Our examiners are extremely good at what they do, but any
good examiner recognizes that data should come from a variety of different
sources, including the signals that come from the market. Therefore, market discipline can be an
important adjunct to the supervisory process. —Roger W.
Ferguson, Jr., Vice Chairman, Board of Governors of the Federal Reserve System
I propose that a formal integration of selected market data
into the regulatory agencies’ analytical systems could substantially improve
the quality of the oversight they can provide. —Mark J. Flannery, Barnett Banks Professor of Finance, University
Market data play an increasingly important role in the
ongoing monitoring of insured institutions’ risks. In the eyes of the supervisory community, the
essence of this role is captured by the two statements quoted above. First, supervisory processes benefit from
consideration of a broad range of different sources of information, including
objective signals offered by market participants. Second, the integration of market data into
off-site monitoring tools and models can improve supervisors’ responsiveness to
emerging risks. The FDIC is also
considering the possible benefits of integrating market data into insurance
pricing and failure loss-prediction models.
This article illustrates various ways in which the
supervisors of depository institutions currently use market information; the
article also highlights some potential applications of market data that the
FDIC is considering in its insurance functions.
The first section reviews the literature on the application of market
data to supervisory risk assessments.
The second section briefly reviews the supervisory process, setting the
context for the current use of market information within that process. The third section illustrates how market
information is currently applied in assessments of both industry risk trends
and institution-specific risk conditions.
The fourth section discusses research and other activities being
conducted at the FDIC with a view to using market information more
broadly. The final section summarizes
and discusses a few of the challenges for wider incorporation of market
information into the supervisory process.
Market Data and the
Literature on Links between Market Signals and Supervisory Risk Assessments
The term “market discipline” assumes that the information
provided by markets can signal that excessive risk levels are present in
banks. From a public–policy standpoint,
supervisors’ use of such signals is highly desirable. Market discipline has the potential to reduce
the extent and frequency of burdensome regulatory oversight; and—because market
signals call immediate attention to potential excessive risk taking—it allows regulators
to take more timely corrective action.
The inclusion of market discipline as Pillar III of the new Basel
Capital Accord (Basel II) proposal underscores the important role regulators
foresee market forces playing in encouraging banks to have adequate levels of
The market information presently available for publicly
traded insured depositories is of three kinds:1 equity information
(prices and trading volumes), debt information (debt ratings and subordinated
debt prices), and analysts’ reports (see table 1).
Data on daily and even intraday equity prices and trading
volumes are widely available for U.S. public companies. As table 2 shows, just over one-half of the
1,002 publicly held U.S. banking and thrift holding companies trade on the National
Association of Securities Dealers Automated Quote System (NASDAQ). However, the largest banking organizations
trade on the New York Stock Exchange (NYSE).
Equity pricing information is also readily available for a number of
large foreign banking organizations that own insured banking subsidiaries
operating in the United States.
Debt information is less widely available than equity
information. As of year-end 2003, debt
ratings from one of the three major rating agencies2 were available
for 133 bank and thrift holding companies with roughly $6.4 trillion in insured
assets. Subordinated debt prices, which
have received a great deal of attention in recent academic research, are
available for roughly 50 of the largest bank and thrift organizations with over
$5 trillion in insured depository assets.
Only about 30 of these companies have issues that are actively traded.
The third kind of market information that is available is
provided by the analyst community, which widely monitors the performance of the
largest 50 or so U.S. banking companies.
Equity and bond analysts make investment recommendations and often
prepare comprehensive analytical reports on the companies they follow. These recommendations and reports can be
useful as confirmation of supervisory assessments of an institution’s risk
profile. Table 3 shows the breadth of
analysts’ coverage for equities of the 10 largest U.S. banking and thrift
Some people within the supervisory community have expressed
doubts about the usefulness of these three kinds of market information. Much of the reluctance about using market
information more regularly seems to center on doubts about whether these
sources of market information can provide consistent, timely, and reliable
indications of risk. In particular, the
question is whether financial markets provide regulators with any information
they do not already possess. Another way
of asking this question is, “Can market participants detect deteriorating
conditions in an institution before the institution’s supervisory rating deteriorates?”
A number of studies have examined the extent to which equity
holders and creditors are able to anticipate changes in the supervisory profile
of regulated financial institutions.
These studies generally incorporate one or more market-based measures
into statistical models, which then attempt to forecast supervisory
ratings. For example, Gunther, Levonian,
and Moore (2001) examined the ability of equity data to predict changes in the
BOPEC ratings of bank holding companies.3 Using Moody’s KMV Corporation’s estimated
default frequencies (EDFs), Gunther et al. concluded that equity prices provide
incremental information to bank supervisors in periods between
inspections. Hall et al. (2001), using
separate equity measures, found similar results. Elmer and Fissel (2001) as well as Curry ,
Elmer, and Fissel (2001) related equity market variables directly to models of
both CAMELS downgrades and bank failures.4 Their findings strengthen the argument that
equity market variables add explanatory value to supervisory models.
