The global structured finance annual default rate fell to a 13-year low in 2020 of 1.4%, from 1.9% the previous year (see table 1). This was the third year since the 2009 financial crisis that the default rate has been under 2%, despite the global recession brought on by the economic stress of the COVID-19 pandemic.

All of the defaults last year were in the U.S. and Europe.

S&P Global Ratings had 32,511 ratings outstanding on global structured finance securities at the start of 2020. The global average change in credit quality (see definition in Appendix I) in 2020 turned negative for the first time since 2016, ending the year at -0.13 notches (see chart 1). The upgrade rate (the proportion of upgrades among all ratings outstanding) fell to 3.7% in 2020--the lowest annual upgrade rate since 2011--from 7.2% in 2019. The downgrade rate (measured as the proportion of downgrades, including defaults, among all ratings outstanding) increased to 7.6% in 2020 from last year's 13-year low of 4.7%.

Credit Performance: Divergence In Resilience Amid a Global Pandemic

The global structured finance 12-month-trailing default rate fell to 1.2%, the lowest year-end reading since 2007 (see chart 2). The 12-month-trailing default rates declined for both investment-grade ratings ('BBB-' or higher) and speculative-grade ratings ('BB+' or lower), to 0.1% and 3.3%, respectively. The default rates for both investment- and speculative-grade structured finance securities have stabilized since peaking in 2009 and resembled precrisis levels.

Region and sector comparisons

Structured finance credit performance in 2020 diverged significantly across sectors and regions. The commercial mortgage-backed securities (CMBS) sector reported the highest downgrade rates, specifically within the U.S. and Europe, at 14.6% and 18.5%, respectively (see chart 3). Downgrade rates across all sectors, except U.S. CMBS, held below their one-year averages. Upgrades were the most prominent in the asset-backed securities (ABS) sector in both the U.S. and Europe, with upgrade rates of 9.9% and 5.2%, respectively, in 2020. European residential mortgage-backed securities (RMBS) had an upgrade rate of 7.9%, while U.S. RMBS had an upgrade rate of 3.2%, surpassing its one-year average of 2.2%.

The U.S. single-name synthetic sector had the highest annual default rate in 2020, at 4.4%, well above its one-year average of 0.7% (see chart 4), followed by European CMBS and U.S. RMBS, at 3.1% and 2.6%, respectively. There were no defaults among European ABS and RMBS, Australian securities, Japanese securities, or securities outside the major regions. Aside from European CMBS, U.S. single-name synthetic was the only sector globally with a default rate in 2020 above its one-year average.

By region, the U.S., which had the most outstanding ratings at the start of the year, reported an upgrade rate of 3.6% in 2020, above its one-year average (see table 1). Europe, the second-largest region in terms of outstanding originations, saw its upgrade rate fall below the one-year average, to 4.8%. Australasia, the third-largest region by number of ratings outstanding at the start of the year, reported an upgrade rate of 4.9% in 2020, above its one-year average of 4.3%. The 2020 upgrade rate was the highest for other emerging markets at 34.2%, out of the 38 ratings outstanding at the beginning of the year.

Downgrade rates remained below one-year averages in every region except other emerging markets. In the U.S., the downgrade rate increased to 8.3% in 2020 from 5.1% in 2019, and the European downgrade rate rose to 3.6% from 1.6% over the same period.

The U.S. reported the highest annual default rate of 2020 at 1.6%, representing 436 ratings. In Europe, the annual default rate was 0.2%, representing eight defaults. There were no defaults outside the U.S. and Europe in 2020 among nearly 1,743 ratings outstanding at the start of the year.

By sector, ABS had the highest upgrade rate globally in 2020, at 9.5%, well above the one-year average of 4.7%. The RMBS upgrade rate of 3.6% also exceeded the one-year average of 2.5%. The CMBS sector led downgrades by far, with a downgrade rate of 14.9% in 2020, well above its one-year average of 12.7%.

The region-sector combination with the highest upgrade rate in 2020 was U.S. ABS, where we raised 9.9% of the ratings that were active at the beginning of the year, mainly attributed to elevated upgrades in the auto subsector, which accounts for one of the largest shares of U.S. ABS securities. Upgrade rates across most region-sector combinations were lower than their respective one-year averages, with the exception of U.S. RMBS, U.S. ABS, Europe ABS, and Australasia securities. The CMBS sector was the hardest hit by the economic lockdowns due to the global pandemic.

The region-sector combination with the highest downgrade rate in 2020 was European CMBS, at 18.5%, still below its one-year average of 22%. Downgrades were also prominent in U.S. CMBS, reporting a downgrade rate of 14.6%, the only region-sector combination to exceed its respective one-year average of 12.2%.

