WP/13/199

Addressing Interconnectedness:
Concepts and Prudential Tools

Nicolas Arregui, Mohamed Norat, Antonio Pancorbo,

and Jodi Scarlata

with Eija Holttinen, Fabiana Melo, Jay Surti, Chris Wilson,

Rodolfo Wehrhahn, and Mamoru Yanase
© 2013 International Monetary Fund WP/13/199

IMF Working Paper

Monetary and Capital Markets Department

Addressing Interconnectedness: Concepts and Prudential Tools

Prepared by Nicolas Arregui, Mohamed Norat, Antonio Pancorbo, and Jodi Scarlata

Authorized for distribution by Michaela Erbenova

September 2013

This Working Paper should not be reported as representing the views of the IMF.
The views expressed in this Working Paper are those of the author(s) and do not necessarily
represent those of the IMF or IMF policy. Working Papers describe research in progress by the
author(s) and are published to elicit comments and to further debate.

Abstract

This paper reviews tools used to identify and measure interconnectedness and raises the
awareness of policymakers as to potential cross-sectional implications of prudential tools
aimed at controlling interconnectedness. The paper examines two sets of tools—developed at
the IMF and externally—to identify the implications of interconnectedness in systemic risk
and how these tools have been applied in IMF surveillance. The paper then proposes a
preliminary framework to analyze some key internationally-agreed-upon and national
prudential tools and finds that while many prudential tools are effective in reducing
interconnectedness, the interaction among these tools is far less clear cut.

JEL Classification Numbers: G20, G21, G22, G23 G28, C38, C45

Keywords: Interconnectedness; network analysis; prudential tools; policymakers; systemic

riskAuthor’s E-Mail Address:jscarlata@imf.org
 2

Contents Page

I. Introduction ............................................................................................................................3

II. The role of interconnectedness analysis in addressing Systemic Risk..................................4

A. Analytical Tools to Assess Interconnectedness and Concentration ..........................6
B. Use of Analytical Tools, their Complementary Nature, and Limitations .................9
C. Analysis of Interconnectedness and Policymaking .................................................11

III. Prudential tools and interconnectedness ............................................................................12

A. Cross-Sectional Prudential Tools: A Recent Review .............................................12
B. Cross-sectional Prudential tools: Assessment of Interactions and Impact ..............23

IV. Policy Considerations and Next Steps ...............................................................................29

References ................................................................................................................................33

Tables
1. Tools for Network Analysis ...................................................................................................7
2. Main Market-Based Measures Used at the IMF ....................................................................9
3. Comparison of Some Methodology to Compute Systemic Risk-Based Charges ................12
4. Comparison of the Structural Reform Proposals .................................................................20
5. Interaction of Prudential Tools to Deal with Bank Interconnectedness: .............................24

Figures
1. The G14 and the CCP Global Network ...............................................................................17
2. Dense Interconnected Network ............................................................................................43
3. Cluster Identification: A Stylized Depiction........................................................................46
4. CoVaR and ΔCoVaR ...........................................................................................................51
Boxes
1. Use of Interconnectedness Analysis by the IMF ...................................................................8
2. Insurance and Interconnectedness........................................................................................15
3. The Key Attributes—A Summary .......................................................................................22
Appendixes
I. Data Requirements for Network Analysis........................................................................40
II. Network Analysis Tools ...................................................................................................43
III. Price-Based Measures ......................................................................................................51
IV. Status of Macroprudential Initiatives for Interconnectedness, by Selected Economy .....55
 3

I. INTRODUCTION1

The financial crisis raised awareness of the need to improve the analysis and
management of the factors underlying financial contagion and risk concentration, i.e.,
interconnectedness. While the research surrounding the modeling of interconnectedness had
been ongoing, the financial crisis saw a surge in the attention and resources it garnered.
Although microprudential tools to control concentration and exposure limits had long since
been an accepted supervisory tool in the banking sector, there has been no explicit
international standard on concentration risk, and even large exposure limits have not been
fully addressed. In recent years, international standard setters have turned their attention to
developing new tools to address complex linkages. These tools have been augmented by
efforts of national authorities to deal with their own domestic problems of
interconnectedness. Consequently, there is now a range of regulatory instruments that
confronts interconnectedness in the banking sector, OTC derivatives, insurance, and the
realm of systemically important financial institutions.

Two sets of tools (developed in-house or externally) are reviewed here that have been
actively used at the IMF after the global financial crisis to identify the
interconnectedness dimension of systemic risk; namely network analysis, and price-
based measures. Network analysis is used to identify interconnectedness risk. Price-based
measures cover both direct and indirect spillover channels. These sets of tools can aid macro
stress testing exercises in measuring concentration risks.

From the understanding developed in existing models, some of the key prudential tools
aimed at interconnectedness are examined and the paper takes a first step at analyzing
how these tools might interact with each other—either as complements or at odds—as
well as their impact on dealing with contagion and risk concentration. Tools include
those involving capital and liquidity requirements, as well as structural frameworks for
banks’ business models, the clearing of OTC derivatives, and resolution of systemically
important financial institutions. The paper proposes a simple framework for reviewing the
tradeoffs a policy maker should take into account when considering the potential
consequences of these tools. As these tools are in a stage of infancy—many not yet
implemented and some still in development—the assessments made are very much
preliminary and based on qualitative assumptions, as no empirical evidence is yet available.

The paper examines models used in the analysis of systemic risk and their potential
application in policy formulation by assessing the models’ strengths and weaknesses,
their usefulness in actual policymaking, and the complementarity or conflict amongst
those prudential tools developed to contain cross sectional risk. The paper begins with a

1
The authors are grateful to staff of MCM’s Financial Supervision and Regulation Division, Marco Espinosa,
Sonia Munoz and Jacek Osinski for their valuable insight and comments.
 4

review of some of the key analytical tools used at the Fund to analyze risk and
interconnectedness. It presents how they have been used—in FSAPs, spillover reports, the
GFSR, and Article IV reports—as well as how they may contribute to policy-making. The
paper then reviews some of the more prominent prudential tools being proposed, and then
follows with an analysis of how these tools interact with each other and with their intended
effects on contagion and risk concentration. The paper concludes with policy considerations
and the use of this framework for future work.

II. THE ROLE OF INTERCONNECTEDNESS ANALYSIS IN ADDRESSING SYSTEMIC RISK

The importance of financial interconnectedness for financial stability has been

illustrated rather dramatically during the recent global financial crisis. Indeed, there is a
growing consensus that the size of an institution alone is not the only (or even the main)
consideration in assessing spillover risk.2 Identification of systemically important institutions
also requires an assessment of the nature and extent of their interconnectedness.
Interconnectedness arises from actual—and perceived—complex webs of contract
relationships across financial institutions.

Financial interconnectedness could have opposing effects on financial stability. On the

one hand, linkages may act as channels to propagate shocks to the whole system, that is, they
act as “shock transmitters.” On the other hand, through these linkages, shocks can be shared
and absorbed by others, that is, financial linkages may act as “shock absorbers.”
Policymakers are, of course, most concerned with the downside of interconnectedness.

Systemic (or spillover) risk arises when the failure or weakness of one or multiple
financial institutions or infrastructures disrupts financial services and imposes costs on
the economy as a whole. The failure or weakness of multiple financial institutions may arise
through a variety of mechanisms.3 Direct bilateral exposures across institutions are the most
direct transmission mechanisms of shocks within a financial network. However, indirect
linkages may arise from exposure to common risk factors such as the adoption of similar
business models, common accounting practices across financial institutions, the market
perception of financial institutions’ coincidence of fortunes, and other factors like fire sales
and informational contagion that might be as important as direct exposures.4

2
BIS, 2011; Arsov and others 2012; Cont and others 2012.
3
According to Nier and others 2007, the failure or weakness of multiple financial institutions at the same time
arises through four main mechanisms: (i) direct bilateral exposures between institutions; (ii) correlated
exposures of financial institutions to a common source of risk; (iii) feedback effects from endogenous fire-sale
of assets by distressed institutions; and (iv) informational contagion.
4
Scott and the Committee on Capital Markets Regulation 2012 argue that asset and liability interconnectedness
were not the main drivers of the systemic risk concerns during the recent financial crisis in the United States,
but that contagion was at the front and center.
 5

What is the optimal level of interconnectedness? Highly stylized analytical work such as
that of Allen and Gale (2000) shows that complete networks of financial intermediaries (in
which every intermediary is connected to the rest of the network)i are more stable than
“incomplete” networks, where not all intermediaries are connected to the rest of the
network.5 The intuition is that in a complete network the system relies less heavily on
individual nodes of the network (because there are more nodes), making it less likely that the
failure of a node will cause the network to fail. However, in reality, complete networks are
not observed, which complicates the assessment of the optimal level of interconnectedness.
Although there has been important empirical work on the topology of banking networks, e.g.,
Hattori and Suda (2001), empirical work relating to the degree of interconnectedness and
financial stability remains limited. As a notable exception, Čihák, Muñoz, and Scuzzarella
(2011) combine data on banking crises around the world with a data set on crossborder
financial linkages. They find that in banking systems that are not very connected to the global
banking network, increases in interconnectedness tend to be associated with increased
financial stability. Once the degree of interconnectedness reaches a certain value,6 further
increases in interconnectedness do not improve financial stability and can in fact increase
fragility.7

Because existing models are not able to assess whether interconnectedness is excessive
in practice, policy efforts to address the cross-sectional dimension of systemic risk have
focused on the identification of SIFIs and the mitigation of their systemic contribution.
For instance, the BCBS has developed an assessment methodology for global systemically
important banks (G-SIBs) based on an indicator-based measurement approach instead of a
model-based approach.8 Current analytical tools cannot replace qualitative assessments but
can contribute to meet the objectives of identification and mitigation in at least three
important ways.9 Firstly, understanding the financial network and contagion channels and

5
Freixas and others (2000) show the possibility for contagion in a system with money-centre banks, where the
institutions on the periphery are linked to banks at the centre but not to each other, crucially depends on the
precise values of the model’s parameters. Battiston and others (2010) show that connectivity and stability of a
network is not a simple monotonic relationship but that, beyond a point, connectivity in a network could
increase instability.
6
The authors estimate this point to be at about the 95th percentile of their distribution of countries in terms of
interconnectedness, when upstream interconnectedness is 0.37. Below this threshold, upstream
interconnectedness reduces the probability of a banking crisis. When upstream interconnectedness is above 0.37
(the remaining 5 percent), the relationship between interconnectedness and crisis probability is more complex: it
is upward-sloping at first, only to become downward-sloping again.
7
Nier and others (2007)
8
Selected indicators are chosen to reflect the size of banks, their interconnectedness, the lack of readily
available substitutes for the service they provide, their global (cross-jurisdictional) activity and their
complexity.
9
The indicator-based measurement approach has the advantage that it is relatively simple and it encompasses
many dimensions of systemic importance that may not be fully captured by certain models.
 6

ranking the systemic risk contribution of different institutions help regulators decide on the
perimeter and intensity of financial individual and systemic oversight. Secondly, using tools
like network models and market-based measures has strengthened our conventional stress
test analysis. Finally, measuring the contribution to systemic risk by individual institutions
provides a natural basis for applying systemic risk surcharges.

A. Analytical Tools to Assess Interconnectedness and Concentration

Two sets of tools actively used to identify systemic risk in the cross-sectional dimension
are network analysis and market-based indicators. They have been developed at the IMF
and externally in the wake of the current crisis and are classified according to their main data
requirements, i.e., balance sheets or market data. These tools have been deployed recently in
the context of Article IV consultations, FSAPs, and stability reports (Box 1).

Understanding the architecture of financial interconnectedness is a step toward both

better analyzing the transmittal and spillovers of shocks and assessing how the
(domestic or global) system could be made more resilient to shocks. Network10 analysis
allows for the identification of core elements of such architecture, thus providing elements
for visual and analytical representation of exposures and facilitating the assessment of risk
transmission (or absorption) of shocks. The analysis requires, as a starting point, the
measurement of exposures among financial institutions. The kind of claims or exposures to
be covered usually depends on the purpose of the analysis. Data availability is sometimes a
constraint that limits the analysis (Appendix 1). Three main tools for network analysis are
used within the IMF and externally: centrality analysis, cluster analysis, and balance sheet
simulation methods (Table 1 and Appendix 2).

Market-based measures of systemic risk rely on asset prices (such as stocks, bonds, and
derivatives) to estimate distress dependence among financial institutions. Distress
dependence is based on the fact that financial institutions are linked both directly and
indirectly through a variety of channels. Methodologies developed for the measurement of
risk in portfolios of securities have been adapted to the measurement of systemic risk for a
“portfolio” of institutions. In this context, the methodologies have been enhanced to identify
common risk factors, track how distress in one institution may affect others, and measure the
contributions of individual institutions to system-wide risks. A variety of market-based tools
are currently used at the IMF (Table 2 and Appendix III).

10
A financial network is a set of bilateral claims (links) among different financial institutions (nodes).
 7

Table 1. Tools for Network Analysis

Centrality Centrality analysis infers from the pattern of linkages among financial institutions the
analysis extent to which a node is “central” in the financial network. Several indicators of
interconnectedness, or “centrality,” are used to quantify the relative importance of
each financial institution in a financial network.11
Cluster Cluster analysis separates the network into subgroups (“clusters”) of nodes that have
analysis closer connections to each other than with those outside the cluster. It can help
identify subgroups of nodes with close connections and “gatekeeper” institutions or
systems that bridge across different clusters allowing for the contagion to spread out.
Balance Balance-sheet simulation methods use simple balance-sheet identities to trace the
sheet effect of difficulties at an individual bank or banking sector through a combination of
simulation data and assumptions. Balance-sheet simulation methods complement the basic
methods mechanisms of shock transmission (via lending exposures) with the mechanisms for
absorption (via bank net worth). The systemic importance of an institution is
quantified by assuming its hypothetical failure and simulating the imposed losses on
each other institution in the network.

11
In addition to the local measures that quantify the relative importance for each node in the network, there are
global measures intended to characterize the network as a whole.
 8

Box 1. Use of Interconnectedness Analysis by the IMF

Surveillance tools like network analysis and market-based indicators have been actively deployed in the
context of IMF Article IV consultations, FSAPs, Early Warning Exercises and spillover reports to assess
interconnectedness and the systemic risk contribution of individual institutions, as well as quantify
contagion.

 Centrality Analysis - Within IMF work, centrality analysis contributed to the identification of
jurisdictions with systemically important financial sectors, which were assigned mandatory financial
stability assessments on a regular basis. Network analyses using institutional-level data are usually
conducted by country supervisory authorities, given the confidentiality of data. As such, measures of
centrality at the institutional level are usually not disclosed. Some supervisors disclose global measures
intended to characterize the network as a whole.12, 13 In the context of FSAPs, information on size and
interconnectedness of individual financial institutions is used to assess systemic importance. For
example, a recent FSAP to Australia called for a special risk mitigation arrangement for a set of
systemically important banks (Australia FSAP 2012).

