Current State of Affairs

Systemic (or spillover) risk arises when the failure or weakness of one or more 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 direct and indirect mechanisms (Table 9.1).¹ 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, fire sales, and informational contagion. These risk factors can be as important as direct exposures.²

Table 9.1

Examples of Direct and Indirect Financial Interconnectedness

Source: Depository Trust and Clearing Corporation (2015).

Table 9.1

Examples of Direct and Indirect Financial Interconnectedness

Examples of Direct Financial Interconnectedness
Credit Exposures between Banks	Financial Market Infrastructure Relationships	Vendors and Other Third-Party Relationships	Other Financial Service Dependencies
Lending and borrowing	Payment	Service relationships	Hedging services
Buying and selling securities	Clearing	IT security protocols	Underwriting services
Derivatives trading	Settlement		Custodial services
Securities financing			Guarantee services
Interbank activity
Examples of Indirect Financial Interconnectedness
Exposure to Common Assets	Mark-to-Market Losses	Margin Calls and Haircuts	Shadow Banking
Market shocks	Fire sales	Holdings of securities	Money market funds
Market volatility	Collateral losses	Internal and external ratings	Mutual funds
Demand and supply dislocations	Liquidity pressures	Collateral framework	Pension funds
Pricing shocks	Funding pressures		Hedge funds
			Activities outside the banking system
Information Spillovers
Crisis of confidence
Negative signals about entities

Source: Depository Trust and Clearing Corporation (2015).

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Table 9.1

Examples of Direct and Indirect Financial Interconnectedness

Examples of Direct Financial Interconnectedness
Credit Exposures between Banks	Financial Market Infrastructure Relationships	Vendors and Other Third-Party Relationships	Other Financial Service Dependencies
Lending and borrowing	Payment	Service relationships	Hedging services
Buying and selling securities	Clearing	IT security protocols	Underwriting services
Derivatives trading	Settlement		Custodial services
Securities financing			Guarantee services
Interbank activity
Examples of Indirect Financial Interconnectedness
Exposure to Common Assets	Mark-to-Market Losses	Margin Calls and Haircuts	Shadow Banking
Market shocks	Fire sales	Holdings of securities	Money market funds
Market volatility	Collateral losses	Internal and external ratings	Mutual funds
Demand and supply dislocations	Liquidity pressures	Collateral framework	Pension funds
Pricing shocks	Funding pressures		Hedge funds
			Activities outside the banking system
Information Spillovers
Crisis of confidence
Negative signals about entities

Source: Depository Trust and Clearing Corporation (2015).

Contagion spillover risks in the LA-7 countries are currently at a low level. Although growing cross-border activity and financial integration increase the potential for contagion spillovers in a crisis, some quantitative analysis suggests that spillover risks among Latin American financial systems are currently contained (see the next section). The conglomerates operating in LA-7 jurisdictions and Latin America in general can act as pathways for increased regional banking and financial sector connectivity through their network of subsidiaries and intergroup and other counterparty exposures. Country authorities have begun to focus on these potential risks, in some cases limiting cross-border activities by imposing formal or informal restrictions. The current low levels of spillover risk leave room for further financial integration while regional supervisory and regulatory oversight is strengthened and any country-specific weaknesses in supervisory frameworks are addressed to avoid regulatory arbitrage. Contagion risks will naturally rise with greater integration or under adverse conditions. This potential requires that cross-border activity and exposures be monitored in a regionally coordinated manner.

Quantifying Market-Implied Spillover Risks

Market-based spillover analysis suggests that contagion risks among large financial institutions in Latin America are contained. This quantitative analysis looks at the market-based interlinkages of large financial institutions in six Latin American countries. In particular, the analysis quantifies potential spillovers across institutions through financial markets using data on traded securities. Overall, the relatively limited market-implied spillovers are in line with the current relatively low levels of cross-border balance sheet exposures within the region.

Financial linkages among financial or banking institutions can be broadly split into two categories: direct and indirect. Direct financial linkages denote explicit balance sheet positions from one financial institution onto another; essentially, assets or liabilities of financial institutions vis-à-vis each other. Indirect linkages arise when there are no explicit direct linkages among financial institutions, but their market indicators (for instance, stock prices or credit default swap spreads) tend to exhibit some degree of comovement or synchronicity. These indirect linkages could be the consequence of having similar business models or common exposures to related economic sectors, or simply of being perceived by the markets as being vulnerable to the same type of shocks (for example, a change in legislation affecting most banks in one country).

