Banking Review 

2006 VOLUME 18, NO. 1 

Challenges to the Dual Banking System: 

The Funding of Bank Supervision (page 1) 

by Christine E. Blair and Rose M. Kushmeider 

As the powers of state-chartered and national banks have converged, the cost of supervision has 

assumed a greater importance in the competition between regulators for member institutions. This 

article examines the funding of bank supervision in the context of the dual banking system. 

Troubled Banks: Why Don’t They All Fail? (page 23) 

by Robert Oshinsky and Virginia Olin 

This article focuses on troubled banks to create a four-state model that predicts failure and three 

alternative outcomes to failure: recovery, merger, and continuation as a problem. The results show 

that the four-state model not only predicts failure, but also offers more information about the possible 

future states of problem banks than a two-state model can. 

The views expressed are those of the authors and do not necessarily reflect official positions of the Federal Deposit Insurance 

Corporation. Articles may be reprinted or abstracted if the FDIC Banking Review and author(s) are credited. Please provide the 

FDIC’s Division of Insurance and Research with a copy of any publications containing reprinted material. 

Acting Chairman Martin J. Gruenberg 

Director, Division of Insurance Arthur J. Murton 

and Research 

Deputy Director Donald Inscoe 

Managing Editor Jack Reidhill 

Editorial Committee Christine E. Blair 

Valentine V. Craig 

Rose M. Kushmeider 

Publication Manager Geri Bonebrake 

 

Challenges to the Dual Banking System: 

The Funding of Bank Supervision 

by Christine E. Blair and Rose M. Kushmeider* 

This article examines the funding of bank supervision in the context of the dual banking system. 

Since 1863, commercial banks in the United 

States have been able to choose to organize as 

national banks with a charter issued by the Office 

of the Comptroller of the Currency (OCC) or as 

state banks with a charter issued by a state government. The choice of charter determines 

which agency will supervise the bank: the primary 

supervisor of nationally chartered banks is the 

OCC, whereas state-chartered banks are supervised jointly by their state chartering authority 

and either the Federal Deposit Insurance Corporation (FDIC) or the Federal Reserve System 

(Federal Reserve).1 In their supervisory capacity, 

the FDIC and the Federal Reserve generally alternate examinations with the states. 

The choice of charter also determines a bank’s 

powers, capital requirements, and lending limits. 

Over time, however, the powers of state-chartered 

and national banks have generally converged, and 

the other differences between a state bank charter 

and a national bank charter have diminished as 

well. Two of the differences that remain are the 

lower supervisory costs enjoyed by state banks and 

the preemption of certain state laws enjoyed by 

national banks. The interplay between these two 

differences is the subject of this article. Specifically, we examine how suggestions for altering the 

way banks pay for supervision may have (unintended) consequences for the dual banking system. 

For banks of comparable asset size, operating with 

a national charter generally entails a greater 

supervisory cost than operating with a state charter. National banks pay a supervisory assessment 

to the OCC for their supervision. Although 

state-chartered banks pay an assessment for supervision to their chartering state, they are not 

charged for supervision by either the FDIC or the 

Federal Reserve. A substantial portion of the cost 

of supervising state-chartered banks is thus borne 

by the FDIC and the Federal Reserve. The FDIC 

derives its funding from the deposit insurance 

funds, and the Federal Reserve is funded through 

* The authors are senior financial economists in the Division of Insurance 

and Research at the Federal Deposit Insurance Corporation. This article 

reflects the views of the authors and not necessarily those of the Federal 

Deposit Insurance Corporation. The authors thank Sarah Kroeger and Allison 

Mulcahy for research assistance; Grace Kim for comments on an earlier draft; 

and Jack Reidhill, James Marino, and Robert DeYoung for comments and 

guidance in developing the paper. Any errors are those of the authors. 

Comments from readers are welcome. 

1 In addition, the Federal Reserve supervises the holding companies of commercial banks, and the FDIC has backup supervisory authority over all insured 

depository institutions. 

FDIC BANKING REVIEW 1 2006, VOLUME 18, NO. 1 
The Funding of Bank of Supervision 

the interest earned on the Treasury securities that 

it purchases with the reserves commercial banks 

are required to deposit with it. By contrast, the 

OCC relies almost entirely on supervisory assessments for its funding. 

The current funding system is a matter of concern 

because—with fewer characteristics distinguishing 

the national bank charter from a state bank charter—chartering authorities increasingly compete 

for member banks on the basis of supervisory costs 

and the ways in which those costs can be contained. Furthermore, two recent trends in the 

banking industry have been fueling the cost competition: increased consolidation and increased 

complexity. Consolidation has greatly reduced 

the number of banks, thereby reducing the funding available to the supervisory agencies, while 

the increased complexity of a small number of 

very large banking organizations has put burdens 

on examination staffs that may not be covered by 

assessments. Together, these three factors—the 

importance of cost in the decision about which 

charter to choose, the smaller number of banks, 

and the special burdens of examining large, complex organizations—have put regulators under 

financial pressures that may ultimately undermine 

the effectiveness of prudential supervision. Cost 

competition between chartering authorities could 

affect the ability to supervise insured institutions 

adequately and effectively and may ultimately 

affect the viability of the dual banking system. 

The concern about the long-term viability of the 

dual banking system derives from changes to the 

balance between banking powers and the costs of 

supervision. If the balance should too strongly 

favor one charter over the other, one of the charters might effectively disappear. Such a disappearance has already been prefigured by events in 

the thrift industry. 

The next section contains a brief history of the 

dual banking system and charter choice, explaining why the cost of supervision has become so 

important. Then we examine the mechanisms 

currently in place for funding bank supervision, 

and discuss the two structural changes in the 

banking industry that have fueled the regulatory 

competition. Next we draw on the experiences of 

the thrift industry to examine how changes in the 

balance between powers and the cost of supervision can influence the choice of charter type. 

Alternative means for funding bank supervision, 

and a concluding section, complete the article. 

A Brief History of the Dual Banking System 

and Charter Choice 

Aside from the short-lived exceptions of the First 

Bank of the United States and the Second Bank 

of the United States, bank chartering was solely a 

function of the states until 1863. Only in that 

year, with the passage of the National Currency 

Act, was a federal role in the banking system permanently established. The intent of the legislation was to assert federal control over the 

monetary system by creating a uniform national 

currency and a system of nationally chartered 

banks through which the federal government 

could conduct its business.2 To charter and supervise the national banks, the act created the Office 

of the Comptroller of the Currency (OCC). The 

act was refined in 1864 with passage of the 

National Bank Act. 

Once the OCC was created, anyone who was 

interested in establishing a commercial bank 

could choose either a federal or a state charter. 

The decision to choose one or the other was relatively clear-cut: the charter type dictated the laws 

under which the bank would operate and the 

agency that would act as the bank’s supervisor. 

National banks were regulated under a system of 

federal laws that set their capital, lending limits, 

and powers. Similarly, state-chartered banks 

operated under state laws. 

2 The new currency—U.S. bank notes, which had to be backed by Treasury 

securities—would trade at par in all U.S. markets. The new currency thus created demand for U.S. Treasuries and helped to fund the Civil War. At the 

time, it was widely believed that a system of national banks based on a 

national currency would supplant the system of state-chartered banks. 

Indeed, many state-chartered banks converted to a national charter after Congress placed a tax on their circulating notes in 1865. However, innovation 

on the part of state banks—the development of demand deposits to replace 

bank notes—halted their demise. See Hammond (1957), 718–34. 

2006, VOLUME 18, NO. 1 2 FDIC BANKING REVIEW 
The Funding of Bank Supervision 

When the Federal Reserve Act was passed in 

1913, national banks were compelled to become 

members of the Federal Reserve System; by contrast, state-chartered banks could choose whether 

to join. Becoming a member bank, however, 

meant becoming subject to both state and federal 

supervision. Accordingly, relatively few state 

banks chose to join. The two systems remained 

largely separate until passage of the Banking Act 

of 1933, which created the Federal Deposit Insurance Corporation. Under the act national banks 

were required to obtain deposit insurance; state 

banks could also obtain deposit insurance, and 

those that did became subject to regulation by the 

FDIC.3 The vast majority of banks obtained federal deposit insurance; thus, although banks continued to have their choice of charter, neither of 

the charters would relieve a bank of federal oversight. 

As noted above, over the years, the distinctions 

between the two systems greatly diminished. 

During the 1980s, differences in reserve requirements, lending limits, and capital requirements 

disappeared or narrowed. In 1980, the Depository 

Institutions Deregulation and Monetary Control 

Act gave the benefits of Federal Reserve membership to all commercial banks and made all subject 

to the Federal Reserve’s reserve requirements. In 

1982, the Garn–St Germain Act raised national 

bank lending limits, allowing these banks to compete better with state-chartered banks. Differences continued to erode in the remaining years 

of the decade, as federal supervisors instituted 

uniform capital requirements for banks. 

As these differences in their charters were diminishing, both the states and the OCC attempted to 

find new ways to enhance the attractiveness of 

their respective charters. The states have often 

permitted their banks to introduce new ideas and 

innovations, with the result these institutions 

have been able to experiment with relative ease. 

Many of the ideas thus introduced have been subsequently adopted by national banks. In the early 

years of the dual banking system, for example, 

state banks developed checkable deposits as an 

alternative to bank notes. Starting in the late 

1970s, a spate of innovations took root in statechartered banks: interest-bearing checking 

accounts, adjustable-rate mortgages, home equity 

loans, and automatic teller machines were introduced by state-chartered banks. During the 1980s 

the states took the lead in deregulating the activities of the banking industry. Many states permitted banks to engage in direct equity investment, 

securities underwriting and brokerage, real estate 

development, and insurance underwriting and 

agency.4 Further, interstate banking began with 

the development of regional compacts at the state 

level.5 At the federal level, the OCC expanded 

the powers in which national banks could engage 

that were considered “incidental to banking.” As 

a result, national banks expanded their insurance, 

securities and mutual fund activities. 

Then in 1991, the Federal Deposit Insurance Corporation Improvement Act (FDICIA) limited the 

investments and other activities of state banks to 

those permissible for national banks and the differences between the two bank charters again 

narrowed.6 In response, most states enacted wildcard statutes that allowed their banks to engage 

in all activities permitted national banks.7 

3 While most states subsequently required their banks to become federally 

insured, some states continued to charter banks without this requirement. 

Banks without federal deposit insurance continued to be supervised exclusively at the state level. After the savings and loan crises in Maryland and Ohio 

in the mid-1980s, when state-sponsored deposit insurance systems collapsed, 

federal deposit insurance became a requirement for all state-chartered banks. 

4 For a comparison of state banking powers beyond those considered traditional, see Saulsbury (1987). 

5 Beginning in the late 1970s and early 1980s, the states began permitting 

bank holding companies to own banks in two or more states. State laws governing multistate bank holding companies varied: some states acted individually, others required reciprocity with another state, and still others participated 

in reciprocal agreements or compacts that limited permissible out-of-state 

entrants to those from neighboring states. In 1994, Congress passed the 

Riegle-Neal Interstate Banking and Branching Efficiency Act, which removed 

most of the remaining state barriers to bank holding company expansion and 

authorized interstate branching. See Holland et al. (1996). 

6 As amended by FDICIA, Section 24 of the Federal Deposit Insurance Act (12 

U.S.C. 1831a) makes it unlawful, subject to certain exceptions, for an insured 

state bank to engage directly or indirectly through a subsidiary as principal in 

any activity not permissible for a national bank unless the FDIC determines 

that the activity will not pose a significant risk to the funds and the bank is 

in compliance with applicable capital standards. For example, the FDIC has 

approved the establishment of limited-liability bank subsidiaries to engage in 

real estate or insurance activities. 

7 For a discussion of the legislative and regulatory changes affecting banks 

during the 1980s and early 1990s, see FDIC (1997), 88–135. 

FDIC BANKING REVIEW 3 2006, VOLUME 18, NO. 1 
 

The Funding of Bank of Supervision 

Most recently, competition between the two charters for member institutions has led the OCC to 

assert its authority to preempt certain state laws 

that obstruct, limit, or condition the powers and 

activities of national banks. As a result, national 

banks have opportunities to engage in certain 

activities or business practices not allowable to 

state banks.8 The OCC is using this authority to 

ensure that national banks operating on an interstate basis are able to do so under one set of laws 

and regulations—those of the home state. In this 

regard, for banks operating on an interstate basis, 

the national bank charter offers an advantage 

since states do not have comparable preemption 

authority. (In theory, however, nothing prevents 

two or more states from harmonizing their banking regulations and laws so that state banks operating throughout these states would face only one 

set of rules.) Thus, the OCC’s preemption regulations reinforce the distinction between the 

national and state-bank charters that characterizes the dual banking system. 

Funding Bank Supervision 

The gradual lessening of the differences between 

the two charters has brought the disparities in the 

fees banks pay for supervision into the spotlight as 

bank regulators have come under increased fiscal 

pressure to fund their operations and remain 

attractive choices. How bank supervision is ultimately funded will have implications for the viability of the dual banking system. It has always 

been the case that most state bank regulators and 

the OCC are funded primarily by the institutions 

they supervise,9 but it used to be that differences 

in the fees paid by banks for regulatory supervision were secondary to the attributes of their 

charters. Now, however, the growing similarity of 

attributes has made the cost of supervision more 

important in the regulatory competition between 

states and the OCC to attract and retain member 

institutions. This competition has tempered regulators’ willingness to increase assessments and has 

left them searching for alternative sources of 

funding that will not induce banks to switch 

charters. The question for state bank regulators 

and the OCC, then, is how to fund their operations while remaining attractive charter choices 

in an era of fewer but larger banks. Here we summarize the funding mechanisms currently in 

place, and in a later section we discuss alternative 

means for funding bank supervision. 

The OCC’s Funding Mechanism 

In the mid-1990s, after charter changes by a number of national banks,10 the OCC began a concerted effort to reduce the cost of supervision, 

especially for the largest banks. The agency instituted a series of reductions in assessment fees and 

suspended an adjustment in its assessment schedule for inflation.11 When the inflation adjustment was reinstated in 2001, it was applied only 

to the first $20 billion of a bank’s assets. In 2002, 

the OCC revised its general assessment schedule 

and set a minimum assessment for the smallest 

banks. These changes reduced the cost of supervision for many larger banks, while increasing the 

cost for smaller banks—thus, making the assessment schedule even more regressive than previously. For example, national banks with assets of 

$2 million or less faced an assessment increase of 

at least 64 percent, while larger banks experienced smaller percentage increases or actual 

reductions in assessments. 

8 On January 7, 2004, the OCC issued two final regulations to clarify aspects 

of the national bank charter. The purpose cited was to enhance the ability 

of national banks to plan their activities with predictability and operate efficiently in today’s financial marketplace. The regulations address federal preemption of state law and the exclusive right of the OCC to supervise national 

banks. The first regulation concerns preemption, or the extent to which the 

federally granted powers of national banks are exempt from state laws. 

State laws that concern aspects of lending and deposit taking, including laws 

affecting licensing, terms of credit, permissible rates of interest, disclosure, 

abandoned and dormant accounts, checking accounts, and funds availability, 

are preempted under the regulation. The regulation also identifies types of 

state laws from which national banks are not exempt. A second regulation 

concerns the exclusive powers of the OCC under the National Bank Act to 

supervise the banking activities of national banks. It clarifies that state officials do not have any authority to examine or regulate national banks except 

when another federal law has authorized them to do so. See OCC (2004b, 

2004c). 

9 Although the OCC is a bureau of the U.S. Treasury Department, it does not 

receive any appropriated funds from Congress. 

10 For example, in 1994, 28 national banks chose to convert to a state bank 

charter; another 15 did so in 1995. See Whalen (2002). 

11 The OCC’s assessment regulation (12 C.F.R., Part 8) authorizes rate adjustments up to the amount of the increase in the Gross Domestic Product 

Implicit Price Deflator for the 12 months ending in June. 

2006, VOLUME 18, NO. 1 4 FDIC BANKING REVIEW 
The Funding of Bank Supervision 

The OCC charges national banks a semiannual 

fee on the basis of asset size, with some variation 

for other factors (see below). The semiannual fee 

is determined by the OCC’s general assessment 

schedule. As table 1 and figure 1 show, the marginal or effective assessment rate declines as the 

asset size of the bank increases. 

The marginal rates of the general assessment 

schedule are indexed for recent inflation, and a 

surcharge—designed to be revenue neutral—is 

placed on banks that require increased supervisory 

resources, ensuring that well-managed banks do 

not subsidize the higher costs of supervising lesshealthy institutions. The surcharge applies to 

national banks and federal branches and agencies 

of foreign banks that are rated 3, 4, or 5 under 

either the CAMELS or the ROCA rating 

system.12 For banking organizations with multiple national bank charters, the assessments 

charged to their non-lead national banks are 

reduced.13 In 2004, these general assessments 

provided approximately 99 percent of the agency’s 

funding.14 The remaining 1 percent was provided 

by interest earned on the agency’s investments 

and by licensing and other fees. As indicated in 

note 9, the OCC does not receive any appropriated funds from Congress. 

Table 1 

12 As part of the examination process, the supervisory agencies assign a confidential rating, called a CAMELS (Capital, Assets, Management, Earnings, Liquidity, and Sensitivity to market risk) rating, to each depository institution 

they regulate. The rating ranges from 1 to 5, with 1 being the best rating 

and 5 the worst. ROCA (Risk management, Operational controls, Compliance, 

and Asset quality) ratings are assigned to the U.S. branches, agencies, and 

commercial lending companies of foreign banking organizations and also 

range from 1 to 5. See Board et al. (2005). 

13 Non-lead banks receive a 12 percent reduction in fees in the OCC’s assessment schedule. See OCC (2003b). 

14 See OCC (2004a), 7. 

Figure 1 

Assessment Paid per $1 Million in Assets 

National Banks, January 2004 

Dollars 

3,000 

2,500 

2,000 

1,500 

1,000 

500 

0 

2 20 100 

Source: OCC (2003b). 

200 

Bank

1,000 

Asset S

2,000 

ize ($ Millions) 

6,000 20,000 40,000 100,000 

Note: These rates apply to lead national banks that are CAMELS/ROCA-rated 1 

or 2 (see footnote 12). 

OCC General Assessment Fee Schedule 

January 2004 

If total reported assets are The semiannual assessment is 

Over But not over 

($ million) ($ million) 

This amount Of excess over 

($) Plus ($ million) 

0 2 5,075 .000000000 0 

2 20 5,075 .000210603 2 

20 100 8,866 .000168481 20 

100 200 22,344 .000109512 100 

200 1,000 33,295 .000092663 200 

1,000 2,000 107,425 .000075816 1,000 

2,000 6,000 183,241 .000067393 2,000 

6,000 20,000 452,813 .000057343 6,000 

20,000 40,000 1,255,615 .000050403 20,000 

40,000 2,263,675 .000033005 40,000 

Source: OCC (2003b). 

