Vítor Constâncio: How fit are statistics for use in macro-prudential
oversight?
Speech by Mr Vítor Constâncio, Vice-President of the European Central Bank, at the Sixth
ECB Statistics Conference, Frankfurt am Main, 17 April 2012.
* * *
1. Introduction
Macro-prudential analysis and oversight are not new tasks for central banks. In broad terms,
the objective of macro-prudential analysis and oversight is to identify and prevent systemic
risk, so as to minimise the costs that financial instability can impose on the real economy.
Pursuing this objective calls for the definition of qualitative and quantitative intermediate
goals, which can pose considerable analytical and informational challenges.
Over the past few years, the financial crisis has clearly illustrated just how devastating the
materialisation of systemic risk can be for the financial sector and the broader economy. In
particular, the financial crisis has demonstrated the need for a coherent and well-articulated
macro-prudential policy framework at the national, European and global level. In this respect,
it exposed deficiencies in the information base on which macro-prudential oversight
was being conducted. It is on this latter topic that I will focus my presentation today.
In assessing the question as to how fit statistics are for use in macro-prudential oversight, I
will outline the data needed for macro-prudential analysis, touching upon the ECB's
responsibilities in the field of macro-prudential oversight. I will then move on to reflect on
what has been achieved so far, paying particular attention to the macro and
microdimensions of data requirements. Finally, I will highlight what is missing and mention a
number of important ongoing initiatives that could help to overcoming the key challenges in
terms data that we still need to deal with.
2. The macro-prudential oversight function and the role of the ECB
Let me start by reflecting on the macro-prudential oversight function. There are three main
components in the macro-prudential oversight process. The first concerns the surveillance
needed to identify plausible and (systemically) important
sources of risks and
vulnerabilities on the basis of an analysis of the individual and collective strength and
robustness of the constituent parts of the financial system - institutions, markets and
infrastructures. The second involves the assessment of the and the ability of
potential costs
the financial system to cope with these costs should some combination of the identified
risks and vulnerabilities materialise. This requires the ability to measure (and model) the
potential costs and to calibrate the plausibility and importance of the various risks. The third
component is the possible policy response that needs to be clearly justified and interlinked
with systemic risk assessments. In particular, it should inform policy decisions on the
appropriate timing of interventions and the selection of tools.
The role that the ECB and the national central banks of the EU Member States play in
contributing to financial stability is set out in the Treaty on European Union. In the wording
of the Treaty, the ECB is requested to contribute to the smooth conduct of policies pursued
by the competent authorities with respect to the prudential supervision of credit institutions
and the stability of the financial system. Furthermore, the ECB's financial stability function is
also related to its responsibility for overseeing financial market infrastructures. The legal
framework under which the ECB collects statistical data has in fact recently been extended to
expressly recognise its powers to collect data for this purpose.
In 2011 the EU institutional framework was revised to explicitly address both macro and
micro-prudential supervision. This led to the establishment of the European System of
Financial Supervision, the three new European Supervisory Authorities (ESAs) and the
European Systemic Risk Board (ESRB). The ECB is in charge of providing analytical
and statistical support to the ESRB, notably by collecting and processing information that
feeds into discussions within the ESRB.1
3. What has been achieved so far?
In recognition of an increasingly interconnected financial system, considerable progress is
being made in the enhancement and development of new statistics at the euro area, EU and
global level.
At the euro area level, improvements in ECB statistics are notable with regard to, in
particular, the development of enhanced statistics relating to monetary financial institutions
(MFIs) and to shadow banking (e.g. securitisation vehicles). The Securities Holdings
Statistics can also contribute to providing a better picture of interconnectedness at the
of the euro area economy. In the same vein, the
financial system level and for sectors
new Centralised Securities Database of the European System of Central Banks that holds
complete and consistent reference information on individual securities is a major step in the
direction of a better understanding of the map of cross-exposures through securities
holdings.