Across rating categories globally, the 'BBB' category reported the highest upgrade rate in 2020 at 7.0%. Additionally, upgrades were prominent in the 'BB' and 'A' rating categories, with respective upgrade rates of 6.2% and 5.8%. However, downgrades outweighed upgrades in almost every rating category in 2020. The downgrade rate was 10.9% for the 'BBB' category, 22.1% for the 'BB' category, and 8% for the 'A' category. The 'CCC' category had the highest default rate of 7.1%, well below the one-year average of 15.2%. Defaults in 2020 occurred in every rating category, with the exception of 'AAA'.

The overall investment-grade upgrade rate was 4% in 2020, above the one-year average of 3.4%, while the downgrade rate of 4.7% was well below the one-year average of 11.1%. The investment-grade default rate was well below its one-year average, at 0.1% in 2020. The only investment-grade rating category to not include a default was 'AAA'.

Table 1

Vintages

Structured finance credit performance continues to be differentiated by the year of issuance--or vintage--of securities. The fundamental credit characteristics and economic conditions surrounding a transaction's vintage can influence its credit behavior.

Segmenting global structured finance credit performance by transaction vintage reveals that the upgrade rates in 2020 among most vintages underperformed compared with the previous year. The highest upgrade rates were that of the 2009 and 2010 vintages, at 13.3% and 5.7%, respectively, both outperforming their one-year averages. More recent vintages have exhibited elevated levels of upgrades compared with older vintages. Only five vintages in 2020 displayed improved upgrade rates compared with the year prior.

Downgrade rates in 2020 across almost all vintages deteriorated from 2019. The 2008 vintage was one of the few exceptions--the downgrade rate improved to 1.8% in 2020 from 15.2% in 2019. The downgrade rates for the 2006 and 2007 vintages fell into the single digits, at 4.1% and 4.2%, respectively, following the weak credit performance these transactions exhibited during the financial crisis (chart 5).

The annual default rate was the highest in the 2005 vintage at 4.1% in 2020, remaining below its one-year average of 5.8% (chart 6). The 2001-2004 and 2012-2014 vintages reported default rates in 2020 higher than their one-year averages.

Ratings Performance: Ratings Have Historically Differentiated Default Rates

Our structured finance ratings express our opinions of securities' creditworthiness, which center on an assessment of default likelihood, rather than the likelihood of upgrade or downgrade. That said, our ratings also consider credit stability as a secondary factor.

Across global structured finance, upgrade and downgrade rates in 2020 were generally differentiated by the ratings at the beginning of the year. While downgrade rates increased across most rating categories, they were generally higher for lower rating categories, ranging from 22.1% for securities rated 'BB' to 5.2% for securities rated 'CC' (see chart 7). The only investment-grade rating category to record a double-digit downgrade rate in 2020 was the 'BBB' category, at 10.9%.

Downgrade rates across all structured finance securities were well below their one-year averages in every rating category. Upgrade rates were generally elevated for higher rating categories. Securities rated 'BBB' recorded the highest upgrade rate in 2020, at 7.0%.

We typically expect default rates to be lower for higher-rated securities, provided that observations are made over sufficiently long time horizons and large samples. Over shorter time frames or smaller samples, this relationship may not always hold, and default rates can vary over time.

For global structured finance, higher-rated securities were clearly associated with lower weighted average one-year default rates between 1976 and 2020 (see chart 8). Default rates in 2020 were generally higher at lower rating categories. Each rating category had at least one default in 2020, with the exception of 'AAA', which had no defaults. Securities we rated in the 'AA' category at the beginning of 2020 had a default rate of 0.05%, contrasting with a default rate of 7.1% for the 'CCC' category.

To further explore how well our structured finance ratings have rank-ordered creditworthiness over time, we can calculate cumulative default rates by rating category for various time horizons, as we do for our corporate default and transition studies. This approach constructs average multiyear cumulative default rates by first aggregating across static pools the period-to-period one-year marginal default rates that are conditional on the securities' survival (that is, nondefault) in the prior one-year period (see Appendix I for more details). This approach differs from the calculations we use in constructing the weighted average multiyear default and transition rates elsewhere in this study, where default rates are not conditional on survival.

The cumulative default rates (conditional on survival) based on our full data history--from the beginning of 1976 to the end of 2020--show that lower ratings have generally been associated with higher default rates and vice versa (see table 2). In other words, ratings appear to have successfully rank-ordered creditworthiness over each time horizon.

Table 2

Default rates calculated on a rolling basis for a given horizon (for example, five years) further demonstrate that this ratings-based rank ordering has generally remained in place over time, even as absolute default rates have fluctuated with differing levels of credit stress (see chart 9). For example, the five-year-trailing 'AAA' default rate for global structured finance was only 0.03% at the end of 2020, unchanged from 2019 and down from the peak in 2012.

