1

 

Evidence of Improved Monitoring and Insolvency Resolution after FDICIA

Edward J. Kane** 

Rosalind L. Bennett*** 

Robert C. Oshinsky*** 

Abstract 

 

To realign supervisory and market incentives, the Federal Deposit Insurance Corporation 

Improvement Act of 1991 (FDICIA) adjusts two principal features of federal banking 

supervision. First, it requires regulators to examine insured institutions more frequently and 

makes them accountable for exercising their supervisory powers. Second, the Act empowers 

regulators to wind up the affairs of troubled institutions before their accounting net worth is 

exhausted. 

Using 1984–2003 data on the outcome of individual bank examinations, this paper 

documents that the frequency of rating transitions and the character of insolvency resolutions 

have changed substantially under FDICIA. The average interval between bank examinations has 

dropped for low-rated banks in the post-FDICIA era. Examiner upgrades have become 

significantly more likely in the post-FDICIA era even after controlling for the state of the 

economy. However, in recessions managers are slower to correct problems that examiners 

identify. As a result, during downturns upgrades become less likely and absorptions become 

more likely. 

Giving the FDIC authority to wind up troubled banks before their tangible net worth is 

exhausted has reduced the role of government in the insolvency-resolution process. Consistent 

with an hypothesis that FDICIA has improved incentives, our data show that a markedly larger 

percentage of troubled banks now search for a merger partner rather than trying to stay in 

business until the regulators force them to fail. This greater reliance on quasi-voluntary mergers 

is observable both within and across various stages of the business cycle. These findings suggest 

that supervisory interventions became more effective at banks during the post-FDICIA era. (JEL 

Classifications: G20, G28, G21; Keywords: FDICIA, bank supervision, bank monitoring) 

This version: December 8, 2008 

*

 For helpful comments on an earlier draft, the authors wish to than

** Cleary Professor in Finance at Boston College *** Federal Deposit Insurance Corporation. 

The views expressed here are those of the authors and not necessarily those of the FDIC. 
2

In hopes of simultaneously improving supervisory and market incentives, the Federal 

Deposit Insurance Corporation Improvement Act of 1991 (FDICIA) expanded the authority and 

responsibilities of federal banking agencies in two ways. First, the Act requires regulators to 

exercise their monitoring and enforcement powers in a particular fashion. Second, the Act 

empowers regulators to wind up the affairs of troubled institutions before their accounting net 

worth is exhausted. 

FDICIA formally requires regulators to conduct an on-site examination of every insured 

bank or thrift within specified intervals. It also requires them to initiate an escalating series of 

corrective actions and formal calls for the replenishment of capital when, and as, the capital 

position of an institution deteriorates. Finally, FDICIA makes the FDIC accountable for 

resolving failing institutions at minimum cost to the insurance fund. These obligations are 

enforced by requiring the Office of the Inspector General at the relevant agencies to file audit 

reports in cases that generate material losses to the deposit insurance fund. These reports review 

the timeliness and cost effectiveness of corrective actions taken (e.g., Office of Inspector 

General, 2003). 

Two hypotheses underlie these changes. The first holds that accounting capital and 

examination ratings are at best lagging indicators of a bank’s health, particularly when the 

economic environment in which it operates undergoes a major improvement or decline between 

reports. The second maintains that, prior to the enactment of FDICIA, incentives facing troubled 

depository institutions, and the agencies responsible for supervising them, perversely extended 

the lives of ruined firms (see, e.g., FDIC, 1997 or Kane, 1989). According to the second 

hypothesis, shortages of budgetary resources, which were in part politically driven, left 

authorities unable to examine banks frequently or carefully enough. Information gaps and delays 
3

intensified incentive conflicts. In turn, these incentive conflicts tempted supervisors to postpone 

the imposition of exit pressure. The result was that federal guarantees kept funds flowing to 

economically insolvent institutions long after private creditors would otherwise have forced them 

out of business. 

This paper uses data from 1984 to 2005 on examination outcomes to test hypotheses 

about whether and how FDICIA influenced the timing and focus of the monitoring process and 

also the channels through which developing shortages of bank capital are treated and cured. 

We want to stress that the influence of FDICIA and examination ratings on the path of 

bank and supervisory risk taking after 1991 was bound to be affected by other developments. In 

particular, large banks increasingly used securitizations and off-balance-sheet investment 

vehicles to mask their true leverage from bank examiners, while relaxed restrictions on interstate 

banking and branching increased the number of potential buyers for troubled banks. Changes in 

macroeconomic conditions should also affect the willingness and ability of bank managers to 

correct problems that examiners identify. In recessions, higher-rated institutions know that 

supervisors have to focus their resources on their most troubled clients and lack the time to exert 

much discipline on minor concerns. 

Our paper seeks to test what we call the better-incentives hypothesis: the claim that, at 

least in the immediate wake of FDICIA, supervisory and failure resolution processes improved 

incentives for regulators and for bank shareholders, especially at banks that received low 

examination ratings. 

Examinations can not register deteriorations or improvements in a bank’s condition until 

some months after they occur. FDICIA encourages examiners to refocus their monitoring effort 

on positions, internal control systems, and strategies that expose the FDIC to loss. Our evidence 
4

shows a reduction in the average interval between completed examinations for low-rated banks. 

Substantial changes occur as well in the frequency and characteristics of rating transitions for all 

ratings classes. 

Our findings also suggest that, at least for the risks that examiners could see, supervisory 

interventions became more effective at troubled banks. Rather than problem institutions 

transitioning into lower rating classes in successive exams and eventual failing, problem banks 

proved significantly more likely to recover. Furthermore, examiners prove significantly more 

likely to upgrade banks in successive examinations. The increased frequency of upgrades 

supports the hypothesis that problem banks faced stronger incentives to correct the particular 

deficiencies that examiners identify. 

Still, common sense suggests that resolving supervisory concerns would require more 

effort as a bank’s rating declines and also as the economic environment weakens. In line with 

this, post-FDICIA differences in ratings transitions prove more strongly significant both in 

business-cycle expansions than in recessions and for higher-rated institutions than for lowerrated ones. 

Regulatory discipline includes: memoranda of understanding; cease-and-desist orders; 

removal, prohibition, or suspension of individuals; and notices of intent to terminate insurance 

(see Curry, O’Keefe, Coburn, and Montgomery, 1999; Office of Inspector General, 2003). 

Giving the FDIC responsibility and authority to wind up troubled banks before their tangible net 

worth disappears reduced the role that supervisory failures play in the insolvency-resolution 

process. Now, only banks in extreme distress find destabilizing “gambles for resurrection” an 

attractive strategy. As long as a troubled bank has substantial intangible franchise value to 

preserve, the prospect of prompt and strong regulatory discipline gives managers an incentive to 
5

rebuild their capital or to shop their enterprise to potential acquirers in and out of their 

headquarters state. 

This paper develops statistical evidence that, aside from instances of sudden and severe 

distress, FDICIA enhanced regulatory and failing-bank incentives. The data show a marked 

increase both in examination frequency and in the percentages of problem banks that remedy 

their weaknesses or submit to a private takeover rather than waiting for regulators to pull their 

charter. 

1. Monitoring: Examiner Risk Assessments

Managers of national safety nets are in the risk-acceptance and risk-management 

business. Conducting this business entails repeatedly monitoring client risk exposure, measuring 

and pricing it in a realistic manner, and taking timely steps to rein in excessive or inappropriate 

client risk-taking whenever it is observed (Kane, 1995 and Llewellyn and Mayes, 2003). 

Using data from examinations conducted by Federal Reserve personnel, Hirtle and Lopez 

(1999, p. 2) estimate that data gathered in an on-site examination cease “to provide useful 

information about the current condition of a bank” somewhere between 18 months and three 

years after an examination. Between 1979 and 1986, the mean interval between successive onsite examinations at U.S. commercial banks surged from roughly a year to 609 days (FDIC, 

1997, p. 429). Although the mean interval fell back thereafter, it did not fall to one year again 

until 1993. Of course, at many banks the interval between examinations would have been larger 

than the mean. 

FDICIA now requires that “the appropriate Federal banking agency shall, not less than 

once during each 12-month period, conduct a full-scope, on-site examination of each insured 

depository institution.” However, FDICIA allows state examinations to be substituted for federal 
6

ones in alternating 12-month periods and expands the permissible interval to 18 months for most 

well-capitalized and well-managed institutions with less than $100 million in total assets. 

Subsequently, for banks that receive high examination ratings on their last exam, the Community 

Development and Regulatory Improvement Act of 1994 increased the size threshold to $250 

million. In December 2006, the Financial Services Regulatory Relief Act increased the threshold 

again, this time to $500 million. 

Upon the completion of an exam, examiners assign each bank a composite grade between 

1 and 5. The grade is based on a series of characteristics that together loosely estimate the risk 

that the bank poses to the deposit insurance fund. Banks rated 1 are held to be sound in every 

respect. Banks rated 2 are deemed fundamentally sound, while those rated 3 raise some degree of 

supervisory concern. Banks rated 4 and 5 exhibit unsafe and unsound practices or conditions. 