 Cluster Analysis - IMF analysis identified a Nordic-Baltic financial cluster. Strong connections from
the Nordic economies (gatekeepers) to the Baltics implied a key role of the former in providing funds
to the latter in the run up to the crisis. During the crisis, policy actions in “gatekeeper” countries —
including strengthening banks—helped limit bank deleveraging and negative output effects in the
regional cluster.

 Balance Sheet Simulation Methods –This methodology is most frequently applied to the exposures of
individual banks within a particular banking system, especially by national regulatory organizations. In
the context of FSAPs, some teams have worked with the local authorities to include such analysis in the
assessment (e.g., India 2011, Brazil 2012). In recent years, the IMF has increasingly applied this
methodology to the global banking network, taking the banking sector in a country as the unit of
analysis. This analysis has been increasingly adopted in FSAPs and Spillover Reports.

 Market-based indicators – These indicators have been actively used for bilateral and multilateral
surveillance at the IMF in recent years. In terms of bilateral surveillance, price-based measures have
been used mostly as early-warning indicators or to quantify systemic risk contribution by individual
institutions (Table 2). Additionally, the JPod/CoPod and Systemic CCA models provide estimates of
probabilities of default and expected shortfall (or loss) during tail events, and therefore, have been used
in the context of stress testing. In terms of multilateral surveillance, price-based measures have been
used for the identification of regional and global systemically important financial institutions.

12
For example, the Reserve Bank of India computes a connectivity statistic, a cluster coefficient and the
average path length both for the domestic Indian interbank network and for the domestic financial network.
13
Cihak and others. (2011) and Minoiu and Reyes (2011) compute measures of country centrality and network
density (connectivity and clustering) for cross-border interbank linkages using BIS locational data. Hattori and
Suda (2007) also study the characteristics of the cross-border bank network topology and find that it has
become tightly connected over time.
 9

Table 2. Main Market-Based Measures Used at the IMF

CoVaR The CoVaR is defined as the VaR (i.e., risk indicator that measures the potential loss
in value of a risky portfolio over a defined period for a given confidence interval used
by financial institutions) for an institution ‘i’ conditional on the financial situation of
another institution ‘j.’ The difference between the CoVaR conditional on distress of
an institution ‘j’ and the CoVaR conditional on the “normal” state of institution ‘j,’
ΔCoVaR, captures the marginal contribution of institution ‘j’ to risk in institution ‘i.’
Returns The return spillover indicator is based on the fraction of the N-step-ahead error
spillovers variance in forecasting the returns to one institution that is attributable to shocks to
each other institution.
Distress The distress spillover indicator uses market data on returns to date “extreme events,”
spillovers The probability of an extreme event happening for an institution is estimated
conditional on extreme events happening or not for other institutions, after
controlling for real and financial developments in the home country and in global
markets.
JPod/CoPoD The JPoD/CoPod methodology estimates the multivariate distribution of asset returns
for all financial institutions, based on estimates of their individual probability of
distress extracted from high frequency market prices. Having obtained this joint
probability distribution of distress across a number of institutions, it is possible to
then “slice” this multivariate distribution to estimate different measures of distress
dependence including a matrix of dependence.
Systemic The systemic CCA uses option pricing theory for individual institutions and estimates
CCA a multivariate distribution to derive a market-implied measure of systemic risk based
on estimates of joint expected losses. This multivariate conditional tail expectation,
by applying a multivariate density, allows quantifying the contribution of each
individual institution to systemic risk.

B. Use of Analytical Tools, their Complementary Nature, and Limitations

Centrality and cluster analysis allow for an initial characterization of a financial

network’s architecture and contribute to the identification of systems in need of
heightened surveillance. Centrality and clustering are descriptive and “behavior-risk
neutral,” that is, they make no assumption about the underlying economic behavior that gives
rise to the observed interconnections. The descriptive analysis must be complemented by
delving deeper into the functional characteristics and understanding the economics
underpinning each cluster.14 Being less data-intensive than balance-sheet simulation methods,

14
Understanding the economic characteristics of a cluster is crucial, as cluster identification is not as readily
interpretable as the output of centrality measures and balance-sheet simulation models.
 10

these tools are useful in a first stage to define the perimeter and intensity of surveillance
(including stress testing).15

Balance-sheet simulation methods complement the analysis by incorporating not only

the role of exposures across the network but also the important role of financial capital
buffers. An institution highly interconnected with well capitalized institutions poses very
different risks than one highly interconnected with poorly capitalized institutions. In addition,
balance-sheet simulations can incorporate and track the implications of liquidity events.

While network analysis focuses on direct bilateral exposures between institutions, some
price-based measures cover also indirect spillover channels. They enable the tracking of
how distress in one institution may affect others. However, price measures fail to identify the
specific channels or mechanisms for contagion at play, only reflecting comovements in risks
as they are priced in by the markets.

Market-based methodologies can be implemented using data publicly available on a

high-frequency basis, limiting the need to rely on detailed supervisory data (which is
usually confidential). Market-based measures are forward-looking, reflecting investors’
assessment of the financial health of a specific institution and the domestic and global
developments that would affect its prospects. Thus, potentially, they can be used to guide
policy actions to contain risk. However, when a large fraction of the financial sector is not
publicly traded or stock price data are not reliable due to thin trading or reporting issues, the
use of market-based measures in not an option. Additionally, the investor or market’s
perception of risk may not always reveal the true default probability of a bank. For instance,
as experienced during the global financial crisis, markets did not price in default of major
financial institutions such as the Lehman Brothers.

These measures help rank relative contributions to systemic risk, but have a short
horizon for the early warning of distress.16 Arsov and others (2012) analyze the early
warning capacity of different price-based indicators. In general, methodologies relying on
market data suffer from the limitation that market perceptions can vary greatly between
normal and crisis times. As a result, the early warning capacity of these indicators is, at best,
a few months ahead of the actual crisis events.17

How these tools work in conjunction also warrants further examination. Centrality and
cluster analysis, balance-sheet (domino) simulations, and market-based measures could
complement each other, but have mostly been used separately. For example, as
mentioned earlier, centrality and cluster analysis could be deployed to help define the

15
IMF 2012 makes use of centrality and cluster analysis. Markose 2012, RBI 2011/10, Muller 2006 and Upper
and Worms 2002 use both centrality analysis and balance-sheet simulation methods.
16
The authors refer to these as “near coincident” indicators.
 11

perimeter of surveillance. Then, domino analysis could be deployed to extract contagion and
vulnerability indicators. Finally, and when relevant market data were available, the results of
the domino analysis could be contrasted with those of the market-based analysis. The use of
these methods is relatively new at the Fund and, as the synergies of these methodologies
become apparent, their sequential use should become more widely spread.

Also, given the confidentiality of domestic financial network studies, almost no

empirical work has been done to study the relationship between network and price-
based measures. As a notable exception, Aydin and others (2011) compute both types of
indicators for domestic banks in Korea, but do not show how the identified relative systemic
importance of each institution compares under both methodologies.

In spite of the recent advances in measuring the cross-sectional dimension of systemic

risk, several weaknesses remain. Firstly, a variety of contagion channels can lead to
financial stability, but the available set of tools does a better job capturing direct than indirect
channels. Network analysis focuses on direct channels. Some price-based measures capture
both, but fail to identify the specific channels conducting to stress dependence between
institutions. Moreover, they are based on market perceptions, which may not always reflect
underlying fundamentals. Secondly, the early warning capacity of the current toolkit is not
strong, possibly leaving policymakers with a limited window for action.

C. Analysis of Interconnectedness and Policymaking

The analysis described in the previous section has laid the ground for the enhancement
of the standard stress-testing analysis focused on the resilience of individual financial
institutions to shocks. A shortcoming of traditional approaches to stress testing is that they
ignore the interdependence among shocks and among affected institutions or systems (IMF
2012). By explicitly tracking possible contagion and distress dispersion across financial
institutions or sectors, these analyses provide the foundation for systemic-focused stress
testing.

In some cases, the network analysis and market-based tools discussed above have been
proposed as a guide to calibrate macroprudential tools to mitigate systemic risks.
Measuring the contribution to systemic risk (the negative externality) of individual
institutions provides a natural basis for the assessment of required levels of systemic-risk-
based capital surcharges.18 For instance, Brunnermeier and others (2009) and Chan-Lau
(2010) propose capital surcharges based on contributions to systemic risk derived from

18
Cont and others (2012) argue that targeting capital requirements to the most contagious institutions is more
effective in reducing systemic risk than increasing capital ratios uniformly across all institutions. Also, capital
requirements should not simply focus on the aggregate size of the balance sheet but depend on their
concentration/distribution across counterparties.
 12

CoVaR and CoRisk, respectively. Espinosa-Vega and Sole (2010) propose capital surcharges
based on their balance-sheet simulation model. Markose (2012) proposes a “super-spreader”
tax based on centrality analysis to raise a fund that would mitigate potential socialized losses
from the failure of highly connected banks (Table 3).

Table 3. Comparison of Some Methodologies to Compute Systemic-Risk-Based Charges

Main data requirements Examples Pros Cons

Market prices Brunnermeier and others (2009) Based on publicly available, Data may be unreliable under tail events
Chan-Lau (2010) high-frequency data. Potentially captures and/or not representative of underlying
channels other than direct exposures fundamentals during stress periods

Bilateral exposures Espinosa-Vega and Solé (2010) Data is reliable and reflects fundamentals Intensive data requirements
Markose (2012) even during stress periods

Predicting the timing and severity of a systemic event will continue to be an uphill
battle. This toolkit of methodologies provides policymakers with much needed help in this
quest. While the toolkit should be considered as work in progress, any promising
contribution in the detection and regulation of interconnectedness and systemic risk warrants
close scrutiny.

III. PRUDENTIAL TOOLS AND INTERCONNECTEDNESS

A. Cross-Sectional Prudential Tools: A Recent Review

As the aforementioned methodologies for determining degrees of interconnectedness

have not yet been introduced to regulatory policymaking, practical options have been
the identification of SIFIs in national stress tests, with relevant bank-specific policy
actions, and the broader application of prudential measures. An example of the former is
the U.S. Supervisory Capital Assessment Program (SCAP) framework that is utilized with
systemically important institutions and that applies existing tools and policy measures to
relevant financial institutions. But in addition to the conceptual modeling approaches to
identify, measure, and monitor systemic risk, systemic risk identification and monitoring
should also encompass evidence and information from supervisory judgment and on-site and
off-site analyses. Prudential tools complement the analytical models by identifying key
variables that indicate levels of contagion and concentration, and that establish enforceable
limits to control financial institutions’ exposures and linkages The prudential tools examined
here are some of the most clearly designed to address interconnectedness: microprudential
exposure limits, capital charges—particularly for systemically important financial institutions
(SIFIs), liquidity regulation and limits on liquidity mismatches, clearing of OTC derivatives
on a central counterparty (CCP), structural limits on activities, resolution frameworks, and
insurance.
 13

Microprudential exposure limits

Microprudential exposure limits are normally designed as nonrisk sensitive backstops

to limit concentration from a microprudential perspective, but they are also relevant
from a macroprudential point of view.19 Rules on exposure limits have long been generally
accepted principles and were broadly defined internationally, but it is not until recently that
the Basel Committee decided to review the framework and establish an internationally
agreed-upon standard.20 Nevertheless, almost all supervisors have set prudential limits to
restrict bank exposures to single counterparties or groups of connected counterparties.21
Normally, exposures representing ten percent or more of a bank’s capital are defined as a
large exposure; and twenty-five percent of a bank’s capital is the limit for an individual large
exposure to a private sector nonbank counterparty or a group of connected counterparties.
However, deviations from these limits are frequent and exceptions abound. Exposures arising
from off-balance sheet as well as on-balance sheet items and from contingent liabilities
should be captured. However, further work is needed on the method for calculating
exposures (e.g., taking into account risk mitigation, how to calculate limits for off-balance
sheet items, etc.), restrictions on a bank’s exposure to other financial institutions (FI),
specific intra-group limits for G-SIFIs, and aggregate limits across all exposures to FIs. Also,
supervisors are expected to review sectoral, geographical, and currency concentrations in
bank portfolios in consideration of Pillar 2 capital add-ons. The relevance that these
prudential requirements have in containing systemic risk deriving from interconnectedness is
clear, as they represent hard limits.

Capital buffers

The capital requirements in Basel I or Basel II did not contain measures to address
concentration or systemic risk. The capital framework required the same minimum capital
requirement for all (internationally active) banks, regardless of their systemic importance. In
terms of risk weights attached to assets, concentration risk was not incorporated. As noted,
Basel II expected that concentration risk should be taken into account under the Pillar 2
framework. However, this was dealt with differently across jurisdictions, as no quantitative
guidelines were provided. There was criticism of the treatment of capital requirements on
instruments such as sovereign bonds, instruments with high credit ratings, and securitized
products under Basel II, whose risk weights are determined by their external credit ratings.
Even risk weights of traditional loans under the standardized approach of Basel II is
determined by external credit ratings, and the global financial crisis showed relative lack of

19
An exception to nonrisk sensitive microprudential exposure limits arises in the EU, where large exposure
limits, in particular, are allowed to be risk-weighted.
20
A draft proposal by the BCB, “Supervisory framework for measuring and controlling large exposures,”
(March 2013) is examining new prudential measures on concentration.
21
Foreign exchange open position limits are additional regulations on exposure.
 14

robustness in high credit ratings for securitized products. However, there was sufficient
flexibility within the Basel II rules for jurisdictions to adopt above-minimum capital ratios
and/or higher risk weights for assets (for specific sectors) that would have tackled
concentration or contagion risks.