We also calculate Gini coefficients to quantify the rank-ordering power of our ratings in relation to securities' observed default propensity. The Gini coefficient is a summary metric that can range from zero to 100%--the closer to 100%, the higher the rank-ordering power of the ratings under observation (see Appendix I for more details).

In 2020, the one-year Gini coefficient for defaults of rated global structured finance securities was 77%, up from 76.1% the previous year (see chart 10). The three-year Gini coefficient was higher as well, coming in at 78.2% for 2020, compared with 77.4% in 2019. The five-year Gini coefficient experienced its first increase after four consecutive years of declines, rising to 79.6% in 2020.

This follows the pronounced dip in Gini coefficients amid the 2008-2009 financial crisis. During this period, a relatively large number of defaults in certain sectors--such as U.S. RMBS and U.S. structured credit--coincided with fewer defaults among lower-rated securities from other sectors, lowering the Gini coefficients. Gini coefficients over the one-, three-, and five-year horizons have come in line with each other over time.

Finally, we also calculated sector-specific historical one-year Gini coefficients. For most sectors, the Gini coefficients have returned to 80%-100% since the end of 2011, following a drop in 2007 (see chart 11). The Gini coefficient for global RMBS has been 60%-70% for the past two years, coming in at about 63% in 2020, down from 65% in 2019. Although about 91% of the global RMBS defaults in 2020 were from the 'CCC' and 'CC' rating categories, some defaults still came from higher ratings, specifically three defaults in the 'AA' category, lowering the Gini coefficient for this sector significantly. The ABS and structured credit sectors saw Gini coefficients increase to 98.7% and 96.1%, respectively.

The Gini coefficient metric is useful but has shortcomings. For example, a value of 100% would be attained only if all defaults occurred among securities rated below some critical rating threshold, with no defaults among securities rated higher than this threshold. However, in a diverse sample of rated securities--such as global structured finance securities--sector- and region-specific credit stresses may cause higher-rated securities in more stressed sectors or regions to default, while at the same time lower-rated securities in less stressed sectors or regions do not default. This effect would lower the reported Gini coefficient, despite reflecting the sample composition rather than a decline in ratings' accuracy.

Regions And Sectors In Detail

U.S. RMBS

In 2020, the overall average change in credit quality for U.S. RMBS continued to decrease, ending 2020 at -0.19 notches, marking the second consecutive year in negative territory (see chart 12). The overall average change in credit quality for RMBS remained positive from third-quarter 2016 through the second quarter of 2019. On a 12-month-trailing basis, the U.S. RMBS default rate fell to 2.6% in 2020, the lowest rate since 2007 (see chart 13). Since 2012, on a 12-month-trailing basis, the RMBS default rate has exceeded the global structured finance default rate.

Of the 15,716 securities outstanding in the U.S. RMBS sector in 2020 (approximately 80% issued prior to 2009), the annual default rate was 2.6%, representing 403 securities, down from 3% at the end of 2019 (see table 3). In response to the global pandemic, the introduction of the CARES Act allowed homeowners whose mortgages are backed by the U.S. federal government to suspend payments under the condition of pandemic-related financial hardship. Despite this cushion for GSE-backed loans, the allowances were not enough to offset general deterioration in the sector.

The U.S. RMBS subprime subsector accounted for the largest amount of U.S. RMBS securities outstanding, at 32.4% in 2020. It had an annual default rate of 2%, down from 2.1% in 2019, and the downgrade rate marginally improved to 5.9% in 2020 from 6.1% in 2019. However, the upgrade rate in the subsector fell to 3.3% from 5.2% in 2019. The sector suffered from the lowering of the interest rate by the Federal Reserve in response to the economic fallout from the pandemic.

Among the remaining subsectors in U.S. RMBS, overall credit quality deteriorated. However, default rates for most segments were below their one-year averages, except for U.S. RMBS prime.

Credit performance was mixed across transaction vintages in U.S. RMBS. Precrisis vintages, specifically 2001-2007, have exhibited generally weaker fundamentals, and 2020 was no different. The 2006 and 2007 vintages saw their respective downgrade rates improve to 3.7% from 6% and 6.4%, but downgrade rates across most pre-2007 vintages increased from the year prior. Default rates declined in almost every pre-2007 vintage, except 2000-2001 and 2006-2007. In 2020, defaults came from pre-2010 vintages, with the highest concentration in the 2005 vintage, whose default rate was 4.5%.