Further work on enhancing statistical sources and output has been carried out in recent
years. A high priority has been given to the development, collection and maintenance of
conceptually sound and consistent granular data, and - by exploiting sources of micro data -
to monitoring credit exposures, especially those of large financial groups. In addition, efforts
have been made to obtain a consistent picture on securitisation and credit risk transfers in
general. At the same time, work is being undertaken in cooperation with the European
Statistical System (Eurostat and National Statistical Institutes) to improve the availability of
macroeconomic data, as well as financial and non-financial accounts statistics.
In the context of the ESRB-related work, data-sharing agreements have been put in place
to allow the regular provision by the ESAs of aggregated information to the ECB in support of
the ESRB's risk analysis. A number of data sets have already been, or are about to be, made
available by the ESAs:

banking sector data, collected by the European Banking Authority (EBA) on a
quarterly basis, relate to: supervisory data on solvency, credit risk and asset quality,
key risk
earnings risk and balance sheet structure ( indicators), as well as to data on
large exposures, broken down by instrument and by sectoral and geographic
counterpart, for samples of EU large banking groups;

insurance sector data collected by the European Insurance and Occupational
Pension Funds Authority (EIOPA) on an annual basis and, possibly, at a higher
frequency relate to aggregate solvency and profit-and-loss data for large EU
insurance groups;

quarterly data provided by the European Securities Markets Authority (ESMA)
refer to the number of shares admitted to trading in the European Economic Area
(EEA), by country and by market, as well as to the list of EEA markets.
The ECB, in turn, is in the process of making datasets available to the ESRB and the ESAs
that meet their requirements. These cover, in particular, monetary and financial statistics,
namely MFI balance sheet data, MFI interest rate statistics, investment funds statistics and
statistics on securitisation, as well as consolidated banking data. Information from market
data providers, available via the ECB's Market Database, as well as from international
institutions such as the Bank for International Settlements (BIS), Eurostat or the International
Monetary Fund (IMF), which is part of the datasets collected by the ECB, complements the
set of information to support the ESRB's analysis and deliberations.
Cooperation is under way to ensure that the new legislative initiatives of the three ESAs
incorporate ESRB requirements to the extent that they can be addressed by using
supervisory data. Extensive work has already been carried out with the EBA and EIOPA on
the new supervisory templates to be introduced in the next few years. Given the need for
agility in responding to new data to cover ESRB requests for information, work on
procedures to conduct ad hoc surveys has been carried out, ensuring that the confidentiality
issues are duly resolved.
All this work requires a very close and ongoing cooperation not only within the ESCB, but
also with the ESAs and national supervisory authorities, within other collaboration fora and
with many other stakeholders, in particular in the industries concerned, as well as with
international organisations in the context of the G20 initiatives. This cooperation is ensured
through a Contact Group recently appointed by the ESRB Steering Committee at my request,
and it has already proved to be very useful. Inter alia, this cooperation will allow longer-term
data requirements of the ESRB to be met. In the future, a key issue in connection with
minimising the reporting burden of the financial sector is the ability to exchange relevant
datasets. Procedures are in place to ensure that confidentiality is protected. At the moment,
however, these procedures are unduly cumbersome. Appropriate ways to exchange the data
and protect their confidentiality more efficiently will be considered.
Against the background of increasing demand for rigour and quality in systemic risk analysis,
it was to be expected that the ECB's legal powers in the field of statistics would be
activated in order to improve the information base that is available, with a focus on the euro
area. To some extent, this has already been undertaken by developing enhanced statistics
on MFIs, as well as statistics on securities holdings. In fact, the amendment of Council
Regulation 2533/98, governing the ECB's powers to collect statistical information, in 2009
enables the ECB to impose requirements on euro area banks and insurance companies to
provide data, also for financial stability purposes.