Basel III minimum capital rules, in contrast, were formulated with explicit
consideration for concentration and systemic risk. The agreed-upon Basel III framework
explicitly states that “addressing systemic risk and interconnectedness” is one of its
objectives. Some new features have been imbedded in the calculation of capital requirements
themselves, such as capital incentives for using CCPs for OTC derivatives clearing, higher
capital requirements for trading and derivative activities, and higher capital requirements for
intrafinancial sector exposures. These new requirements are intended to reduce the level of
bilateral trading (sometimes uncollateralized) among financial institutions, thereby reducing
interconnectedness within the financial sector.22

A prominent feature of Basel III introduced to address systemic risk is the G-SIB
(global systemically important banks) framework.23 The framework requires additional
loss absorbency (as common equity capital surcharge) for larger and more interconnected
global banks. The Basel Committee expects that this framework will provide incentives for
global banks to be smaller and less interconnected. This is not a hard limit, but part of the
conservation buffer, where breaches will only trigger limitations to the allocation of profits.
Surcharges are price-based measures (rather than quantity tools) that act as a levy or a
Pigouvian-type tax, which is less costly (lower adjustment costs for banks) to be changed by
a macroprudential authority. The ultimate aim of such capital surcharges would be to
incentivize banks to hold larger capital buffers and reduce reliance on taxpayer support.
There also would be national frameworks for D-SIB (domestic systemically important
banks), where national supervisors might set capital surcharges for banks that are not G-
SIBs, but still are systemically important for that jurisdiction.24

22
In addition, in the IRB formula, a multiplier introduced to the correlation parameter of all exposures to large
financial institutions (whose total assets are larger than US$100 billion) meant also to tackle concentration risks
and contagion.
23
There are also some aspects in Basel III that address systemic risk and interconnectedness. These include
capital incentives for using central counter parties for OTC derivatives, higher capital requirements for trading
and derivative activities, and higher capital requirements for intrafinancial-sector exposures. These new
requirements are intended to reduce the level of bilateral trading (sometimes uncollateralized) among financial
institutions, thereby reducing interconnectedness within the financial sector.
24
It is important to note that capital surcharge is only one part of the multipronged approach of SIB
frameworks. The frameworks also require intensive and intrusive supervision and effective resolution
mechanisms.
 15

Liquidity regulation and limits on liquidity mismatches

Unlike the capital adequacy ratio, there was no global liquidity requirement before
Basel III. While some countries used quantitative indicators to monitor bank liquidity risk, in
many advanced countries those indicators were not enforced as strict rules.25 The crisis raised
the concern that the lack of liquidity requirements has contributed to some banks’ high
reliance on central-bank funding (as a lender of first resort) and short-term funding from
other financial institutions. This, in turn, increased interconnectedness among financial
institutions and concentrations in short-term wholesale funding risks in the run-up to the
global financial crisis. The lack of information regarding banks’ balance sheet exposures and,
specifically, banks’ reliance on inter-bank and other wholesale markets for liquidity
contributed to the sudden dry-up in these markets after the collapse of some major financial
institutions aggravated the impact of the crisis. The situation was further exacerbated by a
lack of clarity about the role of central banks and governments in supporting large FIs.

Box 2. Insurance and Interconnectedness

Cross-sectional prudential rules to tackle interconnectedness and risk concentrations in the

insurance sector are at a nascent stage. Prior to the crisis, many of the prudential tools tackling
interconnections and risk concentrations in the insurance sector were microprudential in focus, with
limits placed on single exposures and asset classes. The limits are expressed as percentages of the
invested assets. Usually these limits only apply to assets allowed to set up the technical reserves and
capital, insurers can hold non qualified assets beyond the limits. More advanced regimes have tended
to apply the prudent man concept. Post-crisis, the FSB working through the International Association
of Insurance Supervisors (IAIS) is addressing the issue of systemic risk by identifying global
systemically important insurers (G-SIIs). The proposed IAIS policy measures for G-SIIs focus on
systemic risk reduction plans (SRRPs), including prohibitions or strong disincentives for insurers to
be G-SIIs.

In addition, capital surcharges similar to those for G-SIBs are also under discussion. The
methodology is indicator-based, where the selected indicators can be grouped into five categories:
size, global activity, interconnectedness, nontraditional and non-insurance activities (NTNI), and
substitutability. In developing the methodology, consideration was given to the fact that the
traditional insurance business model is different from banking and, in particular, that traditional
business does not involve a payment system, credit intermediation, or investment banking services.
However, nontraditional insurance activities and non-insurance financial activities are potential
drivers of the systemic importance of insurers and thus have the greatest impact on failure. Additional
prudential tools for insurers to tackle interconnectedness and risk concentration have been discussed;
among them monitoring and limiting ratios on capital markets activity, of liquid to illiquid assets, and
of gross negative value of derivatives liabilities with other financial sector participants.

25
More traditional instruments have tended to be employed by emerging market and developing economies to
control banking system risks. Raising reserve requirements and increasing limits to control lending in foreign
currency as well as large, open foreign exchange positions and exposures are some examples.
 16

Basel III, in response to these experiences, introduced new global liquidity standard—
the liquidity coverage ratio (LCR) and the net stable funding ratio (NSFR).26 These two
new ratios, LCR for short-term liquidity and NSFR for long-term liquidity, penalize reliance
on short-term financing, particularly for financing from other financial institutions. For
example, the LCR sets higher run-off rates for deposits from other financial institutions
compared to corporate and retail deposits, increasing the required amount of high-quality
liquid assets (HQLA), such as sovereign bonds, which a bank needs to hold if it relies on this
kind of financing. 27 By increasing banks liquidity buffers and reducing maturity mismatches
at individual banks, the LCR and NSFR aim to indirectly mitigate systemic liquidity and
contagion risk. Moreover, the LCR and NSFR penalize banks for having sizable exposures to
other financial institutions, providing an incentive to reduce funding interconnectedness as
well as counterparty and exposure concentration among banks. With the new LCR published
in 2013, there is some concern that the LCR benefit of reducing contagion and
interconnectedness has diminished somewhat. While there may be some truth in such an
argument, the new LCR with the proposed NSFR is still expected to mitigate systemic
liquidity contagion as well as funding and counterparty interconnectedness.

OTC derivatives and central counterparties

Central counterparties (CCPs) are operators of multilateral systems used for clearing
securities and derivatives transactions. The multilateral nature of CCPs distinguishes them
from other financial institutions, including banks and securities firms.28 The operator of a
CCP interposes itself between counterparties of securities and derivatives transactions,
becoming the buyer to every seller and the seller to every buyer, thus removing the
counterparty credit risk of bilateral clearing.

Despite the recognized benefits of CCPs, the OTC derivatives market remained largely
bilaterally cleared until the default of Lehman Brothers revealed the risks arising from
the complex bilateral interconnections between OTC derivatives counterparties. These
included the build-up of large counterparty exposures between particular market participants
that were not appropriately risk-managed; the contagion risk arising from the

26
LCR rules were recently finalized by the GHOS of the BCBS (January 6, 2013). The package has four
elements: revisions to the definition of high quality liquid assets (HQLA) and net cash outflows; a timetable for
phase-in of the standard in 2015–19; a reaffirmation of the usability of the stock of liquid assets in periods of
stress, including during the transition period; and an agreement for the Basel Committee to conduct further
work on the interaction between the LCR and the provision of central bank facilities. The NSFR is scheduled to
be introduced in 2018; the BCBS will revisit NSFR rules before introduction.
27
The run-off rate is a rate by which a bank must assume that the portion of its liability will outflow over the
next 30 calendar days, thus increasing the bank’s total net cash outflow that needs to be covered by the stock of
high quality liquid assets (HQLA) held by the bank. Most deposits from financial institutions have 100 percent
run-off rate, while the run-off rates for some retail deposits are as low as 3 percent.
28
Payment and settlement systems share the multilateral nature of CCPs.
 17

interconnectedness of OTC derivatives market participants; and the limited transparency of

overall counterparty credit risk exposures, which precipitated a loss of confidence and market
liquidity in time of stress.29

Figure 1. The G14 and the CCP Global Network

Experiences during the crisis led to the G-20 leaders’ commitment to mandate the
central clearing of all standardized OTC derivatives contracts in September 2009. The
mandatory clearing requirement recognizes the various benefits that CCP clearing has over
bilateral clearing. It reduces the contagion effect that a default of one of the counterparties
may trigger by inserting the CCP as central counterparty and thus insulating counterparties
from one another. CCPs mutualize the risk of counterparty failure using various risk
management mechanisms, including prefunded default funds. They also manage counterparty
credit risk centrally and reduce exposures through multilateral netting and collateralization of
initial and potential future exposures (initial and variation margin). CCPs also increase

29
Financial Stability Board, 2010.
 18

transparency of the amount and distribution of risk exposures. CCPs thereby reduce the
potential contagion (shock transmission) effects of the failure of a major counterparty
because the impact is absorbed by the CCP and is mutualized among its clearing members
who must share in any losses.30

CCPs limit contagion risk of derivative exposures, but simultaneously increase the
concentration risk by substituting for a whole network of FIs. By enabling the clearing of
standardized bilateral derivative contracts together with requiring the submission of initial
and variation margins, CCPs help to reduce contagion risk through the netting of such
derivative exposures and the loss absorption from access to collateral. This netting benefit is
most significant with a reduced number of CCPs; in theory, with a single CCP—at the cost of
highly concentrated risk. Specifically, CCPs are currently concentrated on several levels: (i)
there are only three generally recognized globally systemic CCPs thus far, (ii) each CCP
specializes in a particular financial product and globally dominates the clearing of the
product, and (iii) there is a small group of large, globally important derivative traders who
are members of all major CCPs.31 Without an adequate regulation, supervision and resolution
framework of the CCPs, concentration within the financial network could be greatly
increased through CCPs.

At the moment, it is unclear how quickly the risk reducing benefits of CCP clearing can
be realized. This is due to various reasons. Firstly, the legislative and regulatory framework
mandating CCP clearing is still missing in many jurisdictions, and a significant proportion of
trades still remain bilaterally cleared, in particular for certain asset classes.32 Secondly, there
are currently proposals for a proliferation of CCPs that might at least temporarily reduce the
risk mitigating impact of CCP clearing, because the use of multiple CCPs reduces the full
benefits from multilateral netting. Finally, loss sharing arrangements vary widely across
CCPs at present in terms of the distribution of the burden represented by the risk buffers of
the CMs and their clients.33

Structural limits on activities

Financial regulatory and supervisory policy may be construed as the prescription of

minimum standards of business conduct and prudential risk management for financial

30
Some of these benefits are dependent on a market structure wherein a small number of CCPs clear the lion’s
share of standardized OTC derivative contracts globally. From the singular perspective of maximizing netting
potential, Duffie and Zhu (2011) have made it clear that the most efficient market structure is one where a
single global CCP clears all OTC derivative contracts.
31
The three major CCPs are SwapClear, ICE, and the CME.
32
Typically it is equity, commodity, FX and exotic (non-standard) derivatives.
33
For more details and a call for greater disclosure by CCPs of their risk models, see Li Lin and Jay Surti
(2013), Capital Requirements for Over-the-counter Derivatives Central Counterparties, IMF WP/13/3.
 19

institutions (FIs). Correspondingly, prudential instruments, whether individually or taken

together, can be expected to influence and impact the size and scope of FIs’ businesses. As
such these tools act as regulatory and supervisory constraints on the business models of
financial institutions.

At a reasonably broad level, such prudential measures can take either of two forms.
Indirect measures—such as the Basel capital and liquidity requirements for banks, G-SIBs
surcharges—impact the cost and income of FIs from increasing the size and scope of their
businesses, thereby providing them powerful incentives to cap these off at a lower level than
in their absence. And direct measures—such as the historical Glass-Steagall separation of
investment banking from deposits and credit in the U.S.—constrain FI size and scope by
prescription.

The crisis brought about fundamental changes in the approach to, and content of,
indirect measures. It highlighted that neither FIs’ risk management nor market risk
assessments keep pace with financial innovation. There is now considerable skepticism
regarding the ability of FIs’ internal risk models to attenuate—on their own and in the
presence of moral hazard induced by implicit or explicit government support—the likelihood
of institutional or systemic distress. Questions have also arisen regarding the ability of
indirect measures to address the systemic risk implications of FIs’ business practices and
models. This is especially so as the maintenance of complex business models—especially the
G-SIBs—may impair the ability to supervise and enforce the new and enhanced set of post-
crisis rules. Similarly, until a comprehensive, cross-border bank resolution framework
becomes a reality, the ability of national authorities to protect local affiliates of foreign banks
and secure business continuity thereof will be a challenge.

The utility of direct measures in lowering financial system contagion, promoting

continuity of vital banking functions in a crisis and making available a wider set of FI
restructuring and resolution options, has become clearer. Direct restrictions on the scope
of businesses conducted by G-SIFIs—and more generally—large or internationally active
banks and concomitant changes in their business organization can lower complexity and
more assuredly contain intra-system exposures. These measures aim to safeguard core
banking business from contagion shocks that could spill over from riskier business activities
and the subsequent distress that would impact the broader financial system and real economy.

Three sets of direct measures have been proposed by advanced market economies.
These include a narrow banking proposal in the United States, the Volcker Rule, prohibiting
deposit-funded banks from engaging in speculative trading and investments. The two
European proposals (Vickers and Liikanen) have favored a subsidiarization model, wherein
deposit-funded banks are ring-fenced from their investment banking affiliates and, in one
 20

case, prohibited from maintaining business relationships outside a pre-specified geographic

perimeter (Table 4).34

Table 4. Comparison of the Structural Reform Proposals

Liikanen group report United Kingdom United States

Institutional coverage 1/ All E.U. licensed banks and Financial institutions running U.S. banks and their
their subsidiaries U.K. retail deposit and subsidiaries globally;
- includes mutual and payments businesses Non-U.S. banks' U.S.
cooperative banks - excludes U.K. building subsidiaries and branches
societies

Size threshold for application Trading business to exceed: Assets held greater than None
(i) €100 billion in absolute £25 billion
value; or
(ii) 15-to-25% of total
assets; and
(iii) EC calibrated threshold
(not specified)

Activities prohibited for deposit (i) Proprietary trading; (i) Proprietary trading; (i) Proprietary trading;
taking banks 2/ (ii) Market making; (ii) All wholesale and (ii) Investments in hedge
(iii) Investments in hedge investment banking; funds, PE funds and SIVs
funds, PE funds and SIVs (iii) Business with non-EEA
counterparties;

Permitted corporate structure Retail bank/depository can Same as under E.U. Prohibited activities cannot
cohabit in same financial proposal be conducted by depository
group with trading company or any affiliate within BHC
Higher loss absorbency rule Yes, via leverage ratio for Yes, as add-on to the Only for U.S. SIFIs
trading business that conservation buffer
exceeds size threshold
Depositor preference 3/ Presently not envisaged Yes, for U.K. retail banks Yes, under U.S. FDIA

Implemented in legislation? No No. Planned completion by Yes

May 2015
Implementing regulations No No No
finalized?
Proposed implementation Not available Envisaged by 2019 Full implementation was
schedule and status scheduled for July 2014.
May be delayed.

Notes:
1/ Similar conditions have been imposed on U.K. building societies via amendments to the Building Societies Act (e.g., they are subject to higher loss
absorbency requirements.
2/ Structural reform proposals released by France on December 19, 2012 w ould leave market making inside the ring-fence and carry a size threshold
for application, albeit further details are aw aited. Wholesale funding and use of derivatives to hedge business risks remains permitted for U.K. retail banks.
3/ For insured deposits in the U.K.

