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Good Earning Capacity Gives Rated Banks In Emerging Markets A Buffer From COVID-19's Effects

S&P Global Ratings believes that the COVID-19 pandemic will continue to dominate the credit story for emerging markets (EMs) in 2021. We think that vaccine rollouts and exceptionally accommodative monetary policy from developed markets' central banks will help recovery and financing conditions for emerging markets. However, we still expect the asset quality indicators of banks in these markets to weaken.

We analyzed the top 3 rated banks in 15 banking systems among the largest emerging market economies: Argentina, Brazil, Chile, China, Colombia, India, Indonesia, Malaysia, Mexico, the Philippines, Russia, Saudi Arabia, South Africa, Thailand, and Turkey. We have estimated these banks' credit loss absorptive capacity under different scenarios of nonperforming loan coverage by reserves using two simulations. In the first, we focused on banks' profitability (net operating income before provision) and any excess or deficit of provision compared with our coverage thresholds. In the second simulation, we incorporated the capital buffer that banks have in our calculation of their risk-adjusted capital (RAC) ratio potentially more than the threshold for a weaker assessment of capital and earnings.

Overall, we estimate that the rated banks we used in our sample can absorb a shock of $491 billion-$602 billion with limited automatic impact on capitalization, and up to $1.29 trillion while mechanistically hitting the boundaries for a potentially weaker assessment of capital and earning under our criteria. This corresponds to 4.5-11.8 percentage point increases in their nonperforming loans. The largest absolute capacity to absorb losses lies with Chinese banks, which dominate the pack by virtue of their size. When compared with total lending, some Latin American institutions stand out, while banks in South Africa have the thinnest margin. At year-end 2020, we estimate the total lending of the banks in our sample at around $10.6 trillion.

Of note, these numbers hide a lot of differences between banks in our sample. Equally, these numbers do not necessarily speak to the potential movement of bank ratings because they cover only one narrow angle of banks' credit stories, even if they provide valuable insight for our analysis.

S&P Global Ratings believes there remains high, albeit moderating, uncertainty about the evolution of the coronavirus pandemic and its economic effects. Vaccine production is ramping up and rollouts are gathering pace around the world. Widespread immunization, which will help pave the way for a return to more normal levels of social and economic activity, looks to be achievable by most developed economies by the end of the third quarter. However, some emerging markets may only be able to achieve widespread immunization by year-end or later. We use these assumptions about vaccine timing in assessing the economic and credit implications associated with the pandemic (see our research here: As the situation evolves, we will update our assumptions and estimates accordingly.

Rated EM Banks Are Highly Profitable

We used the top 41 banks we rate in our 15 EM countries. In each system, we have selected the top 3 rated banks. For some systems, we rate less than three banks, the overall size of our sample totaled 41. Moreover, banks we rate in one system are not necessarily among the system's largest. Based on reported numbers, rated EM banks' profitability still compares favorably internationally (see chart 1).

Chart 1


Three reasons explain this strong performance:

  • A hefty interest margin, explained for some countries by the low cost of funding and for others by the absence of an alternative to the banking system for the economy's financing. Interest margin for our sample of rated banks reached 5% in 2020 and declined slightly from 2019 levels due to lower global interest rates. Moreover, rated EM bank revenue remains skewed toward interest income, which represented around 70% of total revenue in 2020 (see chart 2).

Chart 2


  • Investment banking's contribution income remained limited, at around 15% of total revenue in 2020. We understand that a portion of this revenue (for example, income from foreign currency exchange) could be seen as sustainable.
  • Bank efficiency is good (see chart 3). The cost-to-income ratio for rated EM banks reached 45% on average in 2020. Low cost of labor, high margins, branch network optimization, and use of technology explain this relatively low level.

Chart 3


Under our base-case scenario, we expect banks' profitability to deteriorate in 2020-2021 because of the pandemic's impact on the economies of some EMs. We expect continuing-but-muted lending growth, lower interest margin, and higher credit losses. In our view, the regulatory forbearance measures enacted by EM governments have helped but as they are due to be lifted in 2021, the positive impact on asset quality indicators will fade away progressively.