4. Macro and micro-dimensions of data requirements
The use of the prefix "macro" and "micro" in the context of the new institutional environment
may create some confusion on the nature of the work to support systemic risk analysis and
related data inputs. There is no such thing like a clear separation of macro - or aggregated -
data inputs that are used in macro-prudential analysis from micro-data, i.e. data at the level
of individual firms, used in micro-prudential analysis. As mentioned before, a range of
important data needed for macro-prudential analysis relate to firm-specific data on
financial firms. Risk assessment tools for example, such as stress tests to assess the
relevance of specific risk scenarios, are labelled macro-stress tests (as opposed to the
"micro" tests run by banks individually at the request of the regulator). Nevertheless, the
usefulness of these tools depends on the quality and detail of the bank-specific data. The
relevance of the results for macro-prudential purposes is, of course, to be found in the
aggregated figures (the impact on banking sector capital) and their subsequently interplay
with the macro-financial environment, lending activities and overall growth.
For stress testing tools, selected supervisory data are important for achieving reliable results.
However, for other types of analytical tools and indicators, the use of publicly available
information may be sufficient, or even preferable for reasons such as the comparability of
data across financial firms or transparency. In official financial stability publications, for
example, it is often considered important that readers and market analysts are able to
replicate analyses with information in the public domain.
Generally speaking, while it is essential that supervisory data are well protected, there would
be merit in distinguishing between different layers of confidentiality and, thereby, to facilitate
that selected supervisory information is made available for macro-prudential analysis.
Furthermore, in view of the importance attached to publicly available data, there is a need for
this information to be harmonised and provided in a standardised format that is easy to
access. As in any other policy field, the higher the quality of the input data, the more
reliable are the results of analytical work, and thus the policy decisions.
In addition, there is the definition of data confidentiality. Taking an extreme view, all
information that has not been published could be labelled "confidential", while the other
extreme would be to make everything public. It would be fair to say that the "definition" used
in Europe appears to be stricter than that in other jurisdictions. For example, some regulators
such as the US Federal Financial Institutions Examinations Council publish selected
supervisory information on banking institutions operating in the US market, including on
subsidiaries of European banking groups, regularly (on a quarterly basis). Parts of these data
are "confidential" in Europe, but this is not so on the other side of the Atlantic. As mentioned
earlier, a change in attitude by EU financial regulators would greatly benefit the quality of the
risk-monitoring and risk-evaluation work undertaken by macro-prudential bodies. In addition,
it would provide a concrete signal of increased transparency to market analysts and financial
market participants. In turn, it would help significantly to minimise the reporting burden of the
industry.
Let me try to illustrate my point with some examples.

The breakdowns of banks' credit exposures by type of collateral or
counterparty sector (e.g. central government, non-financial institutions, financial
institutions, small and medium-sized enterprises (SMEs), residential mortgages or
commercial property) are reported to supervisory authorities, but these breakdowns
are not part of regular harmonised public financial reporting. Hence, surveillance
indicators and assessment exercises based on publicly available credit exposure
data may by impaired by the high level of aggregation of the information disclosed.
For example, if early warning signals were to point to risks emerging in commercial
property or the SME sector, it would be important to assess the relevance of banks'
exposures to this particular asset class in a systematic way. This is not possible if all
credit exposures are disclosed in aggregate. Furthermore, the breakdown of credit
exposures can be rather important for monitoring banks' risk profiles in the
macroprudential context. In risk assessment work, the quality of top-down stress testing
results may be compromised if the distribution of credit exposures by bank across
the main exposure classes needs to be approximated. Likewise, information on
credit risk parameters, notably on incurred losses by type of exposure, would need
to be consistently disclosed by banks, or to be made available to macro-prudential
authorities from supervisory sources. In turn, owing to the importance of such credit
exposure data, I much welcome the efforts being undertaken to harmonise the
datasets in existing credit registers, subject also to an improved coverage, even if
this can only complement extensive supervisory reports.

The analysis of financial institutions' sovereign debt exposures constitutes another
example where (regular) publicly available information has proved to be insufficient
to carry out a reliable macro-prudential analysis. On the eruption of the sovereign
debt crisis, market participants reacted abruptly to any news concerning those
exposures. Analysis on the basis of aggregated data on banks' consolidated foreign
claims vis-à-vis the public sector in several countries proved to be too imprecise.
When the individual exposures to sovereign debt of the largest players in the
European banking system were released by the EBA in the context of the stress test
exercise in July 2011, spillover effects diminished and markets started to
differentiate across the banks. In this case, enhanced transparency proved to be
helpful in influencing markets and market participants' behaviour.