The aim of the market-implied interlinkage analysis is to quantify both direct and indirect linkages among financial institutions in Latin America. The sample includes the largest listed banks from Argentina, Brazil, Chile, Colombia, Mexico, and Peru; it covers the period 2005–16 and relies on publicly available daily time series of financial variables (Table 9.2).

Table 9.2

Latin American Banks Included in the Spillover Analysis

Source: IMF staff compilation.

Table 9.2

Latin American Banks Included in the Spillover Analysis

Bank Acronym	Bank Name	Country
BGALI	Banco de Galicia	Argentina
BVAAR	BBVA-Argentina	Argentina
BMACR	Banco Marco	Argentina
BDOBR	Banco do Brasil (BB)	Brazil
ITAUB	Itaú	Brazil
SANBR	Santander-Brazil	Brazil
SANCL	Santander-Chile	Chile
BDCHL	Banco de Chile	Chile
CORPB	Corpbanca	Chile
BCOLO	Bancolombia	Colombia
BDBOG	Banco de Bogota	Colombia
BANOR	Banorte	Mexico
INBUR	Inbursa, grupo financiero	Mexico
SCOPE	Scotiabank-Peru	Peru
BCREP	Banco de Credito del Peru	Peru

Source: IMF staff compilation.

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Table 9.2

Latin American Banks Included in the Spillover Analysis

Bank Acronym	Bank Name	Country
BGALI	Banco de Galicia	Argentina
BVAAR	BBVA-Argentina	Argentina
BMACR	Banco Marco	Argentina
BDOBR	Banco do Brasil (BB)	Brazil
ITAUB	Itaú	Brazil
SANBR	Santander-Brazil	Brazil
SANCL	Santander-Chile	Chile
BDCHL	Banco de Chile	Chile
CORPB	Corpbanca	Chile
BCOLO	Bancolombia	Colombia
BDBOG	Banco de Bogota	Colombia
BANOR	Banorte	Mexico
INBUR	Inbursa, grupo financiero	Mexico
SCOPE	Scotiabank-Peru	Peru
BCREP	Banco de Credito del Peru	Peru

Source: IMF staff compilation.

The methodology relies on the computation of empirical distributions characterizing the joint and conditional probabilities of distress among financial institutions. This is largely based on Segoviano’s (2006) Consistent Information Multivariate Density Optimizing Methodology.³ In particular, two synthetic measures are used:

1. The vulnerability index (VI), which measures the susceptibility of a particular institution to fall in distress given distress in other financial institutions (loosely speaking, it measures an institution’s vulnerability to contagion from other financial institutions). Algebraically, the VI of a given financial institution “i” is given by:

   $VI(A_i)={\displaystyle {\sum }_{j\ne i}^N{\text{α}}_{j}P(}{A}_i|A_j)$

   where the weight ${\text{α}}_j=\frac{1}{N}P(A_j)$, N denotes the number of financial institutions in the sample, and P(A_j) is the probability that institution j falls in distress.⁴

2. The contribution to systemic risk, which measures the contribution of a given institution to changes in the vulnerability to contagion of other institutions (that is, its role as a source of contagion). In other words, it is the percent share that a given financial institution represents in the changes in the vulnerability index of all other institutions in the sample.

To analyze the dynamics of these two market-based measures, both are computed for a sample of 15 banks from six Latin American countries.⁵ Figure 9.1 shows the evolution of the vulnerability index for the 15 banks (panels 1, 2, and 3). The figure also shows the percentage contribution of each of these banks to the rest of the system’s change in vulnerability during three selected periods (panel 4). Argentinean banks and, to a lesser extent, Banorte (Mexico) appear to have been the most vulnerable to contagion during the global financial crisis (Period I). However, the relatively high market-implied interlinkages during that period appear to be important mainly among themselves (Table 9.3).

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Market-Based Interlinkages in Selected Latin American Banks

Sources: Moody’s KMV; Thompson Reuters Datastream; and IMF staff calculations.Note: See Table 9.2 for bank abbreviations used in this figure.

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Table 9.3

Contribution to Systemic Risk during the Global Financial Crisis

Sources: Moody’s KMV; Thompson Reuters Datastream; and IMF staff calculations. Note: Data are for the period October 31, 2007, to March 2, 2009. See Table 9.2 for bank abbreviations used in this table.

