Daniel K Tarullo: Equipping financial regulators with the tools necessary
to monitor systemic risk
Testimony by Mr Daniel K Tarullo, Member of the Board of Governors of the Federal
Reserve System, before the Subcommittee on Security and International Trade and Finance,
Committee on Banking, Housing, and Urban Affairs, US Senate, Washington DC,
12 February 2010.
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Chairman Bayh, Ranking Member Corker, and other members of the Committee, thank you
for inviting me to testify today. I also want to thank all of you for taking the time to explore a
subject that is easily overlooked in the public debate around financial reform, but that will be
central to ensuring a more stable financial system in the future.
The recent financial crisis revealed important gaps in data collection and systematic analysis
of institutions and markets. Remedies to fill those gaps are critical for monitoring systemic
risk and for enhanced supervision of systemically important financial institutions, which are in
turn necessary to decrease the chances of such a serious crisis occurring in the future. The
Federal Reserve believes that the goals of agency action and legislative change should be
(1) to ensure that supervisory agencies have access to high-quality and timely data that are
organized and standardized so as to enhance their regulatory missions, and (2) to make
such data available in appropriately usable form to other government agencies and private
analysts so that they can conduct their own analyses and raise their own concerns about
financial trends and developments.
In my testimony this morning I will first review the data collection and analysis activities of the
Federal Reserve that are relevant to systemic risk monitoring and explain why we believe
additional data should be collected by regulatory authorities with responsibility for financial
stability. Next I will set forth some principles that we believe should guide efforts to achieve
the two goals I have just noted. Finally, I will describe current impediments to these goals
and suggest some factors for the Congress to consider as it evaluates potential legislation to
improve the monitoring and containment of systemic risk.
The Federal Reserve and macro-prudential supervision
The Federal Reserve has considerable experience in data collection and reporting in
connection with its regulation and supervision of financial institutions, monetary policy
deliberations, and lender-of-last-resort responsibilities. The Federal Reserve has made large
investments in quantitative and qualitative analysis of the U.S. economy, financial markets,
and financial institutions. The Federal Reserve also has recently initiated some new data
collection and analytical efforts as it has responded to the crisis and in anticipation of new
financial and economic developments.
For supervision of the largest institutions, new quantitative efforts have been started to better
measure counterparty credit risk and interconnectedness, market risk sensitivities, and
funding and liquidity. The focus of these efforts is not only on risks to individual firms, but
also on concentrations of risk that may arise through common exposures or sensitivity to
common shocks. For example, additional loan-level data on bank exposures to syndicated
corporate loans are now being collected in a systematic manner that will allow for more
timely and consistent measurement of individual bank and systemic exposures to these
sectors. In addition, detailed data obtained from firms' risk-management systems allow
supervisors to examine concentration risk and interconnectedness. Specifically, supervisors
are aggregating, where possible, the banks' largest exposures to other banks, nonbank
financial institutions, and corporate borrowers, which could be used to reveal large
exposures to individual borrowers that the banks have in common or to assess the credit
impact of a failure of a large bank on other large banks. Additional time and experience with
these data will allow us to assess the approach's ability to signal adverse events, and
together they will be a critical input to designing a more robust and consistent reporting
system.
Furthermore, we are collecting data on banks' trading and securitization risk exposures as
part of an ongoing, internationally coordinated effort to improve regulatory capital standards
in these areas. Moreover, analysis of liquidity risk now incorporates more explicitly the
possibility of marketwide shocks to liquidity. This effort also is an example of the importance
of context and the need to understand the firms' internal risk models and risk-management
systems in designing data collection requirements. Data that only capture a set of positions
would not be sufficient since positions would not incorporate behavioral assumptions about
firms, based on information about firms' business models and practices.
