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Scenario Analysis: How Resilient Are Middle-Market CLO Ratings (2023 Update)?

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Private Credit Could Bridge The Infrastructure Funding Gap

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The Opportunity Of Asset-Based Finance Draws In Private Credit

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Private Credit Casts A Wider Net To Encompass Asset-Based Finance And Infrastructure

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Scenario Analysis: How Resilient Are Middle-Market CLO Ratings (2023 Update)?

(Editor's Note: We periodically generate and publish scenario analysis on our outstanding BSL CLO and middle market CLO ratings. See the Related Research section at the end of this article for some of the previous articles.)

Interest in middle-market (MM) collateralized loan obligations (CLOs) has grown significantly in recent years, driven by the additional spread offered by middle-market CLO tranches over like-rated broadly syndicated loan (BSL) CLO tranches and increased interest in private credit. MM CLOs represent a fast-growing part of the U.S. CLO market, with year-to-date issuance (through September 2023) up 95% over the same period in 2022, while BSL CLO new issuance was down 32.5% over the same period. Also, investors have taken note of the strong rating performance MM CLOs demonstrated during the pandemic. During 2020, S&P Global Ratings lowered just 1.3% of outstanding MM CLO tranche ratings (seven out of 553 outstanding at the time), compared to about 13% (493 out of 3,786) for BSL CLO ratings.

The companies that issue the loans in MM CLOs, like other highly leveraged companies, have felt the impact of rising interest rates and slowing economic growth. As of September 2023, we have nearly 2,500 credit estimates outstanding on these loan issuers. Since the fourth quarter of 2022, credit estimate downgrades have exceeded credit estimate upgrades, following trends in the BSL loan market, with software companies and healthcare providers and services companies leading the way. In this environment, higher-for-longer interest rates could be a drain on the free operating cash flow of small growth companies with high debt levels. Combined with residual inflation, supply issues, and labor constraints, margin compression could lead to more credit estimate downgrades or an increase in loan default rates.

Amid the rising interest rates and slowing economic growth, we again ask how would MM CLO ratings perform if subjected to another downturn? To answer that question, we applied a series of hypothetical stress scenarios to 137 of our rated MM CLO transactions (as we have for the past two years), generating quantitative analysis for each one using our CLO rating models (CDO Evaluator and S&P Cash Flow Evaluator) to assess the potential impact on the CLO ratings. Given the high proportion of CLOs that are outside their reinvestment period, this year, we included both reinvesting and amortizing MM CLOs in our stress test (96 reinvesting and 41 amortizing transactions). As with our previous stress scenario analyses for both BSL and MM CLOs, the stress scenarios in this article show the CLO structure protecting rated noteholders, especially the senior CLO tranches. They also show that MM CLOs can withstand comparable asset default rates with less impact on the CLO ratings than BSL CLOs.

For more information on the performance of credit estimated loan issuers and middle market CLOs, see "SLIDES: Middle-Market CLO And Private Credit Quarterly: Navigating The Post-Pandemic Economy," published July 24, 2023. These slides are updated and published quarterly.

Some Differences Between MM And BSL CLOs

MM CLOs are a segment of the U.S. CLO market, representing about 17% of total S&P Global Ratings-rated U.S. CLOs by par value of the assets, and slightly less by transaction count. They differ from BSL CLOs in some significant ways.

MM CLOs are backed primarily by senior secured loans to smaller companies, typically those with EBITDA of $100 million or lower (and often much lower). Many of the companies that issue the loans in MM CLO collateral pools aren't publicly rated, and instead have credit estimates assigned for purposes of the CLO analysis (see "Anatomy of a Credit Estimate: What It Means and How We Do It," published Jan. 14, 2021). Some MM CLO transactions also include loans from larger unrated obligors and have been labelled as private credit CLOs by market participants, although for the purposes of this article, we'll include both under the MM CLO moniker. The proportion of loans from credit-estimated versus rated companies varies significantly from one MM CLO to another, but all MM CLOs have a much higher proportion of credit-estimated assets than BSL CLOs.