On-site examination provides regulators with better information than they can obtain 

from merely monitoring financial institutions remotely. However, examiners’ time is limited and 

they must employ tools of forensic accounting. The result is that examiners can only 

approximately rank the fragility and resiliency of individual banks. Still, other things equal, the 

higher the composite score, the worse the condition of the bank. 

Traditionally, five characteristics were scored: capital, asset quality, management, 

earnings, and liquidity. These five component ratings were compiled into a single number called 

the composite “CAMEL” rating. However, opportunities for banks of all sizes to assume 

increasingly complex positions have expanded over time. This additional complexity was 

formally acknowledged in 1997, by adding a sixth component to the rating system—sensitivity 

to market risk (S). Furthermore, this revision to the bank rating system required bank 
7

supervisors to place more emphasis on evaluating risk management processes and practices at 

banks. 

To strengthen the link between a bank’s rating history and the degree of supervisory 

pressure that it should experience, the prompt corrective-action (PCA) provisions of FDICIA 

rely on observable capital ratios. Over time, the deeper and more rapidly a bank’s rating moves 

into adverse territory (ratings classes 3, 4, and 5), the more frequently and intensively that bank 

is apt to be re-examined and the more firmly it will be asked to address identified deficiencies 

(e.g., in asset quality or loss reserving) or to replenish its capital position. Presumably, the 

longer a bank languishes in a problem state, the higher the probability that banking authorities 

will decide to wrest control of its affairs from managers and shareholders. 

Table 1 explores the proportion of insured institutions in each composite rating class that 

failed to experience a re-examination within each of three time intervals following a particular 

exam—12 months, 18 months and 24 months.1

 Appendix A details the types of examinations 

included in our sample. 

Table 1 divides the data into the two size categories by which 1994 legislation defined 

the maximum time span that should pass between exams. For each size category, the table 

compares exam frequency before and after the enactment of FDICIA.2

 

Within both size classes, the decline in the proportion of institutions that are not reexamined in the post-FDICIA period is striking and grows with the length of the interval. 

Differences in these distributions are statistically significant at conventional levels, except for the 

 

1

 Because examination end dates are difficult to determine historically, we use start dates to determine the timing of 

the examinations. On the grounds that they merely extend the initial visit, examinations that occur within 30 days of 

the previous examination are not counted. 

2

 We assume that examination timetables are fully compliant with FDICIA. The FDIC Examination Manual (FDIC, 

2004) defines examination frequencies as the “the length of time between the end of one exam to the start of the 

next.” Data limitations force us to measure examination frequency as the length of time between beginning dates of 

examinations. This will tend to overstate the interval between exams. 
8

poorest-rated category of small banks at the 24-month interval.3

 The largest declines in the 

proportion of institutions that are not-reexamined occur for well-rated institutions. An institution 

can expand its loss exposures and dissipate its capital relatively more quickly today than in the 

past. Sponsors of FDICIA hoped that increasing examiner scrutiny would reinforce the 

discipline that private counterparties exert in derivatives, large-deposit, and subordinated-debt 

markets on troubled banks. 

2. Post-FDICIA Changes in Solvency-Enforcement Strategy 

Before running formal statistical tests comparing the pre- and post-FDICIA periods, it is 

important to explain how FDICIA changed the focus of the solvency-enforcement process. 

FDICIA seeks to overcome political and bureaucratic pressures that might unwisely delay the 

resolution of an economically insolvent institution. Procedures for implementing the Act focus 

on leverage ratios (ratios of bank capital to total assets) that are either calculated from data 

contained in bank Call Reports or established in transmittal reports prepared at the end of an 

examination. Typically, examiners identify a bank as a problem months before its accounting 

capital begins to deteriorate (Office of Inspector General, 2003). 

Clever accounting can temporarily keep losses from registering on Call Reports. It often 

takes examiners more than a single examination cycle to uncover the full extent of ongoing 

patterns of loss concealment. By successfully under-reporting imbedded losses or underreserving for its loss exposures, an economically insolvent institution can avoid breaching PCA 

 

3

 Throughout the paper we use four different tests to test for differences in the distributions: a t-test, an F-test, a 

Chi-squared test and a Kolgomorov-Smirnov (K-S) test. The null hypothesis for the t-test is that the probability in 

the subsample is equal to the probability in the whole sample. This test assumes that the probabilities are derived 

from a standard binomial distribution. We use an F-test to examine the null hypothesis that the variance in the 

subsample is the same as the variance for the whole sample. The null hypothesis for the Chi-squared test is that the 

row in each conditional, or subsample, probability matrix is drawn from the same population. Similarly, the null 

hypothesis for the K-S test is that two rows of the observed transition probabilities are drawn from the same 

population distribution. Results are available from the authors by request. 
9

thresholds or lessen the consequences of a particular breach by understating the needed injection 

of new capital (Office of the Inspector General, 2003). Because troubled banks so frequently 

under-reserve for loan losses, Berger, King, and O’Brien (1991) and Shibut, Critchfield, and 

Bohn (2003) suggest introducing a regression-based adjustment to each bank’s reported loss 

reserves into PCA triggers. Such an adjustment could easily be extrapolated from Call Report 

data on delinquent and nonperforming loans. By drawing on recent and future advances in 

modeling credit risk, this approach could generate improved measures of the true quarterly net 

capital positions of problem banks. 

Under the current system, institutions are classified as “undercapitalized” when their 

reported or examiner-adjusted capital (calculated as a percentage of bank assets) dips below any 

one of the thresholds shown in the third line of Table 2. Institutions that become “significantly 

undercapitalized” can be ordered to recapitalize promptly. However, to provide an opportunity 

for consultation, formal orders are preceded by a letter stating the regulatory agency’s intent to 

issue a “PCA Directive”. The PCA Directive imposes specified proscriptions on the bank and 

requires its managers to file a satisfactory plan for restoring its capital to benchmarked levels 

within 60 days of the effective date of the Directive. In most cases, the institution has two weeks 

either to accept the Directive or to schedule an administrative hearing. When issued, the 

Directive notifies the bank that, if after 120 days it has not managed to increase the designated 

leverage ratios as required, it must immediately take “the necessary action” to find an acquirer or 

merger partner. Institutions whose tangible equity falls below two percent are deemed “critically 

undercapitalized.” PCA Directives sent to these firms have a shorter fuse and impose more 

proscriptions. 
10

FDICIA allows even strongly rated banks to be closed or taken over. Whenever serious 

accounting irregularities are discovered that, once corrected, cause the capital of the institution to 

drop below the “critically undercapitalized” threshold, the offending institution can be closed 

immediately. Accounting fraud and depositor runs can short-circuit PCA triggers. Losses to the 

deposit insurance fund in sudden failures (which dominate post-FDICIA failures) are very high. 

Ordinarily, the failure process begins with the issuance of a “Failing Bank Letter” by the 

bank’s chartering authority to the FDIC. To encourage competing bids, the FDIC markets the 

failing bank or thrift widely to potential acquirers. Although individual customers and 

speculators might sense the institution’s growing weakness, its failing status is not revealed to 

the general public. FDIC personnel assemble an information package for potential bidders 

(FDIC, 1998, p. 6). Part of the information package is an asset-valuation review. Alternate 

resolution structures are studied and an on-site analysis is undertaken to prepare for the possible 

closing. A formal information meeting is held to discuss the details of the failing institution with 

the set of approved bidders.4

 According to the FDIC, if the process results in a supervisory 

closure, it is “generally carried out in 90 to 100 days, not including the post-closing settlement 

timeframes” (FDIC, 1998, p. 76). 

3. Markov Transition Matrices: Preliminary Evidence

This study seeks to infer how post-FDICIA examination and resolution protocols altered 

incentives for regulators and shareholders of banks in different CAMELS ratings classes. To do 

 

4

 Potential acquirers submit bids in two parts: the first amount is the premium for the franchise value of the failed 

institution’s deposits, and the second amount covers either all or whatever part of the institution’s assets the bidder 

prefers. Bids are forwarded to FDIC headquarters, where they are compared and a least-cost determination is made. 
11

this, it studies rating transitions observed during 1984 to 2005 in completed exams across 12-

month, 18-month, and 24-month horizons.5 

Our analysis investigates how transition frequencies vary when the data are partitioned in 

interesting ways. To compare any pair of matrices, we focus on their main diagonals and two 

principal subdiagonals. The subdiagonal immediately above the main diagonal (the “upper 

principal subdiagonal”) records the frequency of one-class downgrades. The subdiagonal 

immediately below the main diagonal (the “lower principal subdiagonal”) records the frequency 

of receiving a one-class upgrade. 