The Federal Reserve's responsibilities for monetary policy are also relevant for systemic risk
monitoring. Systemic risk involves the potential for financial crises to result in substantial
adverse effects on economic activity. As the nation's central bank, the Federal Reserve
assesses and forecasts the U.S. and global economies using a wide variety of data and
analytical tools, some based on specific sectors and others on large-scale models. In the
wake of the crisis, research has been expanded to better understand the channels from the
financial sector to the real economy. For example, building on lessons from the recent crisis,
the Federal Reserve added questions to the Survey of Professional Forecasters to elicit from
private-sector forecasters their subjective probabilities of forecasts of key macroeconomic
variables, which provides to us, and to the public, better assessments of the likelihood of
severe macroeconomic outcomes.
The Federal Reserve has made substantial investments in data and analytical staff for
financial market monitoring. Each day, the Trading Desk at the Federal Reserve Bank of
New York analyzes and internally distributes reports on market developments, focusing on
those markets where prices and volumes are changing rapidly, where news or policy is
having a major effect, or where there are special policy concerns. Those analyses begin with
quantitative data, supplemented with information obtained through conversations with market
participants and reviews of other analyses available in the market. Over the past few years,
the Desk has worked closely with our research staff in developing new quantitative tools and
new data sources.
This ongoing monitoring requires continual evaluation of new data sources and analytical
tools to develop new data as new markets and practices develop. For example, information
on market volumes and prices can be collected from new trading platforms and brokers, data
on instruments such as credit default swaps, or CDS, are provided by vendors or market
participants, and fresh insights are gained from new methods of extracting information from
options data. In some cases, publication of data by the private sector may be mandated by
legislation (such as, potentially, trade data from over-the-counter derivatives trade
repositories); in other cases, the Federal Reserve or other government agencies or
regulators require or encourage the gathering and publication of data.
Our experiences with supervision, monetary policy, and financial market monitoring suggest
that market data gathering and market oversight responsibilities must continuously inform
one another. In addition, efforts to identify stresses in the system are not a matter of running
a single model or focusing on a single risk. Rather, it is the assembly of many types of
analysis in a systematic fashion. The Supervisory Capital Assessment Program (SCAP) for
large financial institutions - popularly known as the "stress test" when it was conducted early
last year - illustrates the importance of combining analysis by credit experts, forecasts and
scenario design by macroeconomists, and hands-on judgments by supervisors in assessing
the financial condition and potential vulnerabilities of large financial institutions.
While considerable steps have been made in the wake of the financial crisis, the Federal
Reserve intends to do a good deal more. The Federal Reserve also will continue to
strengthen and expand its supervisory capabilities with a macro-prudential approach by
drawing on its considerable data reporting, gathering, and analytical capabilities across many
disciplines. In the areas in which we are collecting data through the supervisory process on
measures of interlinkages and common exposures among the largest financial firms we
supervise, we are developing new analytical tools that may lead us to change our information
requests from supervised firms. The Federal Reserve is exploring how to develop analytically
sophisticated measures of leverage and better measures of maturity transformation from
information that we can collect from the supervised firms in the supervisory process and from
other available data and analysis. We envision developing a robust set of key indicators of
emerging risk concentrations and market stresses that would both supplement existing
supervisory techniques and assist in the early identification of early trends that may have
systemic significance and bear further inquiry. This kind of approach will require data that are
produced more frequently than the often quarterly data gathered in regulatory reports,
although not necessarily real-time or intraday, and reported soon after the fact, without the
current, often long, reporting lags. These efforts will need to actively seek international
cooperation as financial firms increasingly operate globally.
The potential benefits of additional data
Improved data are essential for monitoring systemic risk and for implementing a
macroprudential approach to supervision. The financial crisis highlighted the existence of
interlinkages across financial institutions and between financial institutions and markets.
Credit risks were amplified by leverage and the high degree of maturity transformation,
especially outside of traditional commercial banking institutions. Moreover, supervision
traditionally has tended to focus on the validity of regulated firms' private risk-management
systems, which did not easily allow comparisons and aggregation across firms.
