five
financial data items for smaller and less
complex branches (those with between
$50 million and $250 million in total assets).

Foreign branches
of insured U.S.chartered commercial
banks

FFIEC 030: Quarterly
or annually (based on
certain thresholds)
FFIEC 030S: Annually

Reported at branch
level with option to
aggregate branches
within same
country

Public aggregate data,
but private
microdata

Set of controlled
entities determined based
on regulatory
definition of
control, not
GAAP definition

Public, unless
BHC requests
confidential
treatment

FR Y-9SP:
Semiannually

FR Y-11S: Annual

Organizational Structure and Attributes
FR Y-6

Includes organizational chart, verification
of domestic branches, and information on
principal shareholders, directors, and executive
officers.

Top-tier BHCs

Annually

FR Y-10

Data on changes in organizational structure,
including establishment, opening, closing, relocation, acquisition, merger, reorganization,
transfer, sale, liquidation, and other changes
of interests.

Variety of financial
institutions, such as
BHCs, state member
banks, Edge and
agreement corporations, and FBOs

As needed

Key: BHC = bank holding company; FBO = foreign banking organization; OBS = off-balance-sheet; FHC = financial holding company;
OTC = over-the-counter

A Structural View of U.S. Bank Holding Companies

Public

Appendix A: Regulatory Reportsa (Continued)

U.S. Bank Holding Companies and Their Subsidiaries (Continued )
Panel B
Name of Report

Description

Unit of Observation

Frequency

Consolidation Rule

Data
Availability

Foreign Exposures of U.S. BHCs and Their Subsidiaries
FFIEC 009,
FFIEC 009a

Data on distribution by country of claims
on foreigners held by U.S. commercial banks
and BHCs. FFIEC 009a is a supplement that
provides information on the institution’s
exposures in certain countries.

FFIEC 009: U.S. commercial banks, BHCs
holding more than
$30 million in claims
on residents of foreign
countries
FFIEC 009a: Subset
of 009 filers based on
exposure thresholds

Quarterly

Consolidated
(GAAP basis)

Published
aggregate data,
but private
microdata

Treasury International
Capital (TIC) Data

Information on cross-border financial flows
and positions between U.S. and foreign
entities. The data cover a variety of financial
information, such as transactions in long-term
securities, claims and liabilities reported
by institutions, and financial derivatives
transactions.

Any individual,
corporation, or
organization located
in the United States

Depends on type
of data

N/A

Published
aggregate data,
but private
microdata

U.S. Entities Controlled by Foreign Banking Organizations Outside a U.S. BHC Structure
FR Y-7Q

Regulatory capital data for all FBOs organized
under foreign law and that engage in banking
in the United States through various types
of financial institutions, such as branches
or agencies and subsidiary banks.

FR Y-7N, FR Y-7NS

FR Y-7N collects balance sheet, income
FBOs with nonbank
statement, and OBS information for U.S.
subsidiaries
nonbank subsidiaries held by FBOs other than
through a U.S. BHC or bank. FR Y-7NS
collects four financial data items for smaller
and less complex subsidiaries.

FFIEC 002,
FFIEC 002S

Balance sheet and OBS information on U.S.
branches and agencies of foreign banks.
No income data are reported. FFIEC 002S is
a supplement that collects balance sheet
information from non-U.S. branches of U.S.
branches or agencies of foreign banks.

FFIEC 101

FR 2436

FBOs that engage
in banking in the
United States

Quarterly or
Consolidated at
annually
FBO level
(based on FHC status)

Public, unless
FBO requests
confidential
treatment

Quarterly or
annually
(based on certain
thresholds)

Unconsolidated by
legal entity

Public

Quarterly
FFIEC 002: U.S.
branches and agencies
of foreign banks
FFIEC 002S: Non-U.S.
branches controlled by
U.S. branches and
agencies of foreign
banks

Each branch files
separately unless
in same state
and district.
Each branch is
consolidated.

FFIEC 002:
Public
FFIEC 002S:
Private
microdata,
occasional
aggregate data

Data on components of capital and riskweighted assets for banks, savings associations,
and BHCs that qualify for and adopt Basel II
in determining their risk-based capital
requirements.

Banks, savings
associations, and
BHCs that qualify for
and adopt Basel II

Quarterly

Consolidated
(GAAP basis)

Private

Data on notional amounts and gross market
values of outstanding OTC derivatives. Used to
compute comprehensive and internationally
consistent information on size and structure
of global OTC derivatives market.

Five of the large U.S.
dealers of OTC
derivatives (reporting
is voluntary)

Semiannual

Consolidated
(GAAP basis)

Published
aggregate
country data,
but private
microdata

Miscellaneous

Key: BHC = bank holding company; FBO = foreign banking organization; OBS = off-balance-sheet; FHC = financial holding company;
OTC = over-the-counter
FRBNY Economic Policy Review / July 2012

Appendix B: Distribution of Subsidiaries by Industry

Number
Industry

Domestic

Foreign

Total

Domestic

Foreign

Total

3,694
2,365
1,437
2,239
1,564
1,682
315
228
68
23
51
41
14
11
14
1
5
0
1
1
1
1

1,911
1,355
1,263
149
683
0
164
164
64
60
15
2
4
7
1
4
0
1
0
0
0
0

5,605
3,720
2,700
2,388
2,247
1,682
479
392
132
83
66
43
18
18
15
5
5
1
1
1
1
1

281.71
802.32
2,440.23
19.26
11,899.93
4.27
2.00
33.22
1.36
0.48
1.36
1.56
1.64
0.24
1.09

673.99
1,836.23
736.76
39.79
1,286.89

955.70
2,638.55
3,176.99
59.04
13,186.82
4.27
236.59
110.85
3.16
3.15
1.73
1.56
1.71
0.24
1.09

13,756

5,847

19,603

15,490.83

Funds, trusts, and other financial vehicles
Securities, commodity contracts, and other
Management of companies and enterprises
Real estate and rental and leasing
Credit intermediation and related activities
Health care and social assistance
Insurance carriers and related activities
Professional, scientific, and technical services
Information
Administrative, support, waste, and remediation services
Utilities
Construction
Wholesale trade
Transportation and warehousing
Other services (except public administration)
Active, but unknown
Mining, quarrying, and oil and gas extraction
Educational services
Arts, entertainment, and recreation
Accommodation and food services
Manufacturing
Retail trade
Total

Assets (Billions of U.S. Dollars)

234.59
77.63
1.79
2.67
0.37
0.07

0.17

4,890.79

20,381.62

Sources: National Information Center; FR Y-10; FR Y-11; FR 2314; FFIEC 031; FFIEC 041.
Notes: Structure data are as of February 20, 2012. Financial data are as of fourth-quarter 2011. The number of subsidiaries for each bank holding company
(BHC) is determined based on the Regulation Y definition of control. Asset data include approximately 3,700 of the more than 19,600 subsidiaries belonging to
the top fifty BHCs (that is, those meeting thresholds for reporting asset data). The sum of total assets reported significantly exceeds Y-9C total assets in Table 1
of the article because of related-party transactions between subsidiaries. See the online appendix for more details.