Note: These rates apply to lead national banks that are CAMELS/ROCA-rated 1 or 2 (see footnote 12). 

FDIC BANKING REVIEW 5 2006, VOLUME 18, NO. 1 
1

The Funding of Bank of Supervision 

The States’ Funding Mechanisms 

The assessment structures used by the states to 

fund bank supervision vary considerably, although 

some features are common to most of them. Most 

states charge assessments against some measure of 

bank assets, and in many the assessment schedule 

is regressive, using a declining marginal rate. 

(See the appendix for several representative 

examples of state assessment schedules.) More 

than half of all states also impose an additional 

hourly examination fee. Only a few states link 

their assessments to bank risk—for example, by 

factoring CAMELS ratings into the assessment 

schedule.15 

To illustrate the differences in the supervisory 

assessment fees charged by the OCC and the 

states, we calculated approximate supervisory 

assessments for two hypothetical banks, one with 

$700 million in assets and one with $3.5 billion. 

We used assessment schedules for the OCC and 

four states—Arizona, Massachusetts, North Carolina, and South Dakota—whose assessment 

structures are representative of the different types 

of assessment schedules used by the states. Like 

the OCC, Arizona and North Carolina use a 

regressive assessment schedule and charge assessments against total bank assets; however, neither 

makes any adjustment based on bank risk. Arizona’s assessment schedule makes finer gradations 

Table 2 

at lower levels of asset size than does North Carolina’s schedule. Massachusetts uses a risk-based 

assessment schedule in which assessments are 

based on asset size and CAMELS rating. Banks 

are grouped as CAMELS 1 and 2, CAMELS 3, 

and CAMELS 4 and 5. Within each CAMELS 

group there is a regressive assessment schedule so 

that banks are charged an assessment based on 

total bank assets. South Dakota charges a flatrate assessment against total bank assets. 

The results are shown in table 2. As expected, 

the assessments for supervision paid by state-chartered banks are significantly less than those paid 

by comparably sized OCC-supervised banks. As 

noted above, a likely cause of this disparity is that 

the states share their supervisory responsibilities 

with federal regulatory agencies (that is, with the 

FDIC and the Federal Reserve) that do not 

charge for their supervisory examinations of statechartered banks. 

15 Among the states that rely primarily on hourly examination fees to cover 

their costs are Delaware and Hawaii. States relying on a flat-rate assessment 

include Maine, Nebraska, and South Dakota. Those using a risk-based assessment scheme include Iowa, Massachusetts, and Michigan. Those assessing 

on the basis of their expected costs include Colorado, Louisiana, and Minnesota. One state, Tennessee, explicitly limits its assessments to no more 

than the amount charged by the OCC for a comparable national bank. For a 

listing of assessment schedules and fees by state, see CSBS (2002), 45–63. 

Comparison of Annual Supervisory Assessment Fees 

OCC and Selected States, 2002 

$700 million bank $3.5 billion bank 

Difference Incidence 

in of 

Assessments Assessment 

(percent) Schedule 

Effective 

Asssessment 

per 

Assessment Thousand $ 

Effective 

Assessment 

per 

Assessment Thousand $ 

Arizona 

Massachusetts 

North Carolina 

South Dakota 

OCC 

$ 54,000 $.077 

52,000 .074 

62,500 .089 

35,000 .050 

159,000 .227 

$205,000 $.058 

227,000 .064 

177,500 .051 

175,000 .050 

569,000 .163 

+279% Regressive 

+336 Regressive 

+184 Regressive 

+400 Flat 

+257 Regressive 

Source: CSBS (2002) and OCC (2002). 

Note: The calculation of assessments for state-chartered banks is based on rate schedules provided by the states to CSBS. Where applicable, the 

assessment is calculated for a CAMELS 1- or 2-rated bank. 

2006, VOLUME 18, NO. 1 6 FDIC BANKING REVIEW 
The Funding of Bank Supervision 

The Effect on Regulatory Competition of 

Changes in the Banking Industry 

Cost competition between state regulators and 

the OCC, and among state regulators themselves, 

has been fueled by two important structural 

changes that have occurred in the banking industry over the past two decades. The number of 

bank charters has declined, largely because of 

increased bank merger and consolidation activity, 

and the size and complexity of banking organizations has increased. 

The first change—a decline in the number of 

charters—means that the OCC and state regulators are competing for a declining member base. 

As we have seen, the cost of supervision remains 

one of the few distinguishing features of charter 

type. In ways that we explain below, the declining member base puts an additional constraint on 

the regulators’ ability to raise assessment rates, 

even in the face of rising costs to themselves. 

The second important structural change of the 

past two decades—the increasing complexity of 

institutions—also complicates the funding issue, 

for it may impose added supervisory costs that are 

not reflected in the current assessment schedules. 

As explained in the previous section, the OCC 

and most states currently charge examination fees 

on the basis of an institution’s assets, but for a 

growing number of institutions, that assessment 

base does not reflect the operations of the bank. 

The Net Decline in the Number of 

Bank Charters 

The net decline in the number of banking charters since 1984 has resulted from two main factors. One is the lifting of legal restrictions on the 

geographic expansion of banking organizations—a 

lifting that provided incentive and opportunity 

for increased mergers and consolidation in the 

banking industry—and the other is the wave of 

bank failures that occurred during the banking 

crisis of the late 1980s and early 1990s.16 

Until the early 1980s, banking was largely a local 

business, reflecting the limits placed by the states 

on intra- and interstate branching. At year-end 

1977, 20 states allowed statewide branching, and 

the remaining 30 states placed limits on intrastate 

branching.17 However, as the benefits of geographic diversification became better understood, 

many states began to lift the legal constraints on 

branching. By mid-1986, 26 states allowed 

statewide branch banking, while only 9 restricted 

banks to a unit banking business. By 2002, only 4 

states placed any limits on branching.18 Interstate banking, which was just beginning in the 

early 1980s, generally required separately capitalized banks to be established within a holding 

company structure. Interstate branching was virtually nonexistent.19 

The passage of the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 

imposed a consistent set of standards for interstate 

banking and branching on a nationwide basis.20 

With the widespread lifting of the legal constraints on geographic expansion that followed, 

bank holding companies began to consolidate 

their operations into fewer banks. Bank acquisition activity also accelerated. 

Bank failures took a toll on the banking industry 

as well, reaching a peak that had not been seen 

since the Great Depression: from 1984 through 

1993, 1,380 banks failed.21 Mergers and acquisitions, however, remained the single largest contributor to the net decline in banking charters. 

Overall, the number of banks declined dramatically from 1984 through 2004, falling from 14,482 

to 7,630. At the same time, the average asset size 

of banks increased. (See table 3.) 

16 See FDIC (1997). 

17 Twelve of the 30 states permitted only unit banking, and the other 18 permitted only limited intrastate branching. See CSBS (1977), 95.
 

18 See CSBS (2002), 154. The four states were Iowa, Minnesota, Nebraska,
 

and New York.
 

19 By the early 1980s, 35 states had enacted legislation providing for regional
 

or national full-service interstate banking. Most regional laws were reciprocal,
 

restricting the right of entry to banking organizations from specified states.
 

See Saulsbury (1986), 1–17.
 

20 The act authorized interstate banking and branching for U.S. and foreign
 

banks to be effective by 1997. See FDIC (1997), 126.
 

21 See FDIC (2002a), 111.
 

FDIC BANKING REVIEW 7 2006, VOLUME 18, NO. 1 
%

%

%

%

The Funding of Bank of Supervision 

The rise in interstate banking, in particular, 

fueled competition both among state regulators 

and between state regulators and the OCC. 

Mergers of banks with different state charters 

caused the amount of bank assets supervised by 

some state regulators to decline, and the amount 

supervised by other state regulators to increase 

commensurately.22 Similarly, mergers between 

state-chartered and national banks caused assessment revenues and supervisory burden to shift 

between state regulators and the OCC. While 

the number of banks was thus declining, the average asset size of the banks was increasing. 

Because of the regressive nature of most assessment schedules, this resulted in a decline of 

assessment revenues per dollar of assets supervised. For bank holding companies, this provided 

an incentive to merge their disparate banking 

charters. For supervisors, mergers have proved 

more problematic. In general, the regressive 

nature of most assessment schedules suggests that 

regulators enjoy economies of scale in supervision. 

However, given the increased complexity of many 

large banks (discussed below), the existence of 

such economies is questionable.23 

A hypothetical example (taken from table 2) further highlights the effects of consolidation and 

merger activity on the regulatory agencies. All 

else equal (that is, holding constant the assessment schedules shown in table 2), changes in the 

Table 3 

structure of the industry over time have reduced 

the funding available to the supervisory agencies. 

Consider a bank holding company with five 

national banks, each with an average asset size of 

$700 million. The lead bank would pay an annual assessment to the OCC of $159,000, and each 

of the remaining banks would be assessed 

$139,920.24 The total for the five banks would be 

$718,680. But if these banks were to merge into 

one national bank with $3.5 billion in assets, the 

assessment owed the OCC would decline to 

$569,000—a saving to the bank of $149,680 in 

assessment fees for 2002. Similar results can be 

derived for each of the states in the table except 

South Dakota, which has a flat-rate assessment 

schedule. 

The Growth of Complex Banks 

During the 1990s, we have seen the emergence of 

what are termed large, complex banking organizations (LCBOs) and the growth of megabanks 

22 When banks merge, management must choose which bank charter to 

retain. That decision will determine the combined bank’s primary regulator.
 

23 The nature and amount of such scale economies in bank examination are
 

beyond the scope of this article to investigate.
 

24 This calculation reflects the 12 percent reduction in fees that non-lead
 

banks receive. See OCC (2003b).
 

Number and Average Assets of Commercial Banks 

by Charter, 1984–2004 

1984 1989 1994 1999 2004 

Percent 

Change change 

1984–2004 

Number of Banks 

National Charter 4,902 4,175 3,076 2,365 

State Charter 9,580 8,534 7,376 6,215 

Total 14,482 12,709 10,452 8,580 

Average Asset Size ($Millions) 

National Charter $305.6 $ 473.8 $ 733.9 $1,383.2 

State Charter 105.5 154.8 237.9 396.4 

All Banks 173.2 259.6 383.9 668.4 

1,906 

5,724 

7,630 

$2,938.9 

491.2 

1,102.6 

(2,996) (61)% 

(3,856) (40) 

(6,852) (47) 

$2,633.3 862% 

385.7 366 

929.4 537 

Source: FDIC Call Reports and FDIC (2002a). Figures not adjusted for inflation. 

2006, VOLUME 18, NO. 1 8 FDIC BANKING REVIEW 
The Funding of Bank Supervision 

owned by these organizations.25 In 1992, 90 

banks controlled one-half of industry assets; by 

the end of the decade, the number of banks that 

controlled one-half of industry assets had shrunk 

to 26, and at year-end 2004 to 13.26 These large 

banks engage in substantial off-balance-sheet 

activities and hold substantial off-balance-sheet 

assets. As a result, existing assessment schedules 

based solely on asset size have become less-accurate gauges of the amount of supervisory resources 

needed to examine and monitor them effectively. 

Because of their size, geographic span, business 

mix (including nontraditional activities), and 

ability to rapidly change their risk profile, megabanks require substantial supervisory oversight 

and therefore impose extensive new demands on 

bank regulators’ resources. In response, supervisors have created a continuous-time approach to 

LCBO supervision with dedicated on-site examiners—an approach that is substantially more 

resource-intensive than the traditional discrete 

approach of annual examinations used for most 

banks. 

For example, the OCC—through its dedicated 

examiner program—assigns a full-time team of 

examiners to each of the largest national banks 

(at year-end 2004, the 25 largest). In size, these 

teams of examiners range from just a few to 50, 

depending on the bank’s asset size and complexity. The teams are supplemented with specialists—such as derivatives experts and 

economists—who assist in targeted examinations 

of these institutions.27 

Like the trend toward greater consolidation of the 

industry, the trend toward greater complexity 

leads us to question the adequacy of the funding 

mechanism for bank supervision. The need for 

additional resources to supervise increasingly large 

and complex institutions, combined with the regulators’ limited ability to raise assessment rates 

given their concerns with cost competition, creates a potentially unstable environment for banking supervision. If regulatory competition on the 

basis of cost should yield insufficient funding, the 

quality of the examination process might suffer. 

To ensure the adequacy of the supervisory process, 

the potential for a funding problem must be 

addressed. In addressing this issue, however, the 

possibility for other unintended consequences 

must not be overlooked. In particular, solutions 

to the funding problem could bring into question 

the long-term survivability of the dual banking 

system. In the next section we look at a lesson 

from the thrift industry to illustrate this problem. 

Funding Supervision: Lessons from the 

Thrift Industry 

The history of the thrift industry shows how the 

choice of charter type can be influenced by 

changes in the tradeoff between the powers conferred by particular charters and the cost of bank 

supervision, and what that implies for the viability of the dual banking system. Like the commercial banking industry, the thrift industry also 

operates under a dual chartering system. States 

offer a savings and loan association (S&L) charter; some states also offer a savings bank charter. 

At the federal level, the Office of Thrift Supervision (OTS) offers both a federal S&L charter and 

25 LCBOs are domestic and foreign banking organizations with particularly 

complex operations, dynamic risk profiles and a large volume of assets. They 

typically have significant on- and off-balance-sheet risk exposures, offer a 

broad range of products and services at the domestic and international levels, are subject to multiple supervisors in the United States and abroad, and 

participate extensively in large-value payment and settlement systems. See 

Board (1999). The lead banks within such organizations form a class of 

banks termed megabanks. Like their holding companies, they are complex 

institutions with a large volume of assets—typically $100 billion or more. 

See, for example, Jones and Nguyen (2005). 

26 The 13 banks that held one-half of banking industry assets as of December 

2004 (according to the FDIC Call Reports) were JPMorgan Chase Bank, NA; 

Bank of America, NA; Citibank, NA; Wachovia Bank, NA; Wells Fargo Bank, 

NA; Fleet National Bank; U.S. Bank, NA; HSBC USA, NA; SunTrust Bank; The 

Bank of New York; State Street Bank and Trust Company; Chase Manhattan 

Bank USA, NA; and Keybank, NA. Of these, only three were state-chartered. 

27 After JPMorgan Chase converted from a state charter (New York) to a 

national charter (in November 2004), the OCC indicated it would increase its 

supervisory staff. The OCC is also emphasizing “horizontal” examinations, 

which use specialists to focus supervisory attention on specific business 

lines. See American Banker (2005). 

FDIC BANKING REVIEW 9 2006, VOLUME 18, NO. 1 
 

 

The Funding of Bank of Supervision 

a federal savings bank (FSB) charter.28 All statechartered thrifts are regulated and supervised by 

their state chartering authority and also by a 

federal agency—the OTS in the case of statechartered S&Ls, and the FDIC in the case of 

state-chartered savings banks.29 

The Thrift Industry to 1989 

Before the 1980s, S&Ls and savings banks operated under limited powers, largely because they 

served particular functions: facilitating home 

ownership and promoting savings, respectively.30 

In 1979, changes in monetary policy resulted in 

steep increases in interest rates, which in turn 

caused many S&Ls to face insolvency. The books 

of a typical S&L reflected a maturity mismatch— 

long-term assets (fixed-rate mortgage loans) funded by short-term liabilities (time and savings 

deposits). When interest rates spiked, these institutions faced the prospect of disintermediation: 

depositors moving their short-term savings 

deposits out of S&Ls and into higher-earning 

assets. In response, many S&Ls raised the rates 

on their short-term deposits above the rates they 

received on their long-term liabilities. The 

resultant drain on their capital, coupled with rising defaults on their loans, caused some institutions to become insolvent. 

In 1980 and again in 1982, Congress enacted legislation intended to resolve the unfolding S&L 

crisis, turning its attention to interest-rate deregulation and other regulatory changes designed to 

aid the suffering industry.31 For federally chartered thrifts, the requirements for net worth were 

lowered, ownership restrictions were liberalized, 

and powers were expanded. The Federal Home 

Loan Bank Board (FHLBB) subsequently extended many of these relaxed requirements to statechartered S&Ls by regulatory action.32 Congress 

also raised the coverage limit for federal deposit 

insurance from $40,000 to $100,000 per depositor 

per institution, and lifted interest-rate ceilings. 

In turn, many states passed legislation that provided similar deregulation for their thrifts.33 

Despite efforts to contain the thrift crisis throughout the 1980s, the failure rate for S&Ls reached 

unprecedented levels. Between 1984 and 1990, 

721 S&Ls failed—about one-fifth of the industry. 

At the end of the decade, with passage of the 

Financial Institutions Reform, Recovery, and 

Enforcement Act of 1989 (FIRREA), Congress 

and the administration finally found a resolution 

to the crisis. FIRREA authorized the use of taxpayer funds to resolve failed thrift institutions, 

and it significantly restructured the regulation of 

thrifts.34 Federal regulation and supervision of all 

S&Ls (both state- and federally chartered) and of 

federally chartered savings banks were removed 

from the FHLBS and placed under the newly created OTS.35 Federal regulation and supervision 

of state-chartered savings banks remained with 

the FDIC. 

28 Originally S&Ls were chartered to facilitate the home ownership of members
 

by pooling members’ savings and providing housing loans. Savings banks, by
 

contrast, were founded to promote the savings of their members; the institutions’ assets were restricted to high-quality bonds and, later, to blue-chip
 

stocks, mortgages, and other collateralized lending. Over time, distinctions
 

between S&Ls and savings banks largely disappeared. Additionally, an institution’s name may no longer be indicative of its charter type. 


29 Before 1990, federal savings institutions were regulated and supervised by
 

the Federal Home Loan Bank System (FHLBS), which was comprised of 12
 

regional Federal Home Loan Banks and the Federal Home Loan Bank Board
 

(FHLBB). The FHLBS was created by the Federal Home Loan Act of 1932 to
 

be a source of liquidity and low-cost financing for S&Ls. In 1933, the Home
 

Owners’ Loan Act empowered the FHLBS to charter and to regulate federal
 

S&Ls. Savings banks, by contrast, were solely chartered by the states until
 

1978, when the Financial Institutions Regulatory and Interest Rate Control Act
 

authorized the FHLBS to offer a federal savings bank charter. In 1989, the
 

Financial Institutions Reform, Recovery, and Enforcement Act abolished the
 

FHLBB and transferred the chartering and regulation of the thrift industry from
 

the FHLBS to the OTS. Additionally, the act abolished the thrift insurer, the
 

Federal Savings and Loan Insurance Corporation, and gave the FDIC permanent
 

authority to operate and manage the newly formed Savings Association Insurance Fund. Although the FHLBB was abolished, the Federal Home Loan Banks
 

remained—their duties directed to providing funding (termed advances) to the
 

thrift industry.
 