34
See Pazarbasioglu and others for further discussion.
 21

Resolution of cross-border financial institutions

As with previous tools, the crisis demonstrated the need for an effective cross-border
resolution framework to minimize the costly contagion effects of the failure of a globally
systemic financial institution. Endorsed by the G20, the Key Attributes for Effective
Resolution Regimes for Financial Institutions” aims to establish a framework that sets out a
series of policies that address the problem of moral hazard of SIFIs and make resolution
feasible, without severe systemic distress or costly taxpayer bail-outs. The Key Attributes is
broad in scope and encompasses any institution deemed to be of systemic importance,
including not only banks, but also nonbank financial institutions and market infrastructures,
such as CCPs. The Key Attributes involve 12 key principles considered essential to an
effective resolution regime (Box 3). These principles can be grouped into three broad
powers: (i) powers to intervene quickly (prior to insolvency) and assume control from
existing owners and managers; (ii) powers to effect a resolution; and (iii) powers to support
the resolution, for example, by suspending third party actions that could otherwise undermine
it.35 Importantly, the objectives of the Key Attributes extend beyond the national level to
ensure the containment of cross-border contagion, whereby jurisdictions establish
arrangements for mutual cooperation in resolving GSIFIs.

35
The Key Attributes of Effective Resolution Regimes for Financial Institutions: Progress to Date and Next
Steps,” August 2012, IMF.
 22

Box 3. The Key Attributes—A Summary1

The Key Attributes set out 12 features considered essential for an effective resolution regime:

 Scope: The regime should cover any financial institution that could be systemically
significant.
 Resolution authorities should be independent and have clear mandates, roles, and
responsibilities.
 Toolkit: Resolution authorities should have broad resolution powers, as described in part III.
 Set-off, netting, collateralization,and segregation of client assets: These should be
preserved, although the authorities should also be able to suspend the operation of such
rights, subject to adequate safeguards.
 Legal Safeguards: While resolution authorities may depart from the hierarchy of claims, they
may have to offer compensation to creditors, and their decisions must be subject to judicial
review.
 Funding of firms in resolution: Authorities should not be reliant upon public funds to
resolve firms.
 Framework for cross-border cooperation: Resolution authorities should be empowered and
encouraged to achieve cooperative solutions with foreign resolution authorities.
Crisis Management Groups: Home and key host authorities should maintain CMGs that
actively review and report on resolvability and on the recovery and resolution planning
process for G-SIFIs.
 Institution-specific cross-border cooperation agreements should be in place among relevant
authorities to manage the sharing of information and specify responsibilities in respect of all
G-SIFIs.
 Resolvability assessments: Resolution authorities should regularly undertake resolvability
assessments for all G-SIFIs, and should be able to require changes to business practices,
structure or organization.
 Recovery and resolution planning: Jurisdictions must require planning for the recovery and
resolution of firms that could be systemically significant or critical.
 Information sharing: Jurisdictions should eliminate impediments to the domestic and cross-
border exchange of information among authorities, both in normal times and during a crisis.
_______________________
1
“The Key Attributes of Effective Resolution Regimes for Financial Institutions: Progress to Date
and Next Steps,” August 2012, IMF.
 23

B. Cross-sectional Prudential tools: Assessment of Interactions and Impact

A simple qualitative framework for cross-sectional analysis

The paper develops a qualitative matrix that serves as a first step in developing a
framework for policymakers to reflect on the potential interactions of prudential tools.
This simple framework is based on several basic parameters—the number of concurrent
tools, the timing of implementation, the number of successive stages of impact, the cross-
sectional dimension of interaction, and the type of institution. The nature of tools analyzed
here is bilateral, for the most part, evaluating the interaction of two tools at a time. Further, it
is assumed that the tools are implemented simultaneously and not sequentially. While the
case of whether one tool is initiated before another may have significant implications for
their subsequent interface and is worthy of subsequent research, the analysis here attempts to
be more singular in approach. The framework largely assesses the first round effects of the
interaction, that is, the more immediate impact of each tool on the other. Introducing
subsequent second and third round effects would introduce not only more ambiguity as to the
interactions, but would also add complexity by drawing in multiple dimensions into the
analysis, i.e., the second round effect might now involve four tools interacting instead of two,
questions as to sequential timing of interaction or spread out the impact over time, and
spillovers that in turn impact the choice of such tools. The focus here remains on the cross-
sectional nature of the interface, as the introduction of a time dimension adds substantial
complexity.36 Lastly, the analysis is targeted, for the most part, at the banking sector. The
analysis does not base assessments on the cost implications of these instruments as the focus
here is on the objective of an instrument with respect to interconnectedness. However, each
of these parameters adds more depth to the analysis and their incorporation into subsequent
frameworks would introduce a more multi-dimensional aspect for policymakers.

In turning to the matrix framework, complementarity and impact assessments in this

section are broad based and qualitative in nature, as many of these tools are only in their
nascent stages—some not yet implemented and others still being finalized in regulation—and
thus difficult to fully assess the materiality and persistence of the effects of regulatory
reforms.37 Table 5 below summarizes the main conclusions of this section. First, it presents
the evaluation of the interaction between the selected prudential instruments and reaches an
overall view of the complementarity (or conflict) of each measure in the context of a general
macroprudential approach to deal with the cross-sectional dimension of systemic risk. Then,
the table presents a preliminary assessment on how these measures may impact concentration
and contagion to reach an indication of their ability to reduce the risks related to

36
The time dimension of macroprudential tools is examined separately in, “SDN Cost-benefits analysis of
macroprudential policies.”
37
For example, it is difficult to distinguish the effects of the reforms from the outcome of crisis related actions
and the current cyclical downturn.
 24

interconnectedness (the spillover consequences for other institutions in the network). Finally,
an overall assessment of the selected measures to address interconnectedness is provided.

Table 5. Interaction of Prudential Tools to Deal with Bank Interconnectedness:

Concentration Risk and Contagion1
TOOLS 2,3 Microprudential Capital buffers Limits on liq. Limits on Resolution CCP
Exposure limits (SIFIs) mismatches activities frameworks clearing
(LCR,NFSR) (V-V-L) requirements
Microprudential
Exposure limits

Capital buffers (SIFIs)

Limits on liquidity
mismatches

Limits on activities
(structural)

Resolution frameworks

CCP clearing
requirements

Overall
Complementarity

Impact on ↓↓ ↓ ↓↑ ↓↓ ↓ ↑
Concentration

Impact on Contagion ↓↓ ↓ ↓ ↓↓ ↓ ↓

Overall reduction in
interconnectedness HIGH LOW MEDIUM HIGH MEDIUM LOW

Complex Regulators
ity of LOW MEDIUM HIGH HIGH HIGH MEDIUM
impleme
ntation Banks
MEDIUM LOW HIGH HIGH HIGH LOW

1
The matrix is characterized by several parameters: tools are analyzed bilaterally; involve simultaneous implementation of the tools; focus on the more
immediate first round effects; and does not involve a time series dimension. Further, the matrix pertains to banks, acknowledging that there may
subsequent implications in the non-bank or non-regulated sectors
2
Fully Complementary: tool is mutually reinforcing the intended objective of another tool (dark blue); Partially complementary: tool may have a
partially offsetting impact on the intended effects of another tool (light blue); Partially conflicting: the tool has conflicting impact with the intent of
another tool but are not major (light red); Not related or not contradictory (white).
3
Arrows indicate an increase (↑) or decrease (↓) in resulting impact.
 25

Microprudential exposure limits

Microprudential exposure limits are, on the whole, partial complements with the other
prudential instruments considered in this paper. Microprudential exposure limits may
interact with capital buffers SIB in several ways. On one hand, the larger capital buffer of a
G-SIB will increase its capital base, and enable a bank’s absolute exposure to a counterparty
to increase (although its exposure does not increase in relative terms). On the other hand, the
increased capital charge may cause a bank to reduce its concentration in riskier assets, thus
overall, have a partially conflicting effect. As regards the interaction with liquidity ratios,
there should be reinforcing characteristics between the objectives of the microprudential
instruments for exposure limits to a single counterparty and the liquidity ratios, such as the
LCR, that limit concentration in particular instruments, such as wholesale funding, and
promote more liquid instruments. However, if a bank builds up required amounts of level 2
liquid assets to meet liquidity ratios (e.g., corporate debt subject to haircuts), it could
subsequently increase the bank’s exposure to the same issuer(s), and thus run up against the
microprudential limits on a bank’s exposure to counterparties. That said, the indirect limit on
wholesale funding may also reduce interbank activity and thereby reducing
interconnectedness. Thus, contagion is considered partially complementary while from the
concentration angle, it is partially conflicting. Exposure limits reinforce the purpose of the
regulations that similarly place limits on banks activities.38 Likewise, they partially
complement the purposes of the resolution frameworks, since having exposure limits in place
should make the resolution process easier. Finally, microprudential exposure limits, such as
banks’ limits on counterparty exposures, may conflict with the purpose of trading through
central clearing systems.39 The requirement to trade standardized contracts on a CCP
concentrates the exposure of a financial institution to a single counterparty—the CCP—and
potentially approach limits on single counterparty exposures. However, unlike an individual
counterparty, CCPs have significant safeguards in place to address risk exposures for both
members and the CCP as a whole, such as capital, collateral
Microprudential exposure limits reduce network complexity, concentration and
connectivity resulting in a less contagious financial network for financial institutions.
FIs can have common exposures that arise both directly and indirectly. FIs may be directly
exposed through financial contracts between systemic institutions, or to one sector or
instrument (e.g., housing, real estate, sovereign bonds). FIs maybe also exposed indirectly
through financial activities with counterparties who themselves are directly exposed to the
same underlying risks. Further, current microprudential regimes do not impose limits on
sectors, instruments or sovereign exposures and ignoring quite often indirect exposures. For
other such exposures, management falls within Pillar II of Basel.

38
There is a risk, however, is that these limits on activities could transfer to the non-regulated sector and
thereby increase interconnectedness outside of the regulated banks.
39
The paper assumes that CCPs are following the CPSS-IOSCO Principles for Financial Market Infrastructures.
 26

Capital buffers

In general, capital buffers for systemically important banks partially complement other
cross-sectional macroprudential tools. Although SIFI capital surcharges do not interact
with liquidity requirements, and central counterparties, they have a minor conflict with
microprudential exposure limits as explained above. But they strongly complement the intent
of regulations on limits on banks’ activities, as both measures aim to limit the
interconnectedness and riskiness of SIBs either via internalizing the costs of their systemic
importance via capital charges or via their business models. Capital surcharges on SIBs
should not interact with resolution framework as the capital surcharge is a going concern
surcharge within a capital conservation buffer. If the bank is to be resolved, the surcharge
will have been long since absorbed. The surcharge does not affect resolution, which is why
the G-SIB package of measures includes a resolution framework. Capital is a first line of
defense so that resolution is not triggered.

Capital surcharges related to a bank’s systemic importance utilize a financial penalty to

lead banks to cost in the systemic growth of a SIFI, but it not clear it provides enough
disincentive. One response to the too-big-to-fail problem is to levy higher capital surcharges
that can be graduated to increase with the systemic importance of the FI. SIFI surcharges can
be viewed as a kind of Pigouvian tax to tackle the externality of systemic risk. Additional
capital buffers such as the proposed Basel Committee’s G-SIB or D-SIB charges, or the
IAIS’s charges on systemically important insurers, are intended to create incentives for SIFIs
and the financial network as a whole to become less concentrated and less contagious.
However it is worth bearing in mind that banks the G-SIB surcharge may be viewed as an
inevitable cost of undertaking business and will be deemed acceptable to the G-SIBs if the
fees and incomes they get from being interconnected more than compensate for this charge.

Furthermore, there is a concern that the new framework may contribute to accelerating
concentration and interconnectedness in ways beyond those identified in Table 5.

 The strengthened capital and liquidity requirements would provide an incentive for
banks to increasingly allocate more of their funds into low risk-weighted and high-
quality liquid assets, notably sovereign bonds. This applies not only to capital buffers
but also for liquidity buffers and CCPs. This would give rise to concentration risk in
banks’ assets and interconnectedness between banks and sovereigns with the potential
risks of an adverse sovereign-banking loop arising in distressed conditions. However,
the capital framework has been complemented with a non-risk sensitive leverage ratio
to prevent excess leverage resulting from the holdings of low risk weighted assets.

 It is also possible that higher requirements could reduce the number of global players
in financial markets that could meet both higher capital requirements and liquidity
requirements, e.g., only the largest banks may have the deepest pockets for HQLA, or
 27

mergers and acquisitions in order to compete globally, increasing concentration risk

and interconnectedness among global financial institutions.

Liquidity regulation and limits on liquidity mismatches

Overall, liquidity regulations strongly complement other prudential tools to limit the
effects of interconnectedness. Despite their neutrality toward capital surcharges to SIBs,
limits on liquidity mismatches strongly complement regulations that limit banks’ activities—
by constraining the reliance on short-term funding and thus reducing rollover risk and access
to short–term funding that could lead to asset fire sales as banks act to obtain liquidity. As a
result, liquidity regulations make banks’ balance sheets more stable, facilitating the
resolution process.40 It is not deemed that limits on liquidity mismatches interact in one way
or another with the requirement to use CCPs as a macroprudential response to
interconnectedness as the objectives of these measures are not conflicting. However, both
banks’ liquidity requirements and CCPs require HQLA for either collateral or LCR, thus
introducing competing demand for and increasing cost of HQLA, although both are intending
to make the system safer.

Liquidity regulations, as with capital buffers, reduce systemic contagion, although the
impact on industry concentration is less clear-cut. Reducing liquidity mismatches through
limits (LCR, NSFR) may mean there are more sizable liquidity buffers (high quality assets)
for FIs to absorb losses and mitigate liquidity runs. That said, the impact of limiting liquidity
mismatches has an uncertain impact on financial network concentration. A more challenging
liquidity standard requiring high-quality liquidity assets, (particularly for Level 1 assets) may
favor larger systemic SIFIs who through their market making positions have access to a
wider variety of such assets at reasonable costs. Smaller SIFIs may find it difficult and costly
to acquire such liquid assets resulting in their exit (through consolidation or failure) with the
overall concentration of the financial increased in this case. Nevertheless, limits on liquidity
mismatches help to make transparent a bank’s positions and exposures enabling easier
comparisons across the financial network and incentivizing reduction in the size of such
mismatches and consequent network concentrations.

Structural limits on activities

Structural limits on activities generally complement other prudential tools to limit the
effects of interconnectedness (concentration and contagion). Structural limits on activities
should reinforce the purposes of microprudential exposure limits, capital surcharges for
SIFIs, and limits on liquidity mismatches.41 They also complement the purpose of regulations
40
It should be noted that in the process of ring fencing of proprietary trading, the investment bank portion of
the institution will need to increase its holding of liquid assets, which could be costly.
41
However, under the Volcker Rule, there are concerns that market liquidity may decline, thereby reducing the
supply of high quality liquid assets and the ability of banks to meet Basel III liquidity requirements.
 28

aimed to facilitate banks’ resolution processes, as both measures—resolution and structural

limits—are intended on achieving simpler institutions with easier resolvability.42 Structural
limits on activities, however, are considered neutral with respect to the use of CCPs as they
tend not to be affected by the institutional requirements set forth for the traders/clearing
members.