A Structural View of U.S. Bank Holding Companies

References

Aharony, J., and I. Swary. 1981. “Effects of the 1970 Bank Holding
Company Act: Evidence from Capital Markets.” Journal
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Ashcraft, A. 2008. “Are Bank Holding Companies a Source of Strength
to Their Banking Subsidiaries?” Journal of Money, Credit, and
Banking 40, no. 2-3 (March-April): 273-94.
Cetorelli, N., and L. Goldberg. 2011. “Liquidity Management of U.S.
Global Banks: Internal Capital Markets in the Great Recession.”
Federal Reserve Bank of New York Staff Reports, no. 511,
August.
Copeland, A. 2012. “Evolution and Heterogeneity among Larger Bank
Holding Companies: 1994 to 2010.” Federal Reserve Bank of
New York Economic Policy Review 18, no. 2 (July): 83-93.
Furlong, F. 2000. “The Gramm-Leach-Bliley Act and Financial
Integration.” Federal Reserve Bank of San Francisco Economic
Letter, 2000-10, March 31.
Goetz, M., L. Laeven, and R. Levine. 2011. “The Valuation Effects of
Geographic Diversification: Evidence from U.S. Banks.” Brown
University working paper.

Kroszner, R. S., and R. G. Rajan. 1994. “Is the Glass-Steagall Act
Justified? A Study of the U.S. Experience with Universal Banking
before 1933.” American Economic Review 84, no. 4
(September): 810-32.
Morgan, D. 2002. “Rating Banks: Risk and Uncertainty in an Opaque
Industry.” American Economic Review 92, no. 4 (September):
874-88.
Omarova, S. T., and M. E. Tahyar. Forthcoming. “That Which We
Call a Bank: Revisiting the History of Bank Holding Company
Regulation in the United States.” Review of Banking and
Financial Law.
Santos, J. 1998. “Banking and Commerce: How Does the United States
Compare to Other Countries?” Federal Reserve Bank of Cleveland
Economic Review 34, no. 4: 14-26.
Stiroh, K. 2004. “Diversification in Banking: Is Noninterest Income
the Answer?” Journal of Money, Credit, and Banking 36,
no. 5 (October): 853-82.
White, E. 1986. “Before the Glass-Steagall Act: An Analysis of the
Investment Banking Activities of National Banks.” Explorations
in Economic History 23, no. 1 (January): 33-55.

Independent Commission on Banking. 2011. Final Report.
September 12. London.
Klebaner, B. 1958. “The Bank Holding Company Act of 1956.”
Southern Economic Journal 24, no. 3 (January): 313-26.

Online Technical Appendix for
“A Structural View of U.S. Bank Holding Companies”
by Dafna Avraham, Patricia Selvaggi and James Vickery

Not for print publication

Sections:
1. Notes on construction of figures and tables
2. Industry breakdown based on Capital IQ data

1. Notes on construction of figures and tables

Table 1: Distribution of subsidiaries: Top 50 BHCs
This table is constructed from the National Information Center (NIC)
(http://www.ffiec.gov/nicpubweb/nicweb), FR Y‐9C, Consolidated Financial Statements of Bank Holding
Companies, FR Y‐10, Report of Changes in Organizational Structure, FR Y‐11, Financial Statements of U.S.
Nonbank Subsidiaries of U.S. Bank Holding Companies, FR 2314, Financial Statements of Foreign
Subsidiaries of U.S. Banking Organizations, and FFIEC 031 and 041 (Call Reports), Consolidated Reports
of Condition and Income for a Bank with Domestic and Foreign Offices and Domestic Offices Only.




We construct the list of top 50 BHCs using the most updated structure data reported as of
February 20, 2012. Financial data is reported quarterly, and thus reflects each firm’s financial
position as of December 31, 2011. Note that two large firms, Taunus Corporation and RBC USA
Holding Corporation, lost BHC status in early 2012; while both these firms were amongst the NIC
top 50 BHCs as of December 2011, they were not BHCs as of February 20, and thus are not
included in our statistics. We include subsidiaries that are controlled and regulated by the BHC,
based on the Regulation Y definition of control.
The FR Y‐10 provides a variety of attributes data on BHCs and their subsidiaries, allowing us to
obtain information on each subsidiary’s primary activity, country, and domestic or foreign
classification. Therefore, we use FR Y‐10 data to create the “Number” section of this table. We
sum the number of entities, by BHC, in each of the four categories shown (domestic commercial
bank subsidiaries, other domestic subsidiaries, foreign subsidiaries, and all subsidiaries). We use
the commercial banking activity code (52211) in order to identify commercial banks, both
foreign and domestic.
We use the Call Reports to obtain financial data on commercial banks, the FR Y‐11 to obtain
financial data on large non‐bank subsidiaries, and the FR 2314 to obtain financial data on foreign
subsidiaries. The financial data is as of 2011:Q4 and includes approximately 3,700 of the over
19,600 subsidiaries belonging to the top 50 BHCs, which met reporting threshold criteria. To
construct the “Asset value (in billions USD)” section, we sum the total assets, by BHC, of
domestic commercial bank subsidiaries and compute it as a percentage of total assets, by BHC,
as reported on the FR Y‐9C.

Table 2: Geographic distribution
Panel A: Geographic location of U.S. BHC subsidiaries
This table is constructed from the National Information Center (NIC)
(http://www.ffiec.gov/nicpubweb/nicweb), FR Y‐10, Report of Changes in Organizational Structure, FR Y‐
11, Financial Statements of U.S. Nonbank Subsidiaries of U.S. Bank Holding Companies, FR 2314,
2

Financial Statements of Foreign Subsidiaries of U.S. Banking Organizations, and FFIEC 031 and 041 (Call
Reports), Consolidated Reports of Condition and Income for a Bank with Domestic and Foreign Offices
and Domestic Offices Only.