The majority (91%) of U.S. RMBS defaults in 2020 were from the 'CCC' and 'CC' rating categories, which constituted about 36% of our U.S. RMBS ratings at the beginning of the year. Default rates increased in many of the rating categories in 2020, though all remained well below the one-year averages.

Table 3

U.S. structured credit

The overall change in credit quality for U.S. structured credit turned negative in 2020--at -0.19 notches in the final month of the year--after almost eight consecutive years in positive territory (chart 14). The downgrade rate increased to 11.8%, still well below the one-year average downgrade rate of 17.8%, and the upgrade rate hit an all-time low of 0.2% in 2020, compared with 3.8% the previous year. In response to the pandemic and subsequent lockdowns at the start of 2020, speculative-grade loans within CLO transactions experienced downgrades in late March and early April, resulting in an increase in the number of CLO ratings in the 'CCC' category.

The U.S. structured credit sector's headline annual default rate declined in 2020 to 0.02% at year-end, down from 0.4% in 2019 (see table 4). The single default in U.S. structured credit in 2020 was on a security that was rated 'CC' at the beginning of the year. Since 2013, the 12-month-trailing default rate for U.S. structured credit has been below that of its global counterpart.

The U.S. structured credit default rate spiked in 2011 following the global financial crisis and defaults of a large number of ratings on collateralized debt obligation (CDO) tranches backed by other structured finance securities, notably U.S. subprime RMBS. At that time, these securities had, in our view, minimal realistic prospects of repayment, and many were unlikely to receive any future principal payments due to the collateral deterioration of the RMBS and other securities backing the transactions.

The overall U.S. structured credit sector remains polarized between collateralized loan obligations (CLOs), which have historically performed very well, and other transactions that performed poorly after 2007 but constitute an ever smaller portion of our active ratings. CLOs grew to more than 94% of the U.S. structured credit sector at the beginning of 2020 (see table 4). Downgrades for the subsector rose sharply to 12.3% in 2020 during the pandemic from just 0.1% in 2019. However, there were no CLO defaults reported during 2020, compared with two defaults in 2019. The upgrade rate retreated to 0.2%, from 3.5% in 2019.

Other U.S. structured credits make up about 5% of overall ratings and had the highest default rate in 2020, at 0.5%, below the one-year average of 1.3%. Downgrades were at 4.8%, while there were no upgrades.

Considering only vintages with more than 30 ratings outstanding at the beginning of 2020, the highest upgrade rate was in the 2014 vintage, where CLO transactions in particular are now amortizing, increasing the relative credit enhancement for the rated securities and raising their creditworthiness, all else being equal. Downgrades were also most prominent in the 2015 vintage, with a downgrade rate of 64.1%.

The single default in U.S. structured credit in 2020 was on a security that was rated 'CC' at the beginning of the year.

Table 4

U.S. ABS

The U.S. ABS sector exhibited some of the best credit performance of any region-sector combination in 2020. The annual average change in credit quality for 2020 remained positive but fell to +0.13 notches from +0.25 notches in 2019 (see chart 16). The 12-month-trailing default rate remained very low historically, though marginally increased to 0.2% in 2020 from 0.1% the previous year (see chart 17). The U.S. ABS 12-month-trailing default rate has remained below that of the global rate since the beginning of 2008. The upgrade rate of 9.9% in 2020 exceeded any other region-sector in the year, surpassing its one-year average of 4.8%. The downgrade rate remained unchanged at 2.9% in 2020, while the annual default rate rose slightly to 0.2%.

The ABS subsector received underlying collateral support during the year because many lenders offered borrowers assistance, including modifications and extensions, in response to the pandemic. While these payment extensions have varied across subsectors, performance remained relatively stable, and in most cases, these extensions ended the year below their pandemic highs.

The U.S. ABS sector is the second-largest structured finance sector in the U.S. by issuer count, behind U.S. RMBS. Further, U.S. ABS accounted for 14% of global structured finance ratings at the start of the year.

The majority of these securities are in the auto loan and student loan subsectors (see table 5). Auto loans specifically had an upgrade rate of 24.3% in 2020, far exceeding the one-year average of 12.3%. The downgrade rate was relatively low at 1%, and there were no defaults. Upgrades were also prominent in the student loan subsector, at a rate of 3.1% in 2020, above the one-year average of 2.5%. In line with auto loans, student loans had a downgrade rate of just 2.4%, with no defaults in 2020.

The only U.S. ABS defaults in 2020 occurred in the manufactured housing and "other" subsectors, and all were from the 'CC' rating category (see table 4). Five defaults came from manufactured housing, yielding an annual default rate of 4.9%, above its one-year average of 2.3%. The other three defaults occurred in the "other" subsector, yielding a default rate of 0.4%, which is below its one-year average of 0.9%.