Because companies in the MM CLOs are smaller than those in BSL CLOs, MM CLOs have more exposure to loans from lower-rated (or credit estimated) obligors than do BSL CLOs. As of September 2023, the average U.S. BSL CLO exposure to loans from companies rated 'B-' and 'CCC' was about 28.6% and 7.1% of total assets, respectively; the proportion for MM CLOs was much higher at about 71.2% and 12.3%, respectively. Note that these figures for MM CLOs include loans with either a credit estimate or a rating. In addition to having a lower-quality credit profile, most MM CLO portfolios tend to have lower diversity, shorter average tenor of the loan collateral, and higher loan spreads relative to BSL CLO portfolios (see tables 1-4 below). However, while there is less diversification within MM CLO collateral pools, there is much greater diversification across MM CLOs issued by different managers, as MM CLO loans are often unique to a single collateral manager or small club of managers (see slides 20-22 in "SLIDES: Middle-Market CLO And Private Credit Quarterly: Navigating The Post-Pandemic Economy," published July 24, 2023).

To compensate for this, MM CLOs tend to have more par subordination for their rated tranches than BSL CLO transactions. There is significant variance in transaction structures, with some MM CLOs having just two classes of notes (a senior rated note and equity), while others look more like a BSL CLO structure, with notes issued from 'AAA' down through 'BB' (and sometimes even a 'B'). The variance in subordination at each CLO tranche rating category is much wider for MM CLOs than it is for BSL CLOs. Generally, MM CLOs with a greater proportion of rated assets (and fewer credit estimates) in their collateral pool have par subordination (and tranching) that looks more like that seen in a typical BSL CLO.

Chart 1

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Chart 2

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Chart 3

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Chart 4

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Generating The MM CLO Rating Stress Scenarios

As we have done for the past two years, we again produced rating stress scenarios for our rated MM CLOs to assess how they might perform under different economic scenarios. The default rate across MM CLO portfolios in a significant downturn would potentially be correlated by the manager, in our view, as many loans within MM CLO portfolios are specific to a single manager or small group of managers. For our stress runs, to maintain consistency across the sample for our four scenarios, we assumed each portfolio experiences the same default level, which are applied with increasing levels of asset default stress to see how the CLO ratings would respond.

This is different from the approach we use for our BSL CLO rating stress analysis, where we sort the performing companies issuing the loans in the collateral pools from weakest to strongest (first by rating, then by loan price) and then hit the stress scenario default targets by starting at the bottom of the list and working our way up. In the BSL CLO rating stress scenarios we have published, the specific asset defaults within each CLO varies by their exposure to the companies we assumed would default. This approach makes less sense for MM CLOs, in our view, because the portfolios are starting with a high proportion of assets from 'B-' and lower rated or credit estimated companies.

For all the stress scenarios outlined below, we excluded CLO combo notes and X notes from the analysis. Our sample of MM CLOs included 137 CLOs (96 reinvesting and 41 amortizing). There was a wide range of structures as well as portfolios, with some of the portfolios being something of a hybrid of both MM and BSL assets. Our specific stress assumptions were:

  • Scenario One: 10% of the assets default with a 50% recovery;
  • Scenario Two: 15% of the assets default with a 50% recovery;
  • Scenario Three: 20% of the assets default with a 50% recovery; and
  • Scenario Four: 30% of the assets default with a 50% recovery.

Chart 5

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None of the above scenarios are meant to be predictive of any specific outcome for the collateral within CLO transactions, or for the most stressful scenarios to even be particularly plausible. But we think the hypothetical scenarios provide insight into how MM CLO ratings might respond to varying stress levels. By setting up the first four scenarios in the way we have, with a simple progression of increasingly severe assumptions, we hope to allow CLO investors and others to make their own view of potential collateral default rates and gauge the potential CLO rating impact. If you have ideas for additional stress scenarios you'd like to see included in future articles, feel free to reach out to the primary analytical contacts listed for this article.

Differences between MM and BSL CLO stress scenarios

There are some differences between our MM and BSL CLO stress scenarios in terms of our assumptions for default rates and rating transition on the non-defaulting loans.