How Much In Credit Losses Can Rated Banks Take?

To assess banks' buffers against credit losses, we have conducted two simulations using three scenarios. The first simulation starts from our estimates of banks' net operating income before loan loss provision projection for 2020 as these already account for any negative impact of lower interest margin and declining lending growth because of the pandemic. We then looked at the existing stock of nonperforming loans (or assets, depending on the system and using the last available observation and sometimes year-end 2019 data if these are higher than the most recent available observations). We compared this stock to the existing loans loss provisions using three assumptions:

  • Scenario 1: A 70% coverage of the existing stock of NPLs. This is sufficient in most of the systems based on prior loss experience.
  • Scenario 2: A 100% coverage of the existing stock of NPLs. Here, we pushed the stress a bit further and assume that recovery prospects will differ from historical performance due to the pandemic. In addition, given regulatory forbearance measures, we think that the full extent of asset quality deterioration because of the pandemic is yet to show.
  • Scenario 3: A 120% coverage of the existing stock of NPLs. This factored in any additional provisions banks might take on with IFRS 9 Stage 1 and Stage 2 loans.

Looking at the profit and loss statement gives only a partial view of banks' loss absorption capacity. To complement that, we use a second simulation where we have used banks' projected RAC ratios stripping out the existing margin in each RAC ratio compared with the lower threshold typically associated with maintaining the same assessment of capital and earnings. This margin was then converted into loan loss absorption capacity using the coverage ratio assumption. These numbers do not necessarily speak to the potential rating movement because they are covering only one narrow angle of banks' credit story. For example, our assessment of risk position serves to refine the view of a bank's actual and specific risks beyond the conclusion arising from the standard assumptions in the capital and earnings analysis. Therefore, a RAC projection falling under a certain threshold would not automatically lead to a lower rating under our criteria. Conversely, we could lower our ratings on banks well ahead of credit losses leading to our projection falling below any of these thresholds. Nevertheless, these numbers do provide valuable insight in our analysis.

Chart 4

Rated banks' capacity to absorb losses varies by country

Overall, banks in our sample can withstand a shock of $491 billion-$602 billion based on simulation 1 and $891 billion-$1.29 trillion based on simulation 2 depending on the scenario. China accounts for 70%-80% of these numbers (see table 1), commensurate with its share of loans, because Chinese banks dominate our sample by the virtue of their size. At 120% coverage, this capacity allows for a 4.7-9.0 percentage point increase in Chinese banks' nonperforming loans (see table 2). By comparison, the Chinese commercial banking system has 2.7% of loans classified as special mention, and we estimate another 3.5% of loans under moratorium that are largely classified as normal. The sector's loan-loss provisions could provide a reasonable cushion for larger banks, but smaller banks might have less buffer. We expect the impact on the largest Chinese banks to be manageable, while smaller banks with aggressive risk appetites or high geographic concentration in heavily hit regions could see a material squeeze on their asset quality, performance, and capitalization. Our assumption for strong economic rebound this year contains the overall asset quality deterioration. Banks in our sample from Brazil, India, and Thailand are the top 3 in terms of absolute level of loss absorption while Argentina, the Philippines, and Russia rank at the bottom of our sample. India's stronger numbers reflect sample bias. The top 3 banks included in this analysis have better capital buffer than the sector. In Argentina and the Philippines, this result is also because we included only two banks in the sample and their overall size is much smaller than other banks in our sample. If we incorporate larger banks in Russia that we don't rate, the picture would show higher loss absorption capacity.

Table 1

Absolute Credit Loss Absorption Capacity
Bil. $
--Simulation 1-- --Simulation 2--
70% coverage 100% coverage 120% coverage 70% coverage 100% coverage 120% coverage


1 1 1 Argentina 2 2 1


49 46 44 Brazil 65 57 53


7 6 6 Chile 9 8 7


419 384 360 China 993 785 695


8 7 6 Colombia 11 9 7


34 26 21 India 55 41 33


14 13 12 Indonesia 14 13 12


8 6 5 Malaysia 25 18 15


12 11 10 Mexico 16 14 13


2 2 2 Philippines 3 2 2


8 2 (2) Russia 25 14 8

Saudi Arabia

12 11 10 Saudi Arabia 20 16 15

South Africa

7 4 2 South Africa 9 5 3


16 13 11 Thailand 34 26 22


5 4 3 Turkey 7 6 5
Total 602 536 491 Total 1,287 1,015 891
Source: S&P Global Ratings.