Table 9.3

Contribution to Systemic Risk during the Global Financial Crisis

	BGALI	BVAAR	BMACR	BDOBR	ITAUB	SANBR	SANCL	BDCHL	CORPB	BCOLO	BDBOG	BANOR	INBUR	SCOPE	BCREP
BGALI		3.9	3.3	0.4	0.7	1.2	0.4	0.2	0.1	0.5	0.2	1.9	0.2	1.5	0.2
BVAAR	4.2		3.3	0.4	0.7	1.1	0.4	0.2	0.1	0.6	0.2	1.9	0.2	1.5	0.2
BMACR	4.3	4.0		0.3	0.5	0.9	0.3	0.2	0.1	0.5	0.2	1.8	0.1	1.5	0.1
BDOBR	2.0	1.6	1.1		2.6	1.9	0.4	0.1	0.8	0.5	0.3	1.0	0.5	1.0	1.1
ITAUB	2.3	2.0	1.3	1.9		2.1	0.5	0.2	0.5	0.3	0.2	1.5	0.5	1.1	0.7
SANBR	3.0	2.5	1.8	1.0	1.5		0.4	0.2	0.3	0.4	0.1	1.5	0.3	1.4	0.3
SANCL	2.6	2.4	1.7	0.7	1.0	1.3		0.4	0.4	0.5	0.0	1.9	0.2	1.7	0.2
BDCHL	2.9	2.7	2.3	0.3	0.6	0.9	0.7		0.1	0.3	0.0	2.6	0.3	1.2	0.0
CORPB	1.8	1.4	0.9	2.1	1.8	1.7	0.7	0.1		0.5	0.2	0.6	0.5	1.5	1.2
BCOLO	3.2	3.0	2.3	0.6	0.6	1.0	0.4	0.2	0.3		0.1	1.3	0.1	1.8	0.1
BDBOG	3.7	3.3	1.9	1.2	0.9	0.9	0.0	−0.1	0.2	0.4		1.4	0.0	1.2	−0.1
BANOR	3.6	3.2	2.6	0.4	0.8	1.2	0.5	0.4	0.1	0.4	0.2		0.3	1.2	0.1
INBUR	2.4	1.9	1.1	1.6	2.0	1.6	0.3	0.3	0.5	0.1	0.0	2.0		0.9	0.4
SCOPE	3.3	3.0	2.6	0.5	0.7	1.3	0.5	0.2	0.3	0.7	0.2	1.4	0.1		0.2
BCREP	2.0	1.7	0.9	2.8	2.3	1.6	0.3	0.0	1.1	0.2	−0.1	0.8	0.3	1.1
STD	20.2	18.4	14.8	3.8	5.4	7.4	2.4	1.4	1.4	2.9	1.0	9.9	1.3	8.3	1.5

Sources: Moody’s KMV; Thompson Reuters Datastream; and IMF staff calculations. Note: Data are for the period October 31, 2007, to March 2, 2009. See Table 9.2 for bank abbreviations used in this table.

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Table 9.3

Contribution to Systemic Risk during the Global Financial Crisis

	BGALI	BVAAR	BMACR	BDOBR	ITAUB	SANBR	SANCL	BDCHL	CORPB	BCOLO	BDBOG	BANOR	INBUR	SCOPE	BCREP
BGALI		3.9	3.3	0.4	0.7	1.2	0.4	0.2	0.1	0.5	0.2	1.9	0.2	1.5	0.2
BVAAR	4.2		3.3	0.4	0.7	1.1	0.4	0.2	0.1	0.6	0.2	1.9	0.2	1.5	0.2
BMACR	4.3	4.0		0.3	0.5	0.9	0.3	0.2	0.1	0.5	0.2	1.8	0.1	1.5	0.1
BDOBR	2.0	1.6	1.1		2.6	1.9	0.4	0.1	0.8	0.5	0.3	1.0	0.5	1.0	1.1
ITAUB	2.3	2.0	1.3	1.9		2.1	0.5	0.2	0.5	0.3	0.2	1.5	0.5	1.1	0.7
SANBR	3.0	2.5	1.8	1.0	1.5		0.4	0.2	0.3	0.4	0.1	1.5	0.3	1.4	0.3
SANCL	2.6	2.4	1.7	0.7	1.0	1.3		0.4	0.4	0.5	0.0	1.9	0.2	1.7	0.2
BDCHL	2.9	2.7	2.3	0.3	0.6	0.9	0.7		0.1	0.3	0.0	2.6	0.3	1.2	0.0
CORPB	1.8	1.4	0.9	2.1	1.8	1.7	0.7	0.1		0.5	0.2	0.6	0.5	1.5	1.2
BCOLO	3.2	3.0	2.3	0.6	0.6	1.0	0.4	0.2	0.3		0.1	1.3	0.1	1.8	0.1
BDBOG	3.7	3.3	1.9	1.2	0.9	0.9	0.0	−0.1	0.2	0.4		1.4	0.0	1.2	−0.1
BANOR	3.6	3.2	2.6	0.4	0.8	1.2	0.5	0.4	0.1	0.4	0.2		0.3	1.2	0.1
INBUR	2.4	1.9	1.1	1.6	2.0	1.6	0.3	0.3	0.5	0.1	0.0	2.0		0.9	0.4
SCOPE	3.3	3.0	2.6	0.5	0.7	1.3	0.5	0.2	0.3	0.7	0.2	1.4	0.1		0.2
BCREP	2.0	1.7	0.9	2.8	2.3	1.6	0.3	0.0	1.1	0.2	−0.1	0.8	0.3	1.1
STD	20.2	18.4	14.8	3.8	5.4	7.4	2.4	1.4	1.4	2.9	1.0	9.9	1.3	8.3	1.5