We construct our list of top 50 BHCs using the most updated structure data reported as of
February 20, 2012. Financial data is reported quarterly, and thus reflects each firm’s financial
position as of December 31, 2011. Note that two large firms, Taunus Corporation and RBC USA
Holding Corporation, lost BHC status in early 2012; while both these firms were amongst the NIC
top 50 BHCs as of December 2011, they were not BHCs as of February 20, and thus are not
included in our statistics. We Include subsidiaries that are controlled and regulated by the BHC,
based on the Regulation Y definition of control.
We partition the data into subsidiaries controlled by the seven largest BHCs (Bank of America, JP
Morgan Chase, Citigroup, Wells Fargo, Goldman Sachs, MetLife and Morgan Stanley),
subsidiaries belonging to the remaining top 50 BHCs, and subsidiaries belonging to all of the top
50 BHCs, and perform the following analysis for each partition.
o The FR Y‐10 provides a variety of attributes data on BHCs and their subsidiaries, allowing
us to obtain information on each subsidiary’s primary activity, country, and domestic or
foreign classification. Therefore, we use FR Y‐10 data to create the “Number” columns
of this table. We sum the number of entities, by country, to arrive at country‐level
number of subsidiaries. We then aggregate by region.
o We use the Call Reports to obtain financial data on commercial banks, the FR Y‐11 to
obtain financial data on large non‐bank subsidiaries, and the FR 2314 to obtain financial
data on foreign subsidiaries. The financial data is as of 2011Q4 and includes
approximately 3,700 of the over 19,600 subsidiaries belonging to the top 50 BHCs,
which met reporting threshold criteria. To construct the “% Total Assets” columns, we
sum the total assets of the subsidiaries, by country, to arrive at country‐level total
assets. We then further aggregate the data by region. Finally, we take region‐specific
total assets as a proportion of all total assets to arrive at each region’s percent of total
assets.

Panel B: Foreign Exposures of U.S. BHCs
This table is constructed from the E.16 Country Exposure Lending Survey and Country Exposure
Information Report, which is in turn based on data from the FFIEC 009 report.
Although the E.16 groups data by country, we aggregate the data by region. We then calculate the world
total of exposures, and calculate the domestic, foreign, and total exposures proportion of world
exposures.

Chart 1: Number and total assets of BHCs

Financial data in this figure is constructed from quarterly Call Report and Y‐9C filings. Organizational
information comes from NIC. We do not restrict the sample to Y‐9C filers with a domestic high‐holder
(i.e. the ultimate parent may be either a US firm, or a foreign firm with a US BHC subsidiary).
Panel A
A large BHC is defined as one that files a Y‐9C report of its financial activities (in recent years this
includes all BHCs with at least $500 million in total assets, this threshold is lower in earlier years).
Commercial bank assets of large BHCs in Panel A are measured as the sum of consolidated assets
reported by each banking subsidiary in its Call report filing. This represents a slight overestimate
because of double‐counting of any related party exposures between banks controlled by the same BHC.
Nonbank assets of large BHCs are the difference between total assets as reported in the Y‐9C and
commercial bank assets as defined above. Assets of small BHCs reflect only their commercial bank
subsidiaries. This is likely to be a good approximation to BHC assets for these firms, however. To identify
banks that are not part of a BHC, we search in NIC for all banks where the highholder is the same entity
as the bank in question.
Panel B
The number of BHCs is a count of Y‐9C filers plus the number of distinct high holders of commercial
banks filing a Call report, exclusive of banks that are their own high holder or have a Y‐9C filer high
holder.

Chart 2: Organizational complexity and international reach of large U.S. BHCs
This figure is constructed from the National Information Center (NIC)
(http://www.ffiec.gov/nicpubweb/nicweb) and FR Y‐10, Report of Changes in Organizational Structure.




For the bottom panel, we sum the number of countries that the subsidiaries are in, by
BHC, in 1990Q4 and 2011Q4. We then sort the BHCs by the number of countries, and
rank the BHCs according to this ordering. As noted above, the sample of BHCs in 1990
differs from the sample in 2011.

Chart 3: Industry breakdown of subsidiaries
This figure is constructed from the National Information Center (NIC)
(http://www.ffiec.gov/nicpubweb/nicweb), and FR Y‐10, Report of Changes in Organizational Structure.
Industry classification is based on the North American Industry Classification System (NAICS)
(http://www.census.gov/eos/www/naics).




Chart 4: Industry breakdown by assets
This figure is constructed from the National Information Center (NIC)
(http://www.ffiec.gov/nicpubweb/nicweb), FR Y‐10, Report of Changes in Organizational Structure, FR Y‐
11, Financial Statements of U.S. Nonbank Subsidiaries of U.S. Bank Holding Companies, FR 2314,
Financial Statements of Foreign Subsidiaries of U.S. Banking Organizations, and FFIEC 031 and 041 (Call
Reports), Consolidated Reports of Condition and Income for a Bank with Domestic and Foreign Offices
and Domestic Offices Only. Industry classification is based on the North American Industry Classification
System (NAICS) (http://www.census.gov/eos/www/naics).



We construct our list of top 50 BHCs using the most updated structure data reported as of
February 20, 2012. Financial data is reported quarterly, and thus reflects each firm’s financial
position as of December 31, 2011. Note that two large firms, Taunus Corporation and RBC USA
Holding Corporation, lost BHC status in early 2012; while both these firms were amongst the NIC
top 50 BHCs as of December 2011, they were not BHCs as of February 20, and thus are not
included in our statistics. We Include subsidiaries that are controlled and regulated by the BHC,
based on the Regulation Y definition of control.
Since the FR Y‐10 provides a variety of attributes data on BHCs and their subsidiaries, we use the
subsidiary’s primary activity data, reported as NAICS codes, to create this figure. We also use
the Call Reports to obtain financial data on commercial banks, the FR Y‐11 to obtain financial
data on large non‐bank subsidiaries, and the FR 2314 to obtain financial data on foreign
subsidiaries. The financial data is as of 2011Q4 and includes approximately 3,700 of the over
19,600 subsidiaries belonging to the top 50 BHCs, which met reporting threshold criteria. We
sum the total assets of the subsidiaries, by BHC and by industry as defined by NAICS (2007).
NAICS codes range from 2 to 6 digits in length, in which 2‐digit codes represent the broadest
categories, and 6‐digit codes represent the most specific categories. The industries displayed in
this figure correspond to 2‐digit NAICS codes, except for the finance and insurance industry,
which we broke out further using 3‐digit NAICS codes. We decompose each industry further by
differentiating into each of the top 7 BHCs (Bank of America, JPMorgan Chase, Citigroup, Wells
Fargo, Goldman Sachs, MetLife and Morgan Stanley) and the remaining 43 BHCs in our sample.

Appendix B: Industry breakdown
This table is constructed from the National Information Center (NIC)
(http://www.ffiec.gov/nicpubweb/nicweb), FR Y‐11, Financial Statements of U.S. Nonbank Subsidiaries
of U.S. Bank Holding Companies, FR 2314, Financial Statements of Foreign Subsidiaries of U.S. Banking
Organizations, and FFIEC 031 and 041 (Call Reports), Consolidated Reports of Condition and Income for a
Bank with Domestic and Foreign Offices and Domestic Offices Only. Industry classification is based on the
North American Industry Classification System (NAICS) (http://www.census.gov/eos/www/naics).




categories shown (domestic subsidiaries, foreign subsidiaries, and all subsidiaries). NAICS codes
range from 2 to 6 digits in length, in which 2‐digit codes represent the broadest categories, and
6‐digit codes represent the most specific categories. The industries displayed in this table
correspond to 2‐digit NAICS codes, except for the finance and insurance industry, which we
broke out further using 3‐digit NAICS codes.
We use the Call Reports to obtain financial data on commercial banks, the FR Y‐11 to obtain
financial data on large non‐bank subsidiaries, and the FR 2314 to obtain financial data on foreign
subsidiaries. The financial data is as of 2011Q4 and includes approximately 3,700 of the over
19,600 subsidiaries belonging to the top 50 BHCs, which met reporting threshold criteria. To
construct the “Asset value (in billions USD)” section, we sum the total assets of domestic
subsidiaries, foreign subsidiaries, and all subsidiaries, by industry as defined by NAICS (2007) and
using the same 2‐digit and 3‐digit breakout as described above.