Tables 3, 4, and 5 highlight differences in Markov transition matrices observed before 

and after FDICIA became effective in 1992. The rows of each matrix display the frequency 

distributions for transitions experienced by banks whose previous rating is indicated by the row 

label. To allow for all possibilities, the columns span not only each rating class, but also three 

absorbing states in which a bank formally ceases to exist6 and two other states that cover the 

possibility that a second examination did not begin during the horizon in question. Even though 

the data indicate that many banks with initial ratings of 1 to 4 did not experience the beginning of 

a new examination within a given time interval, the fraction of banks that were not re-examined 

in these classes declines noticeably after FDICIA. 

For banks with more than $250 million in assets (“large banks”), Table 3 displays the 

frequency distribution of one-year ratings transitions observed before and after FDICIA became 

effective in 1992. Although underlying transition probabilities are bound to vary over time with 

macroeconomic and industry conditions, these observed frequencies can be interpreted as 

estimates of average probabilities within each era. For completed exams at large banks, the odds 

 

5

 If multiple examinations occur within the selected horizon, we record the rating given on the last exam. 

6

 Disappearance can occur in either of three ways: a regulatory closure; a voluntary merger into an unconnected 

enterprise; or a “rollup” in which the bank is merged into a holding-company affiliate. 
12

of keeping the same rating in successive exams, is shown on the main diagonals. In both eras, it 

is unusual for a large bank to move up or down more than one class when it is re-examined. This 

is shown by the unshaded cells in the matrix. Kolmogorov-Smirnov and Chi-squared tests 

establish that, at better than one percent significance, every row of the pre-FDICIA matrix is 

different from the post-FDICIA matrix7

 

Three differences stand out from the table. First, the probability of receiving the same 

rating in the subsequent examination becomes significantly higher in the post-FDICIA era. 

Second, in part because the performance of both the economy and the banking industry was 

stronger after FDICIA than it had been before its passage, banks in the first four categories prove 

substantially more likely to be upgraded than in the past, as shown by the lower principal 

subdiagonals. Nevertheless, the likelihood of receiving a downgrade is more or less the same, as 

shown by the upper principal subdiagonals. Third, although the percentage of problem banks 

that are closed by the regulators approximately equals that of the pre-FDICIA period, the 

percentage of banks that consent to a voluntary merger is more than twice as high. We 

investigate later whether this effect may have been reinforced by the passage of the Interstate 

Banking and Branching Efficiency Act, which made interstate takeovers easier to solicit after 

1994. 

The increase in the frequency of one-step upgrades and voluntary mergers after FDICIA 

at large banks becomes more pronounced when we extend horizon for the transition matrices to a 

two-year horizon as shown in Table 4. Furthermore, one-step downgrades become notably less 

 

7

 According to the K-S test, for each row, the null hypothesis that the observed transition probabilities in the preFDICIA period were drawn from the same population as those in the post-FDICIA era is rejected at one percent 

significance. According to the Chi-squared test, for each row, the null hypothesis that the pre-FDICIA transition 

probabilities are drawn from the same population as the post-FDICIA transition probabilities is also rejected at the 

one percent level. 
13

frequent after FDICIA. This may occur because the longer window allows for the completion of 

a large proportion of more challenging exams. 

Similar patterns emerge for small banks using an 18-month observations window as 

shown in Table 5. In contrast to large banks, the odds of keeping the same rating are higher in 

the post-FDICIA period only for 1- and 2-rated banks. As in the case for large banks, upgrades 

become notably more common and downgrades become somewhat less frequent for all ratings 

transitions during the post-FDICIA era. Also, mergers provide a more frequent destination. 

Notably, for small banks over this longer horizon, the percentage of banks in the three lowestrated categories that have not been re-examined becomes very small in the post-FDICIA period. 

Because banking problems are negatively correlated with national (and local) economic 

growth and positively correlated with sectoral volatility, variations in growth and volatility may 

exert an important influence on the transition probabilities. During the 1992 to 2005 era, these 

factors were favorable, so that the overall incidence of low-rated institutions declined. In the 

next section, we show that the increased reliance on quasi-voluntary mergers to resolve problem 

banks remains evident when pre-FDICIA and post-FDICIA data are segregated by proxies for 

the health of the national and local economic environments. 

4. Effects of National Economic Conditions on Ratings Transitions

To disentangle the effects of differences due to national and local economic conditions 

from changes due to increased supervisory discipline after FDICIA, in this section and the next 

we reduce the dimensions of our analysis by consolidating the three absorbing states into a single 

state of “absorption” and eliminating post-period and not-rated observations. We do this because 
14

the resulting the 5 x 5 square transition matrices are less sensitive to horizon length and can be 

analyzed in powerful ways. 

First we examine the transition matrices during recession periods and expansion periods 

at an 18-month interval for all insured institutions as shown in Table 6. The frequency of 

receiving the same rating is similar in recessions and expansion. The major differences occur in 

the probability of an upgrade along the lower partial subdiagonal and in the probability of 

absorption. During recessions, upgrades become less likely and absorptions more likely, but the 

frequency of downgrades rises only slightly.8

Next we contrast the transition matrices generated by splitting the pre- and post-FDICIA 

periods between observations that occurred during an expansion and during a recession, as 

shown in Tables 7 and 9. For both small and large banks, the probability of being upgraded rises 

after FDICIA during expansions and recessions alike. Although we illustrate only for the 

examination intervals that are most relevant to small and large banks, the same pattern emerges 

at other intervals. Results from Kolmogorov-Smirnov tests indicate that, in general, the 

differences in the transition matrices are more statistically significant along the pre- and postFDICIA dimension than along the expansion and recession dimension. This is shown in Tables 8 

and 10. Furthermore, post-FDICIA differences are more strongly significant in expansions than 

in recessions and among higher-rated institutions. This supports the better-incentives hypothesis, 

because in these circumstances bank managers should find it less costly to respond to examiner 

criticisms. 

 

8

 We should note that the table categorizes examination activity into business-cycle stage if both the beginning and 

ending examination occur within the same business-cycle stage. Because both recessions occurring during this 

period were only nine months long, much shorter than the length of the expansions, this definition results in an 

imbalance in the size of the subsamples—assigning ten times as many observations to expansions than to recessions. 

To investigate the effects of the imbalance, we also studied results for subsamples based only on whether the initial 

exam took place in a recession or expansion. The results were similar. 
15

To examine further the effects of the national economy on the transitions, we look at the 

ratings transitions from a survival analysis perspective. For each ratings class, Table 11 

compares the mean and standard deviation of the number of months that elapse before a bank 

undergoes a ratings change or absorption before and after FDICIA. Within all five CAMELS 

classes, both the mean and the standard deviation of the number of months decline substantially. 

The same pattern emerges across ratings classes for small and large banks taken separately. 

The estimated empirical survival function is displayed in Figures 1 and 2. Treating 

expansion and recession periods separately, each curve plots the estimated probability that an 

institution stays in the same rating class against the number of months it has previously remained 

in that class. In both stages of the business cycle, the post-FDICIA survival functions begin 

above their pre-FDICIA counterparts and truncate sharply instead of developing a long tail. 

Consistent with the dictates of the Prompt Corrective Action provisions of FDICIA, postFDICIA survival functions truncate much earlier in recessions than in expansions. Irrespective 

of whether we apply a log-rank, Wilcoxon, or log-likelihood ratio (LLR) test, the differences 

between the pre- and post-FDICIA survival functions is significant at one percent. 

Similar differences emerge when we construct survival functions along other dimensions. 

When we compare the survival function for pre-FDICIA to post-FDICIA for each size class, the 

curves differ significantly at one percent by all three tests for each business-cycle stage. If we 

then consider the survival function for each ratings class separately, differences are less strongly 

significant. The difference between pre- and post-FDICIA survival functions during expansion 

periods are significantly different at one percent according to the LLR test and at 5 percent or 

better according to the Wilcoxon test. In contrast, during recession periods, differences are never 

statistically significant for institutions rated CAMELS 1 and 5. For institutions rated CAMELS 
16

2, 3, and 4, differences remain statistically significant at one percent for two of the three tests. 

The failure to find significant differences in the transition probabilities facing a 5-rated 

institution in recession implies that forbearance lives on and helps to explain delays in resolving 

zombie institutions like Indymac and Washington Mutual in 2007-08. 

5. Effects of Local Economic Growth on Ratings Transitions

Conventional wisdom holds that small banks might be more sensitive to local economic 

growth than to national macroeconomic experience. This leads us to investigate whether and 

how pre-FDICIA and post-FDICIA ratings transitions differ when we control for local economic 

conditions. 

To measure local economic conditions we chose to look at the growth of inflationadjusted personal income in an institution’s headquarters state. We first calculated quarterly 

year-over-year growth rates for real personal income in each state over the 1984 to 2006 period. 

Within each state we partition the growth rates into quartiles. This variable indicates how strong 

growth in real personal income is in the current quarter is relative to growth over the entire time 

period. For example, growth in the first quartile (minimum to the 25th percentile) would be 

representative of relatively weak growth, whereas growth in the fourth quartile (75th to maximum 

growth) would be relatively strong growth. Finally, we matched each ratings transition with the 

quartile in which that bank’s home-state growth rate lay in the quarter preceding the transitioning 

exam date. 