Sources: Moody’s KMV; Thompson Reuters Datastream; and IMF staff calculations. Note: Data are for the period October 31, 2007, to March 2, 2009. See Table 9.2 for bank abbreviations used in this table.

In the most recent period (Period III), Brazilian banks appear to be important drivers of the market-implied contagion (Figure 9.1, panel 4). However, in terms of absolute magnitude, the actual spillovers and VI outside of Brazil appear to be rather small compared with the VI levels observed during the global financial crisis. In other words, large domestic public banks in Brazil might be very important for the domestic market in Brazil, but they are not so important for the rest of the region. These market-based measures seem to be in line with the limited actual cross-border balance sheet exposures of the banking sectors in Latin America.

Network Analysis and Conglomerate Connectivity

Financial integration brings the prospect of increased financial network connectivity that is already established across the LA-7 and the Central America region through the growth of financial and mixed conglomerates. Banks, particularly from Brazil and Colombia, are becoming regional institutions, with the whole area as their home base. Some of this expansion was linked to the exit of some global banks from the region. Cross-border participation in stock exchanges is also apparent, with the Brazilian stock exchange purchasing 8 percent of the Chilean exchange. Nonfinancial corporations—particularly retail institutions from Chile and conglomerates from Brazil and Mexico—are expanding across the region. Since 2011, the presidents of Chile, Colombia, Mexico, and Peru have been meeting regularly to advance the Pacific Alliance (PA; see Chapter 8). Mercosur has brought six Latin American economies together with the objective of integration; although the Mercosur process has recently lost momentum, conditions may be favorable for a revitalization of the financial integration process. Regional financial integration moves have helped many systemic banks—as part of even more systemic conglomerates—create increased networks through headquarters–subsidiary linkages as well as regional bank linkages to U.S. global banks.

Network Structures: Interconnectedness and Contagion Risks

Analysis of financial networks in Latin America can be a useful tool to capture interconnectedness and contagion (spillover) risks from financial integration. The expansion of systemic banks and financial and mixed conglomerates across Latin and Central America has led to increased direct and indirect financial interconnectedness, which could add to the propagation of shocks through interconnections in the LA-7 financial network. Risks within the LA-7 financial network also reflect the complex organizational structures and the risks inherent in the business models of the financial and mixed conglomerates in the network. A detailed mapping, monitoring, and analysis of the LA-7 financial network would allow supervisors and risk managers to determine: (1) at what point these financial networks become fragile; (2) how that fragility propagates through the network—through specific connections and through systemic conglomerates and other connected entities; (3) what type of financial network structures (topologies) are more fragile than others; and (4) how systemic risks in the network vary over time as a result of interconnectedness and contagion risks from greater regional integration in the LA-7. Network analysis using mathematical graph theoretical frameworks on data from various direct and indirect mechanisms of interconnections (see Table 9.1) can be an extremely useful complement to the analysis of systemic risks from market-based distress dependence models discussed earlier. Specifically, mapping, monitoring, and analysis of the LA-7 financial network provides a more detailed view of systemic risks from interconnectedness and contagion than the view from market-based models on their own.⁶

Financial and mixed conglomerate networks across the LA-7 countries are multilayered and complex, both domestically and across borders. Conglomerate financial networks in the LA-7 countries involve interconnections between systemic and nonsystemic financial and nonfinancial entities. Some of these interconnections are intraconglomerate—between parents (holding companies), subsidiaries, or branches—across multiple types of financial and nonfinancial institutions (multilayered). These networks not only extend across types of institutions but can also extend geographically on a cross-border basis, linked together through a multitude of direct and indirect connections (see Table 9.1). Using simple constructed examples, the authors show that network complexity can extend across multiple dimensions, moving from simpler domestic financial and mixed conglomerate networks to more complex multilayered cross-border networks (Figures 9.2 and 9.3). Domestic conglomerate networks (represented by the gray circle in Figure 9.2) are complex and challenging to supervise, but networks become much more complex and difficult to supervise when interconnections occur across borders (colored circles). This implies that systemic risk would be better estimated by mapping complex financial and mixed conglomerate networks across the LA-7 than by mapping simpler networks. As depicted in Figure 9.3, complex conglomerate networks have cross-border and multilayered dimensions that evolve dynamically over time. Thus, mapping, monitoring, and analysis of real-world complex financial and mixed conglomerate networks across LA-7 countries raises important supervisory, data, and coordination challenges for authorities, central banks, and supervisory agencies in the region.