The various direct measures (Volker, Vickers and Liikanen) that restrict the size and
scope and complexity of bank’s business models should reduce cross-sectional
dimension of systemic risk across the banking system, but not necessarily across the
financial system. Direct structural measures have the potential to significantly reduce the
complexity, risk concentrations and interconnections across the banking system. However,
such direct regulations creates the potential for the transfer of complex risks and increased
interconnections within the lightly regulated shadow banking and financial system as a whole
due to regulatory arbitrage and increased cost of credit and capital within the banking system
due to such direct measures. Recent evidence from the FSB/BIS suggests that both the
banking and shadow banking system have grown over the very period that regulation has
been proposed, it maybe that in this regard the shifts of risks between banking and the
shadow banking system occurs more abruptly after implementation of regulation and
macroprudential tools.43

Resolution of cross-border and systemic financial institutions

An effective resolution framework complements the intent and purpose of other

instruments to tackle interconnectedness. The existence of a sound resolution framework
helps fulfill the purposes of microfinancial exposure limits, and limits on banks activities. It
also strongly complements the limits on liquidity mismatches, making resolution simple. The
only area where the resolution process could enter into conflict with other macroprudential
measures is in the case of CCPs. On one hand, the resolution framework should establish
how financial institutions would be wound down, and make it easier to deal with CCP
exposures. Moreover, a CCP’s net exposure across counterparties should make the
bank/clearing member’s counterparty exposures easier to resolve because they are subject to
multilateral netting and thus reduce counterparty exposures. However, if the execution of the
resolution framework is weak or legal framework is not well defined such as priorities of
precedent in the resolution process (e.g., CCPs before all other creditors) then both CCPs and
resolution mechanisms could conflict in tackling the interconnectedness dimension of

42
The imposition of structural limits could impact resolution through other channels, such as the absence of
bail-ins in the retail portion of the bank, increase difficulty of moving funds across the larger bank holding
company in times of distress and potential runs on the retail side of the bank because of concerns about the
health of the investment bank component.. See Pazarbasioglu and others. for further discussion.
43
Ibid.
 29

systemic risk.

Resolution plans are intended to help to transfer first-loss away from taxpayers to the
owners of SIFIs, helping to contain their impact on network concentration and
contagion. Resolution frameworks/plans, and by definition the elements attached to it—
living wills, bail-ins, group-wide exposure and derivatives netting—help to increase the
feasibility of resolving complex FIs and thereby reducing costly contagion effects. In a well
structured resolution framework that includes, for instance statutory bail in features, as debt
and equity holders would suffer first-loss, investors would push for more rigorous risk
assessment and mitigation to ensure resolvability. For regulators, resolution and recovery
plans and an effective resolution regime aim to transfer first loss of a SIFI failure away from
taxpayers to the owners of a SIFI, reducing overall systemic risk and improving financial
stability. Network concentration and contagion in these circumstances would be reduced as
the size and number of interconnections would be reduced by the resolution framework and
all its tools. Moreover, resolution would also seek to ensure the continuance of critical
(payment and settlement) functions.

OTC derivatives and CCPs

In terms of complementarity, CCP clearing requirement shows, in general, weaker

interactions vis-à-vis other macroprudential tools. Along the previous explanations of this
section, microprudential exposure limits, capital buffers (SIFIs), limits on liquidity
mismatches, and limits on activities have, in general, very limited interaction with the CCP
clearing requirement, while with respect to exposure limits the interactions can be
conflicting. Resolution frameworks could potentially interact positively or negatively,
depending on the sound design of the resolution framework vis-à-vis exposures to CCPs.

IV. POLICY CONSIDERATIONS AND NEXT STEPS

The analysis conducted here emphasizes the importance for policy makers to consider
the nature and significance of the cross-sectional dimension of systemic risk in their
jurisdictions and take actions accordingly. There are a few important considerations worth
bearing in mind with regard to the significance of cross-sectional dimensions of systemic
risk. First, the identification and measurement of risks stemming from the analytical models
would introduce a significant tool into the prudential arsenal and deserve investigation as to
how they could be supportive in the regulatory framework. Second, the application of the
above prudential tools can result in increased costs, for which the qualitative framework here
does not attempt to correct. Lastly, the framework has focused almost entirely on interactions
and impacts with regard to the banking system, and it would be expected that such
interactions will extend to the wider financial system. While it is premature to fully
operationalize hard guidance across different national jurisdictions on the set of cross-
 30

sectional prudential tools to be utilized, the analysis indicates some preliminary

considerations.

A clear conclusion from the analysis was the complexity of the interaction of the various
prudential tools and their impact on interconnectedness. From the point of view of their
singular effect, contagion and concentration are expected to diminish as desired with the
various instruments, with the exception of the CCP clearing requirement, which has a more
conflicting impact on interconnectedness. In terms of their overall reduction in
interconnectedness—considering both contagion effects and risk concentration—the
traditional microprudential exposure limits, resolution framework and limits on activities are
among the most robust. Regardless, these are each measures advisable in addressing
interconnectedness.

However, when examined in terms of bilateral complementarity, simple conclusions are

less clear cut. Liquidity limits, structural measures and resolution frameworks seem, overall,
mostly complementary, while mandatory clearing of OTC derivatives on CCPs has a much
more neutral relationship with other tools. However, the traditional microprudential exposure
limits introduced some of the most difficulty in the analyses, raising questions not only on
how they might interact with other prudential measures but also awareness of gaps that need
to be addressed, particularly in the areas of exposure to sovereigns, product risk and CCPs.
Overall, the analysis reveals the need for a strong precautionary warning in predicting the
impact of the simultaneous implementation of multiple tools. Even for a qualitative analysis
at such a basic level, the potential for nuanced interactions and interplay render cautious
conclusions.

Going forward

The difficulty in analyzing the interactions of microprudential exposure limits elicits the
need for more work on the management of large exposures to domestic sovereigns, on
concentration risk management beyond name risk and exposures to CCPs, each of
which presents complexities outside the more traditional counterparty limits in the
past.44 Many countries currently apply an exposure waiver or discount the consideration of
domestic sovereign exposures with regard to large exposure limits. However, in tail risk
conditions high concentration exposure to a good (low probability of default) counterparty,
such as the recent experience with sovereign, debt could also turn problematic.45 More
examination is also needed on the management of concentration risk beyond name risk.
While Basel II guidance is such that this risk is dealt with in Pillar II, with options including

44
The Basel Committee on Banking Supervision is now considering such measures, and has issued the
consultative document, “Supervisory framework for measuring and controlling large exposures,” (March 2013).
45
In normal conditions, capital accounts for unexpected losses calibrated within a given safety margin but
would not fully account for tails risks.
 31

additional capital buffers, more specific limits should be considered. For example, if a bank
has a substantial concentration in a product, market segment, or economic sector the
supervisor should require on a bank by bank basis to have some safeguard against the
concentration risk. This can be in the form of specific restrictions and limits on these
exposures, or additional capital buffers. Conducting stress-testing for concentration risk to
measure the magnitude and calculate the appropriate amount of buffer may be necessary.
Likewise, standardized derivatives are now being mandated to clear on CCPs—with the
accompanying benefit of multilateral netting to reduce contagion—but would increase a
financial institutions’ exposure to a single counterparty. Exposure to a CCP, which is subject
to significant safeguards for credit and operations risk, should be subject to separate exposure
limits that account for the uniqueness of this type of counterparty.

While new Basel liquidity ratios are designed for banks to increase their holding of
more liquid assets, and thereby reduce holdings of less stable funding sources, an area
for consideration is to link these ratios to the financial institution’s interconnectedness.46
Korea has recently designed a bank levy to increase borrowing costs, to dampen banks and
companies’ demand for external debt (wholesale funding).47 And this is intended to
ultimately reduce external debt at the national level. The bank levy (2-20bp currently, rising
to 50bp) is imposed on bank’s non-deposit foreign currency liabilities, increasing banks’
funding costs. The banks are likely to cover only a part of the additional costs, while the rest
will be passed through to companies’ borrowing interests. As a result, companies will not
only cut the ratio of foreign currency borrowing but rely more on long-term funding, which is
subject to a lower levy rate. As well, the banks will find more incentive to increase the ratio
of relatively low-cost and stable deposits. In all, the bank levy is likely to reduce the overall
demand for wholesale funding and enhance the country’s resilience against pro-cyclicality.
According to preliminary empirical assessment, the overall impact of the Korean macro-
prudential measures appears to be positive, but a longer-term view of the bank levy itself is
still needed with regards to use by other countries especially EM countries.48

The matrix developed in Table 5 provides policymakers with a preliminary qualitative

framework to assess possible interactions of various prudential tools that tackle
interconnectedness (i.e., concentration risks and contagion). This is important given these
tools are not always complementary. The two-dimensional matrix enables us only to consider
interactions between prudential tools as a bilateral relation – namely only interactions for two
tools at a time. Extending this framework to look at simultaneously the interaction between

46
The Basel Committee on Banking Supervision.
47
The Bank of Korea, “Macro-prudential Stability Levy in Korea”(2012), Korean version.
48
Shin and Bruno (2012) find that the sensitivity of Korea-bound capital flows to global conditions decreased in
the period following the imposition of macro-prudential policies, relative to a comparison group of countries.
 32

more than two prudential tools is challenging but is necessary to obtain a more
comprehensive picture of potential interactions.

Another area where this analysis can be taken forward is to look at how prudential-tool
interactions might evolve over time. This raises the prospects of spillovers of such
interactions in terms of additional (2nd and 3rd order) impacts rather than immediate (1st
order) impacts. Similarly, moving from simultaneous implementation to varying the timing
(e.g., sequentially used tools) would add additional insight. Indeed this extension, though
adding complexity and ambiguity to multiple interactions, may give some idea about the mix
of prudential tools that could be applied in the short-term relative to medium and longer-term
prudential policy mixes to tackle the cross-sectional dimension of systemic risk.

Lastly, a dimension that expands the analysis considerably is incorporating the

potential impact and interactions with the nonbank and shadow banking sectors (SBS).
The likelihood of various regulatory measures influencing risk and portfolio adjustments
across financial sectors, movements of traditional banking activities into the SBS, or
opportunities for regulatory arbitrage—across both regulated as well as non-regulated
sectors—are each areas for potential analysis in the framework. All these factors add
complex dimensions to efforts to accurately predict the ultimate consequences of these
prudential instruments.
 33

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 40

Appendix I. Data Requirements for Network Analysis

A crucial first step in network analysis is to define the data on which the analysis will be
based. Depending on the purpose of the analysis, the researcher faces two important choices
regarding (a) the perimeter of the financial network to be analyzed, and (b) the set of
bilateral claims to be considered. In practice, information on bilateral exposures is scarce
and often partial or of limited quality. Therefore, data availability usually constrains the
analysis. This box reviews the perimeter and exposures included in a number of domestic
financial network analyses for selected countries.49

The financial network empirical literature centers almost exclusively on the interbank
market. For the purposes of systemic risk monitoring, one should define a financial firm
broadly to include all institutions which perform critical functions in financial markets,
including credit intermediation, maturity transformation, the provision of savings vehicles,
risk management and savings payments, and the support of primary and secondary funding
markets. Focusing on specific financial sectors may disregard potentially important sources
of systemic risk. For example, Money Market Mutual Funds (MMMFs) in the U.S. are an
important source of liability interconnectedness risk since they invest heavily in the short-
term liabilities of banks. Contagious runs on MMMFs can therefore result in the withdrawal
of a major source of liquidity from the banking sector. However, data on bilateral exposures
covering institutions in multiple financial sectors is rarely available. Some studies
characterize the aggregate exposures across different sectors of the financial system.

The set of bilateral claims that defines the financial network is constrained by data
availability. Supervisors in several countries require banks to report their bilateral exposures.
In some cases, those reports are fairly complete and allow for a representative analysis. In the
majority of cases, however, those reports are subject to some sort of censoring, such as: (a)
excluding certain types of exposures (typically off-balance sheet), (b) being subject to
relatively large reporting thresholds or covering only the largest exposures, and (c) being
available for only large institutions and on a low frequency basis (to avoid imposing
burdensome reporting costs). Additional sources of data on bilateral exposures are Payment
Systems and Credit Registries. There is hardly any work that has quantified the consequences
of censoring. Table 1 reviews the types of exposures included in a variety of domestic
interbank network studies depending on data availability. In other cases, balance sheet data
for each bank reports only aggregate interbank exposures so additional assumptions (e.g.,

49
See Cerutti and others (2011) for a review of the data challenges in measuring systemic risk in global
banking.
 41

maximum entropy) are required to estimate the bilateral exposures.501 As a drawback, these
estimates usually fail to reproduce some properties of real world interbank markets.

50
See, for example, Degryse and Nguyen (2007) for Belgium, Elsinger and others (2006) for Austria, Elsinger
and others (2006) for the U.K., Gauthier and others (2010) for Canada, Sheldon and Maurer (1998) for
Switzerland, and Upper and Worms (2004) for Germany.
 Table 1. Data used in Selected Countries' Network Analyses
Country Reference Data Source Perimeter Exposures

Sweden Blavarg and Nimander, 2002 Bank reporting Interbank network Banks report 15 largest exposures with full principal credit risk
(4 largest banks) Focus on exposures containing full principal credit risk
_ uncollateralized lending
_ holdings of securities issued by counterparties
_ credit element of OTC derivative exposures (gross and net exposures)
_ FX settlement exposures as they do not incorporate PVP or DVP mechanisms
Excludes exchange-traded derivatives and payment and settlement systems with PVP and DVP mechanisms.

Korea Aydin and others, 2011 Bank reporting Interbank network Interbank Assets: bank bonds receivable, loans, call loans, bonds purchased under repurchase agreements,
(18 banks) accounts receivable, derivative assets.
Interbank liabilities: deposits, CD, bank bonds payable, borrowings, call money, bonds sold under repurchase
agreements, accounts payable and derivative liabilities.
Excludes off-balance sheet bilateral exposures.

Mexico Martínez-Jaramillo and others, 2010 Bank reporting Interbank network Focus on largest exposures
_ uncollateralized interbank lending
_ securitites held issued by other banks
_ credit component of derivative transactions and credit lines as part of the interbank market

42
India RBI, 2011 Bank reporting Interbank network Focus on bilateral fund based and non-fund based exposures.
(75 banks) Excludes transactions where settlement takes place through a central counterparty.

Italy Mistrulli, 2007 Bank reporting Interbank network All interbank exposures excepts shares (CDs, current accounts, repos, other loans, subordinated and
unsubordinated loans).

Netherlands van Lelyveld and Liedrop, 2006 Bank reporting Interbank network Focus on interbank deposits.
For all banks, consider deposits larger than 3 percent of actual own funds.
Top 10 banks with respect to interbank assets were asked to fill in a more complete survey.