Compared to the rating stress scenarios we published a few months ago for our rated BSL CLO transactions (see "Scenario Analysis: U.S. BSL CLO Rating Performance Under Four Hypothetical Stress Scenarios (2023 Update)," published July 18, 2023), the default rate assumptions we use here are more punitive (see table 1). We do this to account for the differences in rating/credit estimate profiles for MM and BSL CLO collateral pools. Note that the more stressful default scenarios outlined in this article, like the 20% default scenario in the BSL CLO rating stress article, are well outside the range of default forecasts even under pessimistic scenarios, but we include them as interesting hypotheticals.

Table 1

MM CLO vs. BSL CLO rating stress scenario assumptions
Release date 'CCC' bucket (%) Defaults (%) Recoveries (%)
BSL CLOs July 2023 10, 20, 30, 40 5, 10, 15, 20 45
MM CLOs October 2023 N/A 10, 15, 20, 30 50
MM--Middle market. BSL--Broadly syndicated loan. CLO--Collateralized loan obligation. N/A--Not applicable.

Unlike the BSL CLO rating stresses we've published, the stresses in this article do not assume any rating transition on the non-defaulting loans in the CLO collateral pools (i.e., a 'CCC' bucket stress), and the stress scenarios use a higher recovery rate assumption than that used for the BSL CLO rating stress scenarios (50% versus 45% for the BSL CLO stresses). At first glance, this may seem counterintuitive, given that the companies that issue the loans in MM CLO collateral pools are smaller and have a weaker ratings/credit estimate profile than the companies in BSL CLOs.

The lack of a 'CCC' bucket stress makes sense, in our view, because so much of the MM CLO collateral is already rated (or credit-estimated) at 'b-' or lower to start with. We believe the 50% recovery rate assumption for the loans we're defaulting in these stress runs (versus the 45% assumption for our most recent BSL CLO rating stress scenarios) also makes sense when we consider the fact that loans in MM CLOs are generally not covenant lite, and they tend to have much more constrictive loan document provisions than loans in BSL CLOs, especially for companies further down the EBITDA scale.

MM CLO structures vary more than BSL CLO structures

As noted earlier, MM CLO structures vary more than BSL CLO structures, both in terms of average par subordination for a given tranche rating level, and in which tranches are issued in the first place. About half of our sample consisted of MM CLOs include junior tranches (defined here as tranches with initial ratings in the 'BB' or 'B' categories). These tend to be MM CLOs that include a greater proportion of rated (as opposed to credit estimated) collateral, and unsurprisingly, they have structures more akin to what you would see in a BSL CLO, including lower-rated tranches (see table 2). They also tend to have lower (that is, more BSL CLO-like) subordination levels (see table 3 below).

For example, across MM CLOs issued with only investment-grade-rated notes, the average 'BBB' tranche par subordination was 18.8%; this compares to 17.6% for MM CLO structures that include speculative grade tranches at origination. Additionally, the transactions that include junior tranches tend to have a higher obligor count within their portfolios.

Table 2

Average proportion of credit estimated assets and average obligor count
Reinvesting MM CLO sample cohort(i) Avg % credit estimated Avg. no. of obligors
MM CLOs issued without junior tranches 83.1 89.7
MM CLOs issued with junior tranches 78.6 124.5
(i)Excludes transactions issued without a 'AAA (sf)' rated tranche. CLO--Collateralized loan obligation. MM--Middle market.

Table 3

Average subordination for MM CLO tranches
MM CLOs(i) Average Of 'AAA (sf)' (%) Average Of 'AA (sf)' (%) Average Of 'A (sf)' (%) Average Of 'BBB (sf)' (%) Average Of 'BB (sf)' (%)
MM CLOs issued without junior tranches 43.3 33.6 24.9 18.8
MM CLOs issued with junior tranches 42.7 32.4 24.2 17.6 11.7
(i)Excludes transactions issued without a 'AAA (sf)' rated tranche. CLO--Collateralized loan obligation. MM--Middle market.

The Results Of The Stress Scenarios

Table 4 shows the results of the stress scenarios for the full sample of 137 MM CLOs we tested. To see the stress scenario results broken out between CLOs in their reinvestment period and amortization period, see table 5 in the Appendix.