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Simplified Examples of Domestic and Cross-border Conglomerate Networks

Source: IMF staff.

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Complex, Multilayered Cross-border Networks

Source: IMF staff.

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Some Recent Network Approaches for Latin America

Systemic risk in the Mexican banking system between 2007 and 2013 is underestimated by 90 percent when the focus is on a single exposure network rather than multilayered exposure networks. Recent work by Poledna and others (2015) for the Mexican banking system has shown that analyzing systemic risk contributions from four exposure layers of the interbank network (derivatives, securities cross-holdings, foreign exchange, and interbank deposits and loans) underestimates systemic risk by 90 percent if only a single interbank deposits and loans network is considered. Looking at financial market measures and market-based models using the VIX (the Chicago Board Options Exchange Volatility Index), credit default swap (CDS) spreads, or other market prices might also underestimate systemic risk ex ante.

Colombian multilayered financial institutions and financial market infrastructure networks (FMIs) are better able to capture systemic risks and insulate against them. Work by León, Berndsen, and Renneboog (2014) showed that Colombian transactions and exposures among financial institutions that are registered, settled, cleared, and safeguarded by FMIs can be expressed as multi-layered networks. The analysis makes it clear that systemic risks would be much higher than those of each network in isolation. This result is due to consideration of cross-system risks. The study also suggests that integrating Colombian financial institutions’ networks of transactions and exposures with FMI networks adds resilience to the multilayered network, as FMIs are able to isolate feedback and cascades. However, this result holds only as long as the FMI itself is functioning well and does not fail. The evidence presented makes clear the advantages of mapping, monitoring, and analyzing the real-world multilayered financial networks.

Network analysis has been applied to other regions of the Western Hemisphere outside of LA7 countries. For instance, network analysis of the Caribbean region, in the context of Caribbean Regional Financial Project (CRFP), showed that the financial system of the Caribbean is highly interconnected. However, the system was found to be resilient to a range of moderate to severe propagating shocks (Annex 9.1).

Regulatory Oversight

A key precondition for substantial cross-border financial integration is having a robust and forward-looking best practice regulatory and supervisory framework in place. The global financial crisis highlighted the crucial need to enhance both domestic and international regulatory standards and to strengthen prudential requirements and develop macroprudential tools to reduce risks in the financial system, including cross-border risks. In Latin America, financial activity risks can be mitigated by having a suitable entry, operating, and resolution framework for cross-border institutions;⁷ sound prudential standards and national regulatory frameworks that reflect appropriate timelines and banking system complexity (Basel III); a complete picture of the financial institution (needed for cross-border consolidated and conglomerate supervision); and macroprudential policies that protect the national and regional financial systems from systemic macro-financial stability risks.

Cross-Border Establishments

Legal and regulatory frameworks for subsidiaries and branches of foreign firms have been enhanced but could be further strengthened. The legal frameworks of the surveyed countries generally require that branches and subsidiaries follow all regulations and practices of the host countries. All countries require endowment capital for branches, and most authorities have the power to restrict subsidiaries’ issuance of dividends and capital, including cross-border. In addition, the pricing of centralized functions such as IT and treasury is subject to oversight, thereby avoiding circumvention of the restrictions on dividend and capital transfers. However, there is room for improvement. Local asset maintenance requirements for branches and limits on intragroup exposures for subsidiaries could usefully be reviewed. In the context of a broader update of bank resolution frameworks, powers to deal with cross-border coordination should be strengthened, including by removing the automaticity and discriminatory features of ring-fencing mechanisms.