When we control for local economic growth in this manner, our results generally hold. 

Tables 12 and 13 compare pre-FDICIA and post-FDICIA transition matrices using a one-year 

horizon for large banks and an 18-month horizon for small ones. In each quartile with few 
17

exceptions, the post-FDICIA era has seen upgrades become more likely, downgrades become 

less likely, and rates of absorption fall. Using a Kolmogorov-Smirnov test, the differences prove 

significant at five percent or better for 19 of 20 corresponding rows in the small-bank sample, 

but for only four rows in the large-bank sample. Interestingly, three of the significant large-bank 

differences are found in the most adverse situations. They relate to banks rated 3, 4, and 5 

operating in the lowest growth quartile. 

These results confirm the improved-incentives hypothesis for small banks across the 

board and for the critical class of poorly rated large banks facing difficult local circumstances. 

6. Voluntary Mergers and the Interstate Banking and Branching Efficiency Act

As discussed above, the percentage of banks that consent to a voluntary merger is higher 

in the post-FDICIA period even after controlling for national and local economic conditions. 

One possible explanation for the increase in voluntary mergers is that the passage of the 

Interstate Banking and Branching Efficiency Act (IBBEA) made interstate takeovers easier to 

solicit after 1994. IBBEA authorizes adequately capitalized and well-managed bank holding 

companies to acquire banks in any state. Furthermore, the Act allows interstate mergers between 

adequately capitalized and well-managed banks beginning in June 1997. 

To assess the impact of IBBEA, we investigate the extent to which roll-ups within a bank 

holding company and mergers with targets outside the holding company occurred in different 

states during the pre- and post-FDICIA period. If the IBBEA were driving the increase in the 

voluntary mergers, we would expect that out-of-state mergers would be the major form of 

mergers during the post-1994 period. Figures 3 and 4 show that in-state roll-ups and mergers 

dominate the number of voluntary mergers in all periods. Although the number of out-of-state 
18

mergers and roll-ups increased, the number of in-state mergers increased even more. This is 

evidence that the increasing incidence of voluntary mergers is rooted in more than the IBBEA. 

7. Differences in Transition Frequencies at Different Supervisory Agencies

 Tables 14 through 17 investigate whether the transition matrices differ across the 

different regulators. Although four federal agencies share a responsibility for financial stability, 

their precise missions, supervisory clienteles, and incentive conflicts differ in important respects. 

The Federal Reserve’s prime mission is to stabilize the macroeconomy and watch over the 

purchasing power of the dollar. Its special clientele consists of large financial holding 

companies and state-chartered member banks. The FDIC’s mission is to resolve insolvent banks 

and thrifts and to protect the integrity of its deposit-insurance fund. Its special clientele includes 

nonmember state-chartered banks (“community banks”) and state banking supervisors. The 

Office of the Comptroller of the Currency (OCC) oversees the safety, soundness, and activities 

of national banks and their operating subsidiaries. Its special clientele may be described as 

money-center and regional banks. The Office of Thrift Supervision (OTS) supervises savings 

and loan associations, federal savings banks, and thrift holding companies. Realistically, its 

mission includes – and even stresses – the task of enhancing the availability of mortgage credit. 

That significant differences emerge across agencies in the top two ratings classes and in 

the treatment of small institutions generally is shown in Tables 15 and 17. However, it should be 

noted that the sample contains many more observations for the FDIC than for the Federal 

Reserve, OCC, or OTS. Non-FDIC observations are unbalanced in time and by cycle stage as 

well. For example, at the 18-month interval for the Fed, our dataset records only 833 

observations in pre-FDICIA expansions and 266 observations in pre-FDICIA recessions. The 
19

corresponding sample cells for the OCC contain only 587 and 157 observations respectively; 

OTS counts are larger: 1,915 and 791, respectively. 

Table 18 shows that when we control only for business-cycle stage and the enactment of 

FDICIA, differences in the frequency distributions are significant at 5 percent or better for all 10 

rows at the FDIC, and for 8 of the 10 rows at the OCC, but only for 3 out of the 10 rows at both 

the Fed and OTS. This is consistent with the hypothesis that their more-complex missions 

undercut supervisory incentives at the latter two agencies. 

8. Effects on the Sequencing of Rating Transitions

Our final partition investigates the sequencing of upgrades and downgrades across 

successive examinations. For banks that receive a completed examination within the indicated 

intervals, Tables 19 and 20 show the conditional probabilities that apply pre-FDICIA and postFDICIA to large banks and small banks, respectively. In both tables, post-FDICIA changes in 

probabilities show identical patterns: (1) upgrades become less likely to follow upgrades; (2) 

upgrades become more likely to follow downgrades; and (3) downgrades become less likely to 

follow downgrades. These changes are statistically significant and further support the betterincentives hypothesis. The first pattern may be interpreted as a diminution of possible “halo” 

effects. The second and third show that banks that suffer downgrades are more promptly curing 

the deficiencies that an exam uncovers than they had in the past. 

9. Summary of Policy Implications

O’Keefe and Dahl (1996) found that increases in examination frequency induced by 

FDICIA made CAMELS ratings more reliable indicators of bank condition. Data reviewed in 
20

this paper show that the character and quality of bank supervision in the United States also 

improved in the years following the enactment of FDICIA. During business-cycle expansions, 

our data strongly support the better-incentives hypothesis. Giving supervisors the authority and 

the obligation to wind up troubled banks before their accounting net worth can be exhausted 

helped to make banks respond more promptly to examiner criticism and to lessen the strength of 

go-for-broke incentives at troubled banks. 

In 2007-08, FDICIA protocols have been tested by a deep and long-lasting 

macroeconomic slowdown. It turns out that the timeliness of regulators’ PCA triggers is 

weakened by relying on risk-weighted measures of capital adequacy and by accounting estimates 

of on-balance-sheet net worth rather than broader economic measures of bank capital. 

Nevertheless, during the post-FDICIA era, banks became more concerned with earning a 

favorable CAMELS rating than they had been previously. As opposed to making endgame 

gambles for resurrection or languishing in a problem state until regulators finally pull the plug, 

much larger proportions of problem banks did successfully rehabilitate themselves and preserved 

intangible value by searching out private takeover partners. 
21

References 

Berger, Alan, Katherine King, and James O’Brien, 1991. The Limitations of Market-Value 

Accounting and a More Realistic Alternative. Journal of Banking and Finance 15, 753-

783. 

Curry, Timothy J., John P. O’Keefe, Jane Coburn, and Lynne Montgomery, 1999. Financially 

Distressed Banks: How Effective Are Enforcement Actions in the Supervision Process? 

FDIC Banking Review 12, No. 2, 1-18. 

Federal Deposit Insurance Corporation, 1998. Resolution Handbook: Methods for Resolving 

Troubled Institutions in the United States. Washington: FDIC. 

________, 2004. Risk Management Manual of Examination Policies. Division of Supervision 

and Consumer Protection. Washington: FDIC. December. 

Hirtle, Beverly, and José A. Lopez, 1999. Supervisory Information and the Frequency of Bank 

Examinations. FRBNY Economic Policy Review April, 1-19. 

Kane, Edward J., 1989. Changing Incentives Facing Financial-Services Regulators. Journal of 

Financial Services Research 2 (September), 265-274. 

Kane, Edward J., 1995. Three Paradigms for the Role of Capitalization Requirements in Insured 

Financial Institutions. Journal of Banking and Finance 19 (June), 431-459. 

Kaufman, George, and Robert Litan (Eds.), 1997. FDICIA: Bank Reform Five Years Later and 

Five Years Ahead. JAI Press. 

Llewellyn, David T., and David G. Mayes, 2003. The Role of Market Discipline in Handling 

Problem Banks. Helsinki: Bank of Finland Discussion Paper No. 21/2003. 

Office of Inspector General, Federal Deposit Insurance Corporation, 2003. The Role of Prompt 

Corrective Action as Part of the Enforcement Process. Audit Report No. 03-038 

(September 12). 

O’Keefe, John, and Drew Dahl, 1996. The Scheduling and Reliability of Bank Examinations: 

 The Effect of FDICIA. Washington: FDIC (unpublished working paper). 

Shibut, Lynn, Tim Critchfield, and Sarah Bohn, 2003. Differentiating Among Critically 

 Undercapitalized Banks and Thrifts. FDIC Banking Review 15 (No. 2), 1-38. 
22

Appendix A 

Types of Examinations Included in Source Data 

The source data covers the period from 1984 to 2005. The Pre-FDICIA period is defined as 1984 to 1991 and the Post-FDICdefined as 1992-2005. 