30 For example, thrifts were prohibited from offering demand deposits or making commercial loans—the domain of the commercial banking industry.
 

31 These pieces of legislation were respectively, the Depository Institutions
 

Deregulation and Monetary Control Act of 1980 and the Garn–St Germain Act
 

of 1982.
 

32 See FHLBB (1983), 13, and Kane (1989), 38–47.
 

33 FDIC (1997), 176. More generally, see FDIC (1997), 167–88 (chap. 4, “The
 

Savings and Loan Crisis and Its Relationship to Banking”).
 

34 For a discussion of FIRREA and the resolution of the S&L crisis, see ibid.,
 

100–110 and 186–88.
 

35 Ibid., 170–72.
 

2006, VOLUME 18, NO. 1 10 FDIC BANKING REVIEW 
 

The Funding of Bank Supervision 

FIRREA also imposed standards on thrifts that 

were at least as stringent as those for national 

banks. Such standards covered capital requirements, limits on loans to one borrower, and transactions with affiliates. Moreover, FIRREA placed 

limits on the activities of state-chartered thrifts, 

with the result that differences in the powers of 

state- and federally chartered thrift institutions 

largely disappeared. 

The Demise of the State-Chartered S&L 

FIRREA’s replacement of the FHLBS with the 

OTS as the regulator of state-chartered S&Ls at 

the federal level and the restrictions placed on 

those institutions’ powers were especially important in terms of the subject of this article. Like 

the OCC—but unlike the FHLBS—the OTS 

does not have an internally generated source of 

funding for its supervisory activities.36 The OTS 

funds itself by charging the institutions it supervises for their examinations.37 As a result, since 

1990 state-chartered S&Ls have faced a double 

supervisory assessment: they have been assessed 

both by their state chartering authority and, at 

the federal level, by the OTS. In contrast, a second set of thrifts—state-chartered savings banks 

(regulated by the FDIC at the federal level)— 

continue to pay supervisory assessments only to 

their state chartering authority. (As noted above, 

the FDIC does not charge for supervisory exams.) 

And a third set of thrifts—federally chartered 

thrifts (both S&Ls and FSBs)—are assessed only 

by the OTS. 

Figure 2 demonstrates that between 1984 and 

2004, the number of state-chartered savings institutions declined relative to the number of federally chartered institutions. In 1984, the industry 

was almost evenly split between the two chartering authorities, but by 2004, only 42 percent of 

the industry was state chartered. Further, the percentage of all savings institutions whose regulator 

at the federal level was the OTS or its predecessor 

(the FHLBS) also declined significantly—dropping from 92 percent in 1984 to 66 percent in 

2004. 

The trends in the composition of the savings 

industry are further depicted in figures 3 and 4. 

Figure 3 illustrates trends in charter type and federal regulator for all savings institutions for selected years from 1984 and 2004, and figure 4 depicts 

trends in the federal regulation specifically of 

state-chartered savings institutions.38 

36 Because the FHLBS had an internal source of funding (the Federal Savings 

and Loan Share Insurance Fund), it did not impose supervisory fees on either 

federally or state-chartered thrifts. 

37 The OTS, like the OCC, bases its fees on an institution’s asset size, and 

uses a regressive assessment schedule. Until January 1999, the OTS general 

assessment schedule based assessments on consolidated total assets. The 

assessments for troubled institutions were determined by a separate “premium” schedule. Both schedules were regressive: as asset size grew, the marginal assessment rate declined. In January 1999, the assessment system 

was revised and assessments were based on three components: asset size, 

condition, and complexity. Two schedules implemented the size component—a 

general schedule for all thrifts, and an alternative schedule for qualifying 

small savings associations. The condition component replaced the premium 

schedule; and the complexity component set rates for three types of activities—trust assets, loans serviced for others, and assets covered in full or in 

part by recourse obligations or direct credit substitutes. Rates were adjusted 

periodically for inflation, and other revisions were introduced. Effective July 

2004, the OTS implemented a new assessment regulation that revised how 

thrift organizations are assessed for their supervision. Examination fees for 

savings and loan holding companies were replaced with a semiannual assessment schedule, and the alternative schedule for small savings institutions was 

eliminated. The stated goal was to better align OTS fees with the costs of 

supervision. See OTS (1990, 1998, and 2004). 

38 In the following discussion and in the notation to figures 3, 4 and 6, we 

use “OTS-regulated” as a proxy for federal regulation that was conducted by 

the FHLBS for the years before 1990 and has been conducted by the OTS 

starting in1990. 

Figure 2 

Composition of Savings Institutions 

by Chartering Agent and Federal Regulator, 1984 and 2004 

1984 

Federally Chartered/ 

FHLBS-Regulated 

50% 

State Chartered/ 

FHLBS-Regulated 

42% 

State Chartered/ 

FDIC-Regulated 

8% 

2004 State Chartered/ 

OTS-Regulated 

Federally Chartered/ 

OTS-Regulated 

58% 

State Chartered/ 

FDIC-Regulated 

34% 

8% 

Source: FDIC Call Reports and OTS Thrift Financial Reports. 

FDIC BANKING REVIEW 11 2006, VOLUME 18, NO. 1 
The Funding of Bank of Supervision 

The shift in the composition of federally regulated state-chartered institutions is most noticeable 

between 1989 and 1994—the period since the 

inception of the OTS. During this period, the 

number of state-chartered/OTS-regulated S&Ls 

declined by approximately two-thirds, whereas 

the number of federally chartered/OTS-regulated 

savings institutions declined by only one quarter. 

At the same time, the number of state-chartered/ 

FDIC-regulated savings banks grew by almost 30 

percent. Since 1994, the number of state-chartered/OTS-regulated S&Ls has declined at almost 

double the rate of federally chartered/OTS-regulated savings institutions. In fact, state-chartered/OTS-regulated S&Ls have almost 

disappeared. At year-end 2004, only 104 such 

institutions remained—a decrease of 93 percent 

since 1984. 

Figure 4, focusing on the trends for state-chartered savings institutions alone, juxtaposes the 

growth in the number of state-chartered savings 

institutions regulated by the FDIC against the 

declining numbers of state-chartered savings institutions regulated by the OTS. 

Analysis of the Demise 

The demise of the state-chartered/OTS-regulated 

S&L was probably inevitable after the special 

Figure 3 

powers enjoyed by these institutions were eliminated, as their cost of supervision was higher than 

that of federally chartered S&Ls. In fact, the federal charter might have displaced the state charter to an even greater extent than that noted 

above if not for two important changes. First, 

numerous states began to offer a savings bank 

charter in the early 1990s. Second, FIRREA 

allowed all S&Ls to change their charter to either 

a savings bank or a commercial bank charter. 

(Institutions that changed their charter were 

required to remain insured by the Savings Association Insurance Fund [SAIF] and were designated 

as Sasser banks.)39 For S&Ls chartered in states 

that offered a savings bank charter, converting to 

that charter became a way to eliminate OTS 

supervision and the accompanying fees. In contrast to the demise of the state-chartered S&L, 

the population of state-chartered/FDIC-regulated 

savings banks increased substantially during the 

same period. Although their powers were also 

constrained by FIRREA, these institutions avoided supervisory costs at the federal level. 

Between 1989 and year-end 2004, 350 savings 

institutions took advantage of the Sasser option 

to become state-chartered savings banks, regulated by the FDIC but insured by the SAIF. Figure 5 

39 See FDIC (1997), 133, footnote 181. 

Figure 4 

Trends in Composition of Savings Institutions 

by Chartering Agent and Federal Regulator, 1984–2004 

Number of Institutions 

1,800 

1,659 Federally Chartered/OTS-Regulated 1,585 State-Chartered/OTS-Regulated

1,500 1,441 State-Chartered/FDIC-Regulated 

1,200 1,200 

1,019 929 900 781 

610 600 539 470 459 

337 300 268 

171 104 

0 

1984 1989 1994 1999 2004 

Source: FDIC Call Reports and OTS Thrift Financial Reports. 

Note: In 1984 and 1989 the FHLBS was the federal regulator of both federally 

chartered/OTS-regulated thrifts and state-chartered/OTS-regulated thrifts. 

Trends in the Federal Regulation of StateChartered Savings Institutions 

1984–2004 Number of Institutions 

2,500 

State-Chartered/FDIC-Regulated 2,000 

State-Chartered/OTS-Regulated 

1,500 

1,000 

500 

0 

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 

Source: FDIC Call Reports and OTS Thrift Financial Reports. 

Note: From 1984 through 1989 the FHLBS was the federal regulator of OTSregulated thrifts. 

2006, VOLUME 18, NO. 1 12 FDIC BANKING REVIEW 
 

The Funding of Bank Supervision 

depicts this increase. One reason for these charter changes could have been a desire to escape 

the reputational effects of being known as an 

S&L after the bankruptcy of the Federal Savings 

and Loan Insurance Corporation. However, in 

the years following that bankruptcy, many S&Ls 

were able to change their name—and leave 

behind the reputational problems associated with 

the term S&L—without having to change their 

charter. A more likely cause of the growth in 

Sasser banks was the elimination of special powers enjoyed by state-chartered institutions coupled 

with the extra assessment cost that they could no 

longer justify. 

Evidence on de novo thrifts also supports the 

belief that the double assessment coupled with 

the elimination of special powers played a role in 

the demise of state-chartered S&Ls. An analysis 

of the thrifts chartered after the passage of FIRREA shows that the majority were OTS charters 

(see figure 6). From 1989 through 2004, 34 institutions were chartered at the state level, and 33 

of them chose to become FDIC-regulated savings 

banks; only one chose to become an OTS-regulated S&L.40 By contrast, 147 institutions received 

OTS charters. Thus, 99.4 percent of thrifts chartered from 1989 to 2004 chose a charter that 

allowed them to avoid paying a double assessment. 

Figure 5 

These aggregate data have showed the importance of maintaining balance in the trade-off 

between powers and the cost of supervision in 

charter choice. The experiences of individual 

states show something more: the consequences for 

a dual chartering system when that balance disappears so that one charter becomes clearly favored 

over the other and there is no alternative. In 

California, for example, the imposition of a double assessment on state-chartered institutions and 

the absence of a state-chartered savings bank 

alternative have contributed to the demise of the 

state charter for thrifts. In 1984, 73 percent of 

California thrifts were state chartered; in 2004, 

there were no state-chartered thrifts. Conversely, 

the experience in Illinois illustrates that when 

there is an alternative, the state charter can 

remain a viable choice. In 1984, 44 percent of 

Illinois thrifts were state chartered, although no 

state savings bank charter was available. Following the enactment of FIRREA, Illinois created a 

state savings bank charter and institutions began 

to convert to Sasser banks. By 2004, the percentage of state-chartered thrifts had increased to 52 

percent, with state-chartered savings banks dominating the mix—accounting for 88 percent of 

state-chartered thrifts. 

40 This institution voluntarily liquidated and closed in June 2003. 

Figure 6 

Increase in the Number of Sasser StateChartered Savings Institutions 

1989–2004 

Number of Institutions 

300 

250 

200 

Total Number of Sasser Institutions 150 

Number of Institutions becoming 100 Sassers, by Year 

50 

0 

1989 1991 1993 1995 1997 1999 2001 2003 

Source: FDIC Call Reports and OTS Thrift Financial Reports. 

De Novo Savings Institutions 

1989–2004 

Number of Institutions 

30 

25 

20 

15 

OTS-Chartered/ State-Chartered/ State-Chartered/ 

OTS-Regulated OTS Regulated FDIC-Regulated 10 

5 

0 

1989 1991 1993 1995 1997 1999 2001 2003 

Source: FDIC Call Reports and OTS Thrift Financial Reports. 

FDIC BANKING REVIEW 13 2006, VOLUME 18, NO. 1 
 

The Funding of Bank of Supervision 

Charter Choice—Maintaining an Attractive 

Charter 

The narrowing of differences in state and national 

bank charters has both simplified the process of 

choosing a bank charter and focused greater 

attention on how to remain a viable charter 

choice. For bankers, charter choice is now generally a question of whether the higher assessment 

cost associated with a national charter is offset by 

the benefits of operating under a single set of laws 

and regulations—the OCC’s preemption authority. For bank regulators, charter choice entails 

working to contain the cost of supervision and 

finding alternative ways to make charters attractive. 

For the public, the competition between federal 

and state bank regulators to offer an attractive 

charter and the choices that banks ultimately 

make will affect them in a number of ways. Concerns will be raised about the dual banking system’s ability to generate adequate funding (and 

therefore whether there is an effective level of 

prudential supervision, especially in an era of larger and more complex banks). Concerns will also 

be raised about how consumer protection and 

other laws affected by preemption are applied and 

enforced. Ultimately, concerns will be raised 

about the long-term viability of the dual banking 

structure and whether such a system is still relevant.41 

Switching Charters—A State Responds 

The recent experience of New York shows the 

effects of the decision to switch charters on the 

chartering authorities. In July 2004, J. P. Morgan 

Chase & Co. and Bank One Corporation merged. 

The result was a combined company that had 

over one trillion dollars in assets, five banking 

charters (four national and one state), and operations in all 50 states. In November 2004, the 

charter of the lead bank, J. P. Morgan Chase Bank 

($967 billion in assets), was converted to a 

national bank charter. As a result, the State of 

New York Banking Department (NYBD) lost significant revenue from supervisory assessments. In 

addition, HSBC Holding PLC had converted the 

New York charter of its lead bank, HSBC Bank 

USA ($99 billion in assets), to a national charter 

in July 2004. Together, the assessment revenue 

from J. P. Morgan Chase Bank and HSBC Bank 

USA had accounted for approximately 30 percent 

of the NYBD’s operating budget.42 

Before the loss of these two banks, the NYBD had 

already been working to change its funding mechanism. An NYBD study had found that statechartered banks, which represented 10 percent of 

their state-licensed institutions, were carrying the 

department’s entire budget.43 The NYBD found 

it necessary to revise its assessment schedule and 

expand its assessment base. Effective with the 

2005 fiscal year, the assessment base was revised 

to include all licensed and regulated financial 

institutions. For the first time, financial institutions other than banks paid annual fees for supervision in addition to any exam and licensing fees. 

The NYBD is also considering revising its charter 

to make it more attractive to banks and thrifts. 

In an attempt to modernize, the NYBD proposed 

the adoption of a wild-card statute that would 

convey federal bank powers to banks chartered in 

New York.44 

Switching Charters—The OCC Responds 

Although J. P. Morgan Chase Bank and HSBC 

Bank USA indicated their preference for a 

national charter, the OCC did not fare as well in 

the mid-1990s. For example, when The Chase 

Manhattan Bank N. A. completed its merger with 

Chemical Bank in 1995, it chose to retain Chemical’s New York state charter. The loss of this 

large bank followed the loss of 28 banks under its 

41 In addition, concerns have been raised about the fairness of the current
 

funding mechanism (especially to the extent that national banks may be said
 

to subsidize state-chartered banks) and about the fairness of allowing national
 

banks to disregard state laws that affect their operations.
 

42 See State of New York Banking Department (NYBD) (2005), hereinafter,
 

NYBD (2005).
 

43 American Banker (2004). The New York Banking Department licenses and
 

regulates over 3,500 financial institutions, including foreign and domestic
 

banks, thrifts, mortgage brokers and bankers, check cashers, money transmitters, credit unions, and licensed lenders.
 

44 NYBD (2005).
 

2006, VOLUME 18, NO. 1 14 FDIC BANKING REVIEW 
The Funding of Bank Supervision 

charter in 1994. Beginning in 1995, the OCC 

instituted a series of reductions in assessment fees 

and suspended the inflation adjustment factor in 

its 1995 assessment schedule. It continued to 

lower total assessments in 1996, and then in 

1997, the OCC implemented a restructured 

assessment schedule to more accurately differentiate among banks and the resources they were 

likely to require in an examination. The number 

of national banks that switched charters declined 

after 1994, remaining at about 10 per year, until 

2001 when the number again jumped.45 

The conversion of J. P. Morgan Chase Bank to a 

national charter cited above also poses issues for 

the OCC. The charter switch brought additional 

assets under the OCC’s supervision, and subsequently increased the agency’s supervisory burden. 

The OCC indicated that additional supervisory 

resources would be focused on the risks posed by 

and across business lines. It planned to hire additional examiners and to increase its specialized 

supervisory skills in areas such as derivatives and 

mortgage banking—areas in which J. P. Morgan 

Chase Bank is highly active.46 Revenues from 

the assessments paid by the bank will offset these 

increases in supervisory costs. However, whether 

the revenues will be enough is problematic as a 

one-to-one relationship does not necessarily exist 

between costs and revenues in the assessment 

schedule. 

Approaches to Funding Bank Supervision 

Following the increase in the number of banks 

switching charters in 2001, then Comptroller of 

the Currency, John D. Hawke Jr., began a series of 

speeches calling for reform of the bank supervisory funding system. Arguing that the viability of 

the dual banking system should not rest on the 

maintenance of a federal subsidy for state-chartered banks, he proposed that a new approach to 

the funding of bank supervision be found.47 That 

new approach should “strengthen both the federal 

and state supervisory processes, protect them from 

the impact of random structural changes, and 

ensure that all supervisors, state and national, 

have adequate, predictable resources available to 

carry out effective supervisory programs.”48 

Passing the Cost through the Deposit 

Insurance Funds 

Specifically, Hawke argued that if the costs of 

bank supervision were passed through the deposit 

insurance funds (for example, if the interest 

earned on the deposit insurance funds were used 

to pay for all bank supervision), the subsidy provided to state-chartered banks at the expense of 

national banks could be eliminated and at the 

same time an adequate source of funding for bank 

supervision could be ensured.49 For this result to 

be achieved, all costs for bank supervision (costs 

of the states and the OCC) or some or all of the 

OCC’s supervisory costs would have to be covered. In either case, the federal subsidy (that is, 

the national-bank subsidy) to state-chartered 

banks for the cost of bank supervision would be 

eliminated. The effect on the dual banking system is less clear. Once the states and the OCC 

were no longer competing for member banks on 

the basis of cost, the state charter might become 

relatively less attractive. 

To discover the effects of funding total supervisory costs for the states and the OCC through the 

45 For a discussion of reasons behind charter switches see Whalen (2002)
 

and Rosen (2005).
 

46 American Banker (2005).
 

47 Because state-chartered banks do not pay for federal supervision whereas
 

nationally chartered banks do, it is argued that state-chartered banks are
 

effectively subsidized by nationally chartered banks through the assessments
 

that the latter pay to the deposit insurance funds. See Hawke (2000, 2001)
 

and Rhem (2004).
 