Similar studies have been performed using data from holders
of bank debt. Gilbert , Meyer, and
Vaughn (2001) found that risk premia on jumbo CDs do not predict CAMELS
downgrades as well as early-warning models do.
On the other hand, Evanoff and Wall (2001) examined the degree to which
subordinated debt spreads provide supervisors with additional information. They found that subordinated debt spreads do
at least as well as capital ratios in explaining changes in supervisory
With support mounting for supervisors to use market
discipline, Feldman and Levonian (2001) examined supervisory uses of market
information and the reasons such data are not used more often. They point to several factors inhibiting the
use of market data, including difficulty measuring market signals and the lack
of specific direction from senior supervisory staff for using market data. They urge that multiple sources of market
data be incorporated into three areas of the supervisory process: as an additional
measure to augment supervisory risk assessments, as an element of statistical
models used to forecast the future condition of banks, and as a measure to help
assess banks’ loan quality and capital adequacy. Further, they advocated a combination of changes
to supervisory policies and additional applied research as the next step toward
putting market data to practical use.
More recently, studies by Krainer and Lopez (2003) and
Curry, Elmer, and Fissel (2003) further strengthen the case that market variables
improve predictions of changes in supervisory ratings. Krainer and Lopez examined whether both
equity and debt variables are significant in explaining BOPEC rating
assignments, even after a large number of supervisory variables have been
included in statistical models. They
concluded that supervisors could benefit from incorporating market variables
into their off-site monitoring models.
Curry, Fissel, and Hanweck (2003)
investigated the direction of causality, from changes in equity variables to changes
in BOPEC ratings and the reverse. They
find that, while market variables add value in predicting BOPEC rating changes,
the reverse is only moderately successful, indicating that market variables may
be more predictive of BOPEC rating changes than vice versa. They conclude that the market is able to
obtain independent information about bank holding company risk exposure beyond
the information available from public reporting resources and that therefore
the market ought to be able to provide some degree of independent
oversight. However, it should be noted
that although both of these studies include in-sample and out-of-sample tests,
results tend to be much weaker for out-of-sample prediction.
The Context for
Supervisory Use of Market Information
Ideally, financial markets would provide continuous
monitoring of bank performance in the periods between on-site
examinations. Although on-site
examinations allow the most extensive review of a bank’s financial position,
the information obtained during the examination becomes outdated over time,
especially for rapidly growing institutions.
However, market investors evaluate bank performance continually, even if
they do not have access to as much detailed information as on-site
examiners. Consequently, market signals
could be effective in alerting supervisory agencies to a change in a bank’s
risk profile, and the change might in turn prompt a supervisory response from
the primary regulator.5 A
supervisory response necessarily involves the reallocation of supervisory
resources since it entails a shift in the current supervisory strategy.
Market information and market signals rarely in and of
themselves influence the priorities and strategies of supervisors of U.S.
financial institutions. Rather, when
supervisors are evaluating risk trends, they consider market data in the
context of a number of different sources of information. In other words, market indicators are just
one of many considerations that affect strategic decisions in response to
perceived risk and emerging risk trends.
Figure 1 is a stylized representation of the role that market indicators
might play in influencing supervisory responses to risk.
Aside from influencing supervisory responses (and therefore,
possibly, the reallocation of supervisory resources), market data are also
routinely considered in supervisory risk determinations. All examination activities and all the
information and trends analyzed through these activities are used to support
supervisory risk determinations, but these determinations do not directly
involve a reallocation of resources.
Rather, they involve the assignment of institutions to certain risk
categories for monitoring purposes.
Supervisory risk determinations are commonly summarized by the
assignment of numeric or alphanumeric risk grades to individual institutions.6 These determinations are critical for
purposes of strategic and resource planning.
For the FDIC, supervisory risk determinations are also one of the main
factors influencing the level of deposit insurance premiums that insured
institutions pay.7 This
subject is discussed below in the section “Potential Uses of Market Data.”
It is hard to generalize about the importance of market
indicators in relation to other sources of information when supervisory risk
determinations are prepared. The
difficulty stems partly from the fact that risk surveillance systems are
fundamentally judgment-based processes.
In evaluating market signals, for example, FDIC examiners and analysts
do not apply a formulaic approach.