2. Industry breakdown based on Capital IQ (CIQ) data

CIQ Figures (shown next page): Industry breakdowns of the top 7 BHCs’ subsidiaries by count and total
assets (CIQ)
These figures are constructed from Capital IQ (https://www.capitaliq.com/home.aspx), which we use as
an alternative source of data on large bank holding companies and their subsidiaries.


From Capital IQ, we obtain the organizational structure for the top 7 BHCs (as of February 20,
2012: these are JPMorgan Chase, Bank of America, Citigroup, Wells Fargo, Goldman Sachs,
Metlife, and Morgan Stanley), and the total assets (as of Q4:2011) and primary activities of
these subsidiaries, if available.
o To create the “Count” figure, we sum the number of subsidiaries, by BHC and by
industry. We do not display the uncategorized subsidiaries listed in CIQ (i.e. subsidiaries
where no industry type is recorded). It is important to note that there are >2,000 of
these uncategorized subsidiaries for these 7 firms.
o The financial data is comprised of a subset of the subsidiaries belonging to the top 7
BHCs. To create the “Total Assets” figure, we sum the total assets of the subsidiaries, by
BHC and by industry.

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Number of Subsidiaries

Industry Breakdown of the Top 7 BHCs' Subsidiaries by Count (CIQ)

500

450

400

350

300

250

200

150

100

Wells Fargo

Industry Breakdown of the Top 7 BHCs' Subsidiaries by Total Assets (CIQ)

3,500

3,000

2,500

2,000

1,500

1,000

500

Wells Fargo

Comparison of Capital IQ to BHC regulatory data
This table compares the asset counts from Capital IQ to those from regulatory data. The final column shows that for 6 of the top 7 BHCs,
the reports in Capital IQ capture significantly less than 100% of the individual subsidiary assets reported in these BHCs’ regulatory
reports (the fraction varies between 4% and 77% across firms). MetLife differs because the majority of its assets are in its insurance
subsidiaries, which do not file the Y‐11 report.

BHC
Name
BAC
C
GS
JPM
MET
MS
WFC
Total

Aggregated
Subsidiary Total
Assets, Thousands
USD (CIQ)
2,228,468,507
2,311,946,091
54,298,691
1,994,224,337
213,455,022
81,147,303
1,216,210,058
8,099,750,009

Y‐9C Total Assets,
Thousands USD
2,136,577,907
1,873,878,000
923,718,000
2,265,792,000
799,625,102
749,898,000
1,313,867,000
10,063,356,009

Aggregated Subsidiary
Total Assets,
Thousands USD
(Subsidiary‐Level Reg.
Data)
3,287,483,134
3,367,008,287
1,377,017,750
3,670,870,266
109,935,363
1,505,959,803
1,572,221,151
14,890,495,754

CIQ Total Assets /
Y‐9C Total Assets
104.30%
123.38%
5.88%
88.01%
26.69%
10.82%
92.57%
80.49%

CIQ Total Assets /
Subsidiary‐Level
Reg.Data
67.79%
68.66%
3.94%
54.33%
194.16%
5.39%
77.36%
54.40%

Adam Copeland

Evolution and Heterogeneity
among Larger Bank Holding
Companies: 1994 to 2010
1. Introduction

ver the past two decades, there has been a transformation
in the U.S. financial sector. Alongside the deregulation of
this industry, financial intermediation has shifted from a bankcentered process to one where nonbanks play an increasing
role. Given these changes, questions arise about how banks
have adapted and to what degree their traditional roles in
financial intermediation have changed (see Cetorelli, Mandel,
and Mollineaux [2012]). In this article, I provide a general
perspective on this broad question by documenting how banks
have evolved in terms of income. I measure the amount by
which banks have changed their income-generating strategies
in response to the transformation of the U.S. financial
sector. Further, I describe the heterogeneity in responses
across banks to recent changes in the industry.
In this analysis, I focus on bank holding companies (BHCs)
because, among banks, the BHC legal form of organization
dominates over this period, especially for larger banks.1
Comparing BHCs over the past two decades is difficult,
however, because there has been rapid consolidation. This
results in dramatic differences over time in the set of large
BHCs (as measured by assets). To control for selection effects
and better measure how BHCs have evolved over time, I create
a sample related to the top fifty BHCs in 2006. (Section 2
describes how this sample is constructed.)
1

Stiroh (2000) reports that by 1997, 83 percent of FDIC-insured assets were
held by BHCs. He also details the organizational advantages of BHCs relative
to independent banks.

Adam Copeland is a senior economist at the Federal Reserve Bank of New York.
Correspondence: adam.copeland@ny.frb.org

For this sample of BHCs, I begin by using the standard
measures of interest and noninterest income to infer the degree
to which BHCs’ income mix has changed. In 1994, near the
beginning of the current transformation in the financial sector,
these BHCs were fairly homogenous, earning the vast majority
of their revenue from interest income. Over time, however,
these BHCs pursued different income strategies, so that by
2006 there is a wide disparity in the relative importance of
interest income. Some continue to earn the vast majority of
their revenues from interest income, while for others interest
income no longer accounts for most of their revenues. For this
latter group, this shift in the mix of income suggests that these
BHCs may have started earning income from new financial
services, or at least changed the way they provide and charge for
traditional banking services.
To better analyze BHCs’ different income strategies, I turn
to detailed income data available since 2001. With these data,
I categorize income sources into three groups: traditional,
securitization, and nontraditional. These categories are
constructed so that income earned from new financial services
would fall into either the securitization or nontraditional
category. The securitization category captures income related
to creating, servicing, or selling securitized assets, while the
nontraditional category contains, roughly speaking, sources
of income related to the capital markets.
Analyzing these three income categories, I find that there
is a positive relationship between the relative importance of
nontraditional income sources and asset size. Over the 200110 period, the largest BHCs earn a substantially larger share

The author thanks Nicola Cetorelli and Lindsay Mollineaux for comments and
suggestions as well as help with pulling and understanding the data. The views
expressed are those of the author and do not necessarily reflect the position of
the Federal Reserve Bank of New York or the Federal Reserve System.