Description 

Years 

Observed Number of Examinations Percent of Exam

Examination conducted by: Pre-FDICIA Post-FDICIA Total Pre-FDICIA Post-FD

State Banking Authorities 1984–2005 19,278 36,643 55,921 40.28 FDIC 1984–2005 21,276 25,117 46,393 44.46 Federal Reserve or OCC 1984–2005 398 25,843 26,241 0.84 OTS 1989–2005 777 11,079 11,856 1.62 Joint Examinations 1984–2005 2,753 5,253 8,006 5.75 Concurrent Examinations 1984–1992 3,373 2,354 5,727 7.05 

Total 47,855 106,289 154,144 100.00 . 
23

Table 1 

Percentage of Institutions that Did Not Undergo a Complete Re-Examination

This table provides evidence on the percentage of large and small insured institutions in each composite rating class that did not undergexamination in the three indicated intervals before and after FDICIA. Small institutions are defined as institutions with less than $250 institutions are those with at least $250 million in assets. The pre-FDICIA period is defined as 1984 to 1991. The post-FDICIA period 2003. 

Panel A: Large Institutions 

Pre-FDICIA Period 

Composite Rating Number of Observations Within 12 Months Within 18 Months 

1 421 82.19 59.62 2 1,398 73.18 50.07 3 553 67.81 34.36 4 438 62.10 21.69 5 318 50.94 16.67 

Post-FDICIA Period 

Composite Rating Number of Observations Within 12 Months Within 18 Months 

1 7,790 65.64 6.63 2 9,537 64.28 7.52 3 1,153 55.42 10.13 4 488 45.49 13.46 5 200 32.50 10.00 

Panel B: Small Institutions 

Pre-FDICIA Period 

Composite Rating Number of Observations Within 12 Months Within 18 Months 

1 8,051 70.91 43.71 2 20,659 69.45 42.52 3 8,531 50.87 19.68 4 5,562 44.77 12.69 5 1,675 31.64 8.42 

Post-FDICIA Period 

Composite Rating Number of Observations Within 12 Months Within 18 Months 

1 28,290 78.39 35.98 2 47,376 70.01 27.75 3 8,547 43.62 7.52 4 2,810 34.91 7.14 5 657 25.39 6.58 
24

Table 2 

Prompt Corrective Action Categories 

The Prompt Correction Action categories are provided in the FDIC Rules and Regulations. To be considered well capitalized, an ins

subject to any formal enforcement action that requires it to meet and maintain a certain capital level. If the bank has a composite CAthe most recent examination and is not experiencing or anticipating significant growth, then the leverage ratio can be as low as 3 perc

Adequately Capitalized and Undercapitalized categories. 

Total Risk-Based 

Capital Ratio 

Tier 1 Risk-Based 

Capital Ratio Leverage Ratio 

Well Capitalized 10 percent or higher and 6 percent or higher and 5 percent or higher Adequately Capitalized 10 percent or higher and 4 percent or higher and 4 percent or higher Undercapitalized Less than 8 percent or Less than 4 percent or Less than 4 percent

Significantly Undercapitalized Less than 6 percent or Less than 3 percent or Less than 3 percent Critically Undercapitalized 
25

Table 3 

One-Year Transition Matrix for Large Institutions

This table provides the one-year transition matrix for composite examination ratings assigned in 1984 to 2003 to large FDICinstitutions. The transition probabilities are expressed in percent. Large institutions are defined as those with at least $250 massets. The Pre-FDICIA period is defined as 1984 to 1991 and the post-FDICIA period is defined as 1992 to 2003. “Mergevoluntary merger with an institution outside a bank’s holding company. A roll-up is a merger between two entities within a 

company. “Post-period” refers to the case where the institution was rated within the time horizon but the time horizon did n

after the end of the period. 

Pre-FDICIA Period 

1 2 3 4 5 Failure Merger 

Roll-Up Not 

Rated 

1 12.59 2.38 0.00 0.00 0.00 0.00 0.71 0.48 82.19 2 1.79 16.45 1.65 0.57 0.07 0.00 1.22 0.72 73.18 

3 0.00 4.88 14.47 2.71 0.72 0.00 1.81 1.08 67.81 

4 0.00 0.46 2.97 14.38 5.25 0.46 1.37 1.14 62.10 

5 0.00 0.00 0.94 2.83 9.12 23.27 1.57 1.26 50.94 

Post-FDICIA Period 

1 2 3 4 5 Failure Merger 

Roll-Up Not 

Rated 

1 24.42 3.52 0.13 0.03 0.00 0.00 2.20 2.13 65.64 2 3.62 23.31 1.05 0.20 0.03 0.01 2.67 2.28 64.28 

3 0.00 18.13 15.96 2.52 0.35 0.00 3.64 1.99 55.42 

4 0.00 3.48 16.19 23.16 5.12 0.61 3.69 2.05 45.49 5 0.00 0.00 1.50 12.50 24.50 24.00 3.50 1.00 32.50 

. 
26

Table 4 

Two-Year Transition Matrix for Large Institutions

This table provides the two-year transition matrix for composite examination ratings assigned in 1984 to 2003 to large FDIC

institutions. The transition probabilities are expressed in percent. Large institutions are defined as those with at least $250 massets. The Pre-FDICIA period is defined as 1984 to 1991 and the post-FDICIA period is defined as 1992 to 2003. “Mergevoluntary merger with an institution outside a bank’s holding company. A roll-up is a merger between two entities within a 

company. “Post-period” refers to the case where the institution was rated within the time horizon but the time horizon did n

after the end of the period. 

Pre-FDICIA Period 

1 2 3 4 5 Failure Merger 

Roll-Up Not 

Rated 

1 31.35 12.83 0.24 0.71 0.00 0.00 2.38 0.95 43.23 2 4.15 33.33 6.80 3.43 0.43 0.07 3.08 1.29 34.98 

3 0.18 15.01 25.14 10.31 3.80 0.54 3.44 1.27 22.78 

4 0.00 2.05 8.68 27.17 14.61 3.88 4.57 2.05 10.50 

5 0.00 0.94 3.77 6.29 16.98 36.79 2.52 2.20 6.29 

Post-FDICIA Period 

1 2 3 4 5 Failure Merger 

Roll-Up Not 

Rated 

1 68.35 10.72 0.33 0.01 0.00 0.00 3.77 3.78 2.93 2 12.21 61.43 2.64 0.41 0.08 0.02 4.72 4.03 3.45 

3 0.83 45.99 24.42 5.53 0.37 0.00 5.81 2.86 6.54 

4 0.63 15.66 31.32 24.01 6.89 1.04 6.68 3.76 7.52 

5 0.50 2.01 12.56 25.63 21.11 25.13 6.03 1.51 4.02 
27

Table 5 

18-Month Transition Matrix for Small Institutions

This table provides the 18-month transition matrix for composite examination ratings assigned in 1984 to 2003 to small FDI

institutions. The transition probabilities are expressed in percent. Small institutions are defined as those with less than $250 total assets. The Pre-FDICIA period is defined as 1984 to 1991 and the post-FDICIA period is defined as 1992 to 2003. “Mto a voluntary merger with an institution outside a bank’s holding company. A roll-up is a merger between two entities with

company. “Post-period” refers to the case where the institution was rated within the time horizon but the time horizon did nafter the end of the period.

Pre-FDICIA Period 

1 2 3 4 5 Failure Merger 

Roll-Up Not 

Rated 

1 35.93 10.53 0.56 0.11 0.00 0.04 1.55 0.68 43.71 2 4.45 36.83 4.53 1.06 0.18 0.03 1.80 0.64 42.52 

3 0.21 24.65 33.90 8.77 0.81 0.23 1.92 0.68 19.68 

4 0.00 4.17 20.78 38.85 9.30 2.36 2.36 0.47 12.69 

5 0.00 0.72 3.04 11.58 29.19 32.24 3.88 0.90 8.42 

Post-FDICIA Period 

1 2 3 4 5 Failure Merger 

Roll-Up Not 

Rated 

1 48.44 9.42 0.30 0.04 0.01 0.00 2.19 1.91 35.98 2 8.95 51.95 3.20 0.44 0.06 0.03 2.34 1.72 27.75 

3 0.63 43.73 33.52 4.75 0.38 0.10 2.99 1.34 7.52 

4 0.07 13.05 35.23 28.31 5.52 0.61 5.73 1.48 7.14 5 0.61 4.59 11.03 21.75 22.97 21.75 6.74 2.14 6.58 
28

Table 6 

Transition Matrix for All FDIC-Insured Institutions During Business Cycle Periods 

This table provides the 18-month transition matrix for composite examination ratings assigned in 1984 to 2003 to all FDIC-institutions. The transition probabilities are expressed in percent. Recessions and expansions are defined by NBER busines

and troughs. Transitions are counted only for the transitions in which both end-points occur on the same side of an NBER-dbusiness-cycle peak or trough. Absorption includes failures, mergers within a bank holding company, and mergers with a bthe holding company. 