Rather, they use their best judgment in determining what market data to
consider and how to interpret and respond to the information. It is probably fair to say that the examiners
and analysts responsible for preparing supervisory risk determinations do not
view market information as a substitute for other sources of information. Rather, they tend to view market data as a
supplemental source of information that helps confirm the risk perceptions they
formed by looking first at supervisory information and financial performance
Before reviewing the current uses of market data, we briefly
summarize the three broad types of U.S. supervisory programs—those for large,
midsize, and small institutions—and the role of market data in each. The distinguishing characteristics are the
depth and scope of on-site reviews, the degree of interaction between examiners
and management, and the extent to which the emphasis is on risk-management
information systems and controls as opposed to transaction testing and asset
valuation. Table 4 gives the approximate
number of institutions and insured depository assets covered by each of these
three kinds of program. The table also
distinguishes between institutions that are affiliated with a publicly traded
entity and those that are not.
Large-Institution Supervisory Programs. Large-institution
supervision programs are by far the most intensive of the three types,
subjecting institutions to more frequent and more in-depth on-site reviews and
providing supervisors with a vast amount of nonpublic risk information more or
less continuously. The Office of the
Comptroller of the Currency (OCC), for example, uses teams of resident
examiners to supervise the 23 largest nationally chartered banks. The Federal Reserve System uses designated
supervisory teams, supplemented by teams of specialists in areas such as credit
risk modeling and capital market activities, to oversee the largest complex
banking organizations.8 The
FDIC, like the OCC, uses dedicated staff in its Large-Bank Program, which
encompasses the six largest state-chartered nonmember institutions that the
FDIC directly supervises.9
Although the design and structure of large-institution
programs vary by primary regulator, all have the same goal: to provide
real-time and continuous evaluations of the risks posed by large
institutions. These programs differ from
the more traditional point-in-time examination process in that examiners
interact with bank personnel continually throughout the year. Large-institution programs also place far
greater emphasis on evaluating internal risk-management systems and controls as
opposed to performing the transaction testing and asset valuations (e.g., loan
reviews) that take place during more traditional examinations.
Continuous access to management and to risk-management
information allows supervisors to respond more quickly to emerging problems
than would be possible with an annual examination approach. Because of their ongoing interaction with the
large institutions, supervisors generally learn the nature of negative
announcements, shifts in risk profile, or shifts in strategic direction well in
advance of market investors. Table 5 provides a more detailed breakdown of large-institution programs administered
by the three federal banking agencies in terms of covered insured subsidiaries
and insured subsidiary assets. As this
table reveals, although large-institution programs cover a very small
percentage of the number of FDIC-insured financial institutions (less than 2
percent), they cover the majority of insured-institution assets.
Large-bank examiners are instructed to review all available
information relevant to the risk classification of the bank, including market
information. Although market signals for
these large institutions are unlikely to convey any new information to the supervisor,
they are nevertheless useful in corroborating and validating perceptions and
judgments about risk, particularly when disclosures and trends are hard to
quantify independently. In the context
of large-bank programs, market data are also useful as an alternative measure
of relative risk. In other words, market
data provide a measure of the market’s perception of this company’s risk
relative to the risk of its peers.
Midsize-Institution Supervisory Programs. Thresholds and
considerations for placing institutions in a midsize supervisory program vary
from agency to agency. However, these
programs typically include institutions with more than $5 billion in
assets. Although less formalized and
less intensive than large-bank programs, midsize-institution programs are
designed to provide for reviews of greater depth and frequency than is the case
with a point-in-time examination approach.
Examination programs of midsize institutions are often
tailored to the institutions’ specific risk profiles. For example, institutions engaged in complex
banking activities might be subjected to periodic targeted reviews throughout
the year and be assigned dedicated staff with strong technical expertise
related to the institution’s particular activities. For institutions engaged in less complex
activities, the supervisory approach might resemble the more traditional
periodic-examination approach but generally with a much greater degree of
oversight than is applied to smaller institutions. As a result, market investors typically do
not learn of negative news about a midsize institution before supervisors do.
In midsize supervisory programs, market information is used
in much the same way as in large-institution programs—that is, less as a
signaling device or tool and more as corroboration of risk issues and trends
and as an alternative measure of relative risk.
Small-Institution or Community-Bank Supervisory Programs.