Basel III: Capital, Liquidity, and Leverage Requirements

The LA-7 countries have made progress in adopting the Basel standards (Figures 9.4, 9.5, and 9.6). The Basel Committee’s Eighth Progress Report on the adoption of the Basel regulatory agenda shows rapid recent progress in many emerging markets. Brazil and Mexico are fully compliant with the Basel III capital standard, the liquidity standard, and the leverage ratio. They also are compliant with regard to Basel II and Basel 2.5. Other LA-7 countries are implementing at a pace they consider in line with the complexity and development of their banking systems. With financial integration, many large banking groups and conglomerates face the prospect of varying regulatory capital regimes across the LA-7 countries in which they operate. This creates the potential for adverse incentives to grow in LA-7 countries where capital standards are weaker. A move to the Basel III capital definition across the LA-7 would remove the potential for regulatory arbitrage and—by coalescing on a consistent, high-quality capital measure—would enhance macro-financial stability by increasing loss absorbency against potential spillover risks (see Annex 9.2).

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Progress in Implementing Basel II

Sources: Data for Brazil and Mexico are from the Basel Committee on Banking Supervision (2016); for other countries, from the Bank for International Settlements (2015).Note: AIRB = advanced internal ratings-based approach; AMA = advanced measurement approaches; BIA = basic indicator approach; FIRB = foundation internal ratings-based approach; P2 = Pillar 2; P3 = Pillar 3; SA = standardized approach; TSA = alternative standardized approach.

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Progress in Implementing Basel 2.5

Sources: Data for Brazil and Mexico are from the Basel Committee on Banking Supervision (2016); for other countries, from the Bank for International Settlements (2015).Note: Mkt risk = revisions to the Basel II market risk framework; Rev P1 = revisions to Pillar 1; Rev P3 = revisions to Pillar 3; Suppl P2 = supplemental Pillar 2 guidance.

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Progress in Implementing Basel III

Sources: Data for Brazil and Mexico are from the Basel Committee on Banking Supervision (2016); for other countries, from the Bank for International Settlements (2015).Note: C-Cycl = countercyclical buffer; Conserv = conservation buffer; Def cap = definition of capital; D-SIBs = domestic systemically important banks; G-SIBs = global systemically important banks; LCR = liquidity coverage ratio; Liq = liquidity; LR = leverage ratio; Risk cov = risk coverage.

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Importance and Benefits of Consolidated and Conglomerate Supervision

Forward-looking domestic and cross-border consolidated and conglomerate risk-based supervision is a key supervisory approach to address the complexity and potential underestimation of systemic risks inherent in conglomerate networks in the Latin and Central American region. Many supervisory agencies in the LA-7 countries have moved to a forward-looking risk-based regulatory and supervisory framework that uses supervisory tools such as macroeconomic, multiyear credit, market, and liquidity stress tests to flag solvency (capital) and liquidity vulnerabilities of financial institutions. However, this approach does not fully account for systemic risks, and even the use of price-based models would underestimate systemic risks arising from financial and nonfinancial institutions’ interconnectedness and potential contagion risks. Adopting a domestic and cross-border consolidated and conglomerate supervisory approach would help prioritize the mapping, monitoring, and analysis of financial and mixed conglomerate networks, including through network stress tests as well as onsite and offsite work. This approach would help: (1) fully capture systemic risks, (2) identify vulnerable financial and nonfinancial institutions, (3) identify fragile transactions and exposures, and (4) flag key pathways for contagion. Knowledge of institution and system fragility would enable countries to tailor prudential and macroprudential tools to mitigate risks and ensure macro-financial stability.

The evidence from recent financial stability assessments conducted by the IMF and World Bank under the Financial Sector Assessment Program (FSAP) is that the countries in the region have a ways to go in improving their supervisory frameworks in terms of consolidated and conglomerate supervision. Legal restrictions in some countries prevent full achievement of best practices, in particular in the handling of the nonfinancial components of conglomerates. Although subsidiarization, and regulatory and resolution ring-fencing, can dampen cross-border spillovers, cross-border safety requires that the institution be supervised on a consolidated basis. International best practices for consolidated supervision call for establishing robust supervisory regimes, cross-border supervisory processes, joint monitoring programs, and coordinated corrective/supervisory actions among all parts of a cross-border financial institution or conglomerate.

The structure of Latin American financial institutions makes consolidated supervision particularly important because many are parts of conglomerates. In a number of cases the nonfinancial parts of these conglomerates have already expanded cross-border to a much greater extent than the banks. Even where there are no direct financial flows between the bank and nonbank parts of a conglomerate, problems in the nonbank part can have major knock-on effects on the bank. For example, problems in the retail arm of the group with the first Chilean bank to move cross-border led to financial pressures and ultimate sale to another regional bank, although the Chilean bank itself had faced no difficulties and was making substantial profits.

There is increasing awareness of the importance of consolidated supervision. Uruguayan regulators declined to license a regional bank that was seeking to acquire a bank being sold in Uruguay on the grounds that the regional bank’s supervisor was not conducting consolidated supervision.