The majority of downgrades were on speculative-grade transactions. Further, most downgrades were from nontraditional, manufactured housing and other subsectors, at 7.2% and 7.8%, respectively in 2020. Downgrade rates for most U.S. ABS subsectors remained below their one-year averages.

Table 5

U.S. CMBS

In U.S. CMBS, the average change in credit quality continued to deteriorate in 2020, falling to -0.47 notches at the end of the year (see chart 18). The measure crossed into negative territory in the second half of 2019 and ended the year at -0.06 notches. The 12-month-trailing default rate for U.S. CMBS fell to 0.6% at the end of 2020, from 2.4% at the end of 2019. The U.S. CMBS 12-month-trailing default rate has remained below that of the global rate since early 2020 (see chart 19).

The annual default rate for U.S. CMBS fell to 0.6% in 2020, from 2.4% in 2019 (see table 6). The upgrade rate declined to 0.1%, well below the one-year average of 6%. The downgrade rate increased to 14.6% in 2020, which is above the one-year average of 12.2%. The lodging and retail sectors in CMBS have been some of the hardest hit by the pandemic and associated lockdowns. Also, while not a primary driver for rating actions in 2020, the restructuring of office space by companies to curb costs in light of new remote-working models may cause further disruption.

A total of 15 defaults occurred within U.S. CMBS in 2020, the majority of which were in the conduit/fusion subsector, where the annual default rate fell to 0.9%, below the 3.8% one-year average. The only other CMBS subsector to report defaults in 2020 was the loan/floaters subsector, which accounted for only 6% of outstanding U.S. CMBS ratings in 2020, with a default rate of 2.4%. Defaults were concentrated in the 2005-2008 vintages, and all were speculative grade, primarily from the 'CCC' rating category.

The downgrade rate for the large loan/floater subsector was the highest in 2020, at 50.6%. The single-borrower subsector downgrade rate rose to 14.2%, while the conduit/fusion subsector increased to 10.6%. The downgrade rates for the single borrower and loans/floaters subsectors were well above their respective one-year averages. Downgrades primarily occurred in the 2010-2018 vintages, the majority of which are speculative grade. The investment-grade downgrade rate for all of U.S. CMBS increased significantly in 2020 to 9.2%, above its 6.6% one-year average.

The only upgrades in 2020 within U.S. CMBS occurred in the single-borrower subsector, with an upgrade rate of 0.3%. The 204 and 2017 vintages accounted for the upgrades, all of which were speculative grade.

Table 6

Europe

Credit performance across European structured finance sectors has historically been more positive than that of its U.S. counterparts, and the same held true in 2020. The average change in credit quality remained positive at the end of 2020 at +0.04 notches (see chart 20). Despite remaining positive, the figure is down from +0.37 notches at the end of 2019, which was a post-2009 financial crisis high. The 12-month-trailing default rate for European structured finance fell to 0.3% and has remained below the global rate since late 2007 (see chart 21).

The annual default rate for European structured finance fell to 0.2% in 2020, remaining well below the one-year average of 1% (see table 7). Upgrades decreased significantly in 2020, to 4.8% from 20.2% in 2019. The downgrade rate increased to 3.6%, well below the one-year average of 14.5%. The European securitization market benefited from the support of funding schemes from both the European Central Bank (ECB) and Bank of England in response to the pandemic. Specifically, the ECB responded with the asset purchase programs and loosened terms on its targeted longer-term refinancing operations, while the Bank of England relaunched its Term Funding Scheme in March 2020.

The European structured finance sector consists of a diverse array of subsectors. In terms of defaults, the CMBS subsector was the worst-performing in 2020, at 3.1%, marginally above the one-year average of 3%. The only additional defaults came from the structured credit SF CDO and structured credit CLO subsectors, with default rates of 2.4% and 0.1%, respectively. Defaults were the most prominent in the 2007 vintage as well as the 2013 and 2014 vintages. The investment-grade default rate rose to 0.1% in 2020, on par with its one-year average, while the speculative-grade default rate came in at 0.8%, well below its one-year average. There were three defaults from the 'BBB' rating category, while the remaining defaults were in the lower rating categories.

Downgrades rose across many European sectors in 2020, though very few were above their one-year averages. As with defaults, downgrades were the most prominent in the European CMBS subsector, which recorded a downgrade rate of 18.5% in 2020. The European nontraditional subsector, which accounted for only about 2% of outstanding ratings at the start of 2020, had a downgrade rate of 17.7%. Downgrades spanned every vintage, with the exception of 2001 and 2009. The majority of downgrades in European structured finance occurred within the speculative-grade segment, and the 'BB' rating category had the highest downgrade rate of 14.9%.