As shown in table 4, the vast majority of publicly held insured
institutions fall within a small-institution supervisory program. These programs usually consist of periodic examinations
whose scopes vary considerably, depending on the overall risk profile of the
institution being examined. It is in
this area that market signals, used in conjunction with off-site surveillance
systems, have the potential to provide the most significant benefit to
supervisors, given the time lag between examinations.10
Examples of Regulatory Applications of Market Data
Although the FDIC does not apply a formulaic approach to
evaluating market signals, it does incorporate market data into its analytical
products, early-warning systems, and decision-making processes requiring an
assessment of prospective risks. The
examples presented here relate to off-site monitoring, both of individual banks
and of industry trends; monitoring for potential liquidity pressures in banks;
corroborating the importance of risk events; developing risk rankings;
monitoring credit risk trends in banks’ corporate loan portfolios; formulating
supervisory outlooks and strategies; and influencing decisions about the
appropriate level of contingent loss reserves for potential failures.
Contributing to the Off-site Monitoring of Individual Banks
The FDIC, along with other U.S. banking supervisors, has
developed various off-site monitoring programs to supplement on-site
examination programs. A primary
objective of off-site surveillance systems is to alert supervisors to potential
emerging risk issues. Market indicators
play a significant role in such systems.
As an example, the FDIC’s LIDI program (see note 9) instructs staff to
consider all available data on the companies being reviewed, including more forward-looking
information such as market indicators.
Off-site reviews can influence supervisory strategies in variety of
ways: for example, the scheduling of an on-site examination may be altered or
accelerated, the resources allocated to an examination may be adjusted, or the
planned scope of an on-site examination may be changed.
Another objective of off-site surveillance programs is to
identify institutions whose risk profiles deviate from expectations. When such outliers are identified, examiners
or analysts are typically required to perform follow-up analyses to determine
the reason for the outlier condition and to recommend changes in supervisory
strategies when appropriate. Figure 2
shows how Moody’s KMV information might have been used to identify an outlier
market-based default expectations for an insured institution began to deviate
from those for peer institutions beginning in June 2000. In this particular example, the market
provided an unambiguous and quantifiable signal of financial weaknesses that
led to the institution’s failure some 21 months later. In mid-2000, an analyst would have responded
to this information by reviewing financial data and supervisory information to
try to determine the reasons for the negative market signal. Depending on the results of this review, the
analyst would have either recommended a shift in supervisory strategy, such as
an accelerated examination, or concluded that the strategy in place was sufficient.
Monitoring General Banking Conditions and Trends
Investor sentiment can be a good barometer of general risks
and conditions in the banking sector.
The FDIC and other supervisors evaluate this sentiment by monitoring
banking stock indexes, debt spreads for bank debt, bond rating trends, debt and
equity analyst research opinions, and various other market-based measures, such
as Moody’s Corporation KMV model of expected default. Figure 3, for example, uses Moody’s KMV model
to show the general trend in market default expectations for U.S. commercial
banks since 1996.
Such broad measures are of particular interest to managers
because they provide a barometer of the current health of and outlook for the
industry. Used in conjunction with other
information, such as trends in supervisory ratings and economic indicators,
market indicators can convey a sense of the level of concern that should be
factored into strategic decisions involving the allocation of supervisory
resources and contingency planning.
Figure 4 shows another example of broad industry risk
measures based on market information.
This figure depicts a concept recently developed at the FDIC and
referred to as a dashboard indicator.
This particular indicator was designed to gauge general risk conditions
in the universe of large insured depositories.
Essentially an index compiled from a group of critical market-risk
indicators, this indicator helps risk managers gauge the current health and
outlook of large insured depositories relative to historical patterns. Indicators like this one are also important
inputs into the strategic planning process at the FDIC.
Monitoring Potential Liquidity Situations
Sometimes supervisors must respond to changes in market
indicators because of the liquidity pressures these changes can impose. For example, an organization that relies
extensively on debt funding may face severe liquidity pressures if its debt
ratings are downgraded. Many derivatives
and securitization contracts also contain early termination or collateral
clauses that are triggered by downgrades in the counterparty’s or issuer’s
external debt rating. If a banking
organization has a significant volume of such contracts, it may be unable to
generate sufficient funding or collateral to meet the provisions of such
contracts. As a result, supervisors
closely watch trends in external debt ratings as well as other indicators that
might signal potential contractual performance problems for banking companies
that have issued debt.
Regulators often use market indicators to validate or
corroborate risks they observe in supervised institutions. Market signals can be valuable in this
respect because they not only provide directional signals but also serve as a
quantitative benchmark for the significance of certain risk events. The stock price performance of large U.S.
money-center banks in 2002 is perhaps an example of how market measures convey
information about the magnitude of seemingly unquantifiable risks related to
corporate governance and reputation risk.
Figure 5 shows the stock market’s reaction to a barrage of unfavorable
publicity in late 2001 and early 2002 relating to certain investment banking
practices and dealings with customers in connection with high-profile corporate
failures, including Enron and WorldCom.