Recession Periods 

1 2 3 4 5 Absorption Total 

1 72.76 16.06 0.53 0.11 0.00 10.54 100.00 2 7.14 70.82 8.03 1.87 0.38 11.76 100.00 

3 0.09 30.07 47.10 9.63 1.53 11.58 100.00 

4 0.34 3.21 22.17 50.08 10.15 14.04 100.00 

5 0.00 0.44 1.31 11.35 35.37 51.53 100.00 

Expansion Periods 

1 2 3 4 5 Absorption Total 

1 77.07 15.36 0.55 0.08 0.01 6.93 100.00 2 12.26 74.48 5.54 0.99 0.15 6.58 100.00 

3 0.45 43.48 41.70 8.39 0.87 5.21 100.00 

4 0.04 8.21 31.46 42.42 9.81 8.06 100.00 

5 0.14 1.91 6.34 17.77 31.25 42.58 100.00 
29

Table 7 

Transition Matrix for Small Institutions During Business Cycle Periods 

This table provides the 18-month transition matrix for composite examination ratings assigned in 1984 to 2003 to small FDI

institutions. The transition probabilities are expressed in percent. Small institutions are defined as those with less than $250 assets. The Pre-FDICIA period is defined as 1984 to 1991 and the post-FDICIA period is defined as 1992 to 2003. Recessioexpansion periods are defined by NBER business-cycle peaks and troughs. Absorption includes failures, mergers within a bcompany, and mergers with a bank outside the holding company

Pre-FDICIA Expansion Period 

 1 2 3 4 5 Absorption T

1 72.44 21.86 1.27 0.25 0.04 4.15 2 10.30 73.39 9.12 2.21 0.38 4.60 

3 0.36 34.70 48.03 11.90 1.06 3.95 

4 0.00 5.30 26.60 50.59 11.09 6.43 

5 0.00 1.18 3.74 15.39 36.32 43.36 

Post-FDICIA Expansion Period 

 1 2 3 4 5 Absorption T

1 77.69 15.45 0.49 0.07 0.02 6.28 2 12.84 75.83 4.82 0.68 0.09 5.74 

3 0.71 49.76 38.65 5.38 0.44 5.05 

4 0.08 14.71 38.99 31.44 6.04 8.74 

5 0.67 5.18 12.02 23.71 25.04 33.39 

Pre-FDICIA Recession Period 

 1 2 3 4 5 Absorption T

1 69.49 23.19 1.63 0.31 0.08 5.29 2 9.44 70.01 11.00 3.24 0.69 5.62 

3 0.20 29.41 53.36 10.98 0.60 5.46 

4 0.10 4.03 25.78 54.18 9.67 6.24 

5 0.00 1.32 1.85 15.61 38.36 42.86 

Post-FDICIA Recession Period 

 1 2 3 4 5 Absorption T

1 77.83 17.42 0.51 0.09 0.03 4.12 2 8.92 79.20 6.93 0.92 0.06 3.97 

3 0.00 38.82 46.11 9.17 0.88 5.03 

4 0.65 6.54 39.87 35.29 6.54 11.11 

5 0.00 0.00 11.11 44.44 27.78 16.67 
30

Table 8 

Kolmogorov-Smirnov Test Results 

Transition Matrix for Small Institutions During Business Cycle Periods 

This table provides the results of Kolmogorov-Smirnov (K-S) tests applied to the 18-month transition matrix for the composite examination ratings assigned in 1984 to 2003 to small FDIC-Insurred Institutions. Small institutions are with less than $250 million in total assets. The Pre-FDICIA period is defined as 1984 to 1991 and the post-FDICIA as 1992 to 2003. Recession and expansion periods are determined by the NBER business-cycle peaks and troughs. null hypothesis for the K-S test is that the row probabilities for the two groups are drawn from the same distribution. *=Can reject the null hypothesis at the 90% confidence level, **=95%, ***=99% 

Pre-FDICIA Expansion vs. Post-FDICIA Expansion Pre-FDICIA Recession vs. Post-FDICIA Recess

1 *** 1 *** 2 *** 2 *** 

3 *** 3 *** 4 *** 4 *** 5 *** 5 ** 

Pre-FDICIA Expansion vs. Pre-FDICIA Recession Post-FDICIA Expansion vs. Post-FDICIA Reces

1 1 2 *** 2 *** 3 *** 3 *** 4 4 5 5 
31

Table 9 

Transition Matrix for Large Institutions During Business Cycle Periods 

This table provides the one-year transition matrix for composite examination ratings assigned in 1984 to 2003 to large FDIC-Insuretransition probabilities are expressed in percent. Large institutions are defined as those with at least $250 million in total assets. Th

is defined as 1984 to 1991 and the post-FDICIA period is defined as 1992 to 2003. Recession and expansion periods are defined by cycle peaks and troughs. Absorption includes failures, mergers within a bank holding company, and mergers with a bank outside th

Pre-FDICIA Expansion Period 

 1 2 3 4 5 Absorption 

1 61.54 22.22 2.56 0.85 0.00 12.82 2 7.60 67.30 10.84 5.13 0.95 8.17 

3 0.00 20.82 51.02 15.10 4.90 8.16 

4 0.00 2.41 18.47 51.00 18.47 9.64 

5 0.00 0.49 2.93 11.22 29.27 56.10 

Post-FDICIA Expansion Period 

 1 2 3 4 5 Absorption 

1 76.20 11.59 0.39 0.07 0.00 11.75 2 10.31 72.53 3.35 0.58 0.08 13.16 

3 0.00 42.27 37.80 6.52 0.74 12.66 

4 0.00 6.14 30.32 42.24 9.75 11.55 

5 0.00 0.00 2.21 19.12 36.76 41.91 

Pre-FDICIA Recession Period 

 1 2 3 4 5 Absorption 

1 40.74 25.93 0.00 7.41 0.00 25.93 2 3.42 55.48 23.97 10.27 0.68 6.16 

3 0.00 16.87 32.53 25.30 15.66 9.64 

4 0.00 1.05 9.47 52.63 26.32 10.53 

5 0.00 1.10 3.30 5.49 26.37 63.74 

Post-FDICIA Recession Period 

 1 2 3 4 5 Absorption 

1 80.81 13.41 0.22 0.00 0.00 5.56 2 7.79 81.02 3.90 0.50 0.10 6.69 

3 0.00 41.18 40.00 8.24 2.35 8.24 

4 0.00 5.56 16.67 33.33 27.78 16.67 

5 0.00 0.00 0.00 0.00 0.00 100.00 
32

Table 10 

Kolmogorov-Smirnov Test Results 

Transition Matrix for Large Institutions During Business Cycle Periods

This table provides the results of Kolmogorov-Smirnov (K-S) tests applied to the one-year transition matrix for the composite examination ratings assigned in 1984 to 2003 to large FDIC-Insured Institutions. Large institutions are thwith at least $250 million in total assets. The Pre-FDICIA period is defined as 1984 to 1991 and the post-FDICIA pas 1992 to 2003. Recession and expansion periods are determined by the NBER business-cycle peaks and troughs. null hypothesis for the K-S test is that the row probabilities for the two groups are drawn from the same distribution. *=Can reject the null hypothesis at the 90% confidence level, **=95%, ***=99% 

Pre-FDICIA Expansion vs. Post-FDICIA Expansion Pre-FDICIA Recession vs. Post-FDICIA Reces

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

Pre-FDICIA Expansion vs. Pre-FDICIA Recession Post-FDICIA Expansion vs. Post-FDICIA Rec

1 1 *** 2 *** 2 *** 3 *** 3 4 4 5 5 
33

Table 11 

Number of Months until FDIC-Insured Banks Undergo a Change in State 

This table provides the number of until FDIC-Insured Banks undergo a change in state which is defined as either a ratings changAbsorption includes failures, mergers within a bank holding company, and mergers with a bank outside the holding company. Tpresented by CAMELS rating class. The Pre-FDICIA Period is defined as 1984 to 1991 and the post-FDICIA period is defined 

 1 2 3 4  PreFDICIA Post- FDICIA Pre- FDICIA Post- FDICIA Pre- FDICIA Post- FDICIA Pre- FDICIA Post- FDICIA P

FD

Mean 75.40 51.21 65.38 45.58 28.22 19.71 26.39 19.13 19Standard Deviation 67.85 40.42 52.61 36.18 22.74 15.19 19.48 16.03 24Number of Observations 3,624 9,076 9,609 13,650 5,348 4,316 3,237 1,187 1,
34

Table 12 

Transition Matrix for Large Institutions by Local Economic Conditions

This table provides the one-year transition matrix for composite examination ratings assigned in 1984 to 2003 to large FDIC-Insured inprobabilities are expressed in percent. Large institutions are defined as those with at least $250 million in total assets. The Pre-FDICIA 

to 1991 and the post-FDICIA period is defined as 1992 to 2003. State income growth is the quarterly year-over-year growth in inflatioincome in the state in which in the institution is headquartered. The growth rates are calculated over the 1984 to 2006 period and partitfirst quartile of state personal income growth, representing the weakest growth, is the minimum to the 25th percentile, the second quarti

the third quartile is the 50th to the 75th percentile and the fourth quartile is the 75th to the maximum, representing the strongest growth.