Almost every European subsector reported upgrades--European structured credit SF CDO had the highest upgrade rate of 14.6%. Upgrades dropped significantly in European CMBS, to a rate of just 0.5%. Within European ABS, upgrades were the highest in the credit card subsector, where the upgrade rate was 11.4% in 2020, well above the one-year average of 2%.

Further, upgrade rates were equally spread among the vintages and were similarly spread between investment- and speculative-grade ratings.

Table 7

Outside the U.S. and Europe

Outside the U.S. and Europe, the average change in credit quality remained positive at the end of 2020 at +0.02 notches, though it has been steadily declining since mid-2019 and even dipped into negative territory briefly in the latter half of 2020 (see chart 22). The 12-month-trailing default rate outside of the U.S. and Europe was zero in 2020 for the fourth year in a row (see chart 23).

Structured finance ratings outside the U.S. and Europe accounted for about than 5% of outstanding ratings at the start of 2020. As there were no defaults in ratings outside the U.S. and Europe for the past four years, the annual default rate was 0.0% once again in 2020 (see table 8). The upgrade rate declined to 4.2% in 2020, below its one-year average of 5.4%, with only a handful of region/sectors reporting upgrades. The downgrade rate fell slightly to 3.1%, well below its one-year average of 5.1%.

The majority of ratings outstanding at the start of the year were concentrated in Australasia and Japan, specifically within the RMBS sector (see table 8). Australasia accounted for 68% of all outstanding ratings outside the U.S. and Europe at the start of 2020. The emerging markets subsector had the highest downgrade rate at 31.6%, followed by Australasia "other" (see Appendix I for definitions) at 25%, and Latin America at 14.5%. There were no downgrades in Canada. All downgrades in 2020 outside the U.S. and Europe occurred above the 'CCC' rating category and primarily in pre-2008 vintages.

The highest upgrade rate in 2020 was in emerging markets, at 34.2%, compared with a one-year average of 13.2%. In Japan, upgrades decreased broadly, with both the Japanese RMBS and the Japanese "other" sectors reporting upgrades rates well below respective one-year averages. Australasia saw upgrades in RMBS and ABS subsector at 4.7% and 7.3%, respectively. The majority of upgrades in 2020 outside the U.S. and Europe were among speculative-grade ratings.

Table 8

Appendix I: Terminology, Data Selection, And Calculation Approaches

This appendix details the data selection, calculations, and terminology we use in this report.

This global structured finance default and rating transition study uses our database of long-term global scale issue credit ratings. We do not include national and regional scale ratings, such as those we may assign in Argentina, Brazil, Mexico, Taiwan, and Japan, which are not comparable between countries. The analysis also excludes public information ("pi") ratings, issuer credit ratings, and short-term issue ratings, such as those on asset-backed commercial paper conduits.

Our ongoing enhancement of the database used to generate this study occasionally leads to changes in the reported statistics from one edition of the study to the next. However, each study includes statistics for previous years, ensuring that the study is self-consistent and effectively supersedes all previous editions.

Issues included in this study

This study analyzes the rating histories of 242,506 global structured finance instruments that S&P Global Ratings first rated between 1973 and Dec. 31, 2020. The term "structured finance" in this report refers to ABS, CMBS, RMBS, structured credit, and single-name synthetic transactions. For some analyses, we break down these sectors further into subsectors.

Sector definitions

ABS includes underlying collateral types such as credit card receivables, student loans, and auto loans and leases. The sector also includes manufactured housing, franchise loans, 12b-1 transactions, and corporate securitizations.

RMBS includes transactions backed by subprime mortgage loans, as well as home equity loan transactions and re-REMICS.

Structured credit includes CLOs, both cash and synthetic CDOs backed by exposures to corporate credit or other structured finance securities, and market-value CDOs and other leveraged funds. We also include transactions backed by loans to small and midsize enterprises in the structured credit sector.

CMBS also includes re-REMICS, as well as some CDOs primarily collateralized by commercial real estate loans. Single-name synthetic transactions are also referred to as "repackaged transactions" (or "repacks"), especially in Europe. The definition of a repack in this instance is an issue backed by a single credit, where the rating on the note is directly linked to that on the underlying credit.

In this study, we no longer include structured covered bonds, which we previously treated as a separate sector.

Regional definitions

This study presents rating transitions for global structured finance transactions. In some analyses, we segment default and transition statistics by region. In defining a transaction's region, we primarily use the location where we perform surveillance. We may also consider the transaction's issuer country (unless this is a tax haven such as the Cayman Islands) or its domicile of assets. In some cases, the domicile of assets may fail to provide additional insights into the region, especially when a transaction is backed by assets from more than one country.