Although the interpretation of such signals is not always
straightforward,12 the signals do convey a sense of the magnitude of
events from the market’s perspective. In
this case, the market corroborated the seriousness with which the regulatory
community viewed corporate governance issues surrounding larger banking
Developing Risk Rankings
Market data can be used to inform decisions having to do
with the relative risks posed by institutions with similar supervisory
ratings. Because supervisory-based
ratings fall within a narrow range of possibilities (well-rated companies are
assigned CAMELS or BOPEC composite ratings of 1 or 2), market indicators can
help provide additional granularity to risk rankings. Such rankings can then be used to establish
supervisory priorities. Figure 6 shows
subordinated debt pricing spreads to Treasuries for three large institutions
whose supervisory ratings are identical.
The difference in spreads among the three institutions helps corroborate
the relative risks posed by these companies, and the corroboration in turn
supports decisions about the allocation of resources.
Monitoring Risk in Corporate Credit Portfolios
One of the more significant risks contained on the balance sheets of banks is corporate credit risk. Among larger banks, much of this exposure is related to publicly held companies. Hence, each of the supervisory agencies uses market data as an early-warning indicator of potential corporate loan performance problems. Figure 7 illustrates how Moody's KMV information in 1998, and even more so in 2000, indicated significant deterioration in market-based default measures for U.S. telecommunication firms. By associating such measures with actual loan exposure data, supervisors are able to produce quantitative rankings of industry credit risk exposures, and these rankings in turn support decisions about resource allocations related to on-site loan review work. For instance, in the years 1999—2001 the supervisory agencies used a similar kind of analysis to support resource allocation decisions relating to the Shared National Credit program-an interagency program that annually reviews large syndicated credits held by three or more supervised institutions.13
Influencing Changes in Supervisory Outlook
As mentioned above, market information can contribute to changes in supervisory outlook, and these changes, in turn, can cause shifts in priorities and supervisory strategies. Moreover, for the FDIC as the deposit insurer, the supervisory outlook for a given institution is often reflected both in the level of premiums assessed against insured deposits and in the amount of contingent loss reserves the Corporation sets aside for problem institutions.
To illustrate the market information the FDIC might consider when setting premium levels, figure 8 shows a banking organization that experienced a significant fall in its stock price relative to the prices of other large banking organizations during the latter half of 1998. Around the same time, the FDIC began to have concerns about this otherwise well-rated company and took steps to downgrade its supervisory subgroup rating for purposes of setting deposit insurance premiums (see note 7). In this case, market signals were one of many factors that contributed to a change in the FDIC's overall risk evaluation of the institution. The signals reinforced the FDIC's supervisory outlook for the company, prompting the Corporation to act with one of the tools at its disposal—the imposition of higher deposit insurance premiums.
Figure 9 shows a reverse example. In figure 9, market signals reinforced the
supervisory view that a problem institution’s prospects were improving.
The FDIC’s accounting function requires the Corporation to
establish loss reserves for potential bank and thrift failures. Key factors the Corporation considers when
setting these reserves are the historical failure rates of problem institutions
and factors that might suggest some deviation from recent failure-rate
trends. When the Corporation evaluates
whether contingent loss-reserve allocations should deviate from historical
failure-rate patterns, among the factors it considers are market indicators as
well as a variety of factors including the performance of the economy and the
capital markets. For example, significant
deterioration in market indicators related to the industry as a whole or to
some group of institutions might provide support for increasing the reserve
allocations for potential failures.
Again, a shift in market indicators would probably not be the sole
reason for such an action but could be one of several factors influencing the
Potential Uses of Market Data
Beyond the applications discussed above, market measures
have a number of potential applications.
For the FDIC, some of these relate to the Corporation’s unique role as
the insurer of bank and thrift deposits.
Specifically, market information could enhance the following
applications or processes:
Risk classifications for
deposit insurance pricing purposes
institution-level contingent loss reserves for potential bank and thrift
models used to quantify the likelihood of downgrades in supervisory ratings
Basel II benchmarking
Using Market Data for Insurance Pricing
In April 2001, the FDIC outlined a
number of recommendations for deposit insurance reform, one of which was to
allow the FDIC greater flexibility in setting deposit insurance premiums.14 In December 2003, the FDIC Banking Review
contained an article that explored alternatives to the current risk-based pricing
system, including the potential use of market indicators for setting deposit
insurance premiums for large insured institutions.15 As noted in that article, the evaluation and
pricing of risk related to large complex operations may be more precise when
market indicators complement supervisory ratings than when supervisory ratings
are used alone.
The article also noted that market data help overcome weaknesses in
model-based approaches that rely on accounting data: when funding and liquidity variables are included in such models they tend to unduly penalize larger institutions.