48 See Hawke (2001).
 

49 Work on this article was completed prior to passage of the Federal Deposit
 

Insurance Reform Act of 2005, which will merge the two deposit insurance
 

funds. A variation on the above proposal would have the FDIC rebate to
 

national banks—or through the OCC for pass-through to national banks—an
 

amount equal to its contribution to the cost of state-bank supervision.
 

Although the case can be made that nationally chartered banks have subsidized the FDIC’s supervision of state-chartered nonmember banks, it would be
 

difficult to calculate the precise size of that subsidy. An accurate accounting
 

of the share of the deposit insurance fund(s) attributable to national banks
 

would necessarily have to account for both premiums paid into the funds and
 

the relative expense to the funds of national bank failures.
 

FDIC BANKING REVIEW 15 2006, VOLUME 18, NO. 1 
The Funding of Bank of Supervision 

deposit insurance funds, we performed a sensitivity analysis of four large banks—two regulated by 

the OCC and two by the states—and an average 

community bank. The immediate effects would 

be twofold. First, the operating expenses of the 

FDIC would increase, which in turn would cause 

the reserve ratio—the ratio of the deposit insurance fund balance to estimated insured deposits— 

to be lower than it otherwise would be. Second, 

the assessment base for supervisory costs would be 

changed from assets to domestic deposits because 

deposit insurance premiums are assessed against 

domestic deposits. The incidence of the supervisory assessment would shift, falling more heavily 

on institutions funded primarily by domestic 

deposits. In other words, relying on the deposit 

insurance funds to cover the cost of bank supervision would change the basis on which supervision 

is paid and would therefore alter the allocation of 

cost among banks. 

First we calculated the asset-based fee paid by 

these banks for supervision in 2002 (the latest 

date for which state assessment data were available). For the average community bank, we calculated this cost for three chartering 

authorities—the OCC, Georgia, and North Carolina. For 2002, the supervisory costs of the 

states and the OCC totaled approximately $698 

million.50 

If the FDIC had paid the cost of supervision for 

the OCC and the states through the deposit 

insurance funds, the five banks would have borne 

the cost on the basis of their domestic deposits 

rather than assets. To understand the effect that 

changing the assessment base could have on individual banks, we assumed that the total cost of 

supervision ($698 million) would be passed on to 

the banks. Under this scenario, a flat-rate premium assessment of 1.9 basis points (bp)—or about 

2/100ths of a percent—of domestic deposits 

would be required.51 

As table 4 shows, the incidence of the supervisory 

assessment shifts toward banks that have relatively high domestic deposit-to-asset ratios. Bank of 

America would have owed approximately $23 

million more in assessments. By contrast, 

Citibank would have owed approximately $14 

million less. For the average community bank, 

the difference would depend on its charter. If the 

bank were chartered in Georgia, its assessment 

would have declined by approximately $3,000, 

but in North Carolina, its assessment would have 

risen by approximately $5,000. 

Although this approach would eliminate one 

inequity—the subsidization of state-chartered 

banks by nationally chartered banks—it would 

likely create others. First, assessment fees (and 

supervisory costs) vary considerably from state to 

state, and as a result, states with relatively high 

supervisory costs would benefit at the expense of 

states with lower supervisory costs. Second, funding supervision through the insurance funds 

would remove the incentives for the states and 

the OCC to keep their supervisory costs low. 

Third, the deposit insurance funds were designed 

for other purposes and therefore passing all supervisory costs through the funds would obscure the 

purpose of the funds. 

Other Approaches to Funding Bank 

Supervision 

Although Hawke’s approach focuses on funding 

bank supervision through the use of the deposit 

insurance funds, other approaches exist. One suggestion would be to fund bank supervision 

through the Federal Reserve, another would be to 

alternate examinations between the OCC and 

the other federal regulators, and a third approach 

would be to develop an assessment schedule for 

bank examination at the federal level. These 

approaches are briefly discussed below. 

50 The costs for the OCC represent supervisory and regulatory costs as reported for 2002. To obtain approximate supervisory and regulatory costs for the 

states, we computed from the OCC data an average cost per $1 million of 

assets and then applied that to the assets represented by state banks. See 

OCC (2003a). 

51 In this scenario, it is assumed that supervisory costs would be funded in 

the same manner as shortages in the deposit insurance funds are currently 

handled. That is, the costs of supervision would be funded through a flatrate assessment or surcharge that is levied against the assessable deposits— 

total (adjusted) domestic deposits—of each insured institution. The effect 

would be to replace the current regressive assessment system with a flat-rate 

assessment levied against domestic deposits. Modifications to this system 

could be made, if desired; however, in the interest of simplicity, we did not 

attempt to make any adjustments for bank risk or size. 

2006, VOLUME 18, NO. 1 16 FDIC BANKING REVIEW 
 

 

)

)

The Funding of Bank Supervision 

One alternative approach is to fund bank supervision through the Federal Reserve. Banks do not 

earn any interest on funds they hold in reserve 

accounts at the Federal Reserve, and policy makers (including the Federal Reserve itself) have 

long advocated that interest be paid on required 

reserve balances—sterile reserves. In this suggestion, in lieu of paying interest on sterile reserve 

balances, the Federal Reserve could dedicate that 

implicit interest to cover supervisory costs for all 

banks. All banks are required to hold the same 

percentage of reserves on their deposits, so the 

incidence of this proposal would be neither progressive nor regressive, although banks that were 

especially reliant on deposits would be hit the 

hardest. In effect, a portion of the surplus that 

the Federal Reserve currently transfers to the U.S. 

Treasury would be diverted to cover the costs of 

bank supervision. For the same reasons as enumerated above, this proposal would likely eliminate one inequity but create others. 

Another alternative is for the OCC and other 

federal bank regulators to rotate examination of 

nationally chartered banks, as is done with stateTable 4 

chartered banks. If this were done, state and 

national banks would be treated comparably, and 

the shared examination function would give the 

FDIC a better understanding of its risk exposure 

to national banks. A disadvantage, however, is 

that requiring multiple federal regulators to maintain the resources necessary to examine the same 

set of national banks would introduce inefficiencies to the supervisory process. And where the 

OCC uses a resident examination staff (as it currently does in 25 national banks), alternating 

exams with the FDIC (or the Federal Reserve) 

might be problematic. A second disadvantage is 

that the proposal does not resolve the cost competition between the OCC and the state bank 

chartering authorities. 

The last approach we discuss is for the FDIC and 

the Federal Reserve to assess state-chartered 

banks directly for the cost of their supervision. 

To do this, the FDIC and the Federal Reserve 

would have to unbundle the cost of supervision 

from the cost of their other activities. In the case 

of the FDIC, the assessment it imposes on financial institutions could be broken into a deposit 

Comparison of Bank Supervisory Costs 

Current Funding versus Funding by the Deposit Insurance Funds, June 2002 

Bank of SunTrust Average 

America Citibank Bank BB&T Community 

(OCC) (OCC) (GA) (NC) Banka 

Assets ($Millions) $562,116 $487,074 $105,158 $58,156 $139 

Domestic Deposits (DD) 

($Millions) $326,230 $103,347 $69,028 $33,082 $114 

DD/Assets 58% 21% 66% 57% 82% 

Annual Assessment Cost: OCC: $51,982 

Assets—rates set by GA: $24,819 

chartering authority $38,928,315 $33,974,793 $4,205,479 $1,982,180 NC: $16,680 

DD (1.9 bp) $61,983,700 $19,635,930 $13,115,320 $6,285,580 $21,660 

Incidence of Change in OCC: ($30,322) 

Funding Base $23,055,385 ($14,338,863) $8,909,841 $4,303,400 GA: ($3,159) 

NC: $4,980 

Percent change 59% (42%) 212% 217% OCC: (58%) 

GA: (13%) 

NC: 30% 

Source: Data on deposits and assets are from the FDIC Call Reports and FDIC (2002b). Supervisory assessment schedules are from OCC (2002) and 

CSBS (2002). The calculations are approximations that do not reflect all the nuances inherent in the respective assessment schedules. 

a "Average community bank" represents the weighted average of all banks with $1 billion or less in assets. 

FDIC BANKING REVIEW 17 2006, VOLUME 18, NO. 1 
The Funding of Bank of Supervision 

insurance component and a supervisory component. The deposit insurance component would 

be charged to all FDIC-insured institutions, and 

the supervisory component would be charged to 

institutions for which the FDIC is the primary 

federal regulator.52 Similarly, the Federal Reserve 

could charge state-chartered member banks for 

their cost of supervision. To implement this proposal, the federal regulators could develop separate assessment schedules for each of their 

agencies, or they could work together to establish 

a single, uniform assessment schedule. 

Proponents argue that the imposition of federal 

fees would end the federal subsidy of state-chartered banks. Opponents argue that the proposal 

would damage the dual banking system by eliminating one of its few remaining differences. Proposals to impose federal fees on state-chartered 

banks for their federal supervision have often 

been included in the annual federal budget 

process but Congress has routinely rejected them. 

Conclusion 

As the powers of state-chartered and national 

banks have converged, the number of reasons for 

a bank to choose either a state or a federal charter 

has declined. One of the few remaining differences between the charters is cost. In the competition between regulators for institutions, 

therefore, the cost of supervision has assumed 

greater importance, and in this area, state-chartered banks have the advantage. State-chartered 

banks generally pay lower exam fees, at least partly, because the federal agencies—FDIC or Federal 

Reserve—alternate examinations with the states 

and these federal agencies do not charge for 

exams. The OCC, and national banks, in contrast, must cover the full costs of bank examinations. 

The thrift experience demonstrates how the 

choice of charter type can be influenced by 

changes in the balance between powers and the 

cost of supervision. When differences in the powers of state- and federally chartered savings and 

loans disappeared, the proportion of S&Ls with 

state charters changed dramatically. Many converted from an S&L charter to a savings bank 

charter. In states where this was not an option, 

the number of state-chartered S&Ls declined dramatically, almost disappearing. 

Currently the higher supervisory assessments for 

national banks are offset by the preemption benefits that they enjoy. Conversely, state-chartered 

banks do not receive the benefits of preemption, 

but their supervisory costs are lower. As the situation is developing, the OCC is becoming the 

regulator of large, complex banks—banks that are 

likely to have an interstate presence and benefit 

from preemption. Smaller, more traditional banks 

continue to find the state charter attractive. 

Although both charters remain viable, a bifurcation within the dual banking system appears to be 

developing.53 If either of these components is 

materially changed, then banks—like state-chartered S&Ls —may be induced to switch charters. 

The result may be to undermine the dual banking 

system. 

Before any modification is made to the structure 

for funding bank supervision, a public-policy 

debate should be undertaken. Supervisors need a 

funding mechanism that reflects not only the 

costs they incur to supervise banks but also proves 

to be a stable source of funding in the long term. 

To this end, a number of proposals have addressed 

this issue. Each may provide a solution to the 

funding problem. However, given the few differences that remain between the bank charters, any 

change in the funding mechanism will affect the 

viability of the dual banking system. If the dual 

structure of the banking system still serves a purpose, then its disappearance should not be an 

unintended consequence. 

52 The FDIC engages in many activities currently included in its supervisory 

budget that are required for both its role as deposit insurer and its role as 

primary federal supervisor. The complete separation of these functions might 

be neither possible nor practical. 

53 See Jones and Nguyen (2005). 

2006, VOLUME 18, NO. 1 18 FDIC BANKING REVIEW 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The Funding of Bank Supervision 

REFERENCES
 

American Banker. 2004. N.Y. Banking Commissioner: Status Quo Doesn’t Work. July 13. 

———. 2005. How Addition of JPM Chase Is Changing the OCC. January 28. 

Benston, George J., Robert A. Eisenbeis, Paul M. Horvitz, Edward J. Kane, and George G. 

Kaufmann. 1986. Perspectives on Safe and Sound Banking: Past, Present and Future, A 

Study Commissioned by the American Bankers Association. MIT Press. 

Board of Governors of the Federal Reserve System (Board). 1999. Supervisory Letter SR 

99-15 (SUP) Risk-Focused Supervision of Large Complex Banking Organizations. 

June 23. Board. 

http://www.federalreserve.gov/boarddocs/SRLETTERS/1999/sr9915.htm [April 

2005]. 

Board of Governors of the Federal Reserve System, Federal Deposit Insurance Corporation, 

Office of the Comptroller of the Currency, and Office of Thrift Supervision. 2005. 

Press Release: Interagency Advisory on the Confidentiality of the Supervisory 

Rating and Other Nonpublic Supervisory Information. February 28. FDIC. 

http://www.fdic.gov/news/news/press/2005/pr1805a.html. 

Conference of State Bank Supervisors (CSBS). 1977. A Profile of State-Chartered Banking. 

CSBS. 

———. 2002. A Profile of State-Chartered Banking. CSBS. 

Federal Deposit Insurance Corporation (FDIC). 1997. History of the Eighties: Lessons for the 

Future. Vol. 1, An Examination of the Banking Crises of the 1980s and Early 1990s. 

FDIC. 

———. 2002a. Annual Report. FDIC. 

———. 2002b. Quarterly Banking Profile. Second Quarter. FDIC. 

Federal Home Loan Bank Board (FHLBB). 1983. Agenda for Reform, A Report on Deposit 

Insurance to the Congress from the Federal Home Loan Bank Board. FHLBB. 

Hammond, Bray. 1957. Banks and Politics in America: From the Revolution to the Civil War. 

Princeton University Press. 

Hawke, John D., Jr. 2000. Remarks on Deposit Insurance Reform and the Cost of Bank 

Supervision, Exchequer Club, Washington, D.C., December 20. 

http://www.occ.treas.gov/ftp/release/2000-104a.doc [April 13, 2005]. 

———. 2001. Remarks before the University of North Carolina School of Law Center for 

Banking and Finance. Charlotte, NC, April 5. 

http://www.occ.treas.gov/ftp/release/2001-35a.doc [April 13, 2005]. 

Holland, David, Don Inscoe, Ross Waldrop, and William Kuta. 1996. Interstate Banking— 

The Past, Present and Future. FDIC Banking Review 9, no. 1:1–17. 

Jones, Kenneth D., and Chau Nguyen. 2005. Increased Concentration in Banking: 

Megabanks and Their Implications for Deposit Insurance. Financial Markets, 

Institutions, and Instruments 14, no. 1 (February). 

Kane, Edward J. 1989. The S&L Mess: How Did It Happen? Urban Institute Press. 

FDIC BANKING REVIEW 19 2006, VOLUME 18, NO. 1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The Funding of Bank of Supervision 

Milner, Neil. 2002. Letter to the Honorable George W. Bush. January 11. 

http://www.csbs.org/government/regulatory/comment_ltrs/cl_01.11.01.htm. 

Office of the Comptroller of the Currency (OCC). 2002. Semiannual Assessment Return. 

OCC. 

———. 2003a. Annual Report. OCC. 

———. 2003b. OCC Bulletin 2003-45. OCC. 

———. 2004a. Annual Report. OCC. 

———. 2004b. Final Rule: Bank Activities and Operations. Federal Register 69, no. 

8:1895–1904. 

———. 2004c. Final Rule: Bank Activities and Operations; Real Estate Lending and 

Appraisals. Federal Register 69, no. 8:1904–17. 

Office of Thrift Supervision (OTS). 1990. Guidelines for Implementation of CFR Parts 502 

and 563d Pertaining to Assessments. Thrift Bulletin 48. September 6. OTS. 

––––––. 1998. Assessments and Fees under 12 CFR Part 502. Thrift Bulletin 48-15. 

November 30. OTS. 

––––––. 2004. Assessments and Fees, 12 CFR Part 502 Final Rule. Federal Register 69, no. 

104:30554–71. OTS. 

Rehm, Barbara. 2004. Parting Shot: ICBA Chief Takes Aim at Big Banks. American 

Banker, March 15. 

Rosen, Richard J. 2005. Switching Primary Federal Regulators: Is It Beneficial for U.S. 

Banks? Federal Reserve Bank of Chicago Economic Perspectives, 3rd Quarter. 

Saulsbury, Victor L. 1986. Interstate Banking—An Update. FDIC Regulatory Review (July): 

1–17. 

———. 1987. State Banking Powers: Where Are We Now? FDIC Regulatory Review 

(April/March): 1–16. 

State of New York Banking Department (NYBD). 2005. Superintendent Taylor’s Remarks 

to the New York Bankers Association: Revenue Restructuring and Future Plans, 

January 10. http://www.banking.state.ny.us/sp050110.htm [April 11, 2005]. 

Whalen, Gary. 2002. Charter Flips by National Banks. Economic and Policy Analysis 

Working Paper 2002-1 (June). OCC. 

2006, VOLUME 18, NO. 1 20 FDIC BANKING REVIEW 
 

 

 

The Funding of Bank Supervision 

APPENDIX
 

2002 Supervisory Assessment Schedules 


Arizona, Massachusetts, North Carolina and South Dakota
 

Arizona Assessment Fee Structure 

Annual assessment based on total assets as of June 30. 

If total reported assets are The assessment is 

Over But Not Over 

($ millions) ($ millions) 

This Of Excess Over 

Amount ($) Plus ($ millions) 

0 5 

5 20 

20 85 

85 200 

200 900 

900 2,000 

2,000 4,000 

4,000 6,000 

6,000 

2,322 

2,322 0.000144 5 

4,477 0.000113 20 

11,848 0.000079 85 

20,914 0.000067 200 

67,786 0.000056 900 

129,562 0.000050 2,000 

228,922 0.000044 4,000 

317,482 0.000039 6,000 

� The Arizona State Banking Department is an 

independent agency. 

� Examination fees and supervisory assessments 

are set by the commissioner and by statute. The 

commissioner determines how collected funds are 

allocated, appropriated, and spent. Assessments 

are levied annually. 

� Additional hourly fees: $60 per hour per examiner for trust exams. 

� Fee-sharing agreements: Permitted by the state; 

the Arizona State Banking Department has feesharing agreements with Alabama and North 

Dakota. 

� Agreements to share examiner resources: The 

state of Arizona permits such agreements. The 

Arizona State Banking Department currently has 

none in place. 

� Rebate authority: None. 

Source: CSBS (2002). 

Massachusetts Assessment Fee Structure 

The Division of Banking uses a risk-based assessment system 

in which assessments are based on assets and CAMELS rating. 

For banks The charge per 

with For assets $1000 is 

CAMELS Over But Less Than This Amount 

Rating ($ millions) ($ millions) ($) 

1 and 2 0 10 0.3000 

10 50 0.1000 

50 250 0.0850 

250 5,000 0.0625 

5,000 30,000 0.0500 

3 0 10 0.6000 

10 50 0.2000 

50 250 0.1700 

250 5,000 0.1250 

5,000 30,000 0.1000 

4 and 5 0 10 0.9000 

10 50 0.3000 

50 250 0.2550 

250 5,000 0.1875 

5,000 30,000 0.1500 

� Statute authorized the Executive Office of 

Administration and Finance to set examination 

fees and supervisory assessments. The Massachusetts Division of Banking has wide discretion over 

how collected funds are allocated, appropriated, 

and spent. 

