While the number of defaults fell slightly in 2024 (to 145, from 153 in 2023), the number remained elevated--largely because of distressed exchanges. The number of distressed exchanges rose to its highest level since 2008, accounting for 59.3% of defaults. (We view an exchange of one or more of an issuer's financial obligations as tantamount to default if the issuer is distressed and the transaction offers investors materially less than the original promise of the debt.)

One reason for the rising percentage of distressed exchanges and the high level of repeat defaulters is the desire of financial sponsors to maintain control of their portfolio firms while attempting to reduce debt.

And while the global economy proved stronger than expected in 2024 (giving some entities easier access to capital), persistently high interest rates also contributed to lower-rated companies' use of distressed exchanges to ease near-term debt burdens and financing costs amid weaker cash flows.

With the number of defaults remaining elevated, the global speculative-grade ('BB+' or lower) default rate rose to 3.9% in 2024 from 3.7% in 2023 (see chart 1 and table 1).

High interest rates and stubborn inflation have depleted consumer savings and lowered discretionary income, particularly for lower-income consumers. The consumer/service sector led the default tally for the fourth straight year with 33 defaults in 2024, while the leisure time/media sector had the highest default rate (4.89%).

The U.S. led defaults by region with 97, followed by Europe (33), emerging markets (12), and other developed markets (3).

Even though defaults remained elevated, other measures of credit quality improved in 2024. The downgrade rate fell in 2024, while the upgrade rate increased. This caused the downgrade/upgrade ratio to fall to 0.61 from 0.82 in 2023.

Much of the credit pressure we saw in 2024 was concentrated among the lowest-rated issuers. Of the 130 defaulters in 2024 that were rated at the start of the year, 97 (or about three-fourths) were rated in the 'CCC'/'C' category.

This default and rating transition study includes industrials, utilities, financial institutions (banks, brokerages, asset managers, and other financial entities), and insurance companies globally with long-term local currency ratings from S&P Global Ratings. We calculated all default rates on an issuer-weighted basis. The default rates that we refer to as weighted averages in this study use the number of issuers at the beginning of each year as the basis for each year's weight. (For a detailed explanation of our data sources and methodology, see Appendix I.)

Table 1

Default trends varied across sectors in 2024, with half of the 12 sectors seeing increasing default rates while the other six saw declining default rates. (This excludes the insurance sector, since there were no defaults in the sector in either 2023 or 2024). However, divergences in credit quality by sector became apparent as the number of defaults increased in a few sectors: Forest and building products/homebuilders, high technology/computers/office equipment, real estate, and telecommunications each saw more defaults than in 2023.

Each of these sectors also had a default rate in 2024 that was above the sector's long-term average. Some of the sectors that saw above-average default rates (like leisure time/media and consumer/service) are exposed to shifting consumer spending and preferences, and some (like health care) were especially challenged by higher costs for labor and other business inputs (see chart 2).

Of the 145 total defaulters in 2024, 130 were rated at the start of the year, and all but one of these were speculative grade. Of the publicly rated defaulters, Swedish real estate developer Samhallsbyggnadsbolaget i Norden AB (publ) was the only one with an investment-grade rating one year prior to its default. (Weak liquidity and significant short-term maturities weighed on the company.) It defaulted twice in 2024--once in March and once in July--and it was rated 'CCC' with a negative outlook as of Dec. 31, 2024.

In addition to the 130 defaulters that were rated at the start of 2024, there were 15 defaulters that weren't rated at that time. They include seven issuers that defaulted in 2024; two issuers that S&P Global Ratings initially rated after Jan. 1, 2024; and six that had been previously rated but were not rated at the start of 2024.

Ratings provide our view of the rank-ordering of an entity's default risk, and one measure of how our ratings perform as a rank ordering is the Gini ratio. The Gini ratio is a measure of the rank-ordering power of ratings over a given time horizon. It shows the ratio of actual rank-ordering performance to theoretically perfect rank ordering.

With such a large share of the defaults in 2024 being concentrated in the 'CCC'/'C' category, the one-year Gini ratio remained high for the year at 89.4%--down 0.8 percentage points from 2023 and above the one-year weighted average Gini ratio of 82.9% (see chart 3 and table 2).

Table 2

As the Gini ratios show, corporate ratings have served as effective measures of relative credit risk over time. (For details on the Gini methodology, refer to Appendix II.)

Cumulative default rates and rating transition rates are another measure of ratings performance over time. Cumulative default rates show that lower ratings have historically corresponded to higher default rates over both short and long time horizons (see chart 4). (For more on rating transitions, see table 20 and subsequent exhibits.)