One key feature of the recent crisis was the heavy reliance on short-term sources of funds to
purchase long-term assets, which led to a poor match between the maturity structure of the
firms' assets and liabilities. Such maturity transformation is inherently fragile and leaves
institutions and entire markets susceptible to runs. Indeed, a regulatory, supervisory, and
insurance framework was created during the Great Depression to counter this problem at
depository institutions. However, in recent years a significant amount of maturity
transformation took place outside the traditional banking system - in the so-called shadow
banking system - through the use of commercial paper, repurchase agreements, and other
instruments. Our ability to monitor the size and extent of maturity transformation has been
hampered by the lack of high-quality and consistent data on these activities. Better data on
the sources and uses of maturity transformation outside of supervised banking organizations
would greatly aid macro-prudential supervision and systemic risk regulation.
Another feature of the recent crisis was the extensive use of leverage, often in conjunction
with maturity transformation. The consequences of this combination were dramatic. When
doubts arose about the quality of the assets on shadow banking system balance sheets, a
classic adverse feedback loop ensued in which lenders were increasingly unwilling to roll
over the short-term debt that was used as funding. Liquidity-constrained institutions were
forced to sell assets at increasingly distressed prices, which accelerated margin calls for
leveraged actors and amplified mark-to-market losses for all holders of the assets, including
regulated firms. Here, too, government regulators and supervisors had insufficient data to
determine the degree and location of leverage in the financial system.
More generally, the crisis revealed that regulators, supervisors, and market participants could
not fully measure the extent to which financial institutions and markets were linked. A critical
lesson from this crisis is that supervisors and investors need to be able to more quickly
evaluate the potential effects, for example, of the possible failure of a specific institution on
other large firms through counterparty credit channels; financial markets; payment, clearing,
and settlement arrangements; and reliance on common sources of short-term funding.
A better system of data collection and aggregation would have manifold benefits, particularly
if the data are shared appropriately among financial regulators and with a systemic risk
council if one is created. It would enable regulators and a council to assess and compare
risks across firms, markets, and products. It would improve risk management by firms
themselves by requiring standardized and efficient collection of relevant financial information.
It also would enhance the ability of the government to wind down systemically important firms
in a prompt and orderly fashion by providing policymakers a clearer view of the potential
impacts of different resolution options on the broader financial system.
Additional benefits would result from making data public to the degree consistent with
protecting firm-specific proprietary and supervisory information. Investors and analysts would
have a more complete picture of individual firms' strengths and vulnerabilities, thereby
contributing to better market discipline. Other government agencies, academics, and
additional interested parties would be able to conduct their own analyses of financial system
developments and identify possible emerging stresses and risks in financial markets.
One area in which better information is particularly important is the web of connections
among financial institutions though channels such as interbank lending, securities lending,
repurchase agreements, and derivatives contracts. Regulators also need more and better
data on the links among institutions through third-party sponsors, liquidity providers,
creditsupport providers, and market makers. Knowledge of such network linkages is a necessary
first step to improve analysis of how shocks to institutions and markets can propagate
through the financial system.
Principles for developing a system of effective data and analytical tools
Moving from the recognition of the need for more data to an efficient data system is not an
easy task. Data collection entails costs in collection, organization, and utilization for
government agencies, reporting market participants, and other interested parties. Tradeoffs
may need to be faced where, for example, a particular type of information would be very
costly to collect and would have only limited benefits. The Internet and other applications of
information technologies have made us all too aware of the potential for information
overload, a circumstance in which relevant information is theoretically available, but the time
and expense of retrieving it or transforming it into a usable form make it unhelpful in practical
terms. Collection of more data just for its own sake also can raise systemic costs associated
with moral hazard if investors view data collection from certain firms, products, and markets
as suggesting implicit support. It is thus particularly worth emphasizing the importance of
having data available readily and in a form that is appropriate for the uses to which it will be
put. With these considerations in mind, we have derived a number of guiding principles for a
system of new data and analytical tools for effectively supervising large institutions and
monitoring systemic risk.
