Information about Asia and the Pacific Asia y el Pacífico
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Chapter 8 Systemic Risks and Financial Stability Frameworks

Author(s):
Ana Corbacho, and Shanaka Peiris
Published Date:
October 2018
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Introduction

Association of Southeast Asian Nations–5 (ASEAN-5) financial systems were resilient during the global financial crisis. Although capital outflows and the slowdown in economic activity were comparable to what occurred during the Asian financial crisis, domestic financial stability was preserved. The Asian financial crisis triggered important upgrades in regulatory and supervisory frameworks (discussed in Chapter 3) that helped the ASEAN-5 weather the crisis.

However, some financial vulnerabilities have been rising since the global financial crisis. Although credit growth was moderate between the Asian and global financial crises, it accelerated significantly following the global crisis, after which corporate debt also increased steadily. And in some countries, household debt is substantial. Moreover, the high degree of interconnectivity within the financial sector and between the financial sector and the real sector, while unavoidable in a financial deepening process, could be an emerging vulnerability. Finally, the fast pace of new financial technologies coming on board could bring benefits but also risks to ASEAN-5 financial systems.

This chapter analyzes those vulnerabilities and future challenges and discusses a policy agenda for strengthening financial stability frameworks in the ASEAN-5. The first part of the chapter analyzes systemic risks in ASEAN-5 domestic financial systems along both time and structural dimensions.1 The chapter first zooms in on recent credit trends to determine whether there were credit booms, given that booms are usually associated with financial instability. Then, it examines interconnectivity within the financial system and between the financial system and the real sector. The focus next turns to the corporate sector, since corporate vulnerabilities were at the root of the Asian financial crisis and since leverage has risen since the global crisis. The final major part of the chapter discusses the challenges and policy agenda ahead for strengthening financial stability frameworks in the region, spanning the three core pillars of microprudential regulation, macroprudential policy, and crisis management and resolution.

Credit Trends

A key dimension of systemic risk is related to the evolution and dynamics of credit growth over time. Periods during which credit to the private sector rises fast are often linked to systemic risks and financial instability. During a credit boom the expansion of lending can be so abrupt that the quality of the investment projects financed becomes compromised. This process may ultimately damage lenders’ balance sheets and trigger a financial crisis.

Ample empirical evidence indicates that credit overexpansion and banking crises are related. Demirgüç-Kunt and Detragiache (1997), for example, show that private credit is a significant determinant of banking crises. Mendoza and Terrones (2008) develop a method for identifying credit boom episodes in a sample of 48 industrial and emerging market economies during 1960–2006. They find that credit booms are usually a key component of financial crisis episodes. However, not all credit booms end up in financial crises.

Credit to the private sector in the ASEAN-5 economies grew rapidly in the aftermath of the global financial crisis in a context of exceptionally accommodative monetary policy worldwide. The growth rate of real credit to the private sector rose by more than 5 percentage points, on average, between 2000–09 and 2010–12, but has fallen in most economies since 2013 as global financial conditions tightened after the taper tantrum episode (Figure 8.1). This recent episode of fast credit growth in ASEAN-5 economies resembles, to some extent, the episode that was observed in the early 1990s, when growth of credit to the private sector picked up sharply amid expansionary monetary policies globally.

Figure 8.1.
Growth in Real Credit to the Private Sector

Sources: Country authorities; and IMF staff estimates.

A comparison of the two episodes is presented below through the lens of the literature on credit booms. The objective is to investigate whether there is evidence of credit booms in the ASEAN-5 economies following the global financial crisis. There is no single criterion with which to identify credit booms in the literature, so four different approaches from previous studies are used.

The first approach is based on Mendoza and Terrones (2008) and looks at deviations of real credit per capita from its Hodrick-Prescott trend, identifying credit booms when that deviation is larger than 1.75 times its standard deviation. The analysis uses data for credit to the private sector, inflation, and population during 1980–2016, complemented with IMF projections for 2017–18. Using this approach, credit booms are identified in the period preceding the Asian financial crisis in all ASEAN-5 economies except Singapore (Figure 8.2). However, no credit booms are picked up after the global financial crisis in any of the ASEAN-5 economies—most of the acceleration in credit growth is attributed to trend growth rather than to deviations from trend.

Figure 8.2.
Deviation from Trend in Real Credit to the Private Sector per Capita

Source: IMF staff estimates using the methodology of Mendoza and Terrones (2008).

Note: HP = Hodrick-Prescott; SD = standard deviation.

The second approach is that of Dell’Ariccia and others (2012), which looks at deviations of the credit-to-GDP ratio from a rolling backward-looking cubic trend. A credit boom is identified when either of the following two conditions is satisfied: (1) the deviation from trend is greater than 1.5 times its standard deviation and the annual growth rate of the credit-to-GDP ratio exceeds 10 percent, or (2) the annual growth rate of the credit-to-GDP ratio exceeds 20 percent. Under this approach, evidence of credit booms is detected in the period before the Asian financial crisis in all ASEAN-5 economies (Figure 8.3). However, there are no credit booms after the global financial crisis in any of the ASEAN-5 economies: the credit-to-GDP ratio remained close to trend, and the growth differential between credit and GDP stayed below the 20 percent threshold, although above the 10 percent cutoff in some cases.

Figure 8.3.
Deviation from Trend and Growth of Credit to GDP

Source: IMF staff estimates using the methodology of Dell’Ariccia and others (2012).

Note: SD = standard deviation.

The third approach is that of Chapter 3 of the IMF’s Global Financial Stability Report of September 2011, which finds that increases in the credit-to-GDP ratio of more than 3 percentage points, year over year, could serve as an early warning of credit booms, with increases of more than 5 percentage points indicating more severe credit booms. This approach indicates severe credit booms in all ASEAN-5 economies in the period before the Asian financial crisis, with changes in the credit-to-GDP ratio exceeding the 5 percent threshold by a wide margin (Figure 8.4). After the global crisis, there are no severe credit booms in Indonesia and the Philippines, but there are in the other economies. Malaysia’s credit-to-GDP ratio rose by more than 5 percent in 2011–13, Thailand’s in 2011 and 2013, and Singapore’s in 2011–13 and 2016.