In table 1 of the study, the "Asia (excluding Japan)" region includes transactions with collateral from Hong Kong, Singapore, Korea, and Taiwan, as well as other countries in the region. The "other emerging markets" region includes emerging market countries that are not included in other regions, such as Turkey and South Africa.

Vintage definition

In this report, we classify a security's vintage based on the date when we first assigned a rating. Usually this is close to the security's original issuance date. However, in some cases, we may first assign a rating to a security sometime after closing.

Rating transitions

Our rating transition statistics use a "static pool" approach. To calculate the transition statistics over a given period (or "transition window"), we consider the static pool of ratings outstanding at the beginning of that period. The transition statistics for that static pool of ratings are then based on the movements in ratings between the start and end of the transition window.

For instance, we calculate the 2020 transition rates by determining the ratings on each security outstanding at the start of 2020 and determining the ratings on those same securities at the end of 2020. We then calculate statistics such as upgrade, downgrade, and stability rates, equivalent to the proportions of securities in the static pool with ratings that moved up, down, or remained the same, respectively, over the transition window. During this process, we count each security only once, even if the security experienced more than one rating change during the transition window being observed. In other words, we use the ratings at the start and end of the transition window to calculate the transition rates, disregarding any interim rating changes.

Rating modifiers

We use rating modifiers ("+" and "-") to calculate the upgrade, downgrade, and stability rates quoted in the text, tables, and charts throughout this study. However, the transition matrices in Appendix II of this report show only the less granular, full rating categories for practical reasons. In other words, we count transitions such as to 'AA+' from 'AA' as an upgrade and to 'BBB-' from 'BBB+' as a downgrade in the transition statistics we cite in this report. However, in the corresponding transition matrices, these transitions would appear in the cells corresponding to a stable rating category classification, such as 'AA' to 'AA' or 'BBB' to 'BBB'.

Rating discontinuance or withdrawal

We may discontinue ratings when, for example, a rated obligation's payments have been made in full in accordance with its terms or when a rated issue matures. Ratings may also be withdrawn because of a lack of sufficient information of satisfactory quality or at the issuer's request. In these cases, the rating may change to not rated (NR). When we withdraw or discontinue ratings within the transition window under consideration, we may either derive our reported statistics by classifying the rating transition as a move to NR (the "NR-included" approach) or--for some other analyses--we may classify the transition as a move to the last rating before withdrawal or discontinuance (the "NR-adjusted" approach).

In the text of this report, when we refer to upgrade and downgrade rates, for example, we use the latter approach. In the tables and charts, we clarify the approach used in the footnotes. We do not include a security with a withdrawn rating at the beginning of a transition window in the transition and default rate calculations for that period.

Treatment of 'AAA' ratings

In this study, we include the ratings history of all securities with original ratings of 'AAA', which we term the "uncollapsed" approach. This represents a change in methodology from editions of the study published before 2018. In these previous editions, for each structured finance transaction, we generally included only one of the securities that we originally rated 'AAA', terming this the "collapsed" approach. This was because historically, some transactions had a disproportionate number of 'AAA' rated tranches that were likely to exhibit similar or identical credit performance. By including only one such security per transaction, we aimed to avoid overweighting their behavior in aggregate performance statistics.

However, we now include all securities' rating histories, regardless of the original ratings, for completeness and consistency with some of our other reporting on ratings performance--for example, in regulatory submissions. The effects of altering the treatment of 'AAA' ratings on some example summary statistics are shown in Appendix III.

Treatment of 'D' ratings

Default counts and default rate statistics in this report are based on securities with ratings we lowered to 'D'. For the purposes of this report, when a rating has moved to 'D', we consider this a terminal state and do not, for example, include such a security in any transition windows that start on a subsequent date. In practice, however, some securities with ratings that have migrated to 'D' may later be assigned a different rating. This can occur, for example, if the defaulted security is subsequently restructured to different terms, such as a lower coupon. In these cases, we treat the security's postdefault ratings history as if it were for a new security, beginning from the date that the rating changed from 'D'. Where we segment statistics by vintage, however, we continue to base the vintage on the date we originally assigned a rating to the security.

Average change in credit quality calculation

Certain analyses in this study refer to the "average change in credit quality" of a set of structured finance securities over a given transition window. We define the average change in credit quality as the average number of notches by which ratings changed during the stated transition window, where we take the average across all ratings in the set under consideration (for example, a particular region or sector). In this averaging, we count downgrades as a negative number of notches, whereas we count upgrades as a positive number. We consider stable ratings to have undergone a transition of zero notches. We believe this measure acts as a useful summary of the credit performance of, for example, a given sector, since it combines the relative number of ratings undergoing transition with the severity of that transition.