Conglomerate supervision complements supervision of individual sectors by adding a layer to the solo and consolidated sectoral supervision. Individual supervision faces limitations in dealing with double gearing of capital, conflicts of interest, risks of contagion, concentration, and other specific group risks that may hamper financial stability. Conglomerate supervision should detect and monitor these risks while avoiding unnecessary duplication with sectoral prudential standards.

Internationally agreed upon documents provide national authorities with a set of principles that support consistent and effective supervision of financial conglomerates. The main references are the Basel Committee on Banking Supervision’s “Core Principles for Effective Banking Supervision” and the Joint Forum’s “Principles for Supervision of Financial Conglomerates.”⁸ Focusing on both the cross-border and cross-sector dimensions of the process, these principles set expectations for supervisory powers and responsibilities, corporate governance, prudential requirements, and risk management. They focus on closing regulatory gaps, eliminating supervisory blind spots, and ensuring effective supervision of risks arising from unregulated financial activities and entities. Colombia is currently seeking parliamentary approval for a bill to provide supervisors with powers over the holding companies of financial conglomerates. However, the law would provide only limited reach into mixed conglomerates; much of their activity would remain outside the scope of the financial supervisory and regulatory perimeter.

The Principles are flexible and take a nonprescriptive approach to the supervision of financial conglomerates in order to cover a wide range of structures. They emphasize the importance of recognizing structural complexity and the potential risks it poses. This includes risks arising from all entities—unregulated or regulated—that affect the financial conglomerate’s overall risk profile. The flexibility of this framework is intended to enable policymakers and supervisors to appropriately regulate and supervise financial conglomerates while limiting the scope for regulatory arbitrage.

Beyond consolidated supervision, there is also a need for increased cooperation and data sharing among supervisors to tackle conglomerate and cross-border risks more broadly. Supervisory colleges have been established for major banks in the region. Colombia has gone further with regard to Central America, where its banks have established significant positions in most countries. These countries have established a multilateral memorandum of understanding, a regional council of finance ministers, a regional monetary council, and a joint council of supervisors. The analytical work on cross-border multilevel financial networks highlights the need for more granular direct and indirect data for both on- and off-balance-sheet items (see Table 9.1). However, important data confidentiality concerns must be overcome on a cross-border basis, new analytical tools are needed to handle very large data sets, and investment is required in staff who can work with financial risk modeling tools.

Prudential and Macroprudential Measures

Prudential tools allied with forward-looking, risk-based supervision can address systemic risk arising from financial and mixed conglomerate networks across Latin America. The tools described here are designed to address interconnectedness and contagion (spillover) risks.⁹

• Microprudential exposure limits. Microprudential exposure limits are normally designed as non-risk-sensitive backstops to limit concentration from a microprudential perspective, but they are also relevant from a macroprudential point of view.

• Capital charges, particularly for systemically important financial institutions (SIFIs). Capital requirements in Basel I and II did not directly account for interconnectedness (concentration) and contagion risks, but Basel III minimum capital rules were formulated with explicit consideration for concentration and systemic risk.

• Liquidity regulation and limits on liquidity mismatches. The lack of liquidity requirements encouraged reliance on central bank and wholesale funding in the global financial crisis, increasing interconnectedness and contagion risks among financial institutions. Basel III liquidity requirements (the Liquidity Coverage Ratio and Net Stable Funding Ratio) can mitigate systemic risks by limiting liquidity contagion and reducing funding and counterparty interconnectedness.

• Clearing of over-the-counter derivatives on a central counterparty (CCP). CCPs increase transparency regarding the amount and distribution of risk exposure, helping clarify interconnectedness risks. They also help mitigate contagion by mutualizing losses among all clearing members.

• Structural limits on activities. Direct restrictions on the scope of business of global SIFIs, conglomerates, or large and internationally active banks can help reduce the complexity of business models, which directly reduces interconnectedness and contagion risks.

• Resolution frameworks and insurance. Effective cross-border resolution frameworks can help insulate institutions from each other with regard to failure, which reduces the impact from interconnectedness and contagion risks.

Arregui and others (2013) note that prudential measures can interact bilaterally, either complementing each other in reducing systemic risks or conflicting with one another. Depending on the degree of complementarity or conflict, we can make a qualitative assessment of how each prudential tool is likely to address interconnectedness (concentration) and contagion risks and how difficult it can be to implement from a regulatory or bank perspective (Table 9.4). Prudential tools may be less effective for mixed conglomerates than for financial conglomerates, because they may apply only to supervised and regulated entities within the mixed conglomerate structure.