Examples of indicators where individual bank data would sharpen
macroprudential analysis are numerous. In the context of the analysis and assessment
of funding vulnerabilities, reporting on banks' reliance on retail and wholesale
funding has ample scope for improvement. Details of banks' deposits, interbank,
senior and subordinated debt are poorly disclosed, and the analysis based on
loanto-deposit ratios, currently the best proxy for maturity mismatches, can provide an
only incomplete picture of possibly emerging imbalances. A critical area is also that
of asset quality indicators, the comparability of which is very poor across banks in
Europe on account of different definitions of non-performing assets and loan loss
provisions. A more granular disclosure of data could allow the construction of more
meaningful sets of indicators and prevent misleading comparisons across
institutions. On the analysis of capital adequacy, uncertainly about the computation
of risk-weighted assets is shifting the focus to indicators calculated on the basis of
total assets or tangible assets, balance-sheet equity and leverage ratios.
Clearly, in the medium-term, a higher quality of data for financial stability surveillance and
assessment may also be achieved through a on the part of
better disclosure policy
financial institutions. Benefits would come also from timely and harmonised reporting.
5. What is missing: remaining data gaps and other challenges confronting
macro-prudential analysis
While data gaps can never be closed in full - also because they are a moving target -
attempts to reduce these gaps are vital.
With respect to macro-level data, efforts to improve the effective coverage of the so-called
shadow banking sector - i.e. of credit intermediation, liquidity and maturity transformation
activities that take place outside the regulated banking system - need to be continued.
Important components of the shadow banking system include certain money market funds,
structured investment vehicles, off-balance-sheet vehicles (reliant on banks' credit lines) and
securities lenders. Although some progress has been made, data gaps remain that render
the proper monitoring and assessment of systemic risks arising from securities financing
transactions (notable via repurchase agreements and securities lending) unfeasible.
Challenges also arise from the activities of the shadow banking system that go beyond a
specific group of entities or types of business. Regular information on margins, on other risk
management practices and on the use of the various types of collateral, as well as on the
maturity and liquidity profiles, is important for assessing the risks associated with securities
lending activities from a qualitative and quantitative point of view. Surveys on credit terms in
securities financing and over-the-counter (OTC) derivatives markets, as have been
launched by a number of central banks (around the world) and, soon, by the ECB, are a step
in the right direction. The Financial Stability Board (FSB) is also monitoring efforts to improve
data on shadow banking and OTC transactions.
Even in the case of the regulated sector, objectives have not yet been met. At present, most
efforts relate to harmonising, increasing the frequency, achieving more granularity and
extending the coverage of the data for financial sectors in the EU.
Given the important role played by contagion in the recent crisis, data should enable
analyses of the interlinkages - notably across financial institutions, and between them and
the shadow banking system. Information on interlinkages between important players in the
financial system, including counterparty credit exposures in different forms, funding
exposures of individual financial firms, as well as detailed information on their maturity
mismatches and leverage, is necessary. This is because vulnerabilities can stem, for
example, from common exposures in lending activities, from securities transactions, from
positions in derivatives markets, from funding relationships, or from settlement and clearing
functions. More data on the granularity of balance-sheet exposures and across types of
financial instruments are essential inputs for evaluating propagation effects with contagion
and spillover models. Recent initiatives in central bank statistics also address interlinkages
beyond the sample of large players - for example, by means of so-called "from whom to
whom" information on deposits and loans from financial corporations, or through securities
holding statistics with a view to also creating "who to whom" data for various sectors of the
economy in the Euro Area Accounts. Dedicated ad hoc surveys, for example in the context of
the ESRB's work at an EU-wide level, should also contribute to shedding light on this topic.
Sufficiently granular information would facilitate linking the regulated financial sector with the
shadow banking sector.
In addition, enhancing information on financial conglomerates - banking groups with
substantial activities over and beyond the banking sector - would be essential, as
nonbanking activities may be systemically important. In the case of financial conglomerates,
contagion and concentration risks can be exacerbated by the increased intra-group
complexity and potential conflicts of interest.