Weighted average transition and default rate calculation

For weighted average transition rates (including default rates), we calculate the individual transition rates for different static pools. We then calculate a single averaged transition rate, weighted by the number of ratings in each static pool. We use this technique, for example, to determine the five-year weighted average transition rates, by analyzing the transition rates for static pools over five-year periods and then aggregating them.

Average cumulative default rate calculation

In this report, we also calculate and present average cumulative default rates for different time horizons. For example, table 2 shows that the one-year average cumulative default rate for 'A' rated global structured finance has been 0.42% and the three-year average has been 6.16%.

We first consider the static pool of ratings at the beginning of each calendar year. For each static pool, we calculate the marginal default rates for each calendar year after the static pool's formation. These one-year marginal default rates are "conditional on survival." For example, the marginal default rate for the third year is the number of defaults during the third year divided by the number of ratings from the static pool that had "survived" (that is, not moved to 'D') by the beginning of the third year. We then average the marginal default rates for each time horizon across static pools, weighting by the number of surviving ratings at the beginning of each time horizon, to give an average marginal default rate per time horizon, as well as average marginal survival rates (equal to one minus the average marginal default rate). Finally, the average cumulative default rate of each time horizon is calculated as one minus the product of marginal survival rates up to that time horizon.

We note that this approach differs from the calculations we use in constructing the weighted average multiyear default and transition rates included elsewhere in this study (and as described above), where default rates are not conditional on survival.

Gini coefficient calculation

We calculate Gini coefficients as one way to quantify our ratings' power to rank-order creditworthiness, based on observed default rates.

We first construct a Lorenz curve, which plots the cumulative proportion of all structured finance ratings per rating level on the x-axis, against the cumulative proportion of defaults per rating level on the y-axis (see chart 24). For both axes of the Lorenz curve, the observations are ordered from the low end of the ratings scale ('C') to the high end ('AAA').

If our structured finance ratings only randomly approximated default propensity, the Lorenz curve would fall along the diagonal, shown as the random curve in chart 24. On the other hand, if all defaults occurred only among the lowest-rated securities, with no defaults among the higher-rated securities, the Lorenz curve would lie along the ideal curve in chart 24. Typically, the observed Lorenz curve falls between the ideal and random curves, and we use the Gini coefficient as a summary statistic to quantify its proximity to the ideal curve.

The procedure for calculating the Gini coefficient is illustrated in chart 24. Area B is bounded by the random curve and the Lorenz curve, while area A is bounded by the Lorenz curve and the ideal curve. The Gini coefficient is defined as area B divided by the sum of area A and area B. The Gini coefficient can therefore range from zero (if the Lorenz curve follows the random curve) to 100% (if the Lorenz curve follows the ideal curve). In general, therefore, the higher the Gini coefficient, the greater the link between our ratings and the securities' observed default propensity.

Appendix II: Detailed Default And Transition Statistics

Tables 9-52 provide default and transition rate statistics for global structured finance securities and major structured finance subsectors.

Global structured finance

Table 9

Table 10

Table 11

Table 12

U.S. RMBS

Table 13

Table 14

Table 15

Table 16

U.S. structured credit

Table 17

Table 18

Table 19

Table 20

U.S. ABS

Table 21

Table 22

Table 23

Table 24

U.S. CMBS

Table 25

Table 26

Table 27

Table 28

Europe

Table 29

Table 30

Table 31

Table 32

Other regions

Table 33

Table 34

Table 35

Table 36

Global RMBS

Table 37

Table 38

Table 39

Table 40

Global structured credit

Table 41

Table 42

Table 43

Table 44

Global ABS

Table 45

Table 46

Table 47

Table 48

Global CMBS

Table 49

Table 50

Table 51

Table 52

Appendix III: Comparison Of Alternative Treatments For 'AAA' Ratings

This edition of our global structured finance default and rating transition study adopts a new approach to the treatment of securities with original ratings of 'AAA'. As detailed in Appendix I, this study uses the "uncollapsed" approach to the treatment of securities with original ratings of 'AAA', rather than the "collapsed" approach, which was used in studies published before 2018. Charts 25-28 illustrate the resulting differences in some example summary statistics.

Related Criteria

• Global Framework For Payment Structure And Cash Flow Analysis Of Structured Finance Securities, Dec. 22, 2020
• ABS: Global Methodology And Assumptions For Nonfinancial Future Flow Transactions, Jan. 16, 2020
• U.S. Structured Finance Asset Isolation And Special-Purpose Entity Criteria, May 15, 2019
• U.S. FFELP Student Loan ABS: Methodology And Assumptions, April 4, 2019

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