Switzerland Müller, 2006 Bank reporting Interbank network Focus on 10 largest interbank assets and liabilities (including off-balance sheet). For repos, only unsecured
(300 banks) portion is taken into account).

Hungary Lubloy, 2005 Bank reporting Interbank network Uncollateralized interbank loans and deposits denominated in local currency between domestic banks.

U.S. Furfine, 2003 Payment system Interbank network Focus on overnight bilateral credit exposures arising from federal funds transactions (uncollateralized lending)
(719 banks) estimated from data on large scale payment system (FedWire).

Denmark Amundsen and Arnt, 2005 Payment system Interbank network Focus on overnight bilateral credit exposures arising from domestic overnight loans (uncollateralized)
(117 banks) estimated from data on real time gross settlement payment system (Kronos).

Germany Memmel and Stein, 2008 Credit registry Interbank network All internbank loans when the indebtedness of the borrower exceeds €1.5mn.
Includes traditional loans, off balance-sheet positions and exposures from derivative positions.
Excludes position of trading book.
 43

Appendix II. Network Analysis Tools

Centrality Analysis51

The underlying idea of centrality is to infer from the pattern of linkages among
financial institutions the extent to which a node is “central” in the financial network.
Financial networks usually display a high density of interactions (Figure 2). However, the
distribution of links between nodes does not seem be uniform across the entire network. In
particular, there seem to be a very dense set of relationships occurring at the center of the
network, which peter-out as we travel toward the periphery. Understanding which nodes
belong at the core of the graph and which are peripheral is an important tool.

Figure 2. Dense Interconnected Network

Several indicators of interconnectedness, or “centrality,” are used to quantify the

relative importance of each financial institution in a financial network.52 The most
51
See IMF (2012) and Cihak and others (2011).
52
In addition to the local measures that quantify the relative importance for each node in the network, there are
global measures intended to characterize the network as a whole.
 44

common measures of “centrality” usually take into account whether a relationship between
two nodes exists or not, but not the size of each node nor of the exposure between them.53

 Degree centrality: quantifies the number of connections any given node has to all
others in the network. Degree centrality of a node can be computed respectively as
the sum of: incoming links (in degree); outgoing links (out degree); or all links
(degree).

 Closeness centrality: measures the mean or shortest path in terms of the number of
paths, between one node and all others.

 Random walk betweenness centrality: quantifies the importance of each node in

relaying flows amongst all others. This can be approximated by the expected number
of times that a random walk between any starting and ending node will pass through
an intermediate set of nodes averaged over all starting and ending vertices.

 Eigenvector centrality: defines both the number and the quality of the connections
any given node has within the network. It assigns relative scores to all financial
institutions in the network based on the principle that connections to high-scoring
financial institutions contribute more to the score of the financial institution in
question..

Sometimes, different indicators of interconnectedness are combined into a single

ranking of interconnectedness.54 A percentile rule is usually followed to distinguish the
core from the periphery based on the computed ranking. According to country studies,55
domestic interbank networks tend to exhibit a tiered structure. A tiered structure is one where
different institutions have different degrees or levels connectivity with others in the network.
The bulk of the activity takes place between the financial institutions in the core. These
institutions are closely connected with each other. The institutions in periphery, on the other
hand, are connected with the institutions in the core but have limited exposures to other
institutions in the periphery.

53
Incorporating the size of bilateral linkages in the network model is less prevalent as it increases considerably
the complexity of the calculation, and the tools for this are still evolving in the research community. See Cihak
and others (2011) for an example.
54
Alternatively, just one indicator may be chosen, usually the one related to eigenvector centrality.
55
See Upper and Worms (2004), Craig and von Peter (2009), and Reserve Bank of India (2012).
 45

Cluster analysis56

Cluster analysis condenses the mass of bilateral linkages into subgroups of nodes—
whether in the core or in the periphery—among which connections are particularly
strong. Most cluster identification methods rely on partitioning algorithms which define
separable non-overlapping, non-nested sub-groupings. Such algorithms are subject to some
constraints on the number, size, or shape of the clusters to be identified. For example, such
methods necessitate defining ex-ante the number of clusters into which the network should
be partitioned, so the choice of the number of clusters has a non-trivial effect on the results.
Also, because each node can only belong to a single cluster, these methods ignore the
implications of overlapping or nested subgroups of institutions. This dilutes the potential for
richer understanding of the particular nodes that facilitate such overlaps, and therefore the set
for interactions across nodes.

Work at the IMF has emphasized the importance of methods that allow for
identification of an unknown number of potentially overlapping clusters with varied
membership size. The architecture that emerges from a recently developed cluster
identification algorithm is described in stylized form in Figure 3.57 The system comprises a
number of overlapping clusters of institutions. Connections among institutions within the
cluster are stronger than with those outside. Some institutions are situated in the intersection
of a large number of clusters. These institutions are “central” and, as such, form the core. But
beyond the global core, there are institutions through which clusters are connected either to
the core or to other clusters. Owing to their capacity to act as transmitters (and potentially
amplifiers or mitigators) of shocks, nodes comprising the cluster overlap regions are
“gatekeepers.” Countries can be gatekeepers to multiple clusters. Groups of countries can
also serve as gatekeepers; for example, countries in the core can individually and as a group
serve as gatekeepers to different parts of the system.

56
See IMF (2012).
57
The algorithm is called “Clique Percolation Method” and is described in IMF (2012).
 46

Figure 3. Cluster Identification: A Stylized Depiction

Balance Sheet Simulation Methods58

Balance sheet simulation methods allow analyzing and quantifying contagion and
amplification mechanisms of financial shocks in financial networks. These methods use
simple balance sheet identities to trace the effect of difficulties at an individual bank or
banking sector through a combination of data and assumptions. Initial losses associated with
the failure of a financial institution can potentially lead to the weakening and, sometimes,
failure of additional nodes with further knock-on effects. The IMF’s introductory stress
testing kit by Cihak (2007) includes a simple feature analyzing how a failure of a bank may
affect other banks directly if it defaults on its borrowers. The “pure” interbank contagion
exercise does not take into account the different likelihood of failures in different banks. The
“macro” interbank contagion exercise analyzes situations when all banks are weakened at the
same time by a common external (typically macroeconomic) shock, which affects each bank
differently depending on its exposures to the various risk factors, and makes some of the
banks (perhaps more than one) fail. Although asset exposures have historically been the
focus of balance sheet interconnectedness analyses (a credit shock), recent research by
Espinosa-Vega and Solé (2010) and Tressel (2010) also emphasizes the risks arising from
liabilities.59
58
See Espinosa-Vega and Sole (2010) and Tressel (2010).
59
Cerutti and others (2010) present a stylized analysis of the effects of ring-fencing (i.e., different restrictions
on cross-border transfers of excess profits and/or capital between a parent bank and its subsidiaries located in
different jurisdictions) on cross-border banks.
 47

This methodology incorporates not only the role of exposures across the network but
also the role of financial buffers. On the one hand, linkages may act as channels to
propagate shocks to the whole system, that is, they act as “shock transmitters.” On the other
hand, through these linkages, shocks can be shared and absorbed by others, that is, financial
linkages may act as “shock absorbers.” The network analysis tools described in the previous
sections (i.e. centrality and cluster analysis) determine, solely from the pattern of financial
linkages, the potential importance and role of a financial institution in amplifying or
dampening shocks. Balance sheet simulation methods complement the basic mechanisms of
shock transmission (via lending exposures) with the mechanisms for absorption (via banks’
net worth).

The systemic importance of an institution is quantified by assuming its hypothetical

failure and simulating the imposed losses on each other institution in the network.
Espinosa-Vega and Solé (2010) propose two main criteria to classify potentially systemic
financial sectors (or institutions): the number of failures in the network following a credit
shock; and the capital losses (impairment) in the network of financial institutions following
this credit shock. The measures are computed following domino effects unleashed by the
hypothetical default of a banking system on its interbank obligations—a credit shock. In
addition to the credit shock, Espinosa-Vega and Solé look at a funding shock, where the
failure to roll over short-term funding in the interbank market, results in fire sales with
associated knock-on effects. Additionally, Tressel (2010) includes a deleveraging channel,
whereby, following a negative asset shock, institutions adjust the size of their balance sheet
to maintain a target minimum capital-to-asset ratio.
 Table 1. Network analysis in IMF Surveillance
Bilateral Surveillance
Country Year Document Methodology Unit of analysis Data Goal Policy recommendation
Australia 2012 FSAP Simulation method Cross-country BIS Identify key potential sources of risk
(funding shock)
Interconnectedness Assessment Domestic banks RBA Determine systemic importance Call for special risk mitigation arrangements
Spain 2012 FSAP Simulation method Cross-country BIS Identify key potential sources of risk
(credit and credit+funding shock)
India 2012 FSAP Interconnectedness Assessment Domestic banks and RBI Network descriptive analysis
(RBI calculations) (Centrality analysis) domestic financial sectors
Simulation method Domestic banks and RBI Assess and quantify contagion effects
(credit shock) domestic financial sectors
France 2012 FSAP Simulation method Cross-country BIS Identify key potential sources of risk
(credit and credit+funding shock)
Brazil 2012 FSAP Simulation method Domestic banks BCB Assess and quantify contagion effects
(credit and credit+funding shock)
Japan 2012 FSAP Simulation method Cross-country BIS Identify key potential sources of risk
(credit and credit+funding shock)
2011 Spillover Report Simulation method Cross-country BIS Identify key potential sources of risk
(credit and credit+funding shock) and potential contagion destinations

48
Interconnectedness Assessment Cross-Country BIS Identify key potential sources of risk
Chile 2011 FSAP Interconnectedness Assessment Domestic financial sectors BCCh Network descriptive analysis
United Kingdom 2011 Spillover Report Interconnectedness Assessment Cross-Country BIS Identify key potential sources of risk
(includes upstream vulnerabilty)
Korea 2011 Article IV Simulation method Domestic banks BOK Assess and quantify contagion effects
(credit and credit+funding shock)
Paraguay 2011 FSAP Interconnectedness Assessment Cross-country BIS Assess banking system's ilnkages with the rest of
the world to assess cross-border supervision
Interconnectedness Assessment Domestic banks and cooperatives BCP Network descriptive analysis
Luxembourg 2011 FSAP Simulation method Cross-country BIS Assess and quantify contagion effects
(credit and credit+funding shock)
Finland 2010 FSAP Interconnectedness Assessment Domestic banks FIN-FSA Network descriptive analysis
Simulation method Domestic banks FIN-FSA Assess and quantify contagion effects

BIS: Bank for International Settlements; RBA: Reserve Bank of Australia; RBI: Reserve Bank of India; BCCh: Banco Central de Chile; BCB: Banco Central do Brazil; BOK: Bank of Korea; BCP: Banco Central de Paraguay;
BIN-FSA: Finland Financial Supervisory Authority.
 Table 1. Network analysis in IMF Surveillance
Bilateral Surveillance
Country Year Document Methodology Unit of analysis Data Goal Policy recommendation
Australia 2012 FSAP Simulation method Cross-country BIS Identify key potential sources of risk
(funding shock)
Interconnectedness Assessment Domestic banks RBA Determine systemic importance Call for special risk mitigation arrangements
Spain 2012 FSAP Simulation method Cross-country BIS Identify key potential sources of risk
(credit and credit+funding shock)

India 2012 FSAP Interconnectedness Assessment Domestic banks and RBI Network descriptive analysis
(RBI calculations) (Centrality analysis) domestic financial sectors
Simulation method Domestic banks and RBI Assess and quantify contagion effects
(credit shock) domestic financial sectors
France 2012 FSAP Simulation method Cross-country BIS Identify key potential sources of risk
(credit and credit+funding shock)

Simulation method Domestic and foreign banks BdF Identify key potential sources of risk
(credit and credit+funding shock)

2012 Article IV Simulation method Cross-country BIS Assess and quantify contagion effects
(credit shock)
Brazil 2012 FSAP Simulation method Domestic banks BCB Assess and quantify contagion effects

49
(credit and credit+funding shock)
Japan 2012 FSAP Simulation method Cross-country BIS Identify key potential sources of risk
(credit and credit+funding shock)
2011 Spillover Report Simulation method Cross-country BIS Identify key potential sources of risk
(credit and credit+funding shock) and potential contagion destinations
Interconnectedness Assessment Cross-Country BIS Identify key potential sources of risk
Chile 2011 FSAP Interconnectedness Assessment Domestic financial sectors BCCh Network descriptive analysis
United Kingdom 2011 Spillover Report Interconnectedness Assessment Cross-Country BIS Identify key potential sources of risk
(includes upstream vulnerability)
Korea 2011 Article IV Simulation method Domestic banks BOK Assess and quantify contagion effects
(credit and credit+funding shock)
Paraguay 2011 FSAP Interconnectedness Assessment Cross-country BIS Assess banking system's linkages with the rest of
the world to assess cross-border supervision
Interconnectedness Assessment Domestic banks and cooperatives BCP Network descriptive analysis
Luxembourg 2011 FSAP Simulation method Cross-country BIS Assess and quantify contagion effects
(credit and credit+funding shock)
Finland 2010 FSAP Interconnectedness Assessment Domestic banks FIN-FSA Network descriptive analysis
Simulation method Domestic banks FIN-FSA Assess and quantify contagion effects

BIS: Bank for International Settlements; RBA: Reserve Bank of Australia; RBI: Reserve Bank of India; BdF: Banque de France; BCCh: Banco Central de Chile; BCB: Banco Central do Brazil; BOK: Bank of Korea;
BCP: Banco Central de Paraguay; BIN-FSA: Finland Financial Supervisory Authority.
 Table 1. Network analysis in IMF Surveillance (Cont.)
Multilateral Surveillance1
Authors Year Document Methodology Unit of analysis Data Goal Policy recommendation
IMF 2012 Board paper Centrality and cluster analysis Cross-country BIS Characterize cross-border financial architecture
Cihak and others 2011 WP Centrality Analysis Cross-country BIS Study the relationship between financial
stability and interconnectedness
Minoiu and Reyes 2011 WP Centrality Analysis Cross-country BIS Study the evolution of interconnectedness
over the period 1978-2009
IMF 2010 Board paper Centrality analysis Cross-country BIS Identify systemically important financial sectors Establish high-frequency mandatory FSAPs for
systemically important financial sectors
Espinosa-Vega and 2010 WP Simulation method Cross-country BIS Identify systemically important financial sectors
Sole
Tressel 2010 WP Simulation method Cross-country BIS Identify systemically important financial sectors

BIS: Bank for International Settlements; RBA: Reserve Bank of Australia; RBI: Reserve Bank of India; BCCh: Banco Central de Chile; BCB: Banco Central do Brazil; BOK: Bank of Korea; BCP: Banco Central de Paraguay;
BIN-FSA: Finland Financial Supervisory Authority.
1
Additionally, the IMF Research Department has developed a bank contagion module tool (simulation method) to analyze spillover effects from internationally interconnected banking systems. The module contributes to the
IMF-FSB Early Warning Exercise.