Compared with their lending book, some Latin American banks stand out while Russian and South African banks were at the bottom, because some of these banks start with a low level of coverage of NPLs by loan loss provisions compared with our assumptions. The small margin of the RAC ratio of South African banks vis-a-vis the threshold also contributes to low relative risk absorption capacity. Malaysian banks fared better when we incorporated the capital buffer.

Table 2

Credit Loss Absorption Capacity/Total Loans
Simulation 1 Simulation 2
70% coverage 100% coverage 120% coverage 70% coverage 100% coverage 120% coverage
Argentina 15.9 15.1 14.5 Argentina 26.3 22.3 20.5
Brazil 13.6 12.7 12.1 Brazil 18.0 15.8 14.6
Chile 4.7 4.2 3.9 Chile 6.1 5.2 4.7
China 5.4 5.0 4.7 China 12.8 10.1 9.0
Colombia 6.5 5.3 4.6 Colombia 9.0 7.1 6.1
India 5.5 4.2 3.3 India 8.9 6.6 5.3
Indonesia 8.0 7.3 6.8 Indonesia 7.8 7.1 6.7
Malaysia 2.7 2.1 1.7 Malaysia 8.5 6.1 5.1
Mexico 8.6 8.0 7.6 Mexico 11.4 10.0 9.2
Philippines 5.9 5.2 4.7 Philippines 6.9 5.9 5.3
Russia 3.0 0.8 (0.6) Russia 9.2 5.1 3.0
Saudi Arabia 5.2 4.8 4.5 Saudi Arabia 8.8 7.3 6.6
South Africa 3.3 1.8 0.8 South Africa 4.2 2.4 1.3
Thailand 6.8 5.7 4.9 Thailand 15.0 11.4 9.6
Turkey 7.9 6.5 5.6 Turkey 11.8 9.2 7.8
Weighted average 5.5 4.9 4.5 Weighted average 11.8 9.3 8.2
Source: S&P Global Ratings.

Finally, to assess the magnitude of the calculated loss absorption capacity, we have compared the results of scenario 2 with individual banks' total loans, our expectations of cost of risk for 2020 and our calculated "normalized losses," which we calculate as part of its RAC Framework and which we use here as a proxy for expected losses. Brazilian banks have the highest margin compared with total loans, in our sample, but Saudi banks stand out when we compare the credit loss absorption capacity with the cost of risk for 2020. Finally, adding the capital buffer, leads to somewhat similar results. South African banks appear to have the lowest credit loss absorption capacity in our sample even when we factor capital buffer.

Chart 5


Chart 6


Factors That Might Affect Bank Ratings In Emerging Markets

Many banks in this sample have mitigating factors that could help them withstand a weakening on their capital positions and maintain the rating. Brazilian, Mexican, Argentine, and South African banks have stand-alone credit profiles (SACP) higher than the final ratings by one-to-four notches. As such, a hypothetical one-notch downward revision to the SACP due to a weaker capital ratio simulated in this analysis would not result by itself in a downgrade. For two of the three Colombian banks, a hypothetical one-notch downgrade of their SACP would be compensated by government support. This is also the case for the three Saudi banks. In contrast, Chilean banks' weakening capital positions could lead to a downgrade. Finally, Turkish banks rely on economic change. We anticipate that strong economic rebounds in 2021 and recent monetary policymaking decisions should help stabilize the lira and reduce the probability of a more severe deterioration sharply affecting the banks' financial profiles, limiting the risks.