Market Variables under
Consideration. For purposes of deposit insurance pricing,
the FDIC is presently considering a variety of market variables that best
differentiate risk in financial institutions.
These variables include stock price volatility
measures, external bond ratings, subordinated debt spreads, Moody’s KMV
measures of expected default, and stock price-to-book ratios. As shown in the article mentioned just above,
these variables appear to be strongly correlated with
Ways of Incorporating Market Data into a Deposit Insurance
There are a variety of ways in which market
information could be used in a risk-based premium framework. Three implementation
possibilities, for illustrative purposes only, are described here (figures 10,
11, and 12). Figure 10, for
example, shows a framework that considers market data in conjunction with
supervisory ratings to determine an institution’s risk premium category. In this case, market information results in a
more granular set of risk rankings than would be feasible if only supervisory
ratings were used.16
Figure 11 shows an alternative approach that uses market
data as the basis for adjustments to initial risk assessments that are based on
supervisory ratings, a continuous pricing model, or a scorecard.17
In this example, an institution
with favorable market indicators (e.g., a strong debt rating or relatively low
stock price volatility) would receive an adjustment to a lower-premium
In contrast to figure 11, in which market data are used to adjust initial assessments, figure 12 shows how
market data could be used to trigger changes to an institution’s risk-based
premium subgroup. This trip-wire
approach would result only in negative adjustments and might involve such
occurrences as the lowering of a debt rating to subinvestment-grade
status or the decline in a price-to-book ratio to below 1.0.
If the deposit insurance reform proposals pending before Congress are enacted (see note 7), incorporating market data into a
new risk-based pricing framework will require the resolution of two practical
issues. First, market data are typically
available only for consolidated companies, whereas insurance premiums are currently assessed at the insured-subsidiary level. This issue could be
overcome if an organization-wide view were adopted, at least for
“significant” subsidiaries—those for which there is likely to be a close
correspondence among a subsidiary’s performance, its risk indicators, and the
company’s market signals. For “nonsignificant” subsidiaries—those for which performance
and risk are not linked to market signals—it may be
more appropriate to apply a general framework that does not include market
A second practical issue is the determination of what
constitutes a large institution. As
shown in table 4 above, numerous subsidiaries of companies fall into the
category of midsize institutions.18 Where to draw the line between large
and all other institutions could depend on a variety of factors relating to an
institution’s complexity and the availability of certain kinds of market
information. Continuously available
subordinated debt pricing, for instance, is generally available only for the
largest banking and thrift organizations (perhaps as many as the top 50 in
terms of asset size). Thus, the
availability of certain types of market data could be used to determine which
banks would be priced under one system compared with
Using Market Data in the Evaluation of Contingent Loss Reserves
The FDIC is required to establish adequate reserves to cover
potential insurance fund losses from failures.
The process of establishing such reserves essentially entails
considering three prospective factors: (1) the likelihood of failure of an
individual institution, (2) the loss that will be incurred
if that institution fails, and (3) the level of insured deposits at the
institution when it fails. For publicly
held banking and thrift organizations, market indicators can be useful in
assessing the first two of these factors.
As shown by Moody’s KMV model and others, market information
such as equity prices and subordinated debt spreads can be
used to provide quantifiable measures of market failure
expectations. When supervisors are
evaluating the failure prospects of troubled institutions, they can compare
these measures with judgment-based assessments that rely on supervisory and
financial data. In addition, equity
prices are a direct measure of the value assigned by shareholders to a firm’s
assets and liabilities. Thus, market
valuations may be useful when supervisors evaluate the liquidation-value
scenarios related to probable failures.
Incorporating Market Data into Off-site Surveillance Models
Merton-based models such as those used by Moody’s KMV are
just one of many approaches that incorporate market information in the
measurement of default probabilities.
Arguably, supervisors have the means to improve on these models by
incorporating both public and nonpublic data into failure estimations. For example, logit models
that incorporate market, supervisory, and financial variables could result in
more accurate failure predictions than models that rely solely on market data.
Research at the FDIC has shown that incorporating market
signals into early-warning systems improves the ability of supervisors to
predict supervisory ratings of holding companies.19 Such early-warning systems are
relevant for failure models as well, since it is reasonable to expect the
factors associated with supervisory downgrades to be predictive also of
Using Market Information as Benchmarks for the Outputs of Internal
Ratings-Based Capital Models
Market information could be useful for
evaluating the consistency and integrity of the advanced internal ratings-based
(A-IRB) models used for Basel II capital calculation purposes.20 Given not only the variations among
institutions in the characteristics of loan portfolios but also the flexibility
that exists in the Basel II implementation requirements, it is not feasible to
use market measures to definitively validate or invalidate the outputs of A-IRB
Rather, such measures would provide approximations or rough benchmarks,
which might highlight potential biases or inconsistencies in A-IRB measures
applied to corporate loan exposures.