Defaults in 2024 largely came from the lower rating levels. The default rate rose slightly for the 'B' category, and the 'CCC'/'C' category default rate fell in 2024 to 28.4%; it had spiked to 30.9% in 2023 (see tables 3 and 4).

Table 3

Table 4

Annual Global Trends: Defaults Remained Elevated, Driven By The U.S. And Europe

The number of global corporate defaults fell 5% in 2024, but it was still the fourth-largest number of global corporate defaults since 2008. The dip in 2024, however, ended the trend of rising annual default tallies since 2021.

Defaults in 2021 dipped to a seven-year low amid the pandemic and the resulting fiscal and monetary support; that year saw very low interest rates and extremely easy financing conditions for most borrowers. By 2023, benchmark interest rates were higher with central banks tightening monetary policy globally, and financing conditions were more challenging.

Central banks began cutting rates in 2024, leading to a resurgence in debt markets and an easing in near-term maturities--especially in 2025 speculative-grade obligations, which fell 50% globally.

However, the number of defaults remained elevated in 2024, with the number of rated defaults (that is, defaults of issuers that were rated as of Jan. 1, 2024) staying the same between 2024 and 2023 (at 130). By debt amount, defaults also remained nearly the same between 2024 ($227.4 billion) and 2023 ($222.4 billion) (see charts 5 and 6).

These default counts include issuers that weren't rated as of the beginning of 2024, and we count these as unrated defaults because they weren't in the static pool of rated issuers from Jan. 1, 2024.

Of the regions we track, Europe saw the largest increase in defaults in 2024. Among European issuers, the number of rated defaults rose by five (to 32), while the amount of debt affected rose to $15.47 billion.

Meanwhile, defaults from the U.S. increased by four, while the amount of debt affected rose to $211.7 billion from $65.2 billion the previous year. U.S. issuers accounted for 66% of rated defaults globally (and 66% of the amount of debt affected), even though the U.S. accounts for about 42% of the global population of rated issuers.

With its highly developed capital markets, the U.S. also accounts for most of the world's speculative-grade issuers--49% of the global total. Since most defaults tend to be of speculative-grade issuers, the concentration of defaults among U.S. issuers isn't a surprise.

The speculative-grade default rate increased globally, in the U.S., and in Europe in 2024, while the default rate fell in emerging and frontier markets and in the "other developed markets" region. The speculative-grade default rate in the U.S. rose to 5.1% from 4.5% in 2023, while the default rate in Europe rose by 0.9 percentage points to 4.5%. In both the U.S. and Europe, the speculative-grade default rate in 2024 exceeded the long-term average (since 1981), mostly because of the more pronounced use of distressed exchanges in both regions.

In other developed markets and in emerging and frontier markets, the speculative-grade default rate remained below the long-term average (see table 5 and chart 21).

Table 5

Table 6

Credit quality improved slightly in 2024

Even though the number of defaults remained high in 2024, credit quality improved for some issuers last year, driven by a fall in negative rating activity (which includes both downgrades and negative outlook revisions). The number of upgrades increased while the number of downgrades decreased, and more issuers were upgraded than downgraded.

The upgrade rate rose to 9.6% from 8.7%, and it exceeded the downgrade rate, which fell to 5.8% from 7.3% (see table 7).

Table 7

Multinotch downgrades outpaced multinotch upgrades

We define a large multinotch downgrade as a downward transition of a rating by seven or more notches in a year. There were three such downgrades in 2024, the same as in 2023. Meanwhile, there were no large multinotch upgrades last year, down from two in 2023.

Our count of large downgrades includes moves to 'D' (default). This is different from other parts of this report where we normally exclude defaults from the calculation of downgrade rates. In 2024, Avon Products Inc. defaulted from 'BB-'.

Large multinotch downgrades such as that of Avon Products are outliers, especially in years of high credit stability. Since 1981, the annual average for the number of notches per downgrade has been 1.7 notches. In 2024, the number of notches for a downgrade averaged 1.7, the same as in 2023.

The average number of notches for an upgrade (1.1) also remained the same between 2024 and 2023 (see chart 8).

Lower initial ratings correspond with a shorter time to default

Historically, among the issuers that default, the median time to default is four years after the initial rating. And the average time from initial rating to default tends to be shorter for issuers initially rated at lower rating levels (see chart 9).

Among the issuers with an initial rating in the 'CCC'/'C' rating category, the majority of the defaults occur within the first 15 months after the initial rating. For those with an initial rating in the 'B' category, the