FRBNY Economic Policy Review / July 2012

of their total income from the nontraditional category
compared with their smaller peers. These results demonstrate
that larger BHCs have been much more active in offering
new financial services, and suggest that the transformation
in the financial industry has influenced larger BHCs to a
greater extent.
Building on the above result, I show that large BHCs also
earn substantially larger shares of their interest and noninterest
income from their noncommercial bank subsidiaries.
Consequently, large BHCs seem to be organizing themselves
differently from their smaller peers.2 Consistent with this
result, Avraham, Selvaggi, and Vickery (2012) report that the
largest BHCs are substantially more complex organizations
relative to their smaller peers.
Altogether, these results strongly suggest that overall
changes in the financial sector have most heavily influenced
the larger BHCs. From an income perspective, the smaller
BHCs have not changed much over the past two decades.
Their mix of income continues to rely heavily on traditional
banking sources, and income is still mostly generated by the
commercial bank subsidiary. The larger BHCs, in contrast,
have undergone a significant change, resulting in a reliance
on new sources of income and on income generated by the
BHC’s noncommercial bank subsidiaries.

2. Data
I use BHC data from Federal Reserve Y-9C regulatory filings
covering the period 1994 to 2010.3 The start date was chosen
for two reasons. First, beginning the sample in the early 1990s
allows me to observe a period of time when BHCs were still
somewhat constrained by regulation and therefore fairly
homogenous, providing a good reference point for any
heterogeneity across BHCs that is later observed. Second, by
1994 the largest banks, the focus of this article, were organizing
themselves as BHCs, as opposed to being stand-alone
commercial banks (which are required to file different
regulatory forms). From the Y-9C filings, I use mainly the
income data as well as the information on organizational
structure to track mergers over time.
Tracking mergers over time is crucial to the analysis in this
study, because I intend to describe the evolution of the largest
BHCs while controlling for selection effects. Because of the
2

Clark et al. (2007) also highlight how the largest U.S. banks may be organizing
themselves differently from other banks. They describe how retail banking has
become an area of strategic focus for the largest U.S. banks, which are building
large branch networks and investing in other retail banking infrastructure.
3
For detailed information on the Y-9C filings, see http://www.federalreserve
.gov/reportforms/ReportDetail.cfm?WhichFormId=FR_Y-9C.

Evolution and Heterogeneity

wave of mergers that occurred among BHCs over this period,
the top fifty BHCs in 1994 look quite different from the top fifty
in 2010 along many dimensions. Examples include the entry of
several large, foreign-owned BHCs midway through the sample
as well as Goldman Sachs and Morgan Stanley at the end of
the sample.
To control for selection, I pick the top fifty BHCs in 2006
and construct a data set of bank holding companies that are
linked to these specific BHCs through mergers. Consequently,
in 2006 I have data on exactly fifty BHCs. In any previous year,
more than fifty BHCs are in my sample because I include all the
BHCs that merged into and became part of the top fifty in 2006.
For example, if two BHCs merged in 2005 to become a top fifty
BHC in 2006, then both BHCs would be in the sample in 2005.
Similarly, in 2007 and later, there are fewer than fifty BHCs
in the data because of continued mergers among these BHCs,
in addition to exits.4 I chose the top fifty BHCs in 2006 because
this is the latest year before the recent financial crisis.
The table reports the total number of BHCs in the
constructed data set for each year in the sample. The massive
consolidation among BHCs is readily apparent—268 BHCs in
1994 had merged into 50 BHCs by 2006. This consolidation is
almost completely responsible for the concentration in assets.
In 1994, the 268 BHCs that are linked to the top 50 in 2006
control 58 percent of total assets held by BHCs that file Y-9C
regulatory filings. In 2005, there are sixty-four BHCs linked to
the top fifty, and they control 58 percent of total assets held
by BHCs. Hence, while there has been growth in the value
of assets held by BHCs over this period, this growth has been
equally distributed between those in the sample and all those
outside of it. In 2006, there is a large jump in the percentage
of assets held in the BHC sample, but this is driven by a
change in the rules that lowered the number of BHCs
required to file Y-9C reports. Specifically, before March 2006
all BHCs with more than $150 million in assets were required
to file Y-9C reports, while after March 2006 this asset
threshold was raised to $500 million.
With this sample of BHCs, the analysis in this article
focuses on income reported in the Y-9C regulatory filings.
Typically, analysis of BHC income relies upon the structure
inherent in the regulatory filings, and so focuses on measures
such as interest income and noninterest income. While I
discuss the evolution of these two aggregate income measures,
I also highlight changes in income sources related to offerings
of new financial services. The interest and noninterest income
grouping does not allow for a clean measurement, because new
financial services will show up in both categories. As such,
I construct a different categorization of income sources,
4

Some BHCs reclassified themselves and consequently were no longer
considered BHCs. For example, Charles Schwab Corporation became a savings
and loan holding company in 2007 and so exited the sample.

Statistics on the Constructed Bank Holding
Company Data Set
Summations
over BHC Sample

Comparison of Sample
to All BHCs

Year

Total
(Units)

Assets
(Billions of Dollars)

Total
(Percent)

Assets
(Percent)

1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010

268
256
238
214
170
146
127
106
91
82
69
64
50
43
40
39
38

2,673
2,916
3,139
3,508
4,406
4,855
5,405
6,056
6,413
7,134
8,546
9,405
10,646
11,592
11,780
11,828
11,818

20
18
17
14
11
9
7
6
4
4
3
3
5
4
4
4
4

58
58
59
60
62
58
57
58
57
57
56
58
86
85
85
74
73

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.
Notes: The first pair of columns displays summations over the BHCs in
the sample. The second pair of columns reports the ratio of the summations in the sample of BHCs over the comparable summations for all the
BHCs that file FR Y-9C regulatory forms, as a percentage.

leveraging the increase in income source detail reported after
2000. For the 2001-10 period, I group income sources into
three categories: traditional, securitization, and nontraditional.
The main goal of this new categorization is to have income from
new financial services fall into either the securitization or
nontraditional category. By analyzing these two categories,
then, I can estimate the relative importance of new financial
services both overall and across BHCs.
The traditional category contains the classic sources of
income that most banks have relied upon over time, such as
interest and fee income on loans, service charges on deposit
accounts, fees for providing payments services, and income
from fiduciary activities. (See the appendix for a full mapping
of income sources in the Y-9C filings to each of the income
categories I construct.) These income sources capture services
that BHCs have historically offered; hence, this category
should not contain income derived from the newer financial
services banks offered during the recent transformation of
the banking sector.