In terms of market measures, the most obvious candidate for
producing A-IRB benchmarks is the Moody’s KMV model of estimated default
Although not necessarily synonymous with the Basel II definition of the
probability of default (PD), EDFs are expressed in
the same basic unit of measurement: one-year default expectations related to an
obligor.21 The most
straightforward PD benchmarks would involve comparisons between firm-specific EDFs and the PDs assigned by the
bank for that same firm. Less
straightforward, but relatively easy to construct, would be industry-specific
PD benchmarks that were developed from EDFs and could
be compared with the weighted average portfolio PDs
for similar industry credit exposures held by institutions. Such industry benchmarks hold the possibility
of extending the use of market indicators beyond the exposures of publicly held
External loan and bond ratings (debt ratings) can also be used to develop proxy benchmarks for PDs. Unlike EDFs, debt ratings are not an explicit measure of PDs. Rather, they
are long-run estimates of relative
likelihood of default through an entire business cycle. Nevertheless, default studies produced by the
rating agencies give long-run averages of default by debt grade. Hence, ratings can be associated with PDs if one uses the long-run average historical default
rates for a particular debt rating.
Again, the most straightforward PD benchmarks would involve credit
exposures to firms with rated debt. PD
benchmarks for industry credit exposures could also be
developed if one used average industry debt ratings.
Market signals play an important role in supervisory
processes. Incorporated into
surveillance programs, market signals supplement supervisory and financial
information for purposes of corroborating supervisory risk determinations and
evaluations. Market signals also provide
quantitative rankings of risk that can help in the evaluation of supervisory
priorities. Although market signals in
isolation rarely influence supervisory priorities and strategies, they are
nevertheless a critical factor for supervisors to consider when formulating
their outlooks for U.S. financial institutions.
Market signals are important inputs into off-site surveillance systems,
since they provide supervisors with an objective early-warning indicator. Such signals are especially important during
the period between examinations.
Beyond their use in surveillance programs, market indicators
can play a role in the insurance pricing and funds management processes, where
the deposit insurer requires estimates of both the likelihood of failure and
the liquidation values of failing-institution assets. Market signals can also add explanatory power
to failure- and supervisory downgrade-prediction models. Finally, applied to credit exposures, market
data can be used to construct rough benchmarks for the
outputs of A-IRB models, which serve as critical inputs into regulatory capital
requirements under Basel II.
Broader use of market data largely depends on the
development of a reliable source of market prices that are
linked directly with other supervisory and regulatory financial
data. For example, off-site surveillance
models could be significantly enhanced if they could
be automatically linked to multiple sources of information on debt and equity
prices. To apply this information to
insured subsidiaries, it will also be necessary to identify explicit linkages
between market data, which relate to the consolidated operations of a company,
and financial performance information that is related
to insured subsidiaries. Finally,
analysts and examiners will have to be able to clearly define
the notions of significance and permanence as they relate to changes in market
valuations. For all these reasons, the
FDIC is pursuing the creation of a market data warehouse. Such a warehouse of information will achieve
several objectives, including those of collecting multiple sources of debt and
equity information under one database, linking this information to financial
information on insured institutions, and developing algorithms that alert
analysts and examiners to significant, long-term shifts in debt and equity
Curry, Timothy J., Peter J. Elmer, and Gary S. Fissel. 2001. Regulator Use of
Market Data to Improve the Identification of Bank Financial Distress. Working Paper No. 2001-01. Federal Deposit Insurance Corporation.
Feldman, R., and M. Levonian. 2001. Market Data and Bank Supervision: The
Transition to Practical Use. Federal Reserve Bank
of Minneapolis, The Region 15, no. 3:11–13, 46–54.
Gilbert, A., A. Meyer, and M.
2001. Can Feedback from the Jumbo
CD Market Improve Off-Site Surveillance of Small Banks? Working Paper No. 2002-08. Federal Reserve Bank of St.
Gunther, J. W., M. E. Levonian, and R. R. Moore. 2001.
Can the Stock Market Tell Bank Supervisors Anything They Don’t Already Know?
Federal Reserve Bank of Dallas Economic and Financial Review
Hall, J. R., T. B. King, A. P.
Meyer, and M. D. Vaughn.
2001. What Can Bank Supervisors
Learn from Equity Markets? A Comparison of the Factors Affecting Market-Based Risk Measures
and BOPEC Scores. Working Paper
No. 2002-06. Federal Reserve Bank of St. Louis.