Pre-FDICIA, First Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 69.23 15.38 0.00 0.00 0.00 2 6.06 68.18 12.12 6.06 1.52 

3 0.00 12.77 57.45 14.89 4.26 

4 0.00 0.00 1.79 51.79 30.36 

5 0.00 0.00 0.00 3.33 15.00 

Post-FDICIA, First Quartile State Income Growth 

 1 2 3 4 5 Absorpt

1 81.21 10.69 0.72 0.14 0.00 2 10.78 74.57 3.36 0.61 0.20 

3 0.00 39.58 43.75 6.77 0.00 

4 0.00 6.42 31.19 40.37 12.84 

5 0.00 0.00 4.35 15.22 43.48 

Pre-FDICIA, Second Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 78.57 14.29 0.00 0.00 0.00 2 5.56 74.07 7.41 3.70 0.00 

3 0.00 3.45 58.62 13.79 6.90 

4 0.00 0.00 14.29 61.90 14.29 

5 0.00 0.00 2.94 11.76 17.65 

Post-FDICIA, Second Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 76.46 11.33 0.53 0.18 0.00 2 10.13 69.23 4.10 1.15 0.13 

3 0.00 46.53 31.94 6.94 1.39 

4 0.00 3.80 29.11 48.10 8.86 

5 0.00 0.00 2.13 14.89 36.17 
35

Table 12 (continued) 

Transition Matrix for Large Institutions by Local Economic Conditions

This table provides the one-year transition matrix for composite examination ratings assigned in 1984 to 2003 to large FDIC-Insured inprobabilities are expressed in percent. Large institutions are defined as those with at least $250 million in total assets. The Pre-FDICIA 

to 1991 and the post-FDICIA period is defined as 1992 to 2003. State income growth is the quarterly year-over-year growth in inflatioincome in the state in which in the institution is headquartered. The growth rates are calculated over the 1984 to 2006 period and partitfirst quartile of state personal income growth, representing the weakest growth, is the minimum to the 25th percentile, the second quarti

the third quartile is the 50th to the 75th percentile and the fourth quartile is the 75th to the maximum, representing the strongest growth.

Pre-FDICIA, Third Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 85.00 10.00 0.00 0.00 0.00 2 7.50 77.50 5.00 0.83 0.00 

3 0.00 33.33 52.78 2.78 0.00 

4 0.00 3.85 19.23 57.69 11.54 

5 0.00 0.00 6.25 6.25 37.50 

Post-FDICIA, Third Quartile State Income Growth 

 1 2 3 4 5 Absorpt

1 73.49 10.74 0.17 0.00 0.00 2 13.04 66.91 2.15 0.57 0.00 

3 0.00 43.16 34.74 3.16 2.11 

4 0.00 5.41 29.73 48.65 2.70 

5 0.00 0.00 0.00 25.81 32.26 

Pre-FDICIA, Fourth Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 76.19 19.05 0.00 0.00 0.00 2 12.16 70.27 6.76 1.35 0.00 

3 0.00 27.59 55.17 10.34 0.00 

4 0.00 10.00 40.00 50.00 0.00 

5 0.00 0.00 7.14 14.29 57.14 

Post-FDICIA, Fourth Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 69.91 10.63 0.15 0.00 0.00 2 9.94 68.57 2.92 0.00 0.00 

3 0.00 42.11 35.09 5.26 0.00 

4 0.00 13.89 25.00 33.33 8.33 

5 0.00 0.00 0.00 30.00 20.00 
36

Table 13 

Transition Matrix for Small Institutions by Local Economic Conditions

This table provides the 18-month transition matrix for composite examination ratings assigned in 1984 to 2003 to small FDIC-Insured i

probabilities are expressed in percent. Small institutions are defined as those with less than $250 million in total assets. The Pre-FDIC

1984 to 1991 and the post-FDICIA period is defined as 1992 to 2003. State income growth is the quarterly year-over-year growth in inincome in the state in which in the institution is headquartered. The growth rates are calculated over the 1984 to 2006 period and partitfirst quartile of state personal income growth, representing the weakest growth, is the minimum to the 25th percentile, the second quarti

the third quartile is the 50th to the 75th percentile and the fourth quartile is the 75th to the maximum, representing the strongest growth.

Pre-FDICIA, First Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 72.13 22.86 1.05 0.24 0.00 2 9.26 73.31 10.23 2.91 0.59 

3 0.14 30.20 50.67 14.31 1.10 

4 0.00 4.68 24.27 50.85 13.26 

5 0.00 0.54 1.79 13.77 35.78 

Post-FDICIA, First Quartile State Income Growth 

 1 2 3 4 5 Absorpt

1 78.02 16.41 0.61 0.09 0.06 2 11.50 76.92 5.93 0.86 0.16 

3 0.28 45.29 42.55 7.53 0.45 

4 0.15 9.40 36.52 36.83 8.78 

5 0.55 3.28 8.20 21.86 24.59 

Pre-FDICIA, Second Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 73.52 21.18 1.48 0.31 0.00 2 9.05 75.03 9.45 2.03 0.30 

3 0.42 36.47 46.25 11.58 1.32 

4 0.00 5.47 27.86 48.65 11.78 

5 0.00 0.92 5.07 14.29 35.94 

Post-FDICIA, Second Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 78.18 14.71 0.48 0.00 0.00 2 12.76 75.84 4.79 0.74 0.03 

3 0.73 51.07 35.70 6.06 0.52 

4 0.00 16.37 37.83 31.09 5.50 

5 0.54 4.86 13.51 24.32 30.81 
37

Table 13 (continued) 

Transition Matrix for Small Institutions by Local Economic Conditions

This table provides the 18-month transition matrix for composite examination ratings assigned in 1984 to 2003 to small FDIC-Insured i

probabilities are expressed in percent. Large institutions are defined as those with less than $250 million in total assets. The Pre-FDIC

1984 to 1991 and the post-FDICIA period is defined as 1992 to 2003. State income growth is the quarterly year-over-year growth in inincome in the state in which in the institution is headquartered. The growth rates are calculated over the 1984 to 2006 period and partitfirst quartile of state personal income growth, representing the weakest growth, is the minimum to the 25th percentile, the second quarti

the third quartile is the 50th to the 75th percentile and the fourth quartile is the 75th to the maximum, representing the strongest growth.

Pre-FDICIA, Third Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 74.80 19.36 0.92 0.10 0.00 2 8.82 75.18 8.14 1.27 0.16 

3 0.20 39.95 44.44 10.22 0.95 

4 0.00 6.33 30.03 49.71 8.63 

5 0.00 1.28 5.98 15.81 35.47 

Post-FDICIA, Third Quartile State Income Growth 

 1 2 3 4 5 Absorpt

1 77.99 14.84 0.33 0.00 0.02 2 14.19 74.25 4.19 0.43 0.10 

3 0.81 52.79 36.86 3.95 0.29 

4 0.18 14.08 38.57 32.36 5.48 

5 1.74 7.83 11.30 26.09 20.00 

Pre-FDICIA, Fourth Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 67.85 21.71 0.84 0.21 0.00 2 8.47 74.06 7.59 2.14 0.29 

3 0.66 31.80 48.93 12.52 1.15 

4 0.00 5.44 24.09 46.89 13.73 

5 0.00 1.45 3.62 13.04 36.23 

Post-FDICIA, Fourth Quartile State Income Growth

 1 2 3 4 5 Absorpt

1 77.16 14.88 0.56 0.11 0.02 2 13.32 75.78 4.04 0.59 0.06 

3 1.08 51.29 38.16 3.93 0.48 

4 0.00 18.94 45.17 24.04 4.37 

5 0.00 5.36 16.07 23.21 22.32 
38

Table 14 

Transition Matrix for Large Institutions by Primary Federal Regulator 

This table provides the one-year transition matrix for composite examination ratings assigned in 1984 to 2003 to large FDICinstitutions by primary federal regulator. The transition probabilities are expressed in percent. Large institutions are define

with at least $250 million in total assets. Absorption includes failures, mergers within a bank holding company, and mergeoutside the holding company.