The securitization category tries to capture income
generated from banking activities related to the securitization
of assets. In the past two decades, the creation, servicing, and
sale of securitized assets have developed into an important part
of banking.5 Indeed, a well-known trend in banking is to
substitute away from an originate-and-hold strategy for loans
(particularly mortgages) to an originate-to-sell strategy. The
first strategy involves holding loans on the balance sheet of
BHCs. The second strategy uses financial market expertise to
pool loans and create an asset-backed security that could be
sold to investors. I include income from three sources in this
category. The first two are fees earned from the securitization
of loans and the servicing of financial assets held by others.
The third source captures a BHC’s net interest income from
investing and holding mortgage-backed securities (MBS)
on its balance sheet. I measure this third source of revenues
as the interest and dividend income on MBS minus an
approximation of the associated interest expense. The
approximation is the fraction of interest and dividend income
on MBS to total interest income, multiplied by total interest
expense. Hence, I assume that interest expenses at a BHC are
proportionately divided across all interest income activities.
I view the securitization and traditional categories as
substitutes. Income related to securitization is focused on
process—how a BHC manages its assets—as opposed to
product. In both the originate-and-hold and originate-to-sell
examples, the BHC is providing the same service—loans to
customers. But under the first strategy, the BHC employs
the “traditional” technology of holding and managing the
loans on its balance sheet, while under the second it
transforms the loans into a security. Under the first strategy,
the resulting earned income will be classified as traditional,
while under the second strategy the income will fall into the
securitization category.
The nontraditional category captures income from, loosely
speaking, capital market activities. I argue that most of the new
financial services that BHCs began to offer in the past two
decades were mainly related to capital market services. The five
income sources in this category are net interest income from
trading assets, trading revenues, venture capital revenues,
investment banking, and insurance income. Net interest
income is computed as interest income from trading assets
minus an approximation of the interest expense associated
with this activity. Once again, this approximation is the fraction
of interest income from trading assets divided by total interest
income, all multiplied by total interest expense.
5

Cetorelli and Peristiani (2012) describe in detail the role of securitization
within the banking industry.

FRBNY Economic Policy Review / July 2012

3. Evolution and Heterogeneity
among BHCs
This section analyzes how the largest BHCs, from an income
perspective, have evolved over time. I begin by examining
changes in BHCs using the typical measures employed in the
literature—for example, interest and noninterest income.
I then complement this analysis by using the three income
categories described in Section 2. In particular, I emphasize
that the largest BHCs have a mix of income sources
significantly different from that of other BHCs. Finally, I
present evidence that the largest BHCs are organized quite
differently from other ones.

Chart 1

Evolution of the Components of Operating Revenue
Billions of dollars
800
600
400

Interest income
Noninterest income
Loan loss provisions
Interest expenses

200
0
-200
-400
1994 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10
Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.

3.1 An Analysis of BHC Income
Using Standard Measures
I start by focusing on a commonly used measure of BHC
income: operating revenue and its components. Operating
revenue is equal to interest income minus interest expense
plus noninterest income minus loan loss provisions. The first
two variables are also called net interest income and together
they roughly capture the income BHCs earn on the spread
between the interest rate they earn from lending versus the
interest rate they pay from borrowing. Noninterest income
covers a wide variety of revenue sources, but is typically
considered revenues the bank earns from providing fee-based
services. Since 1994, noninterest income generated by BHCs
has steadily increased, except for a dip during the financial
crisis (Chart 1).6 In addition, noninterest income has grown
as a share of operating revenue, reaching 59 percent in 2010.
This change in the mix of income has been presented as a shift
away from banking services based on interest income and
toward a fee-based operating model of banking (see, for
example, DeYoung and Rice [2004]).
There is, however, a lot of heterogeneity among the largest
BHCs with respect to this greater reliance on noninterest
income. Chart 2 plots the joint distribution of the log of assets
and the ratio of noninterest income to operating revenue for
BHCs in 1994 and 2006. There are two interesting patterns
revealed. First, the rightward shift from circle to triangle
markers illustrates the massive consolidation that occurred
among BHCs between 1994 and 2006. This is visually
reinforced by the contrast in the number of data points; there
were 268 BHCs in 1994 that through mergers became 50 in
6

Stiroh and Rumble (2006) analyze BHCs’ shift toward noninterest income.
They find that the gains from having a more diversified mix of income are more
than offset by the costs associated with the volatility of noninterest income.

Evolution and Heterogeneity

Notes: Operating revenue is equal to interest income minus interest
expense plus noninterest income minus loan loss provisions. The
sample is all bank holding companies linked to the top fifty BHCs
in 2006.

Chart 2

Heterogeneity in the Importance of Noninterest
Income across Bank Holding Companies
Ratio of noninterest income to operating revenue
1.0
0.8

1994
2006

0.6
0.4
0.2
0
12

16
18
Log of assets

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.
Note: There are 268 BHCs plotted in 1994 and 50 BHCs plotted in 2006.

2006. Second, in 2006 BHCs look more diverse. In 1994, for
a strong majority of BHCs the ratio of noninterest income to
operating revenue was less than 0.4. For the most part, then,
BHCs in 1994 relied on interest income as the main source of
operating revenue. In contrast, the BHCs in 2006 are much
more evenly spread between the high and low ratios of
noninterest income to operating revenue. The recent evolution

in banking, then, has produced greater variety among BHCs,
as institutions have pursued different strategies with respect
to their reliance on noninterest income.

Chart 3

Evolution of Traditional, Securitization,
and Nontraditional Income
Percent

Percent

80
Nontraditional income

3.2 An Analysis of BHC Income
Using New Measures

Scale

To better understand what is driving the heterogeneity in
BHCs’ sources of income, I turn to the detailed income
numbers reported in regulatory filings from 2001 onward.
I look for evidence that increased variety across BHCs is related
to the larger changes occurring in the financial sector. An
important trend in the sector has been the ability of banks to
offer a number of new financial products to customers.7 Using
the detailed income data, I intend to measure if income earned
from new financial services is a substantial amount and to what
degree it impacts BHCs’ mix of income sources. To this end,
I use the disaggregated data to construct three categories
of income: traditional, securitization, and nontraditional
(as described in Section 2). These categories are constructed
so that new financial services show up in the securitization
or nontraditional category.
I first look at aggregate measures of traditional, securitization, and nontraditional income from 2001 to 2010
to see if overall trends inform us about the impact of new
financial services on BHCs’ mix of income. If new financial
services are an important source of total BHC income, then
we would expect to see upward trends in securitization’s
and nontraditional’s shares of total income. Chart 3 presents
these shares: the percentage contribution of each income
category to total income over the sample period. Leading
up to the crisis, the share of each income category to total
income is roughly constant, with traditional income
accounting for the majority of total BHC income. During
the crisis, nontraditional income’s share of total income
fell dramatically, with a corresponding rise in traditional
income’s share. Post-crisis, however, nontraditional income
has bounced back and contributes to total income at the same
level observed in 2006. Securitization income started to fall
with the advent of the crisis and has not yet recovered. Its
share of total income dropped to about 7 percent of total
income by 2010, its lowest level over the sample period.
The financial crisis, then, appears to have had a lasting
dampening effect on securitization income, in contrast
to what we observed with nontraditional income.
7
Before passage of the Gramm-Leach-Bliley Act of 1999, BHCs were restricted
from owning both commercial and investment banks and were limited to
providing services closely related to banking. Afterward, BHCs were able
to own both commercial and investment banks and offer customers a wide
variety of financial services.