First, the priorities for new data efforts should be determined by the nature of regulatory and
supervisory missions. In particular, the data need to be sufficiently timely and to cover a
sufficient range of financial institutions, markets, instruments, and transactions to support
effective systemic risk monitoring and macro-prudential supervision, as well as traditional
safety-and-soundness regulation. The events of the past few years have painfully
demonstrated that regulators, financial institutions, and investors lacked ready access to data
that would have allowed them to fully assess the value of complex securities, understand
counterparty risks, or identify concentrations of exposures.
The data needed for systemic risk monitoring and supervision are not necessarily "real-time"
market data - information about trades and transactions that can be reported at high
frequency when the events occur - but certainly data would need to be "timely". What is
considered to be "timely" will depend on its purpose, and decisions about how timely the data
should be should not ignore the costs of collecting and making the data usable. For many
supervisory needs, real-time data would be impractical to collect and analyze in a meaningful
way and unnecessary. For example, while supervisors may indeed need to be able to quickly
value the balance sheets of systemically important financial institutions, very frequent
updates as transactions occur and market prices change could lead to more volatility in
values than fundamental conditions would indicate and would be extraordinarily expensive to
provide and maintain. Certainly, real-time data could be needed for regulators responsible for
monitoring market functioning, and daily data would be helpful to measure end-of-day
payment settlements and risk positions among the largest firms. But for supervising market
participants, real-time market data could require enormous investments by regulators,
institutions, and investors in order to be usable while yielding little net benefit. As
policymakers consider redesign of a system of data collection, the goal should be data that
are timely and best suited to the mission at hand.
A second principle is that data collection be user-driven. That is, data on particular markets
and institutions should be collected whenever possible by the regulators who ultimately are
responsible for the safety and soundness of the institutions or for the functioning of those
markets. Regulators with supervisory responsibilities for particular financial firms and
markets are more likely to understand the relevance of particular forms of standardized data
for risk management and supervisory oversight. For example, supervisors regularly evaluate
the ability of individual firms' own risk measures, such as internal ratings for loans, and of
liquidity and counterparty credit risks, to signal potential problems. As a result, these
supervisors have the expertise needed to develop new reporting requirements that would be
standardized across firms and could be aggregated.
Third, greater standardization of data than exists today is required. Standardized reporting to
regulators in a way that allows aggregation for effective monitoring and analysis is
imperative. In addition, the data collection effort itself should encourage the use of common
reporting systems across institutions, markets, and investors, which would generally enhance
efficiency and transparency. Even seemingly simple changes, such as requiring the use of a
standardized unique identifier for institutions (or instruments), would make surveillance and
reporting substantially more efficient.
Fourth, the data collected and the associated reporting standards and protocols should
enable better risk management by the institutions themselves and foster greater market
discipline by investors. Currently, because the underlying data in firms' risk-management
systems are incomplete or are maintained in nonstandardized proprietary formats, compiling
industry-wide data on counterparty credit risk or common exposures is a challenge for both
firms and supervisors. Further, institutions and investors cannot easily construct fairly basic
measures of common risks across firms because they may not disclose sufficient
information. In some cases, such as disclosure of characteristics of underlying mortgages in
a securitized pool, more complete and interoperable data collection systems could enhance
market discipline by allowing investors to better assess the risks of the securities without
compromising proprietary information of the lending institution.
Fifth, data collection must be nimble, flexible, and statistically coherent. With the rapid pace
of financial innovation, a risky new asset class can grow from a minor issue to a significant
threat faster than government agencies have traditionally been able to revise reporting
requirements. For example, collateralized debt obligations based on asset-backed securities
grew from a specialized niche product to the largest source of funding for asset-backed
securities in just a few years. Regulators, then, should have the authority to collect
information promptly when needed, even when such collections would require responses
from a broad range of institutions or markets, some of which may not be regulated or
supervised. In addition, processes for information collection must meet high standards for
reliability, coherence, and representativeness.