� Additional hourly fees: A per diem fee of $220 

per examiner for nonbank licenses. 

� Fee-sharing agreements: Permitted by the state; 

the Massachusetts Division of Banking has none 

in place. 

� Agreements to share examiner resources: Permitted by the state; the Massachusetts Division of 

Banking has none in place. 

� Rebate authority: None. 

Source: CSBS (2002). 

FDIC BANKING REVIEW 21 2006, VOLUME 18, NO. 1 
 

The Funding of Bank of Supervision 

South Dakota Assessment Fee Structure 

Semiannual assessment of 2.5 cents per $1,000 of total assets; 

Nondepository banks pay an additional $500 semiannually. 

North Carolina Assessment Fee Structure 

Annual assessment based on asset size. 

For assets The assessment is 

Over But Less Than 

($ millions) ($ millions) 

This Amount 

($) 

0 50 

5 250 

250 500 

500 1,000 

1,000 10,000 

10,000 

6,000 

.00012 

.00009 

.00007 

.00005 

.00003 

� The North Carolina Commissioner of Banks 

operates under guidelines set by the Department 

of Commerce and by state policies. Examination 

fees and supervisory assessments are set by statute. 

Any discounts or premiums from the statutory 

rate must be approved by the Commission. The 

Commissioner of Banks also determines how collected funds are allocated, appropriated, and 

spent. 

� Additional hourly fees: None. 

� Fee-sharing agreements: Not permitted by the 

state. 

� Agreements to share examiner resources: Not 

permitted by the state. 

� Rebate authority: None. 

Source: CSBS (2002). 

� South Dakota Assessment Fee Structure 

� Semiannual assessment of 2.5 cents per $1,000 

of total assets; 

� Nondepository banks pay an additional $500 

semiannually. 

� Examination fees and supervisory assessments 

are set by the Banking Board and by statute. The 

Division of Banking’s total budget is appropriated 

by the South Dakota legislature. Expenditures are 

approved by the Director of Banking. Assessments are levied semiannually. 

� Additional hourly fees: None. 

� Fee-sharing agreements: Permitted by the state; 

agreements are in place with Minnesota and 

North Dakota. 

� Agreements to share examiner resources: Permitted by the state; agreements are in place with 

Minnesota and North Dakota. 

� Rebate authority: None. 

Source: CSBS (2002). 

2006, VOLUME 18, NO. 1 22 FDIC BANKING REVIEW 
Troubled Banks: Why Don’t They All Fail? 

by Robert Oshinsky and Virginia Olin* 

A wealth of literature examines the determinants 

of bank failures and of bank mergers or consolidations. Also numerous are studies that develop failure-prediction models and early-warning systems. 

But both groups of studies use samples of all banks, 

and therefore most of this research focuses on pairs 

of outcomes: failure versus nonfailure, merger versus consolidation,1 or problem bank versus nonproblem bank. But in reality, future status is more 

than a binary choice. 

Here we study only troubled banks—banks that 

receive a composite CAMELS rating of either 4 or 

5 when examined.2 A focus on troubled banks is 

valuable to the FDIC and bank researchers for four 

reasons. First, when a bank is troubled, failure is 

but one possible outcome; alternative outcomes are 

recovery, merger, or continuation as a problem. 

Second, between 1990 and 2002, 96 percent of all 

banks that failed had first been troubled banks. 

Including nonproblem banks would add bias 

towards non-failure as a possible outcome since a 

vast majority of nonproblem banks do not fail. 

Third, if the FDIC can better predict the number 

of troubled banks that will not fail, it will be better 

able to estimate the size of its contingent loss 

reserve.3 Finally, development of a multistate 

model identifying financial characteristics that 

contribute to recovery as well as to failure is 

important for the FDIC’s long-term strategic planning: accurate predictions of the future states of 

problem banks would affect the resources applied 

to these banks. 

* Robert Oshinsky is a Senior Financial Economist and Virginia Olin is a 

former Senior Financial Economist, Division of Insurance and Research, 

Federal Deposit Insurance Corporation (FDIC). The authors thank John O’Keefe 

for his overall guidance; Andrew Davenport for his counsel; and Jesse Weiher, 

Brian Lamm, James Marino, and the anonymous readers of the FDIC for their 

careful review of the article and their valuable comments and suggestions. 

The authors also thank Robert DeYoung for his suggestions. Of course, all 

mistakes are the responsibility of the authors. The views expressed here are 

those of the authors and not necessarily those of the FDIC. 

1 In previous studies, a merger is the absorption of a bank by a previously 

unrelated bank while consolidation is the absorption of a bank by a related 

bank. For purposes of this paper, we combine the two types of absorptions 

and refer to them as mergers. 

2 Because of the nature of the resolution process, we deliberately omit 

troubled thrifts, including those resolved by the Resolution Trust Corporation, 

which kept insolvent thrifts open during the resolution process. 

CAMELS is an acronym for the six components of the regulatory rating 

system: Capital adequacy, Asset quality, Management, Earnings, Liquidity, 

and (since 1998) market Sensitivity. Banks are rated from 1 (the best) to 5 

(the worst), and banks with a composite rating of 4 or 5 are considered 

problem banks. A rating of 4 generally indicates that the bank exhibits 

unsafe or unsound practices or is in an unsafe or unsound condition, while a 

rating of 5 means that the bank’s practices or condition are extremely unsafe 

or unsound. 

3 The mission of the FDIC is to protect depositors and promote the safety 

and soundness of insured depository institutions and the U.S. financial 

system by identifying, monitoring, and addressing risks to the deposit 

insurance funds. The FDIC’s Financial Risk Committee quantifies risks to the 

deposit insurance system for purposes of financial reporting and fund 

management, and each quarter it meets to set a contingent loss reserve 

estimated from total assets of banks that may fail within two years. 

FDIC BANKING REVIEW 23 2006, VOLUME 18, NO. 1 
Troubled Banks: oubled Banks: Why Don’t They All Fail? ’t They All Fail? 

As noted, troubled banks have four possible outcomes: recovery, merger, continuation as a problem, and failure. Knowing the future states of 

banks in our sample,4 we construct a financial profile using pre-examination data for the banks 

grouped by their future state and then use these 

profiles to develop a multinomial logit estimating 

procedure that predicts a bank’s likely future state. 

We show that a four-state model predicts failure at 

least as well as binary failure-prediction models 

and, in addition, provides predictive ability for 

three alternative future states. 

The next section describes previous empirical studies of bank failures, mergers, and financial distress. 

The three subsequent sections discuss the methodology we use, the sample and data, and the results. 

The concluding section gives a brief summary. 

Empirical Studies 

Most of the numerous studies that examine the 

determinants of bank failures and bank mergers 

and consolidations, like most of the numerous 

studies that develop early-warning systems predicting deterioration in banks’ financial condition, 

construct financial ratios based on information in 

the Consolidated Reports of Condition and 

Income (Call Reports) that banks file quarterly 

with the FDIC.5 The idea is to construct financial 

ratios that closely resemble the CAMELS rating 

system used by bank examiners and to use the 

ratios to predict pairs of outcomes: failure versus 

nonfailure, merger versus consolidation, or problem bank versus nonproblem bank.6 While the 

information used by examiners is preferable, it is 

not available without an examination, unlike Call 

Report data, which are readily available quarterly. 

Only a few studies have extended this research 

beyond pairs of outcomes. In an effort to improve 

predictive accuracy, DeYoung estimates the longrun probability of failure and acquisition in de 

novo banks by defining three states: failure, merger 

by acquisition, and conversion of a whole-bank 

affiliate of a bank holding company to a branch 

bank of that same bank holding company. 

Wheelock and Wilson use a competing-risks model 

to consider the joint determination of the probability of being acquired, failing, or surviving. Hannan and Rhoades predict that a bank may 

experience one of three outcomes: not be acquired, 

be acquired by a firm operating within the bank’s 

market, or be acquired by a firm operating outside 

the bank’s market.7 DeYoung expects that including the other two exit states (merger by acquisition, and conversion) will make the failure 

estimates more accurate. Wheelock and Wilson 

find that inefficiency increases the risk of failure 

while reducing the probability of a bank’s being 

acquired. And Hannan and Rhoades find that 

adding the third state (distinguishing between 

types of mergers) yields a number of firm and market characteristics that earlier studies did not yield 

and that significantly influence the likelihood of 

acquisition. 

Rarely in life are the possible outcomes binary. 

While studies that examine two-state outcomes 

have benefit, much is lost by not studying other 

possible outcomes. Further, by limiting our universe to only problem banks, we are able to 

remove the inherent bias towards the prediction of 

non-failure status. 

Methodology 

Referencing previous studies, we select certain 

financial variables proven in binary models to be 

useful in determining future bank state. In our 

multistate model we use univariate trend analysis 

to determine whether prior-period financial characteristics differ by future bank state. 

Specifically, in the existing literature on bank performance the reasons suggested for failure include 

4 Our sample consists of institutions assigned a CAMELS rating of 4 and 5
 

between 1990 and 2002. The sample is described in detail in a later
 

section of this article.
 

5 For reviews of the literature, see Demirgüç-Kunt (1989), Jagtiani et al.
 

(2003), and King et al. (2005).
 

6 See Whalen (1991), Cole and Gunther (1998), Kolari et al. (2002), and
 

Jagtiani et al. (2003).
 

7 DeYoung (2003), Wheelock and Wilson (2000), and Hannan and Rhoades
 

(1987).
 

2006, VOLUME 18, NO. 1 24 FDIC BANKING REVIEW 
(1)

Troubled Banks: Why Don’t They All Fail? 

low capital, risky asset portfolios, poor management, low earnings, and low liquidity. Thus, the 

financial variables we select are from those same 

broad categories: capital adequacy, asset quality, 

management, earnings, and liquidity. In addition, 

we run a one-way analysis of variance to examine 

the financial characteristics of recovered banks 

versus banks in the other three states (merged or 

acquired, remained a problem, and failed). 

We use a multinomial logistic estimating procedure 

to model future bank state. Outcomes are nominal, and therefore the multinomial logit model’s 

assumptions are the closest fit to the specification 

of the model being estimated. This model simultaneously estimates three binary logits for pairwise 

comparisons among the outcome categories to a 

reference outcome. These binary logits are (1) 

recover relative to failure, (2) merge relative to 

failure, and (3) remain a problem relative to failure. 

A general form of the model tested is shown in 

equation 1, where Probability of State (k)i,t is the 

probability that bank i will be in state k at time t. 

(1)	 Probability of State (k)i,t = 

F(Financial conditioni,t-1, Economic conditionst

) 

We gauge the model’s effectiveness in several ways. 

First, we compare the out-of-sample forecasting 

accuracy for each of the four states with the actual 

number of banks ending up in each state. We 

compare two competing binary models with the 

multistate model for failure predictions: one of the 

two competing models uses the same variables that 

our multistate model uses, and the other uses the 

same explanatory variables that Jarrow et al. use, 

referred to as the loss-distribution model.8 These 

two comparisons allow us to test whether including 

additional alternative states improves the accuracy 

of failure estimates over the accuracy of binary 

models. Second, we investigate the economic and 

statistical effect of our explanatory variables. 

Third, we check to determine that the banks with 

the highest predicted probability of failure from 

our model are the ones that actually fail. 

Sample and Data 

Our sample consists of 1,996 banks on the FDIC 

problem-bank list from 1990 through 2002. Each 

bank has at least one first event and second event 

that are paired as an observation. The first event 

occurs when a bank is examined and receives a 

CAMELS rating of 4 or 5. The second event 

occurs when the bank does one of the following: 

recovers (improves to a CAMELS rating of 1, 2, or 

3 at the next examination), merges (either merges 

with a bank outside of its multibank holding company or consolidates within its multibank holding 

company),9 remains a problem bank (continues to 

have a CAMELS rating of 4 or 5 at the next 

examination), or fails.10 We use only observations 

in which first events are paired with second events 

that occurred 6 to 24 months after the first events. 

Any second events sooner than 6 months or later 

than 24 months are ignored, and the observation is 

dropped from the sample. The reason for this 

restriction is twofold: first, we want to allow 

enough time to pass for changes in financial condition to occur; second, during most of our period, 

all banks except those with assets under $250 million and a composite CAMELS rating of 1 or 2 

were required by law to receive safety-and-soundness examinations annually.11 As noted above, a 

pairing of events is considered one observation in 

our sample. Our sample consists of 3,747 observations. 

To control implicitly for the effects of economic 

conditions and banking legislation, we divide these 

3,747 observations into annual cohorts corresponding to the year of the first event. But because 

second events usually occur in a different year from 

the first events, we recognize that using annual 

8 Jarrow et al. (2003).
 

9 We recognize that mergers and consolidations have different characteristics.
 

However, during the period we study, the number of consolidations is small
 

(39), so we combined both events into one state.
 

10 Here we define failure either as a closing that results from an action by a
 

regulator or as a merger assisted by the FDIC.
 

11 The frequency of examinations was set by the Federal Deposit Insurance
 

Corporation Improvement Act of 1991 (FDICIA). Further exceptions to the
 

requirement for annual safety-and-soundness exams are listed in the act.
 

FDIC BANKING REVIEW	 25 2006, VOLUME 18, NO. 1 
Troubled Banks: Why Don’t They All Fail? 

cohorts does not completely control for these 

effects. 

A bank appears as an observation in a cohort only 

once, and each observation belongs to only one 

cohort.12 All observations end with the occurrence of the second event. If the bank in a given 

cohort reaches the second event as recovered (or 

merged, or a continued problem), the outcome for 

the observation for that bank in the cohort is considered a recovery (or a merger, or continuation as 

a problem). 

The same bank can be an observation in multiple 

cohorts depending on when it first receives a 

CAMELS rating of 4 or 5 and on its outcome at 

the second event. If, at the second event, the 

bank upon reexamination continues as a problem 

bank, the first observation ends with an outcome 

of continuation as a problem bank, and concurrently a second observation for that bank begins 

and is paired with its corresponding subsequent 

event, which takes place 6 to 24 months later. At 

this subsequent event, an outcome is determined 

for that second observation. In contrast, when a 

bank’s first observation ends with a second event 

of recovery or merger, the bank has no concurrent 

second observation since it is no longer a problem 

bank. However, recovered banks may reemerge in 

our sample in a later cohort (for example, the bank 

recovers but later reverts to problem-bank status), 

whereupon the bank would be considered a new 

observation. Banks cannot appear in cohorts after 

they fail or merge. 

Our sample has the following characteristics: The 

number of problem banks declines drastically during the 1990s as the banking crisis that began in 

the mid-1980s and lasted through the early 1990s 

subsided. As figure 1 shows, the 1991 cohort has 

the highest number (897) and the 1997 cohort the 

lowest (62). Figure 2 shows that the 1990 and 

1998 cohorts have the highest percentage of problem banks that fail—5 percent—and that in the 

1997 and 2002 cohorts, no problem banks fail 

before the second event. Throughout the period 

most banks remain a problem at the second event: 

the range is from a high of 69 percent in the 1990 

cohort to a low of 40 percent in the 1997 cohort, 

with an average of 49 percent. The proportion 

that merge by the second event is small, ranging 

from 3 percent in the 1990 cohort to 20 percent in 

the 1998 cohort. The proportion that recover by 

the second event ranges from a low of 23 percent 

in the 1990 cohort to a high of 53 percent in the 

1997 cohort (figure 2). Moreover, for banks that 

recovered we found that large increases in internal 

capital injections (as a percentage of average 

assets) peaked in 1996. For those banks, external 

capital injections increased sharply from 1994 to 

1995 but did not peak until 1999 (figure 3).13 Figure 4 shows that most banks that remain a problem 

at the second event ultimately recover.14 

Using data from the Call Reports, we calculate 

beginning and ending event financial ratios for 

each bank. The beginning event ratios are calculated from the Call Report filed just before the first 

event and the one filed 12 months previously.15 

Balance-sheet items are averaged for the two 

reporting periods and taken as a ratio of average 

assets for the same two periods; income items are 

summed over the 12-month period and taken as a 

percentage of average assets for the two periods. 

Similar calculations are made for the ending event, 

using the Call Report filed immediately before the 

second event and the one filed 12 months previously. 

We group banks by future state to compare their 

condition and performance. We then compare 

data reported at the ending period with those 

reported at the beginning. We compute the percentage of banks in each state that showed an 

12 Technically a bank may appear as a second observation in the same cohort 

since the window for the second event is as short as six months. 

13 Jones and Critchfield (2004) note three reasons that might explain the 1997 

and 1998 peak years for merger activity and recoveries: (1) banks were highly 

profitable, liquid, and operating in favorable economic and interest-rate 

environments; (2) in 1994 the Riegle-Neal Interstate Banking and Branching 

Efficiency Act removed the remaining barriers to interstate banking and 

branching; and (3) a record-breaking bull market in stocks pushed market 

valuations of banks and thrifts to unprecedented levels, encouraging many 

banking firms to use their stock as currency to purchase other firms. 

14 The reason for the decline beginning in 2001 in the percentage of still-aproblem banks that ultimately recover is that enough follow-up events have 

not yet occurred. Most banks remain a problem beyond a second event. 

15 Gunther and Moore (2000) find atypical movements in Call Report data for 

the quarters in which banks are downgraded by examiners. These Call 

Reports are more subject to revisions. For that reason, we also did our 

univariate analysis on the Call Reports filed before the ones specified in this 

article. The resulting trends in data were similar to the trends reported here. 

2006, VOLUME 18, NO. 1 26 FDIC BANKING REVIEW 
Troubled Banks: Why Don’t They All Fail? 

Figure 1 Figure 3 

866 897 

713 

413 

194 

110 64 62 65 76 74 98 115 

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 0 

200 

400 

600 

800 

1000 

Number of Banks 

Number of Troubled Banks by Cohort 

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 0 

2 

4 

6 

Percent of Average Assets 

0 

20 

40 

60 

Percent of Banks that Recovered 

External Injections 

Internal Injections 

Note: 12 months before recovery. 