Traditional income
Scale

Securitization income
Scale

55
2001

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.

Unfortunately, these aggregate dynamics do not inform us
about the impact of new financial services. The constant trends
may indicate that the introduction of new financial services had
little impact on BHCs’ mix of income. However, BHCs may
have already begun offering new financial services before 2001,
in which case their income mix may have already adjusted.
We may, however, be able to learn something by using the
disaggregated data and analyzing the heterogeneity across
BHCs over this period. Before the banking sector started its
transformation and before the deregulation in the 1990s, BHCs
were constrained to be fairly homogenous in their mix of
income. For 2001 onward, then, we can interpret differences
across BHCs in their reliance on securitization and
nontraditional income as a function of differences in BHCs’
willingness to introduce new financial services and to develop
these new sources of income.
A main result from this approach is a positive relationship
between size (as measured by assets) and reliance on
nontraditional income sources. To illustrate this heterogeneity,
I group BHCs into three categories based on asset size. I label
“large” those BHCs that are linked to the top ten BHCs in 2006.
“Medium” are those BHCs linked to the bank holding
companies whose asset size ranks from eleven to twenty
in 2006 and “small” are the remaining BHCs. As a point of
reference, the median asset sizes in 2006 across these three
groups of BHCs were $505 billion, $147 billion, and $43 billion,
respectively.
Charts 4-6 illustrate the income heterogeneity across BHCs.
They present “box-and-whisker” plots of the ratios of
nontraditional, traditional, and securitization income to total

FRBNY Economic Policy Review / July 2012

Chart 4

Chart 6

Ratio of Nontraditional to Total Income

Ratio of Securitization to Total Income
Ratio

Ratio
0.8

Small BHCs

Medium BHCs

Large BHCs

0.5
0.4

0.4

0.3

0.2

0.1

−0.2

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.

Medium BHCs

Large BHCs

−0.1
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010

2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010

0.6

Small BHCs

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.
Chart 5

Ratio of Traditional to Total Income
Ratio
1.2

Small BHCs

Medium BHCs

Large BHCs

1.0

0.8
0.6

0.4
0.2

2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.

income for each group of BHCs from 2001 to 2010.8 For large
BHCs, nontraditional income accounts for a significantly
larger portion of total revenues. From 2001 to 2010, the median
8

The “box-and-whisker” format is a convenient way to characterize a
distribution. The “box” portion comprises the 25th, 50th, and 75th percentiles.
Consequently, the box contains half of the observations in a category, and the
length of the box provides a measure of the dispersion (heterogeneity) among
them. The “whiskers” plot upper and lower adjacent values, defined hereafter.
Let x represent the variable of interest. Define xi as the ith ordered value of x,
so that (x25 , x75 ) represent the 25th and 75th percentiles, respectively. Let
U = x75 +

3
--2

(x75  x25). The upper adjacent value is defined as xi, such that

xi <= U and xi+1 > U . The lower adjacent value is defined similarly.

Evolution and Heterogeneity

ratio of nontraditional to total revenues was 0.05 and 0.11 for
small and medium BHCs, respectively. In contrast, the median
ratio was 0.21 for large BHCs. These stark differences across
BHC groupings are mirrored in Chart 5, which plots the ratio
of traditional to total income. Except for 2008, when the
financial crisis was in full swing, the median ratio for large BHCs
was significantly below those for small and medium BHCs.
Surprisingly, all three types of BHCs rely on securitization to
the same degree (Chart 6).
I argue that the significant heterogeneity between large
BHCs and the remaining BHCs indicates that new financial
services have had a substantial and uneven impact. The result
suggests that the largest BHCs have most aggressively built up
new sources of income. Small BHCs, in contrast, continue to
rely mainly on the same sources of income available to them
historically. Overall, then, this finding suggests that large
BHCs have been impacted by the larger transformations within
the financial sector to a much greater extent than their smaller
counterparts.
Another interesting feature of Charts 4-6 is the greater
diversity of income shares within large BHCs compared with
shares within medium and small BHCs. As illustrated in
Chart 4, the 75th percentile of large BHCs earn in the
neighborhood of four-tenths of total income from
nontraditional sources (of course, 2008 is a significant
exception). In contrast, small and medium BHCs are more
homogenous, as evidenced by the narrower range between the
25th and 75th percentiles (the length of the “box” portion of
the “box-and-whiskers” plots). This result supports the idea
that large BHCs are experimenting with and developing new
financial services with varying degrees of success, while small

Chart 7

Chart 8

Components of Nontraditional Income, 2001-06

Components of Nontraditional Income, 2007-08
Percent

Percent
80

Insurance
Investment banking
Trading revenue
Venture capital
Net interest income
on trading assets

70
60
50
40
30

0.8
0.7

Insurance
Investment banking
Trading revenue
Venture capital
Net interest income
on trading assets

0.6
0.5
0.4
0.3
0.2

0.1

0
-0.1

0
-10
Small BHCs

Medium BHCs

Large BHCs

-0.2
-0.3
Small BHCs

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.

and medium BHCs continue to earn income from the same
traditional services.
To better understand the differences in nontraditional
income across BHC groupings, I turn to the disaggregated data.
Recall that nontraditional income comes from five sources: net
interest income from trading assets, venture capital revenues,
investment banking, insurance income, and trading revenues.
Because the recent financial crisis had a large impact on these
income sources, I analyze the periods 2001-06, 2007-08, and
2009-10 separately.
From 2001 to 2006, there is a wide difference across the
three BHC types in their reliance on specific income sources
(Chart 7). As a group, small BHCs received over 60 percent
of their nontraditional income from investment banking.
In contrast, medium and large BHCs relied upon trading
revenue, investment banking, and insurance income to a
roughly equally extent. Further, net interest income from
trading assets is substantially higher for medium and large
BHCs relative to small ones.
From 2007 on, there is a shift such that small and medium
BHCs now look similar. Both types of BHCs rely on investment
banking to generate half of their nontraditional income
(Charts 8 and 9). Large BHCs, meanwhile, look significantly
different. Unlike the other two types, large BHCs incurred
massive losses in trading revenue during the financial crisis.
Furthermore, they rely equally on investment banking and
insurance to generate more than half of their nontraditional
income, and they rely on net interest income on trading assets
to a larger extent.

Medium BHCs

Large BHCs

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.

Chart 9

Components of Nontraditional Income, 2009-10
Percent
0.8

Insurance
Investment banking
Trading revenue
Venture capital
Net interest income
on trading assets

0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
Small BHCs

Medium BHCs

Large BHCs

Sources: Federal Reserve System, Form FR Y-9C regulatory filings;
author’s calculations.