Sixth, data collection and aggregation by regulatory agencies must be accompanied by a
process for making the data available to as great a degree as possible to fellow regulators,
other government entities, and the public. There will, of course, be a need to protect
proprietary and supervisory information, particularly where specific firm-based data are at
issue. But the presumption should be in favor of making information widely available.
Finally, any data collection and analysis effort must be attentive to its international
dimensions and must seek appropriate participation from regulators in other nations,
especially those with major financial centers. Financial activities and risk exposures are
increasingly globalized. A system without a common detailed taxonomy for securities and
counterparties and comparable requirements for reporting across countries would make
assembling a meaningful picture of the exposures of global institutions very difficult. Efforts to
improve data collection are already under way in the European Union, by the Bank of
England and the Financial Services Authority, and the European Central Bank, which has
expressed support for developing a unified international system of taxonomy and reporting.
The Financial Stability Board, at the request of the G-20, is initiating an international effort to
develop a common reporting template and a process to share information on common
exposures and linkages between systemically important global financial institutions.
Barriers to effective data collection for analysis
Legislation will be needed to improve the ability of regulatory agencies to collect the
necessary data to support effective supervision and systemic risk monitoring. Restrictions
designed to balance the costs and benefits of data collection and analysis have not kept
pace with rapid changes in the financial system. The financial system is likely to continue to
change rapidly, and both regulators and market participants need the capacity to keep pace.
Regulators have been hampered by a lack of authority to collect and analyze information
from unregulated entities. But the recent financial crisis illustrated that substantial risks from
leverage and maturity transformation were outside of regulated financial firms. In addition,
much of the Federal Reserve's collection of data is based on voluntary participation. For
example, survey data on lending terms and standards at commercial banks, lending by
finance companies, and transactions in the commercial paper market rely on the cooperation
of the surveyed entities. Moreover, as we have suggested, the data collection authority of
financial regulators over the firms they supervise should be expanded to encompass
macroprudential considerations. The ability of regulators to collect information should similarly be
expanded to include the ability to gather market data necessary for monitoring systemic
risks. Doing so would better enable regulators to monitor and assess potential systemic risks
arising directly from the firms or markets under their supervision or from the interaction of
these firms or markets with other components of the financial system.
The Paperwork Reduction Act also can at times impede timely and robust data collection.
The act generally requires that public notice be provided, and approval of the Office of
Management and Budget (OMB) be obtained, before any information requirement is applied
to more than nine entities. Over the years, the act's requirement for OMB approval for
information collection activity involving more than nine entities has discouraged agencies
from undertaking many initiatives and can delay the collection of important information in a
financial crisis. For example, even a series of informal meetings with more than nine entities
designed to learn about emerging developments in markets may be subject to the
requirements of the act. While the principle of minimizing the burdens imposed on private
parties is an important one, the Congress should consider amending the act to allow the
financial supervisory agencies to obtain the data necessary for financial stability in a timely
manner when needed. One proposed action would be to increase the number of entities from
which information can be collected without triggering the act; another would be to permit
special data requests of the systemically important institutions could be conducted more
quickly and flexibly.
The global nature of capital markets seriously limits the extent to which one country acting
alone can organize information on financial markets. Many large institutions have foreign
subsidiaries that take financial positions in coordination with the parent. Accordingly, strong
cooperative arrangements among domestic and foreign authorities, supported by an
appropriate statutory framework, are needed to enable appropriate sharing of information
among relevant authorities. Strong cooperation will not be a panacea, however, as legal and
other restrictions on data sharing differ from one jurisdiction to the next, and it is unlikely that
all such restrictions can be overcome. But cooperation and legislation to facilitate sharing
with foreign authorities appears to be the best available strategy.