Figure 8.4.
Changes in the Credit-to-GDP Ratio

Source: IMF staff estimates.

The last approach builds on Bank for International Settlements methodology. Drehmann, Borio, and Tsatsaronis (2012) argue that financial cycles last longer than economic cycles, and thus propose to examine the credit gap, defined as the deviation of the credit-to-GDP ratio from a Hodrick-Prescott trend with a very high smoothing parameter (an almost linear trend). A credit boom is identified when the deviation from trend exceeds 10 percentage points. Applying this methodology to credit to the private sector shows large credit gaps (above the 10 percent threshold) in all ASEAN-5 economies in the years before the Asian financial crisis (Figure 8.5). However, there is no evidence of credit booms in the period following the global crisis, except in Singapore, where the deviation of the credit-to-GDP ratio from trend exceeded the 10 percent cutoff in 2014 and 2016.

Figure 8.5.
Deviation from Trend in the Ratio of Credit to the Private Sector to GDP

Source: IMF staff estimates using Bank for International Settlements (BIS) methodology.

Overall, the evidence suggests that systemic risks on the time dimension have been contained in the ASEAN-5 since the global financial crisis. Using four different approaches, there is evidence of credit booms in the period before the Asian financial crisis in all ASEAN-5 economies, but little evidence of credit booms after the global crisis. All approaches suggest that Indonesia and the Philippines did not experience credit booms after the global financial crisis. However, the Global Financial Stability Report approach based on the change in the credit-to-GDP ratio suggests that Malaysia, Singapore, and Thailand may have experienced credit booms at some point during 2011–13, while the Bank for International Settlements approach finds evidence of credit booms in Singapore in 2014 and 2016. There is no evidence of credit booms in any of these three countries after the global financial crisis using the remaining two approaches. More weight should be given to the approaches that use deviations from trend analysis because the credit-to-GDP ratios of Malaysia, Singapore, and Thailand are much larger than those of Indonesia and the Philippines, which makes it more likely that the changes in credit-to-GDP ratios exceed the thresholds.

Financial Interconnectivity

Interconnectivity refers to relationships among economic agents that arise as a result of financial transactions and legal arrangements. In a highly interconnected financial system, distress in one entity can be transmitted to other entities in the network, and bank stresses or failures are more likely to occur at the same time.

Understanding the nature of these relationships is essential for tracking the buildup of systemic risk along a structural dimension, identifying the fault lines along which financial shocks may propagate, and enhancing macroprudential surveillance and risk management. Leitner (2005), Gai and Kapadia (2010), Caballero and Simsek (2013), and Minoiu and Reyes (2011) argue that highly complex networks can increase the likelihood of contagion risk when there is financial friction. Peltonen, Rancan, and Sarlin (2015) show that early-warning models augmented with interconnectivity measures outperform traditional models for out-of-sample predictions of recent banking crises in Europe.

Financial interconnectivity has increased significantly in the ASEAN-5 in recent years. A continued search for higher returns (given low global interest rates) has changed the mix of assets and liabilities, which, in turn, has changed the nature and intensity of interconnection among financial institutions and economic agents. The remainder of this section examines links between banks on one side and sovereign, nonbank financial institutions and households on the other in ASEAN-5 countries. In turn, the section “Vulnerabilities in the Nonfinancial Corporate Sector” focuses on the links between banks and nonfinancial corporations.

Interconnectivity between Banks and the Sovereign

Banks are exposed to sovereign risk via holdings of government securities and loans extended to public sector bodies. Sovereign risk can be transferred to banks through two main channels: (1) on the asset side, via valuation losses on bank holdings of sovereign securities (direct sovereign risk) and (2) on the liability side, through an increase in bank funding costs caused by repricing of risk and credit rating downgrades (indirect sovereign risk). In Indonesia, the share of government securities in banks’ assets has declined from 35 percent in 2001 to less than 10 percent since 2011 (Figure 8.6, panel 1). In the other ASEAN-5 countries it remained broadly constant and lower than 15 percent. So the exposure of banks to governments is contained. Banks are also exposed to the sovereign on the liability side because many governments (or government-related agencies) have bank deposits that they could potentially withdraw in a fiscal crisis. Such withdrawal could have a significant effect on banks’ liquidity.

Figure 8.6.
Risks from the Sovereign to the Banks

Public debt levels in ASEAN-5 countries are moderate, and so are the associated risks (Table 8.1). Overall, banks’ holdings of sovereign debt in the ASEAN-5 has either declined or remained low in recent years, and sovereign credit default swap spreads (which measure the risk of a sovereign default) have been compressed (Figure 8.6, panel 2). Singapore’s high level of public debt is a consequence of efforts to develop bond markets, with gross debt fully covered by financial assets. Malaysia is the only country in which public debt is higher than the average for emerging market and developing economies. However, sovereign yields are relatively low, and the public debt ratio is projected to be on a declining path. Holdings of public debt by domestic banks are generally higher than those of the average emerging market and developing economy, but a limited fraction of total public debt. Although its overall debt is manageable, the Philippines has the largest stock of foreign-currency-denominated debt, and therefore has a higher exposure to foreign exchange risk.

Table 8.1.Selected indicators of Sovereign Risk
IndonesiaMalaysiaPhilippinesSingaporeThailandMedian EM
Credit by Banks to the Sovereign, 2015 (percent of GDP)16161527159
Public Debt, 2016 (percent of GDP)2856341124244
Ten-Year Sovereign Yield, End-June 2017 (percent)6.83.95.12.12.55.3
Share of Foreign Currency Public Debt, 2016 (percent)38. . .38. . .535
Share of Public Debt Held by Nonresidents, 2016 (percent)593530. . .1235
Primary Balance Gap, 2017 (percent of GDP)2-0.1-0.6-2.2-3.40.00.1
Sources: Bloomberg Finance L. P.; World Bank, Global Financial Development Database; and IMF, Fiscal Monitor, April 2017.Note: EM = emerging market.

Includes credit to state-owned enterprises.

Change in the primary balance to stabilize the debt-to-GDP ratio at the 2016 level.