Krainer, J., and J. Lopez. 2003.
How Might Financial Market Information Be Used
for Supervisory Purposes? Federal
Reserve Bank of San Francisco Economic Review: 29–45.
* Both authors are in the
Division of Insurance and Research at the Federal Deposit Insurance
Corporation. Steven Burton is a senior
financial analyst and Gary A. Seale is a senior financial economist.
1 Publicly traded insured depositories make up a relatively small
percentage of all insured entities, yet as of September 30, 2004, they held
over 85 percent of all the assets held by insured institutions.
3BOPEC is the acronym for the bank
holding-company rating, assigned by the Federal Reserve Board, and stands for Banking
subsidiaries, Other (nonbanking) subsidiaries, Parent company,
consolidated Earnings, and Consolidated capital. A rating from 1 to 5 is assigned for each
component, with 1 being the best and 5 being the worst. A composite rating from 1 to 5 is also
assigned, reflecting the overall condition of the organization.
4 The CAMELS rating is assigned by a bank’s primary
regulator. The acronym stands for Capital, Assets, Management,
Earnings, Liquidity, and Sensitivity to market risk. A
rating from 1 (the best) to 5 (the worst) is assigned for each of these
component elements, and an overall composite rating based on the component
ratings is then assigned to the bank.
5 The term “market signal” is used to indicate when a change in
investor sentiment about a company’s prospects and risk profile is significant
enough to produce a substantive change in a given market indicator.
6 The CAMELS rating is one example of a supervisory risk
7 The current risk-related premium system is based on a nine-cell
pricing matrix. Institutions are
assigned to cells in this matrix depending on their capital levels (the capital
subgroup) and their CAMELS ratings (the supervisory subgroup). Deposit insurance reform legislation
currently pending before Congress would expand the ability of the FDIC to
consider other factors, including market indicators, when setting insurance
8 These institutions are covered by the Federal Reserve System’s
Large Complex Banking Organization (LCBO) program.
9 Commensurate with its role as insurer and back-up supervisor to
nationally chartered banks and thrift institutions and state-chartered
institutions that are members of the Federal Reserve System, the FDIC has
established two additional surveillance programs for large banks and
thrifts. In each of the two, staff
coordinate their work with their primary-supervisor counterparts to monitor and
independently assess risks in large organizations. One of the two programs is the Dedicated
Examiner program, which assigns dedicated examiners to monitor the activities
of the six largest bank and thrift organizations. The other is the Large Insured Depository
Institution (LIDI) program, which covers all remaining insured organizations
with $10 billion or more in assets.
10 Institutions over $250 million are examined at least once a
year. For institutions under $250
million, the intervals can be extended to 18 months.
11 The Moody’s KMV model uses stock prices and financial information
to derive an expected default probability or expected default frequency (EDFTM) for public firms. The model is based on a Merton contingent
claims approach, where the probability of default is contingent on (1) a firm’s
asset market value, (2) the volatility of a firm’s asset market values, and (3)
the firm’s capital structure or financial leverage.
12 In this illustration, declining credit quality probably
contributed to the declining market valuations.
13 See Burton (2001) for an example of industry risk rankings that
use default expectations and industry loan exposure data.
16 In this example, the intent is to differentiate risk only for
institutions that would be categorized as well-capitalized and highly rated
(that is, 1A institutions) under the current nine-cell risk-based pricing
matrix. The rest of the matrix, which is
reserved for poorly rated and less than well-capitalized institutions, remains the
same. As of year-end 2003, 92 percent of
insured institutions were categorized as 1A institutions.
17 Continuous pricing models might use the output from
failure-prediction models as the basis for pricing deposit insurance
premiums. (Failure-prediction models
typically rely on accounting information.)
The scorecard approach is also based on a failure-prediction model but
applies expert-based subweightings to each variable in the model to produce
discrete risk-based premium subgroups for pricing purposes.
18 As of year-end 2003, approximately 80 insured banking
organizations had between $5 billion and $20 billion in assets.
20 Under the A-IRB approach of Basel II, certain institutions will be
allowed to use internal estimates of credit risk for individual loan exposures
as inputs into regulatory formulas (risk-weight functions), and the regulatory
formulas in turn determine minimum regulatory capital requirements. The principal internal risk measures provided
by A-IRB banks include estimates of probabilities of default, losses given
default, and facility exposures at default.
21 EDFs are point-in-time estimates of the likelihood of default
(usually expressed over a one-year time horizon). In contrast, PDs are intended to represent a
conservative, long-run average view of the likelihood of borrower default.