In summary, by analyzing the disaggregated data, I find that
large BHCs have developed significantly different income
sources relative to medium and small ones. While their smaller
peers continue to rely on traditional income sources that have
been available to BHCs historically, large BHCs have offered
new financial services and have so developed new sources of
income. The changes occurring in the financial sector, then,
seem to have impacted large BHCs the most.

FRBNY Economic Policy Review / July 2012

3.3 The Importance of Noncommercial
Bank Subsidiaries in BHCs
The above analysis has focused on income sources of BHCs,
regardless of where in the BHC entity the income was earned.
Historically, the commercial bank subsidiary of a bank
holding company has been dominant, earning the vast
majority of a BHC’s income. But a well-known feature of the
current evolution in banking is the rising importance of
noncommercial bank entities (see Boyd and Gertler [1994]).
BHCs have the organizational flexibility to incorporate
noncommercial bank subsidiaries, and so in this section
I measure the importance of these subsidiaries in terms
of income.9 The main result is that large BHCs rely on
commercial bank subsidiaries for income to a much lesser
extent than do smaller BHCs. This finding reinforces the
previous result that long-run changes in the financial
industry have had a significant, but differential, impact
on BHCs.
To measure how much BHCs rely on their commercial
bank subsidiaries for income, I compute the fraction of
interest and noninterest income earned by the commercial
bank subsidiaries within a BHC compared with the BHC’s
total interest and noninterest income.10 Charts 10 and 11 plot
the median value of each fraction in each year of the sample
by type of BHC.
Despite the rising importance of noncommercial bank
entities in the financial sector, small BHCs continue to almost
exclusively rely on their commercial bank subsidiaries for
interest income (Chart 10). The same is true for medium
BHCs, except for 2005 and 2006. In contrast, large BHCs
dramatically decreased the share of interest income earned
from their commercial bank subsidiaries. From 2005 to 2009,
noncommercial bank subsidiaries in large BHCs accounted
for roughly one-quarter of total BHC interest income.
A similar story holds for noninterest income (Chart 11). In
this case, small and medium BHCs have slightly decreased the
role of commercial bank subsidiaries in generating income
over time. But this is nowhere near the extent seen for large
BHCs, where commercial bank subsidiaries have gone from
producing almost all BHC noninterest income in the late
1990s to only about 60 percent in 2009 and 2010.
9

Boyd and Graham (1986) also consider the significance of nonbank
subsidiaries to BHCs. Rather than focus on income, they empirically examine
whether nonbank subsidiaries increase a BHC’s risk of failure. They find no
evidence that increased involvement in nonbank business systemically changes
a BHC’s risk of failure.
10
The income earned by commercial banks is reported in the Consolidated
Reports of Condition and Income (the “Call Reports”). Further, these filings
provide information that allows me to link the commercial bank to its
BHC. For detailed information on the Call Reports, see http://www.fdic
.gov/regulations/resources/call/.

Evolution and Heterogeneity

Chart 10

Ratio of Bank to Bank Holding Company Interest
Income by BHC Type
Ratio
1.0
Medium BHCs

Small BHCs
0.8

Large BHCs

0.6

0.4
1994

Sources: Federal Reserve System, Form FR Y-9C and call report
regulatory filings; author’s calculations.

Chart 11

Ratio of Bank to Bank Holding Company Noninterest
Income by BHC Type
Ratio
1.2
Small BHCs
1.0

Medium BHCs
0.8
Large BHCs
0.6

0.4
1994

Sources: Federal Reserve System, Form FR Y-9C and call report
regulatory filings; author’s calculations.

These findings demonstrate a variety of approaches across
BHCs in their strategies to earn income. For large BHCs—and
only for large BHCs—noncommercial bank subsidiaries play a
substantial role in generating income. These results are
consistent with those of Avraham, Selvaggi, and Vickery (2012),
who report that the complexity of a BHC’s structure increases
with size. Furthermore, these results reinforce the earlier
claims that the transformation of the financial sector has
impacted large BHCs to a much larger extent than medium or
small ones.

4. Conclusion
This article uses detailed income data from the Federal
Reserve Y-9C regulatory filings to describe the evolution of
BHCs’ income mix from 1994 to 2010. I find that bank
holding companies have become more diverse over time, as
large BHCs have developed new sources of income by offering
new financial services. Furthermore, large BHCs have

developed income sources outside of their commercial bank
subsidiaries to a much larger extent than their smaller
counterparts. I argue that these results demonstrate that the
transformation of the financial sector over the past two
decades has had a substantial and uneven impact on BHCs.
Specifically, it is the large BHCs that have been most affected,
at least as measured by income.

FRBNY Economic Policy Review / July 2012

Appendix: Income Sources

This appendix lists the income sources reported in the
Federal Reserve Y-9C regulatory filings that are attributable
to the three income categories used in the article. This mapping
works only for those filings from 2001 and thereafter. Before
2001, reporting on income sources lacked sufficient detail to
make this categorization possible.
For interest and dividend income on mortgage-backed
securities (in the securitization category) and interest income
from trading assets (in the nontraditional category), I compute
an associated interest expense in order to arrive at a net interest
measure. For interest income from trading assets, the interest
expense term is equal to the fraction of interest income from
trading assets to total interest income, multiplied by total
interest expense. Similarly, for interest and dividend income on
mortgage-backed securities, the interest expense term is equal
to the fraction of interest and dividend income on mortgagebacked securities to total interest income, multiplied by total
interest expense. These approximations are driven by the
assumption that interest expenses at a bank holding company
are divided proportionately across all interest income
activities. The remaining portion of interest expense is assigned
to the traditional category.
1. Traditional income sources:

(i) Net gains (losses) on sales of loans and leases
(j) Net gains (losses) on sales of other real estate owned
(k) Net gains (losses) on sales of other assets
(excluding securities)
(l) Realized gains (losses) on held-to-maturity
securities
(m) Realized gains (losses) on available-for-sale
securities
(n) Interest expense (excluding the amounts
assigned to securitization and nontraditional
income categories)

2. Securitization income sources:
(a) Net servicing fees
(b) Net securitization income
(c) Interest and dividend income on mortgage-backed
securities minus associated interest expense

(a) Interest and fee income on loans
(b) Income from lease financing receivables
(c) Interest income on balances due from depository
institutions
(d) Interest and dividend income on securities
(except for mortgage-backed securities)

(a) Trading revenue
(b) Investment banking, advisory, brokerage,
and underwriting fees and commissions
(c) Venture capital revenue

(e) Interest income from federal funds sold and
securities purchased under agreements to resell

(d) Insurance commissions and fees

(f) Other interest income

(e) Interest income from trading assets
minus associated interest expense

(g) Income from fiduciary activities
(h) Service charges on deposit accounts in
domestic offices

3. Nontraditional income sources:

Evolution and Heterogeneity

References

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Full text of Economic Policy Review (Federal Reserve Bank of New York) : Volume 18, Number 2 : Special Issue: The Evolution of Banks and Financial Intermediation

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