External and Internal Capital Injections in 

Troubled Banks That Recovered 

Figure 2 Figure 4 

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 0 

20 

40 

60 

80 

100 

Percent 

Fail Remain a Problem Merge Recover

Cohort Composition of Troubled Banks 

at Second Event 

595 

535 

359 

190 

87 52 32 25 27 36 35 47 57 

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 0 

200 

400 

600 

Number of Troubled Banks 

0 

20 

40 

60 

80 

100 

Percent of Banks that Recovered 

Number of Troubled Banks Percent that Ultimately Recovered 

Number of Troubled Banks That 

Remain a Problem and Ultimately Recover 

increase between the two periods for each of the 

financial ratios. Assuming that banks that recover 

are able to improve net income and net noninterest income more than those that fail, we expect to 

see that the percentages of banks with increases in 

such ratios will be greater for banks having a future 

state of recovery than for banks with a future state 

of failure. For expense items, we expect the opposite. Assuming that banks that recover shed nonperforming and past-due assets, we expect that the 

percentages of banks with increases in such assets 

will be less for banks that recover than for those 

that fail. We expect that the percentages of banks 

with increases in volatile liabilities and illiquid 

assets will be smaller for banks having a future 

state of recovery than for banks with a future state 

of failure and that the percentages of banks with 

increases in capital will be larger for banks that 

recover than for those that fail. For the various 

financial ratios, we have no expectations for the 

ranking of banks that merge or are still a problem 

except that their increases or decreases will fall 

between the levels for banks that recover and 

banks that fail. 

For measures of earnings, we compare the percentage of banks in each state that showed increases in 

net interest income, in net noninterest income, 

and in provision for loan losses. For measures of 

risky asset portfolios, we compare the percentage of 

banks in each state that showed increases in average allowance for loan and lease losses, average 

loans and leases past due 30–89 days, average loans 

and leases past due 90 days or more, average 

FDIC BANKING REVIEW 27 2006, VOLUME 18, NO. 1 
 

 

 

Troubled Banks: oubled Banks: Why Don’t They All Fail? ’t They All Fail? 

nonaccrual loans and leases, and average other real 

estate owned. For measures of capital adequacy we 

compare the percentage that showed average riskbased capital and average tangible equity capital; 

for measures of liquidity, the percentage that 

showed average volatile liabilities and loans and 

securities with maturities greater than or equal to 

five years. And for the management measure, we 

use the efficiency ratio (noninterest expense as a 

percentage of net interest income plus noninterest 

income). A lower efficiency ratio is better. 

To model future bank states, we selected almost 

the same financial variables that we used in the 

univariate trend analysis.16 For measures of the 

economy, we added capital injections from a bank 

holding company and capital injections from outside.17 From the univariate trend analysis we are 

able to form expectations about the sign that coefficients on these variables will take when they are 

estimated by logit analysis. A negative coefficient 

implies that an increase in the variable will result 

in the future state’s becoming less likely relative to 

failure. A positive coefficient implies the opposite. 

Table 1 shows the expected sign of explanatory 

variables used in the multistate model. The financial ratios associated with not failing are capital, 

capital injections, allowance for loan losses, interest income, noninterest income, and longer-term 

assets (assets and securities with maturities equal to 

or great than five years). Although we expect a 

negative sign for the efficiency ratio’s coefficient 

(because lower is better), we associate this ratio, 

too, with not failing. The financial ratios associated with failure are those measuring poor asset quality (past-due loans, nonaccruing loans, and real 

estate owned), expense items (interest expense, 

loss provision, loan charge-offs, salaries, expenses 

on premises, and other noninterest expense), and 

volatile liquidity as measured by volatile 

liabilities.18 

Results 

Our results from both the univariate trend analysis 

and the multistate logit estimating procedure generally agree with expectations. Of banks that 

recover, the percentage with increases (between 

the beginning and ending periods) in performance 

ratios such as net income and net noninterest 

income is greater than the percentage of banks in 

any alternative state. For loan-loss provisions, the 

opposite occurs. In addition, the percentage of 

banks that have increases in any of the risky asset 

measures is smaller for banks that recover than for 

banks in any alternative state. These results can 

be seen graphically in the appendix. 

16 For the logits we used total income and detailed expense items instead of 

net interest and net noninterest income as used in the univariate analysis. In 

addition, we also estimated the model using Call Report data from the quarter 

before the quarter that precedes the examination, as in the univariate. The 

results differed little from those reported here. 

17 As pointed out in footnote 13, the economy (a record-breaking bull market) 

was one reason noted for increased acquisitions. 

18 Volatile liabilities are defined in the FDIC data dictionary as (1) federal 

funds purchased and sold under agreements to repurchase, (2) demand notes 

issued to the U.S. Treasury and other borrowed money, (3) time deposits over 

$100,000 held in domestic offices, (4) foreign-office deposits, (5) trading 

liabilities less trading liabilities’ revaluation losses on interest rate, (6) foreign 

exchange rate, and (7) other commodity and equity contracts. 

Table 1 

Explanatory Variables and Expected 

Signs for Predicting Nonfailure 

versus Failure States 

Variable Sign 

Capital 

Tangible Equity Capital + 

Capital Injections: 

From BHC + 

Outside + 

Asset Quality 

Past-Due Loans (30–89 days) – 

Past-Due Loans (90+ days) – 

Nonaccrual Loans and Leases – 

Other Real Estate Owned – 

Allowance for Loan Loss + 

Management 

Efficiency Ratio – 

Earnings 

Total Interest Income + 

Total Noninterest income + 

Total Interest Expense – 

Loan-Loss Provision – 

Loan Charge-offs – 

Expenses on Premises – 

Salaries – 

Other noninterest expense – 

Liquidity 

Volatile Liabilities – 

Loans + Securities > Five Years + 

2006, VOLUME 18, NO. 1 28 FDIC BANKING REVIEW 
 

 

 

Troubled Banks: Why Don’t They All Fail? 

In the logit analysis, we find that 

increases in financial ratios associated with nonfailure have positive 

coefficients, and increases in financial ratios associated with failure 

have negative coefficients. 

Analysis of Variance 

Results from the analysis of variance, reported in tables 2 and 3, 

complement the results of the univariate trend analysis. Both tables 

use the beginning-period data. 

Table 2 shows the mean and standard errors for financial variables 

in each of the four states. Table 3 

shows the differences in means and 

statistical significances for six pairings: (1) recover versus merge, (2) 

recover versus remain a problem, 

(3) recover versus fail, (4) remain 

a problem versus merge, (5) 

remain a problem versus fail, and 

(6) merge versus fail. 

The results reported in table 2 

show that at the first event, the 

mean value for each financial variable is statistically different from 

zero. The results also show that 

the mean values in financial ratios 

associated with not failing are generally larger for banks that recover, 

merge, or remain a problem than 

for banks that fail. The opposite is 

true for the mean values in financial ratios associated with failing. 

There are three exceptions, however: the mean values for total 

interest income, total noninterest 

income, and loans and securities 

with maturities greater than or 

equal to five years are largest for 

banks that fail. These results seem 

counterintuitive until we consider 

that banks with a future state of 

Table 2 

Mean and Standard Errors for Financial Variables, by State 

(Standard Errors in Parentheses) 

Remain a 

Variable Recover Merge Problem Fail 

Number of Banks 1,326 228 2,077 116 

Capital 

Tangible Equity Capital 6.68 *** 6.57 *** 6.39 *** 3.90 *** 

(0.08) (0.20) (0.07) (0.29) 

Capital Injections: 

From BHC 0.19 *** 0.41 *** 0.20 *** 0.14 * 

(0.02) (0.06) (0.02) (0.08) 

Outside 0.36 *** 0.29 *** 0.29 *** 0.42 *** 

(0.04) (0.09) (0.03) (0.13) 

Asset Quality 

Past-Due Loans (30–89 days) 1.88 *** 2.12 *** 2.43 *** 3.08 *** 

(0.04) (0.10) (0.03) (0.14) 

Past-Due Loans (90+ days) 0.59 *** 0.65 *** 0.92 *** 1.17 *** 

(0.04) (0.09) (0.03) (0.13) 

Nonaccrual Loans and Leases 2.17 *** 2.56 *** 2.64 *** 3.82 *** 

(0.06) (0.14) (0.05) (0.20) 

Other Real Estate Owned 2.00 *** 1.88 *** 2.60 *** 3.19 

(0.07) (0.17) (0.06) (0.23)*** 

Allowance for Loan Loss 1.69 *** 1.97 *** 1.72 *** 2.11 *** 

(0.03) (0.07) (0.02) (0.10) 

Management 

Efficiency Ratio 88.32 *** 94.15 *** 94.43 *** 115.77 *** 

(0.67) (1.62) (0.54) (2.28) 

Earnings 

Total Interest Income 8.80 *** 8.99 *** 9.59 *** 10.58 *** 

(0.09) (0.21) (0.07) (0.29) 

Total Noninterest income 1.41 *** 1.44 *** 1.45 *** 1.98 *** 

(0.06) (0.15) (0.05) (0.21) 

Total Interest Expense 4.47 *** 4.51 *** 5.27 *** 6.51 *** 

(0.06) (0.14) (0.05) (0.20) 

Loan-Loss Provision 1.35 *** 2.23 *** 1.81 *** 3.21 *** 

(0.07) (0.16) (0.05) (0.22) 

Loan Charge-offs 1.46 *** 1.78 *** 1.80 *** 2.86 *** 

(0.05) (0.12) (0.04) (0.17) 

Expenses on Premises 0.68 *** 0.75 *** 0.77 *** 0.96 *** 

(0.01) (0.03) (0.01) (0.04) 

Salaries 2.06 *** 2.08 *** 2.18 *** 2.56 *** 

(0.03) (0.08) (0.03) (0.11) 

Other noninterest expense 2.23 *** 2.54 *** 2.43 *** 3.29 *** 

(0.05) (0.11) (0.04) (0.16) 

Liquidity 

Volatile Liabilities 13.26 *** 13.62 *** 14.96 *** 15.04 *** 

(0.27) (0.65) (0.22) (0.91) 

Loans + Securities > Five Years 66.13 *** 68.11 *** 68.71 *** 68.04 *** 

(0.31) (0.76) (0.25) (1.06) 

Significance at 1%, 5% and 10% levels ar eindicated by ***, **, and * asterisks, respectively. 

FDIC BANKING REVIEW 29 2006, VOLUME 18, NO. 1 
 

Troubled Banks: Why Don’t They All Fail? 

Table 3 

Differences in Means and Standard Errors of Financial Variables for Selected Pairs 

(Standard Errors in Parentheses) 

Recover- Merge Remain a 

Recover Remain a Recover- Remain a Problem Merge 

Variable Merge Problem Fail Problem Fail Fail 

Capital 

Tangible Equity Capital 0.10 0.29 ** 2.78 *** 0.19 2.49 *** 2.68 *** 

(0.22) (0.11) (0.30) (0.22) (0.29) (0.35) 

Capital Injections: 

From BHC -0.22 *** (0.01) 0.04 0.21 *** 0.05 0.26 ** 

(0.06) (0.03) (0.08) (0.06) (0.08) (0.10) 

Outside 0.07 0.08 (0.06) 0.00 -0.14 -0.13 

(0.10) (0.05) (0.13) (0.10) (0.13) (0.16) 

Asset Quality 

Past-Due Loans (30–89 days) -0.24 ** -0.55 *** -1.20 *** -0.31 ** -0.65 *** -0.96 *** 

(0.11) (0.05) (0.15) (0.11) (0.15) (0.18) 

Past-Due Loans (90+ days) -0.06 -0.33 *** -0.58 *** -0.27 ** -0.25 * -0.52 *** 

(0.10) (0.05) (0.13) (0.10) (0.13) (0.16) 

Nonaccrual Loans and Leases -0.39 ** -0.47 *** -1.65 *** -0.09 -1.18 *** -1.27 *** 

(0.15) (0.07) (0.20) (0.15) (0.20) (0.24) 

Other Real Estate Owned 0.12 -0.59 *** -1.19 *** -0.72 *** -0.59 ** -1.31 *** 

(0.18) (0.09) (0.24) (0.18) (0.24) (0.29) 

Allowance for Loan Loss -0.29 *** -0.04 -0.42 *** 0.25 ** -0.38 *** -0.13 

(0.08) (0.04) (0.11) (0.08) (0.11) (0.13) 

Management 

Efficiency Ratio -5.83 *** -6.10 *** -27.44 *** -0.28 -21.34 *** -21.62 *** 

(1.76) (0.86) (2.37) (1.71) (2.34) (2.79) 

Earnings 

Total Interest Income -0.19 -0.79 *** -1.78 *** -0.60 ** -0.99 *** -1.59 *** 

(0.22) (0.11) (0.30) (0.22) (0.30) (0.36) 

Total Noninterest income -0.03 -0.04 -0.57 ** -0.01 -0.53 ** -0.54 ** 

(0.17) (0.08) (0.22) (0.16) (0.22) (0.26) 

Total Interest Expense -0.03 -0.79 *** -2.03 *** -0.76 *** -1.24 *** -2.00 *** 

(0.15) (0.07) (0.21) (0.15) (0.20) (0.24) 

Loan-Loss Provision -0.88 *** -0.46 *** -1.85 *** 0.42 ** -1.40 *** -0.97 *** 

(0.17) (0.08) (0.23) (0.17) (0.23) (0.27) 

Loan Charge-offs -0.32 ** -0.33 *** -1.39 *** -0.02 -1.06 *** -1.08 *** 

(0.13) (0.07) (0.18) (0.13) (0.18) (0.21) 

Expenses on Premises -0.07 ** -0.09 *** -0.28 *** -0.02 -0.19 *** -0.21 *** 

(0.03) (0.02) (0.04) (0.03) (0.04) (0.05) 

Salaries -0.03 -0.12 ** -0.50 *** -0.09 -0.38 *** -0.48 *** 

(0.08) (0.04) (0.11) (0.08) (0.11) (0.13) 

Other non-interest expenses -0.30 ** -0.20 *** -1.06 *** 0.11 -0.86 *** -0.76 *** 

(0.12) (0.06) (0.16) (0.12) (0.16) (0.19) 

Liquidity 

Volatile Liabilities -0.36 -1.70 *** -1.78 * -1.34 * -0.09 -1.43 

(0.70) (0.35) (0.95) (0.69) (0.94) (1.12) 

Loans + Securities > Five Years -1.98 ** -2.57 *** -1.91 * -0.60 0.66 0.07 

(0.82) (0.40) (1.11) (0.80) (1.09) (1.31) 

Significance at 1%, 5% and 10% levels ar eindicated by ***, **, and * asterisks, respectively. 

2006, VOLUME 18, NO. 1 30 FDIC BANKING REVIEW 
 

 

(2)

Troubled Banks: Why Don’t They All Fail? 

fail probably take on riskier assets that will have 

higher yields than banks with one of the alternative future states. Or, turning the statement 

around, we can say that banks with riskier assets 

have a higher probability of failure. Fee income 

from these riskier assets may have resulted in higher noninterest income. And in banks with a future 

state of fail, the ratio between loans and securities 

in the longer-term assets may be geared toward 

loans that are usually considered riskier than moreliquid securities. 

The results reported in table 3 show that except 

for two variables (capital injections from the bank 

holding company and from outside), the difference 

in means between banks that recover and those 

that fail is statistically significant. Also significant 

for most variables are the differences in means 

between banks that fail and both banks that merge 

and banks that remain a problem. 

The results from table 3 indicate as well that the 

differences in means between banks that remain a 

problem and both banks that merge and banks 

that recover are statistically significant. For the 

recovery-versus-merger pairing, fewer variables are 

statistically different from one another. And for 

the pairing remain-a-problem versus merge, even 

fewer variables are statistically different from one 

another. 

Logit Analysis 

For our multivariate analysis, we rely on a multinomial unordered logit probability model that takes 

into account all four future bank states. Equation 

2 shows the model tested: 

(2)	 Probability of State (k)i,t = 

F(Financial conditioni,t-1) 

For a number of reasons, we did not include variables for economic condition in our model. First, 

Nuxoll et al. found that state and local economic 

data did not contribute to the performance of standard off-site models.19 Second, much of the literature theorizes that the economy is subsumed in the 

balance sheet, so any effect of the economy will 

already have shown up in the financial data.20 

Finally, we included capital injections as a proxy 

for changes in the economy (see footnote 13). 

We used a stepwise logit estimation procedure to 

identify the terms that have a significant relationship in predicting the likelihood that a bank will 

end up in one of the four states. The stepwise estimation procedure allows us to include several 

measures of the same attribute in the logit model, 

yet isolates the most important factors in terms of 

predicting future bank state. 

Table 4 shows summary statistics for the variables 

used in the logistic regressions. The beginningperiod data, as explained in the section on sample 

and data, are used in this table.21 We estimate the 

logits for each of our cohorts, 1990 through 2002. 

However, because of the small number of failures 

after 1993, beginning with the 1994 logit we combine cohorts. The 1994 model is a combination of 

the 1993 and 1994 cohorts, and the 1995 model 

combines 1993 through 1995. We continue combining cohorts up to five years (the 1993 through 

1997 cohorts for the 1997 logit). For the 1998 

through 2002 models, we use a panel of the most 

recent previous five years. 

Tables 5 through 7 show the results. The reference 

state is failure, so the coefficients are interpreted 

relative to failure. As mentioned above, a negative coefficient means that an increase in a variable will have the result that the future state 

relative to failure becomes less likely. 

19 Nuxoll et al. (2003). 

20 As a robustness check, we estimated the model using three variables for 

the United States economy: a ratio of the number of problem banks to total 

number of banks by state, a ratio of the assets of problem banks to total 

assets by state, and the percentage change in state housing permits. The first 

test was an estimation using only the economic variables as explanatory 

variables. We did two estimations: one used the ratio of the number of 

problem banks to total number by state and the percentage change in state 

housing permits; the second used the ratio of the assets of problem banks to 

total assets by state and the percentage change in housing permits. These 

variables were significant for most of these estimations. However, when 

these variables were included in estimations with the rest of the explanatory 

variables, their significance disappeared. 

21 As with the univariate analysis, we also ran the logits using a beginning 

period one quarter before the quarters specified previously. The results 

revealed little difference. 

FDIC BANKING REVIEW	 31 2006, VOLUME 18, NO. 1 
 

Troubled Banks: Why Don’t They All Fail? 

Eight of the findings are fairly 

interesting. First, more recent 

cohorts (beginning with the 

1995–1999 cohort) have fewer 

statistically significant variables than those in the early 

1990s. This result is most 

likely because of the small 

number of failures, despite the 

paneling of data.22 However, 

those variables that are statistically significant in the more 

recent cohorts have the 

expected sign (as shown in 

table 1) except for capital 

injections. For example, in 

the 1997–2001 cohort, 

expenses on premises is significant and has a negative sign in 

table 5 (recovery) and table 7 

(still a problem). An increase 

in this variable will have the 

result that a future state of 

either recovery or continuation as a problem becomes less 

likely relative to failure. 

On the other hand, for the 

cohorts 1994–1998 through 

1998–2002, capital injections 

from outside are significant— 

but have the unexpected sign 

both for table 6 (merger) and, 

in two of those four cohorts, 

for table 5 (recovery). Perhaps 

the negative sign indicates 

that the institution expects to 

be acquired and either does 

not or cannot raise capital. As 

mentioned in footnote 13, the 

Riegle-Neal Interstate Banking and Branching Efficiency 

Act was enacted in 1994. 