Sources: Bloomberg Finance L. P.; World Bank, Global Financial Development Database; and IMF, Fiscal Monitor, April 2017.Note: EM = emerging market.

Includes credit to state-owned enterprises.

Change in the primary balance to stabilize the debt-to-GDP ratio at the 2016 level.

Similarly, sovereigns are exposed to risk from banks’ instability. Poor bank performance may require public assistance or funding, thus further increasing the debt burden of the sovereign. As discussed in Chapter 3, banks’ balance sheets in the ASEAN-5 remain strong, and nonperforming loan ratios are contained (Figure 8.7, panel 1), suggesting lower exposure of governments to banks. Moody’s Analytics market-based expected default frequency data for ASEAN-5 banking systems, which measure the probability that banks will default over the next year, also show relatively modest risks (Figure 8.7, panel 2). Financial stability risks are further mitigated by the presence of developed microprudential frameworks (aimed at securing the orderly functioning of banks and preventing banking crises), macroprudential frameworks (aimed at containing systemic risk), and bank resolution regimes (which facilitate early intervention and limit the liability of governments during banking crises).

Figure 8.7.
Risks from the Banks to the Sovereign

Interconnectivity among Banks

Banks can be interconnected directly via bilateral transactions, financial service links, or financial infrastructure links. The greater the degree of interconnectivity between banks, the greater the likelihood that financial stress in one bank could trigger spillovers of financial stress to other banks, thereby increasing systemic risks. Interconnectedness can also be indirect: for example, fire sales by a distressed bank may lead to a fall in asset prices and associated mark-to-market losses for other banks.

There are several ways to measure bank interconnectivity. One measure is the share of interbank loans as a proportion of total bank assets (Figure 8.8, panel 1). Interbank assets and liabilities in Singapore are predominantly limited to nonresident banks, reducing the potential for contagion within the network of the three local banks. In Malaysia, where bank penetration is high, the interbank connections are deep among the conventional banks, while interbank borrowing and lending between the Islamic banks is very thin. In Indonesia, the interbank market is thin and segmented, with banks relying largely on household deposits for funding. In addition, smaller banks do not generally access the interbank market, limiting their direct interconnectedness with the rest of the sector. The situation is largely similar in the Philippines, where the interbank market is very shallow and direct bank exposures to other banks are small. In Thailand the share of interbank loans has almost tripled since 2001 (Figure 8.8).

Figure 8.8.
Risks between Banks

Sources: Country authorities; Haver Analytics; and IMF staff calculations.

Market-based measures of bank interconnectivity indicate rising risks during times of market stress. Connectivity among large banks within countries and across the ASEAN-5 can be assessed by techniques developed by Diebold and Yilmaz (2014) using bank-level equity prices. The connectivity index quantifies the contribution of shocks from one bank’s asset returns and volatilities to another’s at different times based on dynamic variance decompositions from vector autoregressions. The time-varying interconnectivity index for the largest banks in the ASEAN-5 shows rising susceptibility to propagation of distress from one bank in the region to another, particularly during times of market stress (Figure 8.8, panel 2). The more frequent spikes in the interconnectivity index among ASEAN-5 banks since the global financial crisis could indicate greater systemic risks in the region, requiring a greater focus on monitoring risks stemming from financial institution interconnectivity.

Interconnectivity between Banks and Nonbank Financial Institutions

Interconnectivity between banks and nonbank financial institutions can take various forms. They often have common ownership links (by belonging to a financial conglomerate or owning stakes in each other) and maintain significant financial links in the form of deposits and common market exposures. Moreover, some nonbank financial institutions play a critical role in the funding strategies of banks, while banks have provided explicit and implicit guarantees of their affiliated banks’ net asset values. Over time, the distinction between banks and some nonbanks has become blurred, but there is one key difference: nonbank financial institutions are typically subject to lighter prudential, regulatory, and reporting standards than banks. While the rapid development of nonbank financial institutions could reflect progress toward a more diversified financial system, it could also go hand in hand with financial stability risks.

Nonbank financial institutions in the ASEAN-5 have grown, albeit at different rates (Figure 8.9). Singapore’s nonbank sector is nearly half the size of the banking system, and most nonbank players (except wealth management institutions) have limited links with local banks and are unlikely to pose a systemic risk. Strong performance of global and regional equities in recent years provided the wealth management sector—the largest nonbank player in Singapore—a boost, spurring higher sales of unit trusts and other investment products. Local banks have been a key factor behind the wealth management sector’s growth and have been its main beneficiary. The size of nonbank financial institutions in other ASEAN-5 countries is modest, suggesting that, all else equal, there is less risk of lower stability as a result of interconnection with banks.

Figure 8.9.
Assets of Nonbank Financial Institutions

(Percent of GDP)

Sources: National authorities; Financial Stability Board database; and IMF staff calculations.

Interconnectivity between Banks and Households

Banks are connected with households through both the asset and liability sides of their balance sheets. On the asset side, the exposure takes the form of various types of loans extended by banks to households. On the liability side, households’ claims on banks can take the form of deposits and equity. Although the aggregate net exposure of banks to the household sector provides useful guidance for the riskiness of the link between banks and households, the disparities in income and debt-servicing capacity between household groups, as well as maturity mismatches between assets and liabilities, requires a more granular view and prudent macroprudential oversight.

Among the ASEAN-5, household-debt-to-GDP ratios are high in Malaysia, Singapore, and Thailand, but significantly lower in Indonesia and the Philippines (Figure 8.10).

  • Having stabilized recently, the household debt level in Singapore is about 60 percent of GDP. Recent macroprudential measures have slowed the growth of household debt and helped build households’ financial buffers and reduce the risk for banks and nonbank lenders (see Chapter 6 and IMF 2017d).

  • Household indebtedness in Malaysia is higher (at nearly 90 percent of GDP). However, risks are mitigated by high levels of financial assets, exceeding 180 percent of GDP as of the end of 2015 (IMF 2017c).