Table 9.4

Interaction of Prudential Tools

Source: IMF staff compilation. Note: CCP = central counterparty; LCR = liquidity coverage ratio; NFSR = net funding stable ratio; SIFIs = systemically important financial institutions.

¹Fully complementary: tool mutually reinforces 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: tool has a conflicting but not major impact on the intent of another tool (light red); not related or not contradictory (white).

²Arrows indicate an increase (↑) or decrease (↓) in resulting impact.

³Refers to the Volker, Vickers, and Liikanen structural measures—see Pazarbasioglu and others (2013).

Table 9.4

Interaction of Prudential Tools

Tools1,2		Microprudential Exposure Limits		Capital Buffers (SIFIs)	Limits on Liquidity Mismatches (LCR, NFSR)		Limits on Activities3	Resolution Frameworks		CCP Clearing 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
Complexity of implementation	Regulators	LOW		MEDIUM	HIGH		HIGH	HIGH		MEDIUM
	Banks	MEDIUM		LOW	HIGH		HIGH	HIGH		LOW

Source: IMF staff compilation. Note: CCP = central counterparty; LCR = liquidity coverage ratio; NFSR = net funding stable ratio; SIFIs = systemically important financial institutions.

¹Fully complementary: tool mutually reinforces 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: tool has a conflicting but not major impact on the intent of another tool (light red); not related or not contradictory (white).

²Arrows indicate an increase (↑) or decrease (↓) in resulting impact.

³Refers to the Volker, Vickers, and Liikanen structural measures—see Pazarbasioglu and others (2013).

View Table

Table 9.4

Interaction of Prudential Tools

Tools1,2		Microprudential Exposure Limits		Capital Buffers (SIFIs)	Limits on Liquidity Mismatches (LCR, NFSR)		Limits on Activities3	Resolution Frameworks		CCP Clearing 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
Complexity of implementation	Regulators	LOW		MEDIUM	HIGH		HIGH	HIGH		MEDIUM
	Banks	MEDIUM		LOW	HIGH		HIGH	HIGH		LOW

Source: IMF staff compilation. Note: CCP = central counterparty; LCR = liquidity coverage ratio; NFSR = net funding stable ratio; SIFIs = systemically important financial institutions.

¹Fully complementary: tool mutually reinforces 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: tool has a conflicting but not major impact on the intent of another tool (light red); not related or not contradictory (white).

²Arrows indicate an increase (↑) or decrease (↓) in resulting impact.

³Refers to the Volker, Vickers, and Liikanen structural measures—see Pazarbasioglu and others (2013).

Since the global financial crisis there has been considerable global progress in designing and implementing a macroprudential toolkit. If they consider that cyclical conditions warrant, macroprudential authorities have the power to impose additional capital charges beyond those imposed institution by institution. Specific instruments—such as limits on loan-to-value and debt-to-income, and sectoral risk weights or floors—can be helpful.

Such instruments are likely to be designed and implemented at the national level, given the different risk exposures of each country. However, where cross-border financial activity exists, especially in the case of financial and mixed conglomerates, there is a clear need for coordination and reciprocity to avoid arbitrage and macroprudential leakage across countries. In addition to the complementarity and conflicts among prudential tools, there are complementarities and conflicts when prudential and macroprudential tools operate together to address systemic risks. Policymakers need to address this tension when they design policy frameworks and institutional mechanisms, to ensure effective coordination between these tools.

Policy Recommendations

Latin American countries can benefit from taking a regional approach to implementing the remaining elements of the global regulatory agenda and developing their emerging prudential and macroprudential toolkits to address systemic risks. They should do the following:

• Align timelines while reflecting international commitments and local circumstances as national authorities move forward with implementing the regulatory agenda.¹⁰

• Invest in staff and resources to fully capture systemic risks through the use of new data analysis tools and mapping, monitoring, and analyzing financial and mixed conglomerate networks that can be integrated with solvency and liquidity stress tests. Coordination across the LA-7 in sharing such information (legally enshrined, if possible) would help the region tackle appropriate systemic risk analysis and address data confidentiality concerns as well.

• Introduce or strengthen consolidated supervision—with technical assistance from the IMF or other sources—in line with recommendations from the IMF FSAPs and the Joint Forum’s Principles.

• Introduce or enhance conglomerate supervision, including establishing regulatory limits for intragroup exposures within banking groups and between bank and nonbank segments of conglomerates.

• Continue the development of macroprudential tools through regional conferences and possibly a more formal regional arrangement, so that tools can be designed and implemented on a regional basis to avoid cross-country regulatory arbitrage and coordinate dealing with spillovers.