Significant practical barriers also exist that can, at times, limit the quality of data collection
and analysis available to support effective supervision and regulation, which include barriers
to sharing data that arise from policies designed to protect privacy. For example, some
private-sector databases and bank's loan books include firms' tax identification (ID) numbers
as identifiers. Mapping those ID numbers into various characteristics, such as broad
geographic location or taxable income measures, can be important for effective analysis and
can be done in a way that does not threaten privacy. However, as a practical matter, a firm
may have multiple ID numbers or they may have changed, but the Internal Revenue Service
usually cannot share the information needed to validate a match between the firm and the ID
number, even under arrangements designed to protect the confidentiality of the taxpayer
information obtained.
In addition, a significant amount of financial information is collected by private-sector vendors
seeking to profit from the sale of data. These vendors have invested in expertise and in the
quality of data in order to meet the needs of their customers, and the Federal Reserve is a
purchaser of some of these data. However, vendors often place strong limitations on the
sharing of such data with anyone, including among federal agencies, and on the manner in
which such data may be used. They also create systems with private identifiers for securities
and firms or proprietary formats that do not make it easy to link with other systems. Surely it
is important that voluntary contributors of data be able to protect their interests, and that the
investments and intellectual property of firms be protected. But the net effect has been a
noncompatible web of data that is much less useful, and much more expensive, to both the
private and the public sector, than it might otherwise be.
Protecting privacy and private-sector property rights clearly are important policy objectives;
they are important considerations in the Federal Reserve's current data collection and
safeguarding. Protecting the economy from systemic risk and promoting the safety and
soundness of financial institutions also are important public objectives. The key issue is
whether the current set of rules appropriately balances these interests. In light of the
importance of the various interests involved, the Congress should consider initiating a
process through which the parties of interest may exchange views and develop potential
policy options for the Congress's consideration.
Organization structure for data collection and developing analytical tools
In addition to balancing the costs and benefits of enhanced data and analytical tools, the
Congress must determine the appropriate organizational form for data collection and
development of analytical tools. Budget costs, production efficiencies, and the costs of
separating data collection and analysis from decision-making are important considerations.
Any proposed form of organization should facilitate effective data sharing. It also should
increase the availability of data, including aggregated supervisory data as appropriate, to
market participants and experts so that they can serve the useful role of providing
independent perspectives on risks in the financial system.
The current arrangement, in which different agencies collect and analyze data, cooperating
in cases where a consensus exists among them, can certainly be improved. The most
desirable feature of collection and analysis under the existing setup is that it satisfies the
principle that data collection and analysis should serve the end users, the regulatory
agencies. Each of the existing agencies collects some data from entities it regulates or
supervises, using its expertise to decide what to collect under its existing authorities and how
to analyze it. Moreover, the agencies seek to achieve cost efficiencies and to reduce burdens
on the private sector by cooperating in some data collection. An example is the Consolidated
Reports of Condition and Income, or Call Reports, collected by the bank regulatory agencies
from both national and state-chartered commercial banks. The content of the reporting forms
is coordinated by the Federal Financial Institutions Examination Council, which includes
representatives of both state and federal bank regulatory agencies.
A standalone independent data collection and analysis agency might be more nimble than
the current setup because it would not have to reach consensus with other agencies. It might
also have the advantage of fostering an overall assessment of financial data needs for all
governmental purposes.
However, there would also be some substantial disadvantages to running comprehensive
financial data collection through a separate independent agency established for this purpose.
A new agency would entail additional budget costs because the agency would likely need to
replicate many of the activities of the regulatory agencies in order to determine what data are
needed. More importantly, because it would not be involved directly in supervision or market
monitoring, such an agency would be hampered in its ability to understand the types of
information needed to effectively monitor systemic risks and conduct macro-prudential
supervision. Data collection and analysis are not done in a vacuum; an agency's duties will
inevitably reflect the priorities, experience, and interests of the collecting entity. Even regular
arms-length consultations among agencies might not be effective, because detailed
appreciation of the regulatory context within which financial activities that generate data and
risks is needed. The separation of data collection and regulation could also dilute
accountability if supervisors did not have authority to shape the form and scope of reporting
requirements by regulated entities in accordance with super