22 From the 1995–1999 cohort through the 

1998–2002 cohort, the number of failures 

totaled 7, 7, 8, and 8, respectively, compared 

with 45, 36, and 17 for the cohorts 1990 

through 1992. 

Table 4 

Selected Descriptive Statistics for Data in Logits: 

Mean Standard Deviation, and Minimum and Maximum Values 

of Financial Ratios for Each State 

Remain a 

Variable All Recover Merge Problem Fail 

Number of Banks 3,747 1,326 228 2,077 116 

Capital 

Tangible Equity Capital 

Mean 6.42 6.68 6.57 6.39 3.90 

Standard Deviation 3.12 2.54 3.42 3.37 2.76 

Minimum -4.77 -0.10 -4.77 -1.26 -1.37 

Maximum 63.10 38.34 34.52 63.10 15.79 

Capital Injections: 

From BHC 

Mean 0.20 0.19 0.41 0.20 0.14 

Standard Deviation 0.87 0.82 1.41 0.84 0.65 

Minimum -1.07 -1.07 0.00 -0.93 -0.02 

Maximum 12.87 9.98 12.87 8.97 4.74 

Outside 

Mean 0.36 0.36 0.29 0.29 0.42 

Standard Deviation 1.38 1.46 1.52 1.25 2.24 

Minimum -2.03 -1.89 -0.07 -2.03 -0.62 

Maximum 25.16 15.98 15.98 25.16 18.38 

Asset Quality 

Past-Due Loans (30–89 days) 

Mean 2.24 1.88 2.12 2.43 3.08 

Standard Deviation 1.58 1.38 1.84 1.60 1.95 

Minimum 0.00 0.00 0.00 0.00 0.25 

Maximum 18.66 12.41 18.66 13.96 9.59 

Past-Due Loans (90+ days) 

Mean 0.79 0.59 0.65 0.92 1.17 

Standard Deviation 1.39 0.81 0.81 1.66 1.82 

Minimum 0.00 0.00 0.00 0.00 0.00 

Maximum 44.66 10.25 6.22 44.66 14.42 

Nonaccrual Loans and Leases 

Mean 2.51 2.17 2.56 2.64 3.82 

Standard Deviation 2.13 1.83 2.62 2.19 2.36 

Minimum 0.00 0.00 0.00 0.00 0.05 

Maximum 24.71 15.60 24.71 17.67 11.18 

Other Real Estate Owned 

Mean 2.36 2.00 1.88 2.60 3.19 

Standard Deviation 2.55 2.13 1.97 2.79 2.63 

Minimum -10.05 0.00 0.00 -10.05 -0.24 

Maximum 20.20 18.61 10.99 20.20 12.48 

Allowance for Loan Loss 

Mean 1.74 1.69 1.97 1.72 2.11 

Standard Deviation 1.13 1.08 2.01 1.03 0.95 

Minimum 0.11 0.11 0.36 0.14 0.28 

Maximum 26.45 19.82 26.45 14.13 5.63 

Management 

Efficiency Ratio 

Mean 92.91 88.32 94.15 94.43 115.77 

Standard Deviation 25.00 22.85 25.34 25.09 29.99 

Minimum -30.64 -30.64 35.09 29.38 26.72 

Maximum 198.71 193.89 195.03 198.71 194.40 

2006, VOLUME 18, NO. 1 32 FDIC BANKING REVIEW 
Troubled Banks: Why Don’t They All Fail? 

Second, both the pairing of 

recovery versus failure (table 

5) and the pairing of merger 

versus failure (table 6) have 

more statistically significant 

variables than the pairing of 

continuation as a problem versus failure (table 7). We 

expect that banks that remain 

a problem more closely resemble banks that fail than they 

resemble banks that recover or 

merge. In fact, the univariate 

trend analysis showed that for 

most of the financial variables, 

the percentage of banks that 

remained a problem was closer 

to the percentage that failed 

than were the percentages for 

the other two future states. 

Third, for all cohorts and in 

each future state, asset-quality 

variables are statistically significant more often than other 

variables (tables 5, 6, and 7). 

Moreover, the variable nonaccrual loans and leases is more 

often statistically significant 

than past-due loans (either 

30–89 days or 90 days or 

more), a result we would 

expect inasmuch as past-due 

loans are more likely to 

improve and be worked out 

than nonaccrual loans and 

leases. Further, these 

asset-quality variables are 

often negative (as expected 

from table 1), a sign indicating 

that an increase in the variable will have the result that 

the future state relative to failure becomes less likely. 

Fourth, surprisingly, tangible 

equity is highly statistically 

significant for only the 1990, 

1991, and 1992 cohorts in 

Table 4 (continued) 

Selected Descriptive Statistics for Data in Logits: 

Mean Standard Deviation, and Minimum and Maximum Values 

of Financial Ratios for Each State 

Remain a 

Variable All Recover Merge Problem Fail 

Earnings 

Total Interest Income 

Mean 9.30 8.80 8.99 9.59 10.58 

Standard Deviation 3.14 2.60 4.63 3.14 4.11 

Minimum -0.01 -0.01 5.24 0.97 4.47 

Maximum 64.32 33.69 64.32 32.78 26.25 

Total Noninterest income 

Mean 1.45 1.41 1.44 1.45 1.98 

Standard Deviation 2.31 2.18 1.84 2.38 3.20 

Minimum -0.09 -0.09 0.00 -0.05 0.18 

Maximum 46.35 37.82 16.34 46.35 30.51 

Total Interest Expense 

Mean 4.98 4.47 4.51 5.27 6.51 

Standard Deviation 2.18 1.76 2.25 2.28 2.95 

Minimum -0.68 -0.68 1.25 0.25 0.95 

Maximum 17.01 14.74 15.42 17.01 16.57 

Loan-Loss Provision 

Mean 1.72 1.35 2.23 1.81 3.21 

Standard Deviation 2.43 1.72 6.07 2.02 2.69 

Minimum -13.56 -2.17 -1.54 -13.56 -0.42 

Maximum 87.33 23.14 87.33 24.55 13.82 

Loan Charge-offs 

Mean 1.71 1.46 1.78 1.80 2.86 

Standard Deviation 1.89 1.41 3.52 1.86 2.06 

Minimum -6.32 -0.49 -6.32 0.00 0.25 

Maximum 47.20 19.12 47.20 24.12 11.50 

Expenses on Premises 

Mean 0.75 0.68 0.75 0.77 0.96 

Standard Deviation 0.46 0.40 0.44 0.47 0.67 

Minimum -0.48 -0.48 0.00 -0.04 0.15 

Maximum 4.46 3.38 2.79 4.35 4.46 

Salaries 

Mean 2.14 2.06 2.08 2.18 2.56 

Standard Deviation 1.18 0.95 0.99 1.23 2.32 

Minimum 0.00 0.06 0.00 0.04 0.43 

Maximum 22.99 16.14 9.17 22.36 22.99 

Other noninterest expense 

Mean 2.39 2.23 2.54 2.43 3.29 

Standard Deviation 1.68 1.55 2.43 1.61 2.12 

Minimum -3.03 -3.03 0.45 -0.41 0.71 

Maximum 32.70 22.46 32.70 25.38 14.86 

Liquidity 

Volatile Liabilities 

Mean 14.28 13.26 13.62 14.96 15.04 

Standard Deviation 9.85 9.51 11.08 9.90 9.26 

Minimum 0.00 0.00 0.00 0.00 0.00 

Maximum 90.19 86.08 90.19 89.43 51.54 

Loans + Securities > Five years 

Mean 67.74 66.13 68.11 68.71 68.04 

Standard Deviation 11.51 11.39 12.15 11.43 11.21 

Minimum 19.40 24.31 19.40 22.14 37.34 

Maximum 102.02 102.02 96.38 101.05 90.33 

FDIC BANKING REVIEW 33 2006, VOLUME 18, NO. 1 
Table 5 Multinomial Logit Regressions of Determinants of Bank State: Recovery versus Failure (Estimation Period in Years) Explanatory Variables 1990 1991 1992 1993 1993-94 1993-95 1993-96 1993-97 1994-98 1995-99 19

Intercept Constant -0.2388 10.6388 *** -2.0548 -2.8325 8.4024 * 7.0800 * 6.2905 6.0942 14.2305 Capital Tangible Equity for PCA 0.7743 *** 1.0350 *** 0.7071 *** -0.1248 -0.1827 -0.0345 -0.0198 -0.0262 1.4338 BHC Capital Injections 2.0621 -0.3816 0.6065 0.5490 0.4402 0.3137 0.3806 0.3978 -3.1364 External Capital Injections 0.0021 0.1636 5.1764 ** 0.8219 1.1397 1.5649 1.5940 1.6146 -0.9101 Asset Quality Loans Past Due 30 to 89 Days -0.4142 *** -0.4417 *** -0.2429 -0.8305 ** -0.4773 ** -0.2567 -0.1913 -0.1730 0.5548 Loans Past Due 90 Days or More -0.4630 *** -0.1805 -0.5600 -0.3232 -0.1968 -0.3677 ** -0.4260 *** -0.4530 *** -1.0422 ** Nonaccrual Loans and Leases -0.2163 ** -0.3689 *** -0.4007 ** -0.7762 * -0.6210 *** -0.5803 *** -0.6002 *** -0.6283 *** -2.9354 ** Other Real Estate Owned -0.3847 *** -0.2984 *** 0.1820 0.3759 0.3007 0.2900 0.3299 0.3245 7.6096 ** Allowance for Loan Losses 0.3333 0.7585 *** 0.1987 2.5538 ** 0.9456 * 0.7284 0.7687 * 0.7911 * 4.1672 Management Efficiency Ratio -0.0010 -0.0218 -0.0233 0.0277 -0.0398 -0.0406 -0.0328 -0.0341 -0.0417 Earnings Total Interest Income 1.0295 -0.9335 0.6710 2.3293 -0.3460 -0.3550 -0.1461 -0.1235 -3.0691 Total Noninterest Income 0.6360 -0.6387 0.3575 2.2171 * 0.4048 0.1514 0.2814 0.2917 -2.3035 

Total Interest Expense -1.2585 * -0.0224 -0.6493 -1.2851 0.7541 0.3780 0.0680 0.0577 -0.7468 Loan-loss Provision -0.7479 *** -0.6765 *** -0.1868 -1.2186 * -0.9301 ** -0.8185 ** -0.9011 ** -0.9159 ** 0.1979 Loan Charge-offs 0.7248 *** 0.6950 *** -0.4833 0.8751 0.6614 0.7422 0.7013 * 0.6955 ** 1.5349 Expenses on Premises -0.3109 -0.3120 -2.5638 -1.7553 -0.6163 -0.9336 -1.0243 -0.9938 -2.3193 Salaries -1.4292 ** 0.5001 0.9138 -1.6762 -0.0150 0.1143 -0.0836 -0.1369 7.9328 Other Noninterest Expense -0.3044 0.0733 -0.4493 -3.4496 ** -0.7108 -0.3225 -0.4617 -0.4250 -0.0248 Liquidity Volatile Liabilities -0.0130 0.0180 0.0191 -0.0726 -0.0456 -0.0072 0.0087 0.0117 -0.3340 * Loans Plus Securities >= Five years 0.0225 0.0033 0.0730 0.0743 0.0807 0.0792 .0798 0.0856 0.0863 Log Likelihood -584.9 -662.5 -561.8 -328.8 -505.8 -597.7 -660.9 -708.4 -416.7 Number of Observations 866 897 713 413 607 717 781 843 495 Akaike Information Criteria 1289.8 1445.0 1243.6 777.6 1131.6 1315.4 1441.8 1536.8 953.4 Pseudo R squared 0.090 0.222 0.170 0.195 0.162 0.159 0.144 0.145 0.172 

-2.8352 

0.2043 

-0.6126 -0.3444 * 

0.3001 

-0.5484 *** 

-0.6012 ** 

0.6112 

0.8971 

0.0685 0.4429 

0.7560 

-0.9387 

-0.5587 

0.6323 

-2.3415 

-0.6335 

-1.1180 

-0.0723 * 

0.0708 

-339.3 

377 

798.5 

0.121 

Significance at 1%, 5% and 10% levels are indicated by ***, ** and * asterisks, repectively. 

2006, VOLUME 18, NO. 1 34 FDIC BANKING REVIEW 
Table 6 

Multinomial Logit Regressions of Determinants of Bank State: Merger versus Failure (Estimation Period in Years) 

Explanatory Variables 1990 1991 1992 1993 1993-94 1993-95 1993-96 1993-97 1994-98 1995-99 1

Intercept Constant -4.4684 9.6836 ** -7.5929 -5.191 4.203 4.6942 4.5547 4.7692 11.3291 

Capital Tangible Equity for PCA 0.5301 *** 0.8500 *** 0.7454 *** -0.0461 -0.1382 -0.0093 -0.0002 -0.0191 1.4089 BHC Capital Injections 2.1647 -0.1048 0.3075 1.0384 0.7004 0.5830 0.5993 0.5579 -3.1430 External Capital Injections -0.9151 -0.0810 5.0893 ** 0.8027 0.9729 1.3522 1.3519 1.3907 -1.6622 ** Asset Quality Loans Past Due 30 to 89 Days -0.6823 *** -0.4077 ** -0.2239 -0.8464 ** -0.4781 ** -0.1863 -0.2035 -0.1915 0.6182 Loans Past Due 90 Days or More -0.3236 -0.0706 -0.5440 -0.1931 -0.2134 -0.5354 ** -0.5049 ** -0.5198 ** -0.9865 ** Nonaccrual Loans and Leases -0.2397 -0.4158 *** -0.3294 ** -0.7045 -0.6407 *** -0.5988 *** -0.6019 *** -0.6018 *** -2.9516 ** Other Real Estate Owned -0.1902 * -0.4054 *** 0.2594 0.3367 0.3322 0.2715 0.3054 0.3055 7.6746 ** Allowance for Loan Losses 0.3356 0.8715 *** 0.3666 2.6342 ** 1.2752 ** 0.9467 ** 0.9844 ** 0.9958 * 4.3713 Management Efficiency Ratio 0.0094 -0.0345 -0.0171 0.0437 -0.0179 -0.0297 -0.0320 -0.0379 -0.0522 Earnings Total Interest Income 1.1992 -1.5633 ** 0.5040 2.2421 -0.1898 -0.5105 -0.3677 -0.3640 -3.3443 Total Noninterest Income 0.7799 -1.4107 ** 0.2819 2.5038 ** 0.5521 0.1408 0.1259 0.0759 -2.6277 Total Interest Expense -0.9474 0.7870 -0.4657 -0.8863 0.7604 0.6581 0.4352 0.4075 -0.3228 Loan-loss Provision 0.1164 -0.1086 0.0177 *** -1.0359 -0.6691 -0.5882 -0.6731 ** -0.7569 ** 0.2790 Loan Charge-offs -0.0145 0.0398 -0.7365 ** 0.8755 0.3109 0.3865 0.3321 0.3975 1.0550 Expenses on Premises -0.8320 1.1644 -1.5325 -1.7446 -0.2103 -0.4991 -0.4863 -0.3517 -1.2111 Salaries -1.7712 * 1.4012 * 0.8435 -1.5131 -0.0220 0.2606 0.1441 0.1638 8.1622 

Other Noninterest Expense -0.2371 * 0.6104 ** -0.0030 ** -4.1409 -1.3090 -0.4806 -0.4177 -0.3441 0.2520 Liquidity Volatile Liabilities -0.0085 -0.0177 0.0025 ­ 0.1507 * -0.1159 -0.0679 -0.0431 -0.0379 -0.3553 ** Loans Plus Securities >= Five years 0.0159 0.0091 0.0927 ** 0.0593 0.0729 0.0791 0.0805 0.0855 * 0.1157 Log Likelihood -584.9 -662.5 -561.8 -328.8 -505.8 -597.7 -660.9 -708.4 -416.7 Number of Observations 866 897 713 413 607 717 781 843 495 Akaike Information Criteria 1289.8 1445.0 1243.6 777.6 1131.6 1315.4 1441.8 1536.8 953.4 Pseudo R squared 0.090 0.222 0.170 0.195 0.162 0.159 0.144 0.145 0.172 

-5.1144 

0.2249 

-0.8561 

-1.2036 ** 

0.3477 

-0.3893 * 

-0.4764 * 

0.5882 0.5819 

0.0580 0.2597 

0.6042 

-0.5881 

-0.6447 

0.7349 

-1.3686 

-0.6658 

-0.8389 

-0.0813 * 

0.0861 

-339.3 

377 

798.5 

0.121 

Significance at 1%, 5% and 10% levels are indicated by ***, ** and * asterisks, repectively. 