Table 4

Scenario cash flow results - full sample
Downgrade notches under scenario
Current rating category 0 (%) -1 (%) -2 (%) -3 (%) -4 (%) -5 (%) -6 (%) -7 or more (%) Avg. notches Speculative grade (%) 'CCC' category (%) Below 'CCC-' (%)
Scenario One: 10% default/5% par loss
'AAA' 98.90 1.10 -0.01
'AA' 100.00 0.00
'A' 99.27 0.73 -0.01
'BBB' 96.58 3.42 -0.03 3.42
'BB' 86.57 7.46 1.49 1.49 1.49 1.49 -0.34 100.00 2.99 1.49
Scenario Two: 15% default/7.5% par loss
'AAA' 98.17 1.83 -0.02
'AA' 98.83 1.17 -0.02
'A' 94.16 3.65 1.46 0.73 -0.09
'BBB' 90.60 6.84 2.56 -0.12 5.13
'BB' 65.67 20.90 4.48 1.49 1.49 1.49 4.48 -0.82 100.00 2.99 4.48
Scenario Three: 20% default/10% par loss
'AAA' 93.04 6.96 -0.07
'AA' 95.91 2.92 1.17 -0.05
'A' 63.50 23.36 11.68 0.73 0.73 -0.52 0.73
'BBB' 48.72 41.03 5.98 2.56 1.71 -0.68 48.72
'BB' 25.37 28.36 8.96 11.94 2.99 7.46 4.48 10.45 -2.33 100.00 14.93 10.45
Scenario Four: 30% default/15% par loss
'AAA' 53.11 45.79 1.10 -0.49
'AA' 55.56 19.30 23.98 1.17 -0.73
'A' 11.68 3.65 29.20 16.79 32.85 5.11 0.73 -2.74 10.95
'BBB' 5.98 45.30 13.68 17.09 11.11 4.27 2.56 -2.14 94.02 0.85 1.71
'BB' 8.96 4.48 2.99 1.49 82.09 -6.06 100.00 1.49 82.09

We note both similarities and differences between this year's results and prior year results. Specifically, the 2023 results are very similar to 2022, but there are some material differences between these two sets of results and the 2021 results. Chart 6 below compares the average-notch downgrade at different CLO tranche levels under the 20% default scenario for 2021, 2022, and 2023 for samples of reinvesting transactions only. The 'A' and 'BB' tranches in the sample this year seem to be a tiny bit more resilient under this stress, while the 2021 results were notably weaker.

Chart 6

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This is because the MM CLOs we tested last year included transactions that had gone through the 2020 pandemic economic downturn and experienced collateral credit deterioration (and for some of the CLOs, par loss and overcollateralization [O/C] test cushion deterioration). MM CLOs made it through the 2020 economic dislocation with very few tranche ratings being lowered (seven, to be exact), but the stress left some of the CLOs with less cushion as noted in the 2021 results. Since then, there has been an uptick in new issuance across the MM CLO space, some of which are new managers issuing their first deal. Additionally, the count of MM CLOs within our sample today with a 'BB' tranche has increased notably since our 2021 study.

MM CLOs Perform Better Than BSL CLOs In The Amortization Phase

Across both the BSL CLO and MM CLO markets, a historically large proportion of transactions are currently outside of their reinvestment periods. In part, this is due to a very limited number of CLO resets over the past year-and-a-half. Because of this, we decided to include amortizing transactions in our sample this time, many of which were reinvesting during the pandemic downturn in 2020.