50
 51

Appendix III. Price-Based Measures

CoVaR/CoRisk. The most common measure of risk used by financial institutions, the value
at risk (VaR), focuses on the risk of an individual institution in isolation. It measures the
potential loss in value of a risky portfolio over a defined period for a given confidence
interval. The CoVaR is defined as the VaR for an institution i conditional on the financial
situation of another institution j.60 The difference between the CoVaR conditional on distress
of an institution j and the CoVaR conditional on the “normal” state of institution j, ΔCoVaR,
captures the marginal contribution of institution j to risk in institution i (Figure 4). The
measures can also be computed to assess the distress dependence between the market and
particular institution (yielding the contribution to systemic risk and exposure to systemic risk
for each institution). The CoVaR uses market data (e.g., equity prices, CDs spreads, or
market value of assets) to assess the contribution of an individual financial institution to
systemic risk and is therefore available on a high frequency basis. The CoVaR measure is
usually estimated using quantile regressions61, which makes it possible to evaluate the
response of the dependent variable within particular segments of the conditional distribution.
The time variation in the CoVaR can be estimated conditional on a vector of lagged state
variables that affect the joint distribution of returns between institutions.

Figure 4. CoVaR and ΔCoVaR

Returns spillovers. The spillover measure suggested by Diebold and Yilmaz (2009) is a
time-varying indicator of outward returns spillovers of institutions – the contribution of one
institution to systemic risk. The indicator uses market data on returns (CDS spreads or equity
prices) to estimate average (not “extreme”) contributions. Vector Autoregressions are used to

60
Chan-Lau and others (2011) developed an analogous measure, the CoRisk model, which estimates the co-
movements of financial institutions risk factors taking into account their non-linear relationship, based on CDS
spreads.
61
CoVaRs may potentially be computed in various ways.
 52

derive the spillover index. Specifically, Variance Decomposition62 allows assessing the
fraction of the 10-step-ahead error variance in forecasting the returns to one institution that is
attributable to shocks to each other institution. The spillover contribution index for institution
i is given by its outward spillovers (computed adding, for each institution other than i, the
share of its variance that is attributable to institution i) divided by the sum of outward
spillovers for all institutions.

Distress spillovers. The distress spillover measure by Chan-Lau and others (2012) is an
indicator of outward spillovers of institutions during extreme times – the potential
contribution of one institution to systemic risk during crisis. The indicator uses market data
on returns (based on CDS spreads, equity prices or market value of assets) to identify
“extreme events” by looking at the 1st or 5th percentile of the joint distribution of returns. The
probability of an extreme event happening for an institution is estimated conditional on
extreme events happening or not for other institutions, after controlling for real and financial
developments in the home country and in global markets. To calculate a the systemic
importance of each institution in terms of “spilling over” to others, the authors take the
number of significant spillover coefficients as a fraction of the number of significant
spillover coefficients for all institutions. Alternatively, an index could be constructed based
on the marginal effects derived from the regressions, in which case the intensity of spillovers
would be taken into account.

JPoD, CoPoD. Segoviano and Goodhart (2009) propose a methodology to estimate the
multivariate distribution of asset returns for all financial institutions, based on estimates of
their individual probability of distress extracted from high frequency market prices (CDS
spreads, equity prices or out of the money option prices).63 This multivariate density can
capture linear (correlation) and non linear interdependence among all institutions and
changes over the economic cycle. Having obtained this joint probability distribution of
distress across a number of institutions, it is possible to then “slice” this multivariate
distribution to estimate sets of pair-wise conditional probabilities of distress -CoPoD- (i.e. the
probability that a financial institution experiences distress conditional on another institution
being in distress). Alternatively, other measures can be computed like the joint probability of
distress for multiple institutions –JPoD-, the expected number of banks becoming distressed
even that at least one bank has become distressed -BIS-, or the probability that at least one
bank becomes distressed given that a particular bank has become distressed.

62
Variance Decomposition requires identifying assumptions. Results based on traditional Cholesky-factor
identification may be sensitive to ordering. Diebold and Yilmaz find that aggregate spillover index is generally
robust to the Cholesky ordering but directional connectedness, however, is found more sensitive to ordering.
63
The approach consists on a non-parametric methodology (CIMDO methodology) that obtains the banking
system multivariate density using as input empirical measurements of probability of distress for individual
institutions.
 53

Systemic CCA. Gray and Jobst’ (2010) Systemic Contingent Claim Analysis quantifies the
system-wide financial risk and government contingent liabilities by combining individual
risk adjusted balance sheets of financial institutions and the dependence between them. The
methodology consists of two estimation steps. The first step uses CCA64 to estimate market
implied potential losses for each sample financial institution. The second step uses Extreme
Value Theory to model the joint market implied losses of multiple institutions as a portfolio
of individual losses with time-varying and non-linear dependence among institutions, and
estimates system-wide losses. The approach quantifies the contribution of specific
institutions to the dynamic of systemic risk. It also shows how this risk affects the
government’s contingent claims over time. In this sense, it gives a magnitude of expected
losses in a forward-looking manner taking into account time-varying interdependence of
financial firms.

64
The CCA is a generalization of option pricing theory pioneered by Black and Scholes (1973) and Merton
(1973). It is based on three principles: (1) the values of liabilities are derived from assets; (2) assets follow a
stochastic process; and (3) liabilities have different priorities (senior and junior claims). Equity can be modeled
as an implicit call option, while risky debt can be modeled as the default-free value of debt less an implicit put
option that captures expected losses.
 54

Table 1. Priced-based measures in IMF Surveillance

Bilateral Surveillance
Country Year Document Methodology Unit of Analysis Goal

Chile 2009Article IV CoVaR/CoRisk Domestic and foreign banks Measure risk codependence

France 2010Article IV CoVaR/CoRisk Domestic and foreign banks Measure risk codependence

United Arab Emirates 2012Article IV CoVaR/CoRisk Domestic banks Measure risk codependence
Domestic and foreign banking system Measure risk codependence
Segoviano-Goodhart Domestic banks BSI, Jpod.

Qatar 2012Article IV CoVaR/CoRisk Domestic banks Measure risk codependence

Segoviano-Goodhart Domestic banks BSI, S.C.

Korea 2011Article IV CoVaR/CoRisk Domestic banks Measure risk codependence

Segoviano-Goodhart Domestic banks BSI, Jpod, CoPod.

Finland 2010FSAP Segoviano-Goodhart Domestic and foreign banks Measure risk codependence
BSI, Jpod, CoPod.

Singapore 2008Article IV Segoviano-Goodhart Domestic banks Jpod, CoPod.

Domestic and regional banks Jpod, CoPod.

United Kingdom 2011FSAP Segoviano-Goodhart Domestic and foreign banks Jpod, CoPod.
Systemic CCA Domestic banks Stress testing.

United States 2010FSAP Segoviano-Goodhart Domestic and foreign banks Jpod, CoPod.
Systemic CCA Domestic banks Stress testing

Sweden 2011FSAP Systemic CCA Domestic banks Stress testing

Spain 2012FSAP Systemic CCA Domestic banks Stress testing

Germany 2011FSAP Systemic CCA Domestic banks Stress testing

United Kingdom 2006Article IV Distress spillovers Domestic and foreign banks Analyze contagion risk

Ireland 2006FSAP Distress spillovers Domestic and foreign banks Analyze contagion risk

Multilateral Surveillance1
Authors Year Document Methodology Unit of Analysis Goal
Lopez-Espinosa and others 2012WP CoVaR Large international banks Identify main factors behind systemic risk.

Ilyina and Mitra 2012Spillover Report CoVaR European SIBs and Global SIBs Analyze spillover potential.
Returns Spillovers
Distress Spillovers

Arsov and others 2012WP CoVaR Large financial institutions in the U.S. Assess performance of measures as early
Jpod and Euro area warning indicators. Estimate potential for
Systemic CCA spillover of risk.
Returns Spillovers
Distress Spillovers

BSI: Bank Stability Index; Jpod: Joint Probability of Default; S.C.: Spillover Coefficient; CoPoD: Coinditional Probabilities of Default.
1
Additionally, price-based measures are used in the context of the IMF-FSB Early Warning Exercise.
 55

Appendix IV. Table 1. Status of Macroprudential Initiatives for Interconnectedness, by Selected Economies

Brazil Canada China European Union Hong Kong India Japan Russia Singapore South Africa Switzerland United Kingdom United States
BCBS BCP advice currently BCBS BCP advice currently BCBS BCP advice currently BCBS BCP advice currently BCBS BCP advice currently
states that ten percent or more states that ten percent or more BCBS BCP advice currently
states that ten percent or more states that ten percent or more BCBS BCP advice currently states that ten percent or more BCBS BCP advice currently
of a bank's capital is defined as of a bank's capital is defined as states that ten percent or more
of a bank's capital is defined as of a bank's capital is defined as states that ten percent or more of a bank's capital is defined as BCBS BCP advice currently states that ten percent or more
large exposure. Twenty-five large exposure. Twenty-five of a bank's capital is defined as
large exposure. Twenty-five large exposure. Twenty-five of a bank's capital is defined as large exposure. Twenty-five states that ten percent or more of a bank's capital is defined as
percent of a bank's capital is percent of a bank's capital is large exposure. Twenty-five
percent of a bank's capital is BCBS BCP advice currently percent of a bank's capital is large exposure. Twenty-five percent of a bank's capital is of a bank's capital is defined as large exposure. Twenty-five BCBS BCP advice currently BCBS BCP advice currently
the limit for an individual large the limit for an individual large percent of a bank's capital is
the limit for an individual large BCBS BCP advice currently states that ten percent or more the limit for an individual large percent of a bank's capital is the limit for an individual large large exposure. Twenty-five percent of a bank's capital is states that ten percent or more states that ten percent or more
expsoure to a private sector expsoure to a private sector the limit for an individual large
expsoure to a private sector states that ten percent or more of a bank's capital is defined as expsoure to a private sector the limit for an individual large expsoure to a private sector percent of a bank's capital is the limit for an individual large of a bank's capital is defined as of a bank's capital is defined as
non-bank counterparty or group non-bank counterparty or group expsoure to a private sector
non-bank counterparty or group of a bank's capital is defined as large exposure. Twenty-five non-bank counterparty or group expsoure to a private sector non-bank counterparty or group the limit for an individual large expsoure to a private sector large exposure. Twenty-five large exposure. Twenty-five
of connected counterparties. of connected counterparties. non-bank counterparty or group
of connected counterparties. large exposure. Twenty-five percent of a bank's capital is of connected counterparties. non-bank counterparty or group of connected counterparties. expsoure to a private sector non-bank counterparty or group percent of a bank's capital is percent of a bank's capital is
Minor deviations from these Minor deviations from these of connected counterparties.
Minor deviations from these percent of a bank's capital is the limit for an individual large Minor deviations from these of connected counterparties. Minor deviations from these non-bank counterparty or group of connected counterparties. the limit for an individual large the limit for an individual large
limits may be acceptable, limits may be acceptable, Minor deviations from these
limits may be acceptable, the limit for an individual large expsoure to a private sector limits may be acceptable, Minor deviations from these limits may be acceptable, of connected counterparties. Minor deviations from these expsoure to a private sector expsoure to a private sector
especially if explicitly temporary especially if explicitly temporary limits may be acceptable,
especially if explicitly temporary expsoure to a private sector non-bank counterparty or group especially if explicitly temporary limits may be acceptable, especially if explicitly temporary Minor deviations from these limits may be acceptable, non-bank counterparty or group non-bank counterparty or group
or related to very small or or related to very small or especially if explicitly temporary
Microprudential Exposure or related to very small or non-bank counterparty or group of connected counterparties. or related to very small or especially if explicitly temporary or related to very small or limits may be acceptable, especially if explicitly temporary of connected counterparties. of connected counterparties.
specialised banks. For the specialised banks. According to or related to very small or
Limits specialised banks. In Brazil of connected counterparties. Minor deviations from these specialised banks. or related to very small or specialised banks. The Japan especially if explicitly temporary or related to very small or Minor deviations from these Minor deviations from these
European Union (2006) as the Law on the Central Bank of specialised banks. UK large
(2008) rules set a maximum Minor deviations from these limits may be acceptable, Concentration limits specialised banks. India has 2012 FSAP recommended or related to very small or specialised banks. In South limits may be acceptable, limits may be acceptable,
regards the quantitative limits, Russian Federation (Article 62) exposures and risk
exposure limit to a single limits may be acceptable, especially if explicitly temporary The Monetary Authority (MA) the following exposure limits large exposure rules to be specialised banks. In singapore Africa In terms of section 73 of especially if explicitly temporary especially if explicitly temporary
there is set of limits compliant the Bank of Russia establishes concentrations are fully outlined
counterparty at 25% of a bank’s especially if explicitly temporary or related to very small or requires all locally incorporated and norms (full details are revised and strengthened so the following statutory limits the Banks Act a bank or a bank or related to very small or or related to very small or
with relevant Directive of the the following concentration in FSA BIPRU handbook,
regulatory capital. A single or related to very small or specialised banks. China is authorized institutions (AIs) to available from RBI website) that all exposures from ana were applied (1) Single controlling company shall not specialised banks. In specialised banks. The US is
European Union, particularly limits (ratios). broadly in line with latest BCPs
counterparty is defined as a specialised banks. In Canada largely compliant with BCP on comply with statutory limits The exposure ceilings for a individual client or group or counterparty limits where: make investments with or grant Switzerland risk concentrations compliant with BCP on large
with Directive 2006/48/EC, - N6: Aggregate size of loans in this area - waivers are
customer or a group of OSFI advice is aligned with large exposures and exposures stipulated in Part XV of the single borrower and group of connected clients are taken into (a) aggregate exposure to a loans or advances or other and large exposure limits are exposure limits and exposures
Articles 106 - 122. Main to one borrower and/or a group allowed for sovereign debt
customers that represent a BCPs. to related parties as of April Banking Ordinance (BO) for borrowers are 15% and 40%, account, limits are set as a single counterparty group credit to any person to an aligned with latets BCP advice to related parties, as of May
stipulated concentration limits of connected borrowers is holdings. UK was compliant on
single economic interest. Loans 2012. controlling their large respectively, of the bank’s percentage of tier 1 or core tier cannot exceed 25% of its aggregate amount exceeding and EU driectives. 2010.
for banking book are as follows: limited to 25% of bank’s large exposure limits with BCPs
to the public sector (at all exposures and risk capital funds (Tier I and Tier II). 1 capital, and all banks capital funds; and 10 per cent of its net qualifying
capital; but largely compliant on
levels) are also limited at 45% concentrations. The main properly manage risk capital and reserves without
exposures to related parties, as
of a bank’s regulatory capital. limits are: concentrations with respect to having obtained the
- of July 2011.
different regions
an AI’s financial exposure to a (ii) These limits can be and industries. N7: Aggregate large credit (b) aggregate of all exposures permission of its board of
person or a group of related exceeded by 5% and 10% of exposures is limited to 800% of exceeding 10% of eligible total directors, or a board appointed
persons should not exceed capital funds in the case of bank’s capital. An exposure to capital to any single committee for this purpose (the
25% of its capital base (section single borrower and a group of one borrower (a group of counterparty group cannot Registrar needs to approve the
81); borrowers, respectively, if the connected borrowers) which exceed 50% of its total composition of the board
• an AI’s unsecured exposure to borrower is engaged in exceeds 5% of a bank’s capital exposures. appointed committee).
10% of capital to single obligor its connected parties (section infrastructure activities. This is treated as large credit These limits apply at both the
There is also an aggregate or group of connected persons 83) should be within the has been done to increase the exposure. solo and the group level. A list The aggregate amount of
limit: the sum of exposures at most; the sum of such large following limits: flow of credit to infrastructure of exempted exposures is set investments, loans, advances
representing 10% or more of individual exposures should not ─ each individual : HK$1m; sector as part of the overall out in Appendix 1 of MAS or other credit to a private
the regulatory capital is limited exceed 800% of the capital; ─ aggregate of individual strategy of Government Notice 639 and include: sector non-bank person is
to 600% of the regulatory 20% of capital within the group exposures : 5% of the AI’s regarding India’s economic • exposures to central limited to 800 per cent of the
Microprudential Exposure capital. Name concentration to which bank belongs to at capital base; development. (iii) With the governments, central banks, net qualifying capital and
Limits risk includes exposures in most; 25% of capital outside ─ aggregate of all unsecured approval of the Board of and public sector entities, that reserves.
banking and trading book. As of the group to which bank connected exposures directors, in exceptional cases, are AAA-rated;
July 2012 Brazil in compliant belongs to at most. Most of (including exposures to the banks can assume a further • short-term exposures to
with BCP on large exposure Europe is compliant or largely individuals and companies) : exposure of up to 5% of capital banks; and
limits and exposure to related compliant with BCPs on large 10% of the AI’s capital base; funds to a single borrower or a • exposures to counterparties
parties. exposures and exposures to • an AI’s holding of share group of borrowers. arising from the clearing or
related parties as of mid-2012. capital of a company or settlement of transactions,
companies in aggregate should granting intra-day facilities or
not exceed 25% of its capital entering into overnight
base (section 87); and repurchase or reverse
• an AI’s holding of interest in repurchase transactions.
land in or outside Hong Kong
should not exceed 25% of its
capital base (section 88)
Section 90 further limits an AI’s (iv) The exposure for this When calculating the above (2) Equity investment limit Written approval needs to be
aggregate exposures under purpose gas been defined mentioned ratios (N6 and N7) where an exposure to any obtained from the Registrar of
sections 83, 87 and 88 to within comprehensively and includes claims to the borrower (net of equity investment in a single Banks for all exposures to a
80% of its capital base. both on-balance sheet and off- provisions) are risk-weighted company cannot exceed 2% of private sector non-bank
The MA generally applies the balance sheet exposures. The with coefficients used for the capital funds of a bank. persons in excess of 25 per
above-mentioned limits to AIs exposure also includes determining the capital cent of net qualifying capital
on both a solo basis and a investments and derivative adequacy ratio. (3) Limit on holdings of and reserves.
consolidated basis (i.e. products. For derivative These limits are applied both immovable property where In addition to the above
including an AI’s subsidiaries). products, the exposure amount on a solo and on a group-wide exposure to immovable applying to private sector non-
Exemptions are allowed (See is required to be computed as consolidated basis. property in aggregate cannot bank persons exempt
HKMA website) per the “current exposure exceed 20% of the capital exposures include the
method”. funds of a bank. following:
Microprudential Exposure • financial exposure to other AIs (v) Apart from limiting the (a) exposures to, or guaranteed
Limits or overseas incorporated banks exposures to an individual or a (4) Immovable property sector by, the Government of the
(which are not AIs but are Group of borrowers, as limit where property sector Republic of South Africa or the
regarded by the MA as being indicated above, banks have exposure cannot exceed 35% South African Reserve Bank;
adequately supervised); been advised that they may of total eligible assets of a (b) exposures to, or guaranteed
• financial exposure to the also consider fixing internal bank. by, the public sector;
extent to which it is secured by limits for aggregate (c) exposures secured by cash
cash deposit, guarantee or commitments to specific deposited with either the
undertaking, securities or letter sectors, e.g. textiles, jute, tea, reporting bank or banks within
of comfort accepted by the MA; etc., so that the exposures are the same group as the
• financial exposure arising evenly spread over various reporting bank,
from some trade financing sectors.
transactions;
• financial exposure acquired
under underwriting or sub-
• financial exposure acquired These limits could be fixed by Calculation methods of (the above exempt exposures
under underwriting or sub- the banks having regard to the required ratios for banking are, however, still under
underwriting contracts (the performance of different sectors (consolidated) groups including discussion. As of December
exemption will only last for a and the risks perceived. The specific methods for non-credit 2010 South Africa was found to
period not exceeding 7 working limits so fixed may be reviewed institutions – members of be materially non-compliant for
days or such further period periodically and revised, as groups are established exposures to related parties,
approved by the MA); and necessary. (defined) by the Bank of but compliant with respect to
• financial exposure to a Russia. large exposure limits of the
multilateral development bank, Russia as of November 2011 BCPs.
the HKSAR Government or was materially non-compliant
other government acceptable to with regard to exposures to
the MA, or such other related parties as part of the
Microprudential Exposure government-related body or BCPs.
Limits public sector entity in Hong
Kong as specified in the BO
(subject to conditions where
applicable).
Exemption from the limits in
sections 87 and 88 is also
available in some
circumstances, such as where
the share capital or interest in
land is held as collateral for
facilities granted or acquired
(during debt recovery) by an AI.
In the latter case, such share
capital or interest in land
 57