FDIC BANKING REVIEW 35 2006, VOLUME 18, NO. 1
Table 7 Multinomial Logit Regressions of Determinants of Bank State: Remain a Problem versus Failure (Estimation Period in Years) Explanatory Variables 1990 1991 1992 1993 1993-94 1993-95 1993-96 1993-97 1994-98 1995-99 19

Intercept Constant -1.7037 9.8229 *** -5.7298 -8.1433 3.4994 1.9090 2.3718 2.9545 11.8183 -4.7010 Capital Tangible Equity for PCA 0.6653 0.9255 0.6366 -0.0180 -0.1213 0.0157 0.0210 0.0161 1.4656 0.2476 BHC Capital Injections 1.8868 -0.2906 0.5581 0.8628 0.4019 0.2479 0.2982 0.3084 -3.3388 -0.8366 External Capital Injections -0.2729 0.1045 5.0410 ** 0.4656 0.9132 1.4138 1.4588 1.4872 -0.9185 -0.3014 Asset Quality Loans Past Due 30 to 89 Days -0.1508 * -0.1852 * -0.0386 -0.6301 -0.2901 -0.0618 -0.0480 -0.0389 0.6652 * 0.3108 Loans Past Due 90 Days or More -0.1451 -0.0449 -0.2691 -0.1211 0.0590 -0.0202 -0.0798 -0.0852 -0.6682 -0.2518 Nonaccrual Loans and Leases -0.0503 -0.0609 -0.2043 -0.5441 -0.4911 *** -0.4661 *** -0.5049 *** -0.5101 *** -2.9075 *** -0.5721 Other Real Estate Owned -0.1520 * -0.0992 0.3269 0.5932 0.5444 ** 0.5269 ** 0.5422 ** 0.5437 ** 7.8727 0.7603 Allowance for Loan Losses 0.2190 0.4678 ** -0.1398 2.0740 0.6592 0.3662 0.4775 0.4219 3.8584 0.5901 Management Efficiency Ratio -0.0094 -0.0479 ** -0.0088 0.0608 -0.0183 -0.0160 -0.0218 -0.0298 -0.0504 0.0616 Earnings 

Total Interest Income 0.5102 -1.4084 ** 0.8538 2.3853 -0.2317 -0.2204 -0.1554 -0.2602 -3.2794 0.3022 Total Noninterest Income 0.0929 -1.6561 *** 0.4092 2.3166 * 0.4836 0.2710 0.2199 0.1216 -2.5602 0.6202 Total Interest Expense -0.4149 0.7310 -0.8402 -1.6448 0.4186 0.0461 -0.0415 0.0889 -0.4817 -0.5840 Loan-loss Provision -0.5443 * -0.2876 0.0509 -0.8631 -0.5969 -0.4833 -0.5775 * -0.5975 * 0.4569 -0.4709 Loan Charge-A5offs 0.5898 * 0.2622 -0.6566 * 0.8309 * 0.5432 0.6234 0.5602 0.5720 1.3316 0.6531 Expenses on Premises -0.0152 1.0657 -1.8408 -1.8289 -0.4222 -0.9661 -0.7504 -0.6864 -1.6630 -1.7840 Salaries -0.4521 1.5279 *** 0.6316 -1.4041 0.2488 0.3225 0.2618 0.3786 8.4899 -0.3599 Other Noninterest Expense 0.1244 0.8622 ** -0.4144 -3.9178 ** -1.0867 * -0.6549 -0.5648 -0.4626 0.1029 -1.0150 Liquidity Volatile Liabilities -0.0006 0.0166 0.0404 -0.0821 -0.0456 -0.0061 0.0126 0.0192 -0.3160 * -0.0456 Loans Plus Securities >= Five years 0.0273 0.0089 0.0877 ** 0.0966 0.1024 * 0.1027 ** 0.0997 ** 0.1050 ** 0.1040 0.0777 Log Likelihood -584.9 -662.5 -561.8 -328.8 -505.8 -597.7 -660.9 -708.4 -416.7 -339.3 Number of Observations 866 897 713 413 607 717 781 843 495 377 Akaike Information Criteria 1289.8 1445.0 1243.6 777.6 1131.6 1315.4 1441.8 1536.8 953.4 798.5 Pseudo R squared 0.090 0.222 0.170 0.195 0.162 0.159 0.144 0.145 0.172 0.121 

2

0

-0

-0

0

-0

-0

0

0

0

0

0

-0

-0

0

-2

0

-0

-

Significance at 1%, 5% and 10% levels are indicated by ***, ** and * asterisks, repectively. 

2006, VOLUME 18, NO. 1 36 FDIC BANKING REVIEW 
Troubled Banks: Why Don’t They All Fail? 

table 5 (recovery) and table 6 (merger). It is not 

statistically significant in the remaining years in 

tables 5 or 6, nor is it significant in any year in 

table 7 (continuation as a problem).23 

Fifth, another surprise is in the 1992 cohort, where 

external capital injections are significant and positive for all three future states (and yet are not significant again until the 1994–1998 cohort for 

merger [table 6], where the sign is negative). 

Sixth, the efficiency ratio is significant only for the 

1991 cohort for continuation as a problem versus 

failure (table 7). Since this ratio uses income and 

expense variables, we omitted the earnings variables from the model as a robustness check. The 

results showed that without the earnings variables, 

the frequency of significance improved in the efficiency ratio. For example, in the 1993–1997 and 

1994–1998 cohorts, the efficiency ratio is significant in all three future states and has the expected 

sign. In the 1991 and 1992 cohorts, it is significant for recovery versus failure and has the expected sign. 

Seventh, among the earnings ratios, loan-loss provision is the most consistently significant ratio in 

all three future states, but more so for recovery 

(table 5) than for the other two outcomes (table 6 

and table 7). This result makes sense since the 

sooner loan losses are recognized, the more likely it 

is that a bank will survive. We also tried running 

the logits without the efficiency ratio to see 

whether we could gain more significance in the 

earnings ratios. However, the significance in the 

earnings ratios still did not become more frequent. 

Finally, the most startling result is in the 

1994–1998 cohort for all three future states: the 

coefficients for loans past due 90 days, nonaccrual 

loans and leases, and other real estate owned are 

much larger than in any other cohorts, and the 

sign on other real estate owned is positive (indicating that an increase in this variable is more likely 

to result in nonfailure). The likely explanation 

lies in the small number of failures and the particular nature of the banks in the 1994–1998 cohort. 

The number of failures fell from 10 in the 

1993–1997 cohort to 7 in the 1994–1998 cohort, 

and one of the failures in 1998 was a bank that 

failed because of fraudulent activity and therefore 

had a very low amount of other real estate 

owned—perhaps low enough to skew the model. 

For example, the mean of other real estate owned 

(as a percentage of assets) for failed banks in the 

1993–1997 cohort equaled 3.0 percent; for the 

1994–1998 cohort, the mean dropped to 0.62 percent. 

Prediction of State: Out-of-Sample Results 

The true measure of the logit model’s contribution 

is its accuracy in making out-of-sample predictions. 

To test the accuracy, we forecast future bank states 

using prior-period estimations from our unordered 

logit model on the following year’s cohort. For 

example, we use the coefficients from the 1990 

cohort to predict the future state of the 1991 

cohort, coefficients from the 1991 cohort to predict the future state of the 1992 cohort, and so on. 

Since our model is estimated from paired observations of first events and outcomes at second events, 

no observations that are in the 1990 cohort can be 

in the 1991 cohort (see explanation of observations in the section above on sample and data). 

To determine all predictions of state, we summed 

predicted probabilities of state for the cohort, 

deriving the expected number of banks in each 

future state. Figures 5 through 7 show the results. 

All three figures show that the number of banks 

predicted for each state is very close to the number 

of banks that actually ended up in the state. For 

1996, for example, figure 5 shows that the logit 

predicts 27 banks to recover, and 26 banks actually 

recovered; figure 6 shows that 5 banks are predicted to be acquired, compared with 3 that actually 

were; and figure 7 shows that 26 banks are predicted to remain a problem, compared with 29 that 

actually did remain a problem. 

To test binary forecasts against our multistate 

model, we do two comparisons. First, we run a 

23 Thinking that tangible equity would be correlated with capital injections, 

we ran the models using only tangible equity. However, taking out capital 

injections made no difference in significance. 

FDIC BANKING REVIEW 37 2006, VOLUME 18, NO. 1 
 

Troubled Banks: Why Don’t They All Fail? 

binary model using the same financial variables 

as in the multistate model to predict failure 

versus nonfailure. We then compare the predicted probabilities of failure from this binary 

model with predicted probabilities of failure 

from the multistate model. 

The first comparison is shown in figure 8, 

which compares the forecasts of the two models with the actual number of failed banks. As 

can be seen, both models predict failure fairly 

accurately. The second comparison is shown in 

figure 9, which compares the predicted probabilities of failure from our multistate model 

with predictions from the loss-distribution 

model (LDM). This model uses variables 

found in conventional bank-failure literature to 

predict bank failure within the second quarter 

after the Call Report is filed. In our test, we 

use the betas from the LDM estimated one year 

earlier to predict failures of problem banks for 

the following year. For example, the LDM predicted that eight banks would fail in 1994 (figure 9). The predictions resulted from the use 

of the betas estimated in the 1993 LDM. 

However, as noted above in the section on 

sample and data, a second event for an observation may occur as many as 24 months after 

the first event. A bank on the problem list in 

December 1993 may be in our 1992 cohort 

that used Call Report data after 1993 in the 

estimation. Thus, to get a true out-of-sample 

prediction using our model, we have to use the 

estimated betas from a cohort two years before 

the date for which we are predicting failures for 

problem banks. The prediction that six banks 

would fail in 1994 resulted from the use of estimated betas from our 1992 model (figure 9). 

But since the LDM requires only a one-year 

prediction horizon, one would expect it to be a 

better predictor of failure than our model. This 

expectation is not quite borne out. As figure 9 

shows, the two models are comparable. The 

advantage of ours is that we can predict not 

only problem-bank failure but also problembank recovery, merger, and continuation as a 

problem. 

Figure 5 

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 

0 

50 

100 

150 

200 

250 

300 

Number of Banks 

Actual 

Unordered 

Note: One-year-ahead forecasts versus actual. 

Banks That Recovered 

Figure 6 

Figure 7 

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 

0 

5 

10 

15 

20 

25 

30 

35 

40 

Number of Banks 

Actual 

Unordered 

Note: One-year-ahead forecasts versus actual. 

Banks That Were Acquired 

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 

0 

100 

200 

300 

400 

500 

600 

700 

Number of Banks 

Actual 

Unordered 

Note: One-year-ahead forecasts versus actual. 

Banks That Continued as a Problem 

2006, VOLUME 18, NO. 1 38 FDIC BANKING REVIEW 
Troubled Banks: Why Don’t They All Fail? 

To determine whether banks with the highest 

probability of failure are the ones that actually 

fail, we rank banks that our model predicts to 

fail in each period by their probability of failure. We then divide the predicted failures into 

deciles to determine whether the highest decile 

contains the largest number of banks that actually failed. Of the 65 failed banks in our 

cohorts from 1991 through 2002, 38 were in 

the tenth decile.24 An additional 8 banks were 

in the ninth decile. 

The results for the remaining three states, however, were not quite as accurate. Of the 1,058 

recovered banks in our cohorts from 1991 

through 2002, 166 (16 percent) were in the 

tenth decile; adding the 159 banks in the ninth 

decile raises the percentage to 31. For banks 

that are predicted to merge, 14 percent are in 

the tenth decile (26 banks out of the 191 banks 

that merged in our cohorts from 1991 through 

2002); and for banks that are predicted to 

remain a problem, 15 percent are in the tenth 

decile. 

Despite the weaker results for the remaining 

three states, the accuracy in forecasting future 

bank states is noteworthy. Arguably, this 

model could be used to predict troubled banks’ 

future state with decent reliability. 

Economic Significance 

To test the economic significance of the 

explanatory variables, we use a fairly standard 

approach: first we evaluate in-sample predicted 

state probabilities on the basis of the mean values of explanatory variables, and then we evaluate how these probabilities change with 

marginal changes in key explanatory variables. 

Because asset-quality variables—specifically, 

loans past due 90 days or more and nonaccrual 

loans and leases—were the variables most consistently significant across panels, we compared 

their economic significance in two periods: 

1990 and the panel 1995–99. 

24 For the binary model, 39 of the 65 failed banks were in the tenth 

decile. 

We use the predicted in-sample state probabilities for 

1990 and the 1995–99 panel based on the mean values for explanatory variables in 1990 and in the 

1995–99 panel. The means for the sample of banks 

used in model estimation for both periods are shown 

in table 8. 

The predicted state probabilities evaluated at the 

mean for banks in the 1990 cohort are 16.41 percent 

for recover, 1.82 percent for merge, 80.82 percent for 

remain a problem, and 0.95 percent for fail. Both 

loans past due 90 days or more and nonaccrual loans 

and leases were statistically significant in 1990 and in 

the 1995–99 panel. Table 9 shows the effects on estimated state probabilities, ceteris paribus, should each 

Figure 8 

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 0 

10 

20 

30 

40 

Number of Banks 

Actual 

Binary 

Unordered 

Note: One-year-ahead forecasts versus actual 

Banks That Failed, Multistate and Bivariate Models 

Predictions of Unordered Multistate and Bivariate Models 

Figure 9 

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 

0 

10 

20 

30 

40 

Number of Banks 

Actual 

Unordered 

LDM Bivariate 

Note: One-year-ahead forecasts versus actual 

 Total problem-bank list at year-end 

Banks That Failed, Multistate and LDM Models 

Predictions of Unordered Multistate Model and LDM Models 

FDIC BANKING REVIEW 39 2006, VOLUME 18, NO. 1 
Troubled Banks: Why Don’t They All Fail? 

of these ratios experience a 1 percentage point 

increase in either of the periods examined. For 

example, in 1990 the mean for loans past due 90 

days or more equaled 0.7964 percent of assets. If 

that is increased 1 percentage point to 1.7964 percent, the probability of recovery decreases from 

16.41 percent to 12.52 percent, the probability of 

merger decreases from 1.82 percent to 1.59 percent, the probability of continuation as a problem 

increases from 80.82 percent to 84.74 percent, and 

the probability of failure increases from 0.95 percent to 1.15 percent. 

Table 8 

Means Ratio: 1990 and 1995–99 Panel 

Percentage of Assets 

Variable Mean Mean 

1990 1995–99 

Capital 

Tangible Equity Capital 5.3409 7.297 

Capital Injections: 

From BHC 0.1399 0.2176 

Outside 0.1888 0.6267 

Asset Quality 

Past-Due Loans (30–89 days) 2.2262 2.5514 

Past-Due Loans (90+ days) 0.7964 1.1164 

Nonaccruing Loans 2.6136 2.5111 

Other Real Estate Owned 2.6808 1.4720 

Loan Charge-offs 1.6613 1.7754 

Allowance for Loan Loss 1.7465 1.9878 

Management 

Efficiency Ratio 93.5429 93.5453 

Earnings 

Interest Income 9.6398 8.2684 

Noninterest Income 1.2205 2.1216 

Interest Expense 5.8164 3.4738 

Loss Provision 1.6035 1.7133 

Salaries 1.9194 2.7150 

Expenses on Premises 0.6952 0.8492 

Other Noninterest Expense 2.0764 2.8551 

Liquidity 

Volatile Liabilities 14.4676 14.2472 

Loans and Sec. > 5 years 65.1021 68.6646 

Table 9 

Effects of One Percentage Point Change in 

Selected Variables on Predicted Probability 

Increase 

in Loans Increase in 

Past-Due Nonaccrual 

90 Days Loans 

1990 At Mean to 1.7964% to 3.6136% 

Recovery 16.41% 12.52% 14.29% 

Merger 1.82 1.59 1.55 

Remain a problem bank 80.82 84.74 83.13 

Failure 0.95 1.15 1.02 

Increase 

in Loans Increase in 

Past-Due Nonaccrual 

90 Days Loans 

1995–99 At Mean to 2.1164% to 3.5111% 

Recovery 43.22% 36.45% 42.14% 

Merger 6.61 6.53 7.30 

Remain a problem bank 49.93 56.65 50.12 

Failure 0.25 0.37 0.45 

Summary 

We offer an approach that differs from that of previous failure-prediction models by focusing on 

troubled banks only. As a result, we can estimate a 

model that predicts failure as well as the three 

alternative outcomes to failure: recovery, merger, 

and continuation as a problem. Further, this 

model predicts failure as successfully as the standard binary failure-prediction model. 

For the deposit insurer, this four-state model offers 

more information about the possible future states 

of problem banks than a two-state model can. 

This additional information can better assist the 

FDIC in long-term strategic planning regarding 

problem banks. This planning involves budgeting 

personnel, time, and funding. Moreover, our 

model shows that certain explanatory variables 

affect future bank state. This knowledge may help 

regulators choose policies that affect the likelihood 

that troubled banks can successfully resolve their 

own problems. 

2006, VOLUME 18, NO. 1 40 FDIC BANKING REVIEW 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Troubled Banks: Why Don’t They All Fail? 

REFERENCES 

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Cole, Rebel A., and Jeffery W. Gunther. 1998. Predicting Bank Failures: A Comparison of 

On- and Off-Site Monitoring Systems. Journal of Financial Services Research 13, no. 

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Gunther, Jeffery W., and Robert R. Moore. 2000. Financial Statements and Reality: Do 

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Jarrow, Robert A., Rosalind L. Bennett, Michael C. Fu, Daniel A. Nuxoll, and Huiju Zhang. 

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Whalen, Gary. 1991. A Proportional Hazard Model of Bank Failure: An Examination of Its 

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FDIC BANKING REVIEW 41 2006, VOLUME 18, NO. 1 
Troubled Banks: Why Don’t They All Fail? 

APPENDIX 

Figure A1 Figure A3 

28% 

47% 47% 

62% 

Failure Still a Problem Merger Recovered 

0 

20 

40 

60 

80 

100 

Percent 

Increases in Net Interest Income 

Figure A2 

46% 

41% 

36% 

28% 

Failure Still a Problem Merger Recovered 

0 

20 

40 

60 

80 

100 

Percent 

Increases in Loss Provision 

Figure A4 

32% 

42% 43% 

52% 

Failure Still a Problem Merger Recovered 

0 

20 

40 

60 

80 

100 

Percent 

Increases in Net Noninterest Income 

72% 

64% 67% 

50% 

Failure Still a Problem Merger Recovered 

0 

20 

40 

60 

80 

100 

Percent 

Increases in Loan-Loss Reserves 

2006, VOLUME 18, NO. 1 42 FDIC BANKING REVIEW 
Troubled Banks: Why Don’t They All Fail? 

Figure A5 Figure A8 

Increases in Loans 30–89 Days Past Due Increases in Other Real Estate Owned 

Percent Percent 

100 

80 

60 

40 

20 

0 

56% 

46% 50% 

36% 

Failure Still a Problem Merger Recovered 

Figure A6 

Increases in Loans 90 Days or More Past Due 

Percent 

100 

80 

60 

40 

20 

0 

56% 

47% 46% 

41% 

Failure Still a Problem Merger Recovered 

Figure A7 

Increases in Nonaccrual Loans 

Percent 

100 

80 

60 

40 

20 

0 

Failure Still a Problem Merger Recovered 

61% 59% 

52% 

38% 

100 

80 

60 

40 

20 

0 

76% 

63% 

52% 

44% 

Figure A9 

Percent 

100 

80 

60 

40 

20 

0 

14% 

47% 46% 

72% 

Figure A10 

Percent 

100 

80 

60 

40 

20 

0 

13% 

41% 

47% 

70% 

Failure Still a Problem Merger Recovered 

Failure Still a Problem Merger Recovered 

Increases in Risk-Based Capital 

Failure Still a Problem Merger Recovered 

Increases in Tangible Capital 

FDIC BANKING REVIEW 43 2006, VOLUME 18, NO. 1 
Troubled Banks: Why Don’t They All Fail? 

Figure A11 Figure A13 

Figure A12 

19% 23% 

29% 26% 

Failure Still a Problem Merger Recovered 

0 

20 

40 

60 

80 

100 

Percent 

Increases in Volatile Liabilities 

22% 

40% 40% 

59% 

Failure Still a Problem Merger Recovered 

0 

20 

40 

60 

80 

100 

Percent 

Improvement in the Efficiency Ratio 

40% 38% 

32% 

37% 

Failure Still a Problem Merger Recovered 

0 

20 

40 

60 

80 

100 

Percent 

Increases in Loans and Securities with 

Maturities Greater than or Equal to Five Years 

2006, VOLUME 18, NO. 1 44 FDIC BANKING REVIEW