  • Household debt in Thailand peaked at about 80 percent of GDP in 2015. On a net basis, both banks and nonbanks are borrowers from households (Figure 8.11 and Table 8.2). However, in recent years, banks’ net liabilities to households have declined, a result of a massive increase in banks’ gross claims on households, while nonbanks’ net liabilities have increased, shifting much of the risk associated with high household debt to banks’ balance sheets. The higher household debt with nonbank financial institutions could represent an increase in systemic liquidity risk because the shorter maturity of nonbank products results in maturity mismatches (IMF 2017e).

  • In Indonesia, banks are also net borrowers from households, which reduces the potential loan losses on that segment of banks’ portfolios.

  • Household debt is still less than 15 percent of GDP in the Philippines, taking into account housing-related mortgages from government financial institutions not covered in the financial system surveys. However, bank credit to households has been expanding rapidly since 2010, and close monitoring of credit standards is warranted, particularly given shadow banking by real estate developers and informal financial institutions in the Philippines that may mask the true level of household leverage (IMF 2015).

Figure 8.10.
Household Debt

(Percent of GDP)

Source: CEIC Data.

Figure 8.11.
Thailand: Bank and Nonbank Financial Institution Exposure to Households

(Percent of GDP)

Sources: Country authorities; and IMF staff calculations.

Note: Size of 2017 and 2015 circles reflects relative size as a percentage of GDP. NBFI = nonbank financial institution.

Table 8.2.Thailand: Balance Sheet Analysis Matrix—Intersectoral Net Positions(Percent of GDP)
Government1Central BankBanks2NBFIs3NFCsHHsROW
2007
Government1-6.7-4.44.90.34.11.2
Central Bank6.79.84.11.21.5-32.5
Banks24.4-9.82.0-21.4-9.31.5
NBFIs3-4.9-4.1-2.0-17.8-5.2-2.4
NFCs4-0.3-1.221.417.820.7
HHs-4.1-1.5-29.3-25.20.0
ROW-1.232.5-1.52.4-20.70.0
2015
Government1-5.1-0.87.90.31.74.7
Central Bank5.119.95.20.70.1-42.1
Banks20.8-19.95.8-14.116.99.8
NBFIs3-7.9-5.2-5.8-18.635.5-2.5
NFCs4-0.3-0.714.118.616.9
HHs-1.7-0.1-16.9-35.50.0
ROW-4.742.1-9.82.5-16.90.0
Sources: Bank of Thailand; and IMF staff calculations.Note: HHs = households; NBFIs = nonbank financial institutions; NFCs = nonfinancial corporations; ROW = rest of world.

Includes central government and local governments.

Includes all depository corporations excluding the Bank of Thailand.

Includes all other financial corporations.

NFCs Includes state-owned enterprises.

Sources: Bank of Thailand; and IMF staff calculations.Note: HHs = households; NBFIs = nonbank financial institutions; NFCs = nonfinancial corporations; ROW = rest of world.

Includes central government and local governments.

Includes all depository corporations excluding the Bank of Thailand.

Includes all other financial corporations.

NFCs Includes state-owned enterprises.

Vulnerabilities in the Nonfinancial Corporate Sector

Recent Trends in Corporate Debt

Corporate debt in the ASEAN-5 has increased faster than GDP since the global financial crisis.2 It rose from 77 percent of GDP in 2010 to 102 percent in 2016 in Malaysia, from 155 to 166 percent in Singapore, from 24 to 31 percent in Indonesia, from 25 to 30 percent in the Philippines, and from 64 to 68 percent in Thailand (Figure 8.12, panel 1).3 The increase in debt was on account of rapid growth in both bond issuance and bank loans. In particular, corporate bond issuance nearly tripled during this period, driven by an increase in domestic and foreign currency bonds.

Figure 8.12.
The Corporate Sector

Higher debt led to rising leverage in the corporate sector, although leverage ratios are still low compared with what they were during the Asian financial crisis (Figure 8.12, panel 2). At the same time, corporate profitability had weakened amid moderation in regional economic growth in recent years (Figure 8.12, panel 3). As a result, average debt-servicing capacity appears to be weakening despite remaining resilient (Figure 8.12, panel 4). Although most bonds have matured, some countries have a relatively large number that are maturing in the next two years (Figure 8.12, panel 5).

The ability to refinance short-term debt and the adequacy of internal cash buffers to meet these debt obligations along with operational costs are important. For most countries, cash buffers are adequate. However, median ratios of cash and cash equivalents to short-term debt seem relatively low in Indonesia and Thailand (Figure 8.12, panel 6). It is worth noting that low cash levels may reflect better reinvestment opportunities in some of these countries. However, cyclical global headwinds, especially during periods of dislocation in global capital markets, can amplify rollover risks and affect firms’ short-term refinancing needs. Moreover, higher risk premiums lead to higher borrowing costs and lower earnings.

Corporate Vulnerabilities

An increase in global trade protectionism measures could significantly affect exports and corporate earnings in emerging market economies, including ASEAN-5 countries. Historically, world trade and corporate returns on assets are positively associated (Figure 8.13). In 2009, global trade declined close to 25 percent year over year, driven by protectionist measures, in addition to the sharp contraction in global demand in the aftermath of the global financial crisis and reduced access to credit to finance trade. Recently, the number of discriminatory trade measures has been on the rise again. Further increases in trade protectionism, including retaliations, could disrupt global trade and jeopardize corporate earnings. At the same time, cyclical headwinds associated with volatility in global financial markets could lead to exchange rate depreciation and higher risk premiums and borrowing costs. A combination of these factors could increase corporate sector risks.

Figure 8.13.
World Trade, Global Corporate Return on Assets, and Discriminatory Trade Measures

Sources: Global Trade Alert; IMF, Corporate Vulnerability Utility; and World Trade Organization.

Note: ROA = return on assets.

One way to quantitatively assess corporate vulnerabilities is to examine debt-service capacity and the share of debt at risk. Using firm-level data for about 2,600 companies from the Bloomberg database, the interest coverage ratio for each firm is computed by dividing earnings before interest and taxes by interest expenses in 2016. The share of debt at risk is the sum of the debt of all firms with an interest coverage ratio lower than 1 divided by the sum of the debt of all firms.