FDIC 

 1 2 3 4 5 Absorption 

1 79.16 9.93 0.08 0.00 0.00 10.84 2 12.25 73.00 3.08 0.90 0.06 10.71 

3 0.00 38.93 42.14 6.79 2.14 10.00 

4 0.00 5.52 22.07 48.28 16.55 7.59 

5 0.00 0.00 3.53 12.94 34.12 49.41 

Federal Reserve 

 1 2 3 4 5 Absorption 

1 70.53 12.09 1.01 0.00 0.00 16.37 2 10.60 71.57 4.58 0.48 0.00 12.77 

3 0.00 41.77 45.57 1.27 0.00 11.39 

4 0.00 0.00 30.00 60.00 5.00 5.00 

5 0.00 0.00 0.00 0.00 75.00 25.00 

OCC 

 1 2 3 4 5 Absorption 

1 77.05 11.77 0.30 0.00 0.00 10.88 2 9.34 74.38 1.97 0.21 0.10 14.00 

3 0.00 42.37 37.29 11.86 3.39 5.08 

4 0.00 15.79 10.53 31.58 15.79 26.32 

5 0.00 0.00 0.00 6.67 13.33 80.00 

OTS 

 1 2 3 4 5 Absorption 

1 52.55 8.03 0.00 0.00 0.00 39.42 2 8.06 51.64 2.99 0.30 0.00 37.01 

3 0.00 30.37 42.96 5.19 0.00 21.48 

4 0.00 0.79 26.98 51.59 9.52 11.11 

5 0.00 0.00 1.94 15.53 24.27 58.25 
39

Table 15 

Kolmogorov-Smirnov Test Results 

Transition Matrix for Large Institutions by Primary Federal Regulator

This table provides the results of Kolmogorov-Smirnov (K-S) tests applied to the one-year transition matrix for the composite examination ratings assigned in 1984 to 2003 to large FDIC-Insured Institutions by primary federal regulaLarge institutions are those with at least $250 million in total assets. The null hypothesis for the K-S test is that the roprobabilities for the two groups are drawn from the same distribution. *=Can reject the null hypothesis at the 90% confidence level, **=95%, ***=99%

FDIC vs. Federal Reserve OCC vs. FDIC

1 ** 1 (None significant) 2 2 

3 3 

4 4 

5 5 

OCC vs. Federal Reserve OCC vs. OTS 

1 (None significant) 1 *** 2 2 *** 

3 3 

4 4 

5 5 

OTS vs. Federal Reserve OTS vs. FDIC 

1 *** 1 *** 2 *** 2 *** 

3 3 

4 4 

5 5 
40

Table 16 

Transition Matrix for Small Institutions by Primary Federal Regulator

This table provides the 18-month transition matrix for composite examination ratings assigned in 1984 to 2003 to small FDIC-Insured institutions by primary federal regulator. The transition probabilities are expressed in percenSmall institutions are defined as those with less than $250 million in total assets. Absorption includes failures, mergers within a bank holding company, and mergers with a bank outside the holding company

FDIC 

 1 2 3 4 5 Absorption Total 

1 77.99 16.21 0.53 0.08 0.01 5.19 102 12.17 75.89 5.98 1.05 0.16 4.76 10

3 0.38 43.03 43.17 9.19 0.80 3.42 10

4 0.02 7.52 31.65 45.03 10.12 5.66 10

5 0.15 2.25 5.77 18.28 35.21 38.35 10

Federal Reserve 

 1 2 3 4 5 Absorption Total 

1 73.93 16.77 0.61 0.12 0.06 8.51 102 11.68 76.19 5.10 0.51 0.10 6.42 10

3 0.36 42.53 42.35 7.83 0.71 6.23 10

4 0.00 4.23 31.69 42.25 12.32 9.51 10

5 0.00 0.89 8.93 10.71 33.04 46.43 10

OCC 

 1 2 3 4 5 Absorption Total 

1 74.93 13.61 0.79 0.05 0.00 10.61 102 8.21 77.90 4.74 0.74 0.06 8.36 10

3 0.21 40.81 44.15 6.16 0.94 7.72 10

4 0.00 8.47 32.88 30.51 7.80 20.34 10

5 0.00 0.00 7.14 11.90 27.78 53.17 10

OTS 

 1 2 3 4 5 Absorption Total 

1 72.96 14.78 0.26 0.00 0.00 12.01 102 12.41 73.53 5.44 0.58 0.08 7.97 10

3 0.19 41.12 44.98 6.27 0.10 7.34 10

4 0.17 10.45 32.93 40.94 6.62 8.89 10

5 0.29 0.88 5.56 17.25 30.12 45.91 10
41

Table 17 

Kolmogorov-Smirnov Test Results 

Transition Matrix for Small Institutions by Primary Federal Regulator

This table provides the results of Kolmogorov-Smirnov (K-S) tests applied to the 18-month transition 

matrix for the composite examination ratings assigned in 1984 to 2003 to small FDIC-Insured Institutions by primary federal regulator. Small institutions are those with at less than $250 million in total assets. The null hypothesis for the K-S test is that the row probabilities for the two groups are drawn from the same distribution. *=Can reject the null hypothesis at the 90% confidence level, **=95%, ***=99%

FDIC vs. Federal Reserve OCC vs. FDIC

1 ** 1 *** 2 2 *** 

3 3 * 4 4 *** 

5 5 ** 

OCC vs. Federal Reserve OCC vs. OTS 

1 1 2 ** 2 *** 

3 3 4 * 4 *** 

5 5 

OTS vs. Federal Reserve OTS vs. FDIC 

1 (None significant) 1 *** 2 2 ** 

3 3 4 4 

5 5 * 
42

Table 18 

Kolmogorov-Smirnov Test Results 

Transition Matrix for Small Institutions by Primary Federal Regulator, FDICIA and Business C

This table provides the results of Kolmogorov-Smirnov (K-S) tests applied to the 18-month transition matrix for the composite exaassigned in 1984 to 2003 to small FDIC-Insured Institutions by primary federal regulator, FDICIA periods and business cycle perio

are those with at less than $250 million in total assets. The pre-FDICIA period is defined as 1984 to 1991. The post-FDICIA perioto 2003. The business cycle periods are defined by the NBER business-cycle peaks and troughs. The null hypothesis for the K-S teprobabilities for the two groups are drawn from the same distribution. *=Can reject the null hypothesis at the 90% confidence leve

FDIC Federal Reserve 

Pre-FDICIA Expansion vs. Post-FDICIA Expansion Pre-FDICIA Expansion vs. Post-FDICIA 

1 *** 1 

2 *** 2 *** 

3 *** 3 *** 

4 *** 4 *** 

5 *** 5 

Pre-FDICIA Recession vs. Post-FDICIA Recession Pre-FDICIA Recession vs. Post-FDICIA 

1 *** 1 (None significant) 2 *** 2 

3 *** 3 

4 *** 4 

5 ** 5 

OCC OTS 

Pre-FDICIA Expansion vs. Post-FDICIA Expansion Pre-FDICIA Expansion vs. Post-FDICIA 

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

Pre-FDICIA Recession vs. Post-FDICIA Recession Pre-FDICIA Recession vs. Post-FDICIA 

1 *** 1 (None significant) 2 *** 2 

3 *** 3 

4 4 

5 5 
43

Table 19 

Transition Matrix for Large Institutions 

This table provides the one-year transition matrix for composite examination ratings assigned in 1984 to 2003 to large FDIC-Insured institutions. The transition probabilities are expressed in percent. Large institutions are defias those with at least $250 million in total assets. The Pre-FDICIA period is defined as 1984 to 1991 and the posFDICIA period is defined as 1992 to 2003.

Pre-FDICIA 

 Upgrade Stay the Same Downgrade Sample Size 

Upgrade 20.00 65.00 15.00 20 

Stay the Same 13.82 74.80 11.38 123 

Downgrade 5.88 70.59 23.53 17 

Post-FDICIA

 Upgrade Stay the Same Downgrade Sample Size Upgrade 9.95 77.73 12.32 211 Stay the Same 11.25 82.56 6.19 1,244 Downgrade 36.96 57.97 5.07 138 
44

Table 20 

Transition Matrix for Small Institutions 

This table provides the one-year transition matrix for composite examination ratings assigned in 1984 to 2003 to small FDIC-Insured institutions. The transition probabilities are expressed in percent. Small institutions are defias those with less than $250 million in total assets. The Pre-FDICIA period is defined as 1984 to 1991 and the pFDICIA period is defined as 1992 to 2003.

Pre-FDICIA 

 Upgrade Stay the Same Downgrade Sample Size 

Upgrade 17.81 68.02 14.18 2,617 

Stay the Same 18.92 69.99 11.09 9,408 

Downgrade 35.29 53.82 10.90 2,083 

Post-FDICIA 

 Upgrade Stay the Same Downgrade Sample Size 

Upgrade 11.60 72.99 15.41 6,413 

Stay the Same 12.63 79.76 7.61 27,246 

Downgrade 43.23 51.33 5.44 3,620 
45

Figure 1

Estimate of the Survival Functions

During Expansion Periods

0

0.2

0.4

0.6

0.8

1

1.2

0 50 100 150 200 250 300

Months in Rating

Survival Function

Post-FDICIA

Pre-FDICIA

Figure 2

Estimate of the Survival Functions

During Recession Periods 

0

0.2

0.4

0.6

0.8

1

1.2

0 20 40 60 80 100 120 140 160 180 200

Months in Rating

Survival Function

Post-FDICIA

Pre-FDICIA
46

Figure 3

External Mergers

0

50

100

150

200

250

300

350

400

450

500

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Year

Number

FDICIA Reigle Neal

Total

In State

Figure 4

Roll-Ups

0

50

100

150

200

250

300

350

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year

Number

Total

In State

FDICIA Riegle Neal