At the micro-level, improvements to data for characterising interconnectedness are being
pushed forward by several initiatives with different objectives and time lines. Let me mention
three: (i) the revision of the reporting framework for large exposures by the EBA (for
microprudential supervision), (ii) the FSB's common template (limited to a small number of globally
systemic institutions) to improve data on global banking interlinkages and (iii) a UK exercise
to collect interbank data on recovery and resolution plans (with very detailed instrument and
maturity breakdowns). While these initiatives address primarily micro-prudential data needs
for the time being, their use for macro-purposes could be envisaged, provided that data
confidentiality is preserved and that requests are duly justified. For macro-prudential
oversight, the importance of reducing gaps in the data on credit and funding exposures
beyond jurisdictions and the sample of global players, appears particularly relevant. As the
crisis has illustrated, the structure of bank liabilities and the way in which assets are funded
are of utmost importance for understanding maturity mismatches and interlinkages.
Related to funding, data gaps also arise from limited information on the degree of
asset
encumbrance stemming from secured funding, as well as from inadequate data on the
levels and characteristics of innovative sources of funding used by banks. At present,
these elements are essential for analysing fragilities in the funding models of banks
established in the EU. Uncertainty about the level of banks' asset encumbrance is also
hampering market participants' capacity to assess banks' creditworthiness, thereby reducing
the availability and increasing the costs of unsecured funding. Risks to financial stability can
also stem from novel sources of funding such as exchange traded funds (ETFs) or liquidity
swaps. There is no consistent framework at the EU level for collecting data on the use of
these instruments, but attempts to limit information gaps on this topic in the EU are under
way, possibly by means of ad hoc surveys under the aegis of the ESRB.
6. Concluding remarks
As mentioned earlier in my remarks today, data challenges would be far more modest, and
the need for supervisory information reduced, if the level of public disclosure, the quality
and the accessibility of, and consistency in, financial public reporting were more satisfactory.
This would also benefit market participants at large - notably by reducing uncertainty with
respect to counterparties. Further encouragement and guidance by national authorities (in
addition to another FSB initiative on disclosure) could be provided to improve the financial
reporting of institutions and to enhance the quality of disclosures.
On another front, the establishment of a common legal entity identifier (LEI) that is applied
universally should contribute greatly to the quality of macro-prudential analysis. It would, for
example, facilitate the aggregation of the single-name counterparty risk at the level of the
system and can, for example, help in the identification of the building-up of concentrations
towards single counterparties. Unique identification codes at the EU level will be valuable
for meaningful data aggregations, and would allow the use of this information for
macroprudential purposes. In fact, the demand for micro-prudential datasets for macro-prudential
analysis also results from the fact that the form in which existing aggregated data can be
disseminated is often of poor quality, is not sufficiently granular and is not suited for
analytical purposes.
Ahead of reaping the benefits from the various initiatives that are under way at the global, EU
and euro area level to limit data gaps, there is a need for close cross institutional
cooperation between supervisory authorities and macro-prudential bodies, at the national
and supra-national level. This calls for more interaction and data-sharing between the ECB
(also when acting on behalf of the ESRB) and the ESAs that have access to supervisory
reporting data and can collect ad hoc data more easily upon request. Procedures for the
secure transfer of information and appropriate legal provisions need to be in place to
safeguard confidentiality.
More broadly, it is important that the pace at which efforts are being made to address current
information needs - at the macro- and micro-levels - does not slow down. At the same time,
improvements in datasets already in use for macro-prudential analysis should continue to be
given priority. This needs to be done in an innovative way, reusing existing information where
possible, so as to minimise the reporting burden, whilst serving the increased demands of
users. Furthermore, challenges in ensuring that the appropriate statistical basis is available
for macro-prudential oversight cannot, by definition, be addressed in full as data sets are
dynamic, in the same way that the risks they capture evolve over time. Agility in the
collection of statistics will therefore continue to be essential so as to accompany innovation in
the financial industry and the associated vulnerabilities.