To examine the sensitivity of firms to shocks, an illustrative sensitivity analysis of the firms’ balance sheets based on publicly available information is undertaken using the following three shocks:

  • Firms’ earnings decline by ¾ standard deviation, based on regression analysis that shows that a 25 percent decline in global trade leads to a ¾ standard deviation deterioration in corporate return on assets in emerging market economies. Implicit in this assumption is that global trade will decline by the same order of magnitude as in 2009.

  • The exchange rate depreciates by 15 percent against the US dollar, derived from Fibonacci retracement of the US Dollar Index from 2000 to June 2017, which suggests potential US dollar appreciation by another 15 percent.4

  • Interest expenses increase by 20 percent, based on the average of the largest increase in emerging market economies during 2008–16.

The results suggest that corporate debt at risk could increase significantly in some ASEAN-5 countries, though it would remain at low levels overall (Figure 8.14). To an extent, the level of debt at risk will depend on the magnitude of foreign exchange hedging from natural hedges (export and foreign currency earnings) and derivative hedges. In this exercise, the median ratios of foreign sales to total sales are used as a proxy for natural hedges. It is worth noting that although foreign exchange derivative hedging instruments and markets are more developed now than during the Asian financial crisis, some of these instruments are complex. For example, some currency hedges terminate when exchange rates depreciate beyond certain “knock-out” thresholds, thus rendering the hedges worthless. Moreover, firms are exposed to liquidity and rollover risks when these contracts expire.

Figure 8.14.
Debt at Risk

(Percent of total debt)

Sources: Bloomberg Finance L.P.; IMF, Corporate Vulnerability Utility; and IMF staff calculations.

Interconnectivity with Banks

Weaknesses in the corporate sector could put pressure on banks’ asset quality through increases in nonperforming loans. The ability of banks to withstand these shocks will depend on the size of their buffers, comprising Tier 1 capital and provisions (Figure 8.15). Since 2010, the banking sector’s Tier 1 capital ratios have been rising in the region. Nonetheless, provision coverage has weakened somewhat in recent years in a number of countries, as shown by the decline in the ratio of bank provisions to nonperforming loans.

Assuming in a stress scenario that all the corporate debt at risk owed to banks defaults, sensitivity analysis suggests that gross nonperforming loan ratios could increase 0.4–2.8 percentage points. This would erode banks’ loss-absorbing buffers by 0.4–3.5 percentage points. However, banks’ capital ratios would remain strong when benchmarked against Basel III’s minimum capital requirements.

Figure 8.15.
The Banking Sector

The reduction in bank capital could lead to weaker credit growth, though, because banks tend to de-risk when their capital ratios fall to limit losses and meet regulatory requirements. In emerging market economies, a 1 percentage point decline in banks’ capital-to-assets ratio could lead to as much as a 4.6 percentage point reduction in loan growth. In turn, the decline in bank credit could weaken economic growth. Previous studies have found the sensitivity of GDP growth to bank credit growth ranging from 0 to 0.4, depending on the extent of credit deepening and economic circumstances. Within the ASEAN-5 region, bank credit growth has already slowed compared with average growth rates, except in the Philippines (Figure 8.1).

Challenges and Policy Agenda Ahead

The global financial crisis propelled a wave of reforms in financial sector regulation across the world. Existing financial regulations were considered too weak, and a multilateral reform effort kicked off with the goal of making financial systems worldwide more resilient to shocks. The Basel III agreement reached in 2011 was a major achievement toward enhancing regulatory standards for capital and liquidity requirements. It also included special capital requirements for global systemically important financial institutions. Some final elements of the Basel III reforms, aiming to improve the credibility of the bank capital framework, were agreed to only in late 2017.

An important lesson from the global financial crisis is that traditional microprudential regulation is not sufficient to secure the stability of the financial system as a whole. A broader macroprudential approach is needed to mitigate systemic risks and safeguard financial systems. Moreover, the global financial crisis exposed the limitations of crisis management and resolution frameworks, particularly when systemic institutions operating on a large and cross-border basis are involved.

Microprudential regulation focuses on the financial soundness of an individual financial entity, while macroprudential regulation focuses on the financial soundness of the whole system. Yet, even with strong micro- and macroprudential regulation in place, some financial institutions may eventually fail. Against this backdrop, sound crisis management frameworks are essential to contain the risks to taxpayers. The international standards on how banks should be restructured or closed are known as the Key Attributes of Effective Resolution Regimes for Financial Institutions, elaborated by the Financial Stability Board.

The rest of this chapter outlines challenges and the policy agenda ahead for strengthening financial stability frameworks in ASEAN-5 countries. It first delves into current issues in financial sector regulation from a microprudential perspective and then elaborates on next steps for upgrading macroprudential frameworks and crisis management and resolution regimes. The last subsection discusses the potential benefits and risks of new financial technologies such as cryptocurrencies.

Financial Sector Regulation

Basel III is a comprehensive set of voluntary capital and liquidity requirements, developed by the Basel Committee on Banking Supervision, that aims to strengthen banking sectors. These requirements were agreed to by the committee in 2011 and were scheduled for gradual adoption during 2013–27. They call on banks to have (1) more and better capital to absorb shocks and (2) more liquid assets to weather liquidity shocks.

An important challenge in the implementation of the Basel III standards is to ensure that they are reasonable for each financial system and each financial institution. Adrian and Narain (2017) argue that the Basel III standards were a response to the global financial crisis and hence naturally focus on global systemically important financial institutions. This suggests that there is a need for proportionality in the application of the standards for less complex financial systems and institutions.

ASEAN-5 countries made significant strides in strengthening microprudential regulations after the Asian financial crisis. The main challenge ahead is to adopt Basel III standards but also to tailor the rules to the sophistication of the financial sector and financial institutions of each country. ASEAN-5 economies are at different stages in this process:

  • Indonesia implemented new capital and liquidity rules in line with Basel III. New rules for systemically important banks were approved in March 2016. A liquidity coverage ratio was established in December 2015. Large banks (banks with core capital of at least 30 trillion rupiah) and foreign branch offices were required to have an liquidity coverage ratio of at least 70 percent at the end of 2015. Midsize banks (banks with core capital between 5 trillion and 30 trillion rupiah) and foreign banks have had a 70 percent liquidity coverage ratio since July 2016.