In our BSL CLO rating stress tests (see "Scenario Analysis: U.S. BSL CLO Rating Performance Under Four Hypothetical Stress Scenarios (2023 Update), published July 18, 2023), amortizing transactions showed materially weaker performance than reinvesting CLOs. For the MM CLOs we stressed in this article, however, the gap in rating outcomes from the stress tests differed less for amortizing vs. reinvesting CLOs (see chart 7). This is partly because the third-quarter credit metrics for amortizing and reinvesting MM CLOs are fairly close to each other in ways that they're not for BSL CLOs:

  • The average 'CCC' basket (including exposures without an outstanding credit estimate or rating) for an amortizing MM CLO is about 1% higher than the average reinvesting MM CLO (17.6% vs. 16.5%, respectively), compared to an over three-point gap for amortizing vs. reinvesting BSL CLOs (10.5% vs. 6.8%, respectively).
  • The average S&P Global Ratings' weighted average rating factor (SPWARF) for an amortizing MM CLO is about 33 points higher than the average reinvesting MM CLO (slightly worse in ratings distribution; 3842 vs. 3809), versus a 167-point gap for the average amortizing vs. reinvesting BSL CLO (2911 vs 2744).
  • Most reinvesting MM CLOs maintained their target par balances while reinvesting during the pandemic, unlike most BSL CLOs, which lost some par during that period.

Chart 7

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As these MM CLOs amortize, given these transactions have higher subordination levels to begin with, the model results under our stresses improve more notably relative to the equivalent paydown across a typical BSL CLO, especially if the transaction has experienced minimal par loss within the residual portfolio. In fact, some amortizing MM CLOs are above their target par balances.

Some Testing Limitations And Caveats

For the purposes of our scenario testing, we generated a quantitative analysis for our sample CLOs using the same tools we use when rating transactions. Our CDO Evaluator credit model assesses the overall credit quality of a portfolio of assets based on the rating and maturity of each asset, as well as the correlation between assets, and produces expected asset default rates at stresses commensurate with our various CLO rating levels. Our S&P Cash Flow Evaluator model, on the other hand, is used to assess the ability of the tranches in a given CLO to withstand loss rates under various interest rate and default timing scenarios (see "S&P Global Ratings' CLO Primer," published Sept. 21, 2018). While ratings are assigned by committee and our criteria encompass a variety of qualitative and quantitative components, looking at the output of these two models for a given CLO portfolio and structure should provide an indication of the ratings a surveillance committee might assign following a given stress scenario.

Also, a few caveats worth highlighting:

  • The stresses we selected for the scenarios are hypothetical and not meant to be predictive or part of any outlook statement.
  • The stresses we selected aren't meant to calibrate to any of the economic scenarios we associate with our ratings.
  • The stresses were applied at time zero in the analysis; in reality, defaults would occur over a longer time span, giving the O/C tests time to pay down some of the senior CLO note balances and replenish some of the senior tranche credit enhancement.
  • The results are based on the application of the models we use to rate CLOs; a rating committee applying the full breadth of our criteria and including qualitative factors under our criteria might in some instances assign a different rating than the quantitative analysis would indicate.

Study Conclusion: The Fundamentals Of The MM CLO Structure Prove To Be Resilient Against Shocks

As with the previous rating stress analyses we've published for both BSL and MM CLOs, the analysis outlined in this article shows the fundamentals of the MM CLO structure protecting senior noteholders, with 98.9% of CLO 'AAA' tranche ratings either experiencing an affirmation or one-notch downgrade to 'AA+' even under our most punitive scenario (30% of the obligors are immediately defaulted).

Outcomes for tranches further down the CLO capital stack depend upon the severity of the assumptions applied, but no tranche rated 'A' or higher defaulted under any of our scenarios. Finally, we note that the 'AAA' CLO tranche downgrade rate in the real world would likely be lower than indicated in the stress test transition tables above. This is because our rating committees sometimes take into account qualitative considerations, our expectations for future senior tranche pay downs, and other factors beyond the results of the quantitative analysis done for this article.

Appendix: Scenario Results Broken Out By Reinvesting and Amortizing MM CLOs

Table 5 below shows the stress test results for the same set of 137 MM CLOs shown in table 4 above, but separated into two mutually-exclusive cohorts: 96 MM CLOs still within their reinvestment period at the time the scenario analysis was generated, and 41 CLOs in their amortization (post-reinvestment) period.