Brazil Canada China European Union Hong Kong India Japan Russia Singapore South Africa Switzerland United Kingdom United States
Responsibility for supervision
of CCPs has now passed to
Bank of England from the now
defunct FSA. Bank of England
requires CCPs to hold cash,
potentially supplemented with
other highly liquid collateral, to
Legislation adopted via reform
meet the minimum regulatory
to the Financial Instruments
Legislation relating to clearing liquidity needs set out in the
Legislation not yet proposed. and Exchange Act (FIEA) in
services and legislation relating revised CPSS/IOSCO
Mandatory clearing applies Legislation is in place in PBOC are taking measures to May 2010. Initially the
Legislation not yet proposed. to tax code create the legal Principles for Financial Market
only to exchange traded provinces where the majority of encourage Shanghai Clearing obligation will apply only to yen
Tightening of OTC EMIR adopted by the Council CCIL to transition soon to basis for promulgation of A working group was set up in Infrastructures and reflected in Legislation adopted (Dodd-
derivatives. A working group OTC derivatives are booked, House to establish detailed Legislative drafting has started, interest rate swaps and CDS. A Public consultation issue on Financial Markets Bill
derivatives regulation and Parliament in July 2012. guaranteed settlement of regulation dealing with central 2011. Draft legislation the EU regulation on OTC Frank in 2010). SEC and
was set up to evaluate which but further work is required to schemes for central clearing of with the aim to have legislation cabinet ordinance to be February 2012. Legislation to submitted to the National
Mandatory clearing of Regulatory technical standards interest rate swaps; no clearing of standardized OTC scheduled for consultation in derivatives, central CFTC are finalizing
OTC derivatives could be harmonize across provinces. OTC derivatives. Interest rate approved by end 2012. implemented by November be introduced by end 2012. Treasury.
standardized trades by CCPs came into force in March 2013. immediate timeframe for derivatives. They have both the second half on 2012. counterparties and trade regulations.
cleared by CCPs and draft new Provincial legislation expected swaps central clearing 2012 includes a requirement
guarantee settlement of CDS. been adopted. Pending repositories (EU/648/2012)
regulation. by end 2012. operation scheme is under for central clearance of “trades
regulations that implement new “EMIR”, which will apply to
discussion. that are significant in volume
requirements. CCPs as they are authorized
and would reduce settlement
under EMIR. The main UK
risk in the domestic markets.”
CCPs have right of re-use to
cash margins provided by
members, giving them access
to an extensive pool of liquidity
that is not available to CCPs
that do not have such rights of
reuse.

Under the Dodd-Frank , bank

The Financial Services Act holding companies with total
adopted (2010) requires banks consolidated assets of $50
While no Canadian banks have
High-level Expert Group on to produce RRPs. All banks billion or more and non-bank
been identified as G-SIFIs, draft D-SIBs required to develop
possible reforms to the Recovery plans to be Plans to produce RRP for D- and systemic investment firms financial companies designated
Recovery and resolution recovery and resolution plans recovery and resolution plans. SIBs are required to produce
N.A. structure of the EU banking N.A. N.A. N.A. developed for D-SIBs H2 2012, N.A. SIBs to be put in place during are required to complete RRPs by the Financial Stability
plans are being developed for largest An RRP for Bank of China (G- RRPs.
sector set up on February 22, and resolution plans H1 2013. 2012. by June 2012. Most UK banks Oversight Council for
banks, due to be completed in SIFI) is being developed.
2012. have completed first drafts of supervision by the Fed must
2012.
their RRPs which will be submit resolution plans
continuously updated. annually to the FDIC and the
Federal Reserve.

Vickers commission structural

changes in UK banking. White
Paper to implement Vickers
Proposals in Europe are mainly The extra capital requirements published in June 2012. Latest
Structural changes to banks in the discussion stage of Swiss G-SIFIs (the "Swiss version incorporating the Volcker rule to limit proprietary
and limitations on bank N.A. N.A. N.A. especially with regard to the N.A. N.A. N.A. N.A. N.A. N.A. finish") which go beyond Basel Vicker's proposals are trading in banks and
activities Liikanen, French and German III (and need to be in place by contained in the Banking investment in private equity.
proposals. 2019). Reform Bill due to become law
in 2014.The Bill also includes
provisions to enforce full
separation by the PRA.

The EC issued a draft directive

June 2012 which would closely A temporary resolution regime
align national resolution was introduced in 2008, and
regimes in the EU with the KA. Resolution regime was replaced with a permanent
The KA are being reviewed to The final resolution directive is enhanced in 2007, and The resolution regime was special resolution regime in
Review of legislative and Review of legislative and The resolution regime was
Preparing draft legislation to determine legislative or Plans to introduce deposit planned to be implemented by extended to insurers in 2011. strengthened prior to and since 2009. This has many of the
Changes in crisis resolution regulatory changes required to regulatory changes required to extensively revised under Dodd
address gaps in powers v-a-v regulatory changes which may insurance are being 2014. The draft directive on N.A. N.A. Plans to further enhance N.A. the crisis (Banking Act was powers contained in the KA
regimes implement outstanding aspects implement outstanding aspects Frank, including by extending
the FSB's Key Attributes (KA). be required to comply with the accelerated. Deposit Guarantee Schemes is regime to address some amended in Sept. 2011) and and applies not only to banks.
of the KA is underway. of the KA is underway. to non-banks and BHC's.
KA. still under discussion but is outstanding aspects of KA over has most of the tools in the KA . UK proposals will also be
hoped to be agreed the next two years. updated in line with the EU
simulataneously with the bank Recovery and Resolution
Recovery and Resolution Directive.
Directive.

Sources: Basel Committee on Banking Supervision, European Union, Financial Stability Board, G20, Independent Commission on Banking, International Association of Insurance Supervisors, International Organization of Securities Commissions, and PriceWaterhouse Coopers.

1
This table relies on the sources above and reflects the most recent information available; the most recent information may be subject to delays in publication. Entries with N.A. indicate the information is either non-available or non-applicable.

2
Basel III liquidity framework is not finalized in detail. The entries, therefore, seek to reflect the existence of any quantitative liquidity requirements in the selected countries, and implementation of the 2008 “Principles for Sound Liquidity Risk Management and Supervision."
 56

Brazil Canada China European Union Hong Kong India Japan Russia Singapore South Africa Switzerland United Kingdom United States
AI. In the latter case, such
share capital or interest in land
acquired should be disposed of
within 18 months (or such
further period approved by the
MA) after the acquisition.
Prudential limits
Apart from the statutory limits,
the HKMA may set prudential
limits on an AI’s exposures to
particular counterparties,
groups of counterparty,
Microprudential Exposure economic or geographical
Limits sectors if the AI is, in the
HKMA’s opinion, exposed to a
significant level of
concentration risk that may
affect its financial stability.
These limits will be determined
on a case-by-case basis,
having regard to the AI’s
individual circumstances.
In addition, AIs are expected to
set an internal “clustering” limit
to control the aggregate of their
non-exempt large exposures
(i e exposures equal to or
equal to or exceeding 10% of
an AI’s capital base). Such
limit should be approved by the
Board of Directors and agreed
with the HKMA. An industry
benchmark of 200% of capital
base is provided to AIs as
reference for setting their
clustering limit.
The above provisions are
contained in the HKMA’s
supervisory guideline CR-G-8
Microprudential Exposure “Large Exposures and Risk
Limits Concentrations.”

Legislation adopted September

2011, draft regulation
Basel III regulation finalized and
published December 2011. On
released in June 2012, will be
Countries will not be limited in top of the CET1, SIBs must G-SIBs not yet covered as
implemented from Jan 1 2013
their capacity to require more have a capital conservation Basel has not finalized its
to 2018. Domestic systemically Draft legislation requiring
capital than the Basel III buffer of 8.5% (5.5% framework. There are
important banks (D-SIBs) above Basel III capital,
minimum especially with regard conservation buffer and references to systemic
G-SIFI buffer N.A. N.A. additional capital requirements N.A. N.A. N.A. N.A. N.A. N.A. composed of common equity
to the systemic buffer under additional 3% of “recovery institutions under the rule
are 1%. If the D- SIB is a G- and will be brought in line with
published CRDIV. The CoCos”) and a systemic making under Dodd Frank
SIB, the additional capital published CRDIV.
systemic risk buffers can apply surcharge of up to 6% (s165 and 166) as issued in
requirement for this bank
to all banks in the system. (depending on market share December 2011
cannot be lower than the Basel
and balance sheet size),
minimum level.
bringing total capital
requirements to 19%.

Liquidity requirements are

currently used for supervisory Implemented 2010. UK rules
Not implemented. CRDIV will
Quantitative liquidity monitoring only. They will be Quantitative metric for will be further amended in light
2 Draft for consultation. consider final BCBS proposals N.A. N.A. Basel III schedule. Since 2004, reviewed 2011. Not required. Basel III timetable. For G-SIBs only. N.A.
requirements formally introduced in national monitoring. of BCBS final proposals and
on NSFR and liquidity rules.
legislation according to the their incoporation into CRDIV.
Basel III schedule.