  • Malaysia adopted new capital rules in January 2013. Global standards related to capital conservation and countercyclical capital buffers were met in 2016, and the bank leverage ratio has been in effect since January 2018, in line with the global timeline. A minimum liquidity coverage ratio of 60 percent came into force in mid-2015 and will be stepped up gradually to 100 percent by January 2019.

  • In the Philippines, commercial banks have stricter capital requirements than mandated under Basel III. Local regulations stipulate a 6 percent ratio for common equity Tier 1 capital, compared with 4.5 percent under Basel III; a 7.5 percent ratio for Tier 1 capital (6 percent under Basel III); and a 10 percent ratio for total capital (8 percent under Basel III). The authorities also introduced a 2.5 percent capital conservation buffer at the start of 2014, five years ahead of the Basel III schedule. In 2015, the authorities set a leverage ratio of 5 percent for local banks.

  • In Singapore, capital requirements for banks are higher than those established by Basel III, and their adoption has been front-loaded. The introduction of the capital conservation buffer follows the same phase-in schedule as Basel III. The liquidity coverage ratio was introduced in January 2015. The minimum requirement started at 60 percent and is scheduled to rise in equal annual steps to reach 100 percent by January 2019.

  • In Thailand, Basel III capital rules have been in force since January 2013. The Bank of Thailand issued seven notifications regarding the Basel III capital framework to require Thai banks to maintain a minimum common equity ratio of 4.5 percent, Tier 1 ratio of 6 percent, and total capital ratio of 8.5 percent. In 2017, the Bank of Thailand also identified systemically important banks required to hold a capital buffer above the minimum requirements. In 2016, the Band of Thailand began to phase in the liquidity coverage ratio requirement at 60 percent for all commercial banks; it will reach 100 percent in 2020.

Macroprudential Frameworks

ASEAN-5 countries have been at the frontier in the implementation of macroprudential policies, especially those applicable to specific sectors of the economy (see Chapter 6). Still, although the use of macroprudential tools has grown, an important agenda to upgrade and fully develop macroprudential frameworks lies ahead. Perhaps the most important challenge in the ASEAN-5 is to enhance the ability to identify and monitor emerging systemic risks in a structural dimension, especially with the expansion of nonbank financial institutions (see the “Financial Interconnectivity” section). Macroprudential policies remain hampered by data and institutional gaps. Moreover, the experience and evidence on the use of macroprudential tools continue to evolve worldwide.

ASEAN-5 institutional frameworks for macroprudential policies follow a wide range of models (Box 8.1). The IMF (2011b) classifies macroprudential institutions using five key dimensions, leading to seven distinct models (Table 8.3). The dimensions are (1) the degree of institutional integration between central bank and financial regulatory policy functions, (2) ownership of the macroprudential mandate, (3) the role of the government, (4) the degree to which there is organizational separation of decision-making and control over instruments, and (5) whether there is a coordinating committee that, while not itself charged with the macroprudential mandate, helps coordinate several bodies. The ASEAN-5 countries sit in either model 1 or 4, characterized by partial or full central bank independence, with ownership of macroprudential policies mainly with the central bank.

Table 8.3.Models of Macroprudential Institutions
Features of the ModelModel 1Model 2Model 3Model 4Model 5Model 6Model 7
Degree of Institutional Integration of Central Bank and Supervisory AgenciesFullPartialPartialPartialNoneNoneNone
Ownership of Macroprudential Policy and Financial Stability MandateCentral bankCommittee related to central bankIndependent committeeCentral bankMultiple agenciesMultiple agenciesMultiple agencies
Role of Ministry of Finance, Treasury, GovernmentActivePassiveActiveNonePassiveActiveNone
Separation of Policy Decisions and Control over InstrumentsNoIn some areasYesIn some areasNoNoNo
Existence of Separate Body Coordinating across PoliciesNoNoNoNoYesYesNo
Examples of Specific ModelSingapore, Malaysia, Czech Republic, IrelandRomania, United Kingdom, CambodiaBrazil, France, United StatesThailand, Philippines, Indonesia, Hong Kong SAR, Lao P.D.R., NetherlandsAustraliaCanada, VietnamIceland, Japan, Korea, Peru, Switzerland
Source: IMF (2011b).
Source: IMF (2011b).

Recognizing the numerous approaches, the IMF (2014) establishes some criteria for assessing the strengths and weaknesses of macroprudential frameworks:

  • Analysis: The central bank should have an important role within the framework reflecting its experience in monitoring macro-financial developments and conducting risk assessment.

  • Monitoring: The framework should provide for the effective monitoring and identification of systemic risk, which require, among other things, assured access by agencies to all relevant information.

  • Organization: It must be clear where the mandate and powers reside for the timely and effective use of macroprudential policy once concerns about systemic risk have been identified.

  • Prudential policies: Since macroprudential policy relies on the use of microprudential tools, the framework must facilitate a very high level of coordination across agencies and provide adequate respect for their policy autonomy.

Macroprudential Institutional Arrangements in the ASEAN-5

The ASEAN-5 have used a mixture of institutional arrangements to implement macroprudential policies.

Indonesia: The central bank formally began conducting macroprudential surveillance of the Indonesian financial system in 2003. A law passed in 2011 established the Indonesian Financial Services Authority, which is independent and enumerates microprudential powers. The law also assigned responsibility for macroprudential regulation and supervision to the central bank. Overall, financial stability is in the hands of Financial System Stability Forum, coordinated by the minister of finance. The forum is responsible for monitoring and assessing financial stability, making policy recommendations, and facilitating information exchange among government agencies and, in crisis situations, with crisis management.

Malaysia: Under the Central Bank of Malaysia Act 2009, the bank has been given a financial stability mandate and broad powers to ensure financial stability. In addition to powers to regulate and supervise financial institutions and specific markets under its purview, the bank can invoke powers over financial institutions beyond its regulatory reach and make recommendations to any other supervisory authority. Governance for these latter powers is provided by the Financial Stability Executive Committee, chaired by the governor and comprising one deputy governor and three to five other members appointed by the finance minister—which includes a Treasury representative in practice.

Philippines: Responsibility for financial stability is shared among different agencies: the Bangko Sentral ng Pilipinas (BSP) has responsibility for, among other things, monetary policy and banking sector stability; the Securities and Exchange Commission is responsible for market conduct and consumer protection; the Insurance Commission, a government agency under the Department of Finance, regulates and supervises life and non–life insurance companies. The Financial Stability Committee, chaired by the central bank governor, was set up in 2010 to develop an overarching approach to systemic risk monitoring. The BSP has been promoting the exchange of financial stability issues in the framework of the high-level Financial Stability Coordination Council since 2011.

Thailand: Thailand currently has no law explicitly defining financial stability or assigning the mandate of financial stability to any institution. In practice, dating back to 2004, the Bank of Thailand’s mandate as spelled out in its law, “maintaining monetary stability, financial institutions system stability and payment stability,” broadly supports its activities as the lead financial stability framework agency. At the national level the central bank’s role is limited by the existence of other regulators. The Securities and Exchange Commission and the Office of Insurance Commission have narrower mandates. Nevertheless, these areas have important links with banks and the broader financial system. The establishment of the Financial Stability Unit housed in the Bank of Thailand in 2016 has facilitated information sharing, monitoring, and coordination among regulators.

Singapore: The Monetary Authority of Singapore (MAS) is responsible for conducting macroprudential policy. The MAS is both a central bank and an integrated financial supervisor overseeing all financial institutions and is mandated with promoting financial stability. Under the current institutional arrangement, the deputy prime minister and minister of finance serves as the chairman of the board of the MAS and presides over the board-level chairman’s meeting, where microprudential and macroprudential policies, as well as monetary policy, are determined. At the level of the chairman’s meeting, the MAS holds meetings with the Ministry of Finance to discuss macroeconomic and financial stability issues and seek agreement on policies that can have broad ramifications. The role of the chairman’s meeting in macroprudential policy is supported by the MAS Management Financial Stability Committee, chaired by the MAS managing director and comprising other MAS senior managers. It coordinates policies aimed at maintaining financial stability as well as the stability of asset and consumer prices and collaborates with all relevant government agencies.

This framework provides for effective identification, analysis, and monitoring of systemic risk and timely and effective use of macroprudential policy tools, and it avoids coordination problems when addressing systemic risk to reduce gaps and overlaps (Figure 8.16).

Figure 8.16.
Criteria for Effectiveness of Macroprudential Institutional Model

Source: IMF 2011b.

Within their current arrangements, all ASEAN-5 countries have scope to close gaps in their macroprudential frameworks. Challenges and priorities ahead include the following:

  • Data and surveillance: The surveillance of cross-border financial flows needs to be enhanced to derive a comprehensive picture of the deeper network of interconnections and spillovers across countries. Each country also needs to continue identifying and closing data gaps. In Indonesia, the general framework that underpins information sharing between agencies is adequate, although there are some practical difficulties, particularly related to data collection and validation. In the Philippines, a financial stability coordination council was created in 2014 to address informational and regulatory gaps among the financial regulators. In Thailand, there is significant scope to gather and analyze granular data on balance sheet exposures and interconnectedness, as well as to develop macro stress-testing tools.

  • Policy tools: Upgrading the macroprudential framework requires advancing the agenda on analytical frameworks for assessing systemic stability, developing new instruments, and advancing the work on interactions between macroprudential and other policy instruments. The authorities should select a set of macroprudential instruments that can help address the key potential sources and dimensions of systemic risk. Since the manifestations of systemic risk may be country specific, the set of desirable tools will vary from country to country. In general, ASEAN-5 countries have been prominent users of sectoral macroprudential tools, including for the housing sector. More recently, some countries (for example, Indonesia, Philippines, Thailand) have added capital surcharges for domestic systemically important banks to their toolkits. On the time dimension of systemic risk, many ASEAN-5 countries have implemented capital adequacy ratios in a countercyclical manner on a de facto basis (see Chapter 6). However, only Indonesia and Malaysia have rules-based countercyclical capital buffer requirements.

  • Communication: Macroprudential policy cannot rely on rules but must be based on a continuous assessment of evolving risks (IMF 2014); therefore, ASEAN-5 authorities should communicate openly on macroprudential policy. Clear communication of policy intentions can improve transmission of macroprudential action, both when measures are taken and when they are relaxed. Communication can also promote public understanding of the need for macroprudential measures, counter biases in favor of inaction, and enhance legitimacy and accountability of macroprudential policy. Clear communication can be achieved by setting out and maintaining a policy strategy, periodically publishing risk assessments, and publishing the records of policy meetings.

  • Coordination: Interagency coordination needs to be improved, and clarity about roles, responsibilities, and powers is key to ensuring effective and timely decisions. Since macroprudential policy relies on the use of microprudential tools, the framework must facilitate a very high level of coordination across agencies and provide adequate respect for each agency’s policy autonomy.

Crisis Management

Contingency planning is a critical element of crisis preparedness that lays out responsibilities and implementation arrangements for early intervention and resolution measures. Advanced preparation covering the way in which difficult decisions will be made and coordinated among institutions if a broad-based financial crisis gets underway can help promote an effective response to a crisis.

Although early intervention is likely to restore financial soundness in most financial distress situations, there will be occasions when such intervention is not possible and some form of resolution will be required. The procedure for resolving banks must swiftly protect systemic functions and reassure depositors. Ordinary insolvency proceedings normally cannot guarantee this result, which is why most countries already have special administrative (out-of-court) procedures for handling bank resolution.

An effective resolution framework has clear mandates for resolution, provides independence and adequate legal protection for supervisors, and grants appropriate resolution powers to the resolution authority. The Key Attributes of Effective Resolution Regimes for Financial Institutions adopted by the Financial Stability Board is the new, nonbinding international standard. The attributes specify essential features that should be part of the resolution framework to make resolution feasible without severe systemic disruption and without exposing taxpayers to loss.

In all ASEAN-5 countries, there is scope for improving coordination mechanisms:

  • In Indonesia, the responsibilities of each agency have been further clarified in the Prevention and Resolution of Financial System Crisis Law, enacted in 2016. However, the legal protection of staff and agencies involved in bank resolution could be strengthened.

  • In Malaysia, the Deposit Insurance Corporation is the resolution authority for its member institutions, while the central bank is the resolution authority for other financial entities. The Deposit Insurance Corporation’s resolution powers could be strengthened; it currently must seek High Court approval for some measures.

  • In the Philippines, weaknesses in resolution-related legal powers and protection remain. For example, the central bank’s authority to place a bank in receivership or suspend shareholder rights, even when a bank’s failure is imminent, is very limited.

  • In Singapore, crisis management and resolution agreements are generally strong, but could be further enhanced. The resolution regime does not accord any preference to deposit liabilities held at foreign branches of local banks, which could encourage ring-fencing measures in host jurisdictions and discourage cooperative approaches.

  • In Thailand, although the central bank has de facto responsibility for bank resolution, much of the legal authority rests with the Cabinet. The Ministry of Finance is still in charge of granting, suspending, and revoking licenses; approving mergers and acquisitions; and liquidating problem assets.

Cryptocurrencies

Cryptocurrencies challenge the paradigm of state-supported fiat currencies and the dominant role that central banks and conventional financial institutions have played in the operation of the financial system (IMF 2016). They are issued without the backing of a state and allow for direct peer-to-peer transactions and eliminate the need for central clearinghouses. They have the potential to deepen financial inclusion by offering secure and lower-cost payment options.

Cryptocurrencies also pose serious risks because they can facilitate money laundering, terrorism financing, tax evasion, and other illegal activities. They could eventually entail risks to financial stability if their use becomes widespread.

ASEAN-5 countries have adopted a variety of regulatory responses for dealing with cryptocurrencies:

  • The central bank of Indonesia issued a statement in 2014 saying that Bitcoin and other virtual currencies are not legitimate payment instruments and may not be used for payment in Indonesia. That statement was affirmed in January 2018. The central bank prohibits all payment system operators and financial technology from processing transactions using virtual currencies.

  • The central bank of Malaysia issued a statement in 2014 saying that although it did not recognize Bitcoin as legal tender, the central bank would not impose prudential or consumer conduct regulations on cryptocurrency exchangers. In December 2017, the central bank announced that cryptocurrency exchangers would be designated as reporting entities under anti–money laundering laws.

  • The central bank of the Philippines adopted a cautious approach to cryptocurrencies. In June 2014, it released a warning regarding the proliferation of virtual currencies in the Philippines, citing that without authorities regulating these platforms, no institution could provide consumers protection and insurance in the event of financial losses. In February 2017, the central bank issued guidelines for cryptocurrency registration, operations management, and reporting requirements.

  • The central bank of Singapore indicated that it would not regulate cryptocurrencies but plans to stay watchful of the risks posed by the technology. The emphasis is more on the risks associated with activities surrounding cryptocurrencies.

  • The central bank of Thailand has repeatedly warned consumers and investors that cryptocurrencies are just electronic data with no intrinsic worth, whose value can vary rapidly based on market conditions. The central bank remains concerned about the general public’s potential lack of understanding on the subject. From a legal standpoint, regulations in place do not explicitly address the use of digital currencies.

The international standard-setter in the area of anti–money laundering and combating the financing of terrorism (AML/CFT) is the Financial Action Task Force (FATF). In 2015, it adopted guidance for the application of the AML/CFT standard in the area of virtual currency. The FATF has issued specific guidance for countries to impose customer due diligence obligations and other AML/CFT preventive measures on virtual currency service providers (IMF 2017a).

Conclusion

Sustaining financial stability will require continuous efforts in ASEAN-5 countries. Financial systems are much more resilient today than during the Asian financial crisis. The global financial crisis and the taper tantrum in 2013 were two “stress tests” that were passed without much trouble. But financial systems should always aim to be ready for the next stress episode.

Credit growth in ASEAN-5 countries accelerated significantly after the global financial crisis. However, there is no clear evidence of credit booms in any of these countries. It should be underscored that not all credit booms end in financial crisis. Often credit booms emerge in the context of a financial deepening process. High interconnectivity within financial systems and between financial systems and the rest of the economy highlight how financial distress in one sector of the economy can spill over to other sectors. Closely monitoring financial links across sectors is essential to ring-fence the propagation of adverse shocks.

Policymakers should carefully monitor and contain the rapid growth of corporate leverage using a combination of macro- and microprudential policies. In particular, there is a need to guard against a buildup of leverage and accumulation of unhedged foreign currency liabilities, as well as to monitor corporate liquidity and debt maturity to ensure sound debt-servicing capacity. Where necessary, preemptive measures such as debt rescheduling, capital requirements, and non–core asset disposal should be undertaken, particularly for highly leveraged corporations with low interest coverage ratios.

Household debt is high in some ASEAN-5 countries, entailing both macroeconomic and financial stability risks. Those risks could be contained with demand-side measures (such as limits on debt-service-to-income and loan-to-value ratios) and supply-side measures (such as limits on banks’ credit growth, loan contract restrictions, and loan loss provisions).

Because they can smooth credit cycles, macroprudential policies are a key pillar for containing the dangers of rapid credit growth. Financial system regulation and supervision and crisis management frameworks are other key pillars for resilience. The Basel III standards should be a benchmark that all countries aspire to meet. Similarly, the Key Attributes for Effective Resolution of Financial Institutions are the relevant metric for resolution frameworks. Regulatory frameworks for cryptocurrencies are still evolving, but they should balance containing risk against promoting innovation.

References

Chapter 10 examines financial integration from a cross-border perspective.

See Chapter 3 for corporate restructuring and deleveraging since the Asian financial crisis.

Bloomberg Finance L.P.’s coverage of nonfinancial corporations comprises publicly listed entities with published balance sheet information.

Fibonacci retracement is a popular technical analysis tool that shows the possible price-level movements of an underlying asset (foreign exchange in this case). It takes two extreme points (usually a major peak and a trough), computes the distance between them, and, using some key Fibonacci ratios, identifies a range for price movements.

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