Table 5

Scenario cash flow results across amortizing and reinvesting transactions
Downgrade notches under scenario
Current rating category 0 (%) -1 (%) -2 (%) -3 (%) -4 (%) -5 (%) -6 (%) -7 or more (%) Avg. notches Speculative grade (%) 'CCC' category (%) Below 'CCC-' (%)
Scenario One: 10% default/5% par loss - amortizing transactions
'AAA' 100.00 0.00
'AA' 100.00 0.00
'A' 100.00 0.00
'BBB' 100.00 0.00
'BB' 72.22 22.22 5.56 (0.33) 100.00
Scenario One: 10% default/5% par loss - reinvesting transactions
'AAA' 98.56 1.44 (0.01)
'AA' 100.00 0.00
'A' 98.98 1.02 (0.01)
'BBB' 95.12 4.88 (0.05) 4.88
'BB' 91.84 2.04 2.04 2.04 2.04 (0.35) 100.00 4.08 2.04
Scenario Two: 15% default/7.5% par loss - amortizing transactions
'AAA' 98.39 1.61 (0.02)
'AA' 100.00 0.00
'A' 95.24 4.76 (0.05)
'BBB' 89.19 5.41 5.41 (0.16) 2.70
'BB' 66.67 16.67 5.56 5.56 5.56 (0.72) 100.00 5.56
Scenario Two: 15% default/7.5% par loss - reinvesting transactions
'AAA' 98.08 1.92 (0.02)
'AA' 98.39 1.61 (0.03)
'A' 93.88 3.06 2.04 1.02 (0.10)
'BBB' 91.46 7.32 1.22 (0.10) 6.10
'BB' 65.31 22.45 4.08 2.04 6.12 (0.86) 100.00
Scenario Three: 20% default/10% par loss - amortizing transactions
'AAA' 96.77 3.23 (0.03)
'AA' 100.00 0.00
'A' 83.33 9.52 7.14 (0.24)
'BBB' 67.57 18.92 8.11 5.41 (0.51) 29.73
'BB' 27.78 33.33 5.56 11.11 5.56 5.56 11.11 (2.17) 100.00 11.11 11.11
Scenario Three: 20% default/10% par loss - reinvesting transactions
'AAA' 91.83 8.17 (0.08)
'AA' 94.35 4.03 1.61 (0.07)
'A' 56.12 28.57 13.27 1.02 1.02 (0.62) 1.02
'BBB' 41.46 50.00 4.88 1.22 2.44 (0.73) 56.10
'BB' 24.49 26.53 10.20 12.24 2.04 10.20 4.08 10.20 (2.39) 100.00 16.33 10.20
Scenario Four: 30% default/15% par loss - amortizing transactions
'AAA' 83.87 16.13 (0.16)
'AA' 84.44 6.67 8.89 (0.24)
'A' 35.71 11.90 28.57 7.14 11.90 4.76 (1.62) 4.76
'BBB' 16.22 51.35 8.11 8.11 10.81 5.41 (1.62) 83.78
'BB' 22.22 77.78 (5.67) 100.00 77.78
Scenario Four: 30% default/15% par loss - reinvesting transactions
'AAA' 43.27 55.29 1.44 (0.60)
'AA' 44.35 24.19 29.84 1.61 (0.92)
'A' 4.08 28.57 20.41 40.82 5.10 1.02 (3.13) 13.27
'BBB' 3.66 41.46 15.85 20.73 10.98 3.66 3.66 (2.32) 96.34 1.22 2.44
'BB' 4.08 6.12 4.08 2.04 83.67 (6.20) 100.00 2.04 83.67

Related Research

This report does not constitute a rating action.

Primary Credit Analysts:Stephen A Anderberg, New York + (212) 438-8991;
stephen.anderberg@spglobal.com
Daniel Hu, FRM, New York + 1 (212) 438 2206;
daniel.hu@spglobal.com
Secondary Contacts:Ramki Muthukrishnan, New York + 1 (212) 438 1384;
ramki.muthukrishnan@spglobal.com
Evan M Gunter, Montgomery + 1 (212) 438 6412;
evan.gunter@spglobal.com
Research Contributors:Victoria Blaivas, New York + 1 (212) 438 2147;
victoria.blaivas@spglobal.com
Dmytro Saykovskyi, New York + 1 (212) 438 1296;
dmytro.saykovskyi@spglobal.com

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