Major Brazilian banks have significantly boosted their provisioning coverage to protect their balance sheets against COVID-19-related losses, and have remained profitable thanks to their healthy margins, efficiency improvements, and revenue diversification. As such, they show good buffers. The buffers of sample banks in Argentina have improved following moderate credit growth (below inflation), no dividend distributions (as part of restrictions in the country), and still-high profitability despite inflation and economic contraction, helped by high yields from holdings in central bank securities and other one-time effects. In contrast, Buffers in Chile have been somewhat eroded by delays in implementing Basel III standards (effective application is by the end of the year), potentially exerting pressures on some entities should the recovery face delays or the economy deteriorate. Authorities have taken actions to temper the effects of the pandemic in 2020-2021 and social unrest events in 2019.

Large Mexican banks entered the pandemic with healthy balance sheets, sound profitability, healthy loan-loss reserves that fully cover nonperforming assets (NPAs), and solid risk-adjusted capitalization. These factors provide good buffers against a weak economy and challenging operating environment. In Colombia, large banks arrived with NPAs at above-average historical levels and risk-adjusted capital ratios that we assess in the weak or moderate categories. This reflects large amounts of goodwill in their balance sheets and significant exposure to Central American countries (estimated at about 30% of their balance sheets), which in general face higher economic risks than Colombia, representing higher risk weights. In our view, these factors limit these banks' capacity to increase their buffers.

Although Russian banks face elevated risks due to the pandemic, we expect the system to be resilient. We think the country's economy can absorb the shock and economic growth will likely resume in 2021, if oil prices are supportive and the global economy starts recovering. We consider most large Russian banks better prepared to cope with adverse economic conditions than they were before past recessions. They started 2020 with stronger balance sheets, strengthened capital ratios, and improved risk management frameworks. Also, positively for these banks, their exposure to the sectors most affected by the coronavirus pandemic (such as commercial real estate, small and midsize enterprises (SMEs), travel and tourism, entertainment, and leisure) is limited, supporting the sector's credit quality.

South and Southeast Asian (SSEA) banks in this sample have multifaceted rating factors that encompass a wide range of factors, from economic conditions to bank-specific exposure to segments vulnerable to COVID-19. The negative outlook on Malaysia banks reflects the outlook on Malaysia. Banks' asset quality hinges critically on the employment situation in the country, given 58% of the system's loan book is exposed to the household sector. In our base-case scenario, we expect unemployment to be largely stable, increasing to 4.5% in 2020 and moderately declining to 4.0% in 2021. For Thailand, Indonesia, and Philippine banks, we believe economic risk are elevated due to COVID-19. Thailand is vulnerable given the country's reliance on tourism and widening economic imbalances with already-high household and corporate leverage. Indonesia banks saw restructured loans grew to about 18% of total loans in 2020, from mid-single digits in 2019. Regulatory forbearance allowing restructured loans to be classified as performing through March 2022 have mitigated damage to bank financials. We believe underlying deterioration in asset quality could become more apparent in 2022 after regulatory relaxation expires. SMEs have been one of the most affected segments due to thin cash buffers, narrow margins, and limited resources, compared to large corporates. Banks with a retail and SME focus have reaped the benefits of higher yields during good times but are subject to greater risk during times of stress. Capital and provisioning buffers built up over the years have supported SSEA banks through the economic downturn. Multiple stimulus packages to support businesses and minimize unemployment have also mitigated the direct impact of COVID-19 on banks. We believe most SSEA governments are highly supportive of the country's banking system, and will provide timely financial support to ensure stability, if needed.

State-owned Indian banks benefit from ongoing capital support by the Government. The Indian government has committed capital infusion of 400 billion rupees in state-owned banks by March 2022. Private sector banks are also bolstering their balance sheets by raising additional capital.

Related Research

This report does not constitute a rating action.

Primary Credit Analyst:Mohamed Damak, Dubai + 97143727153;
Secondary Contacts:Cynthia Cohen Freue, Buenos Aires + 54 11 4891 2161;
Geeta Chugh, Mumbai + 912233421910;
Natalia Yalovskaya, London + 44 20 7176 3407;
Ming Tan, CFA, Hong Kong + 852 2532 8074;
Ivan Tan, Singapore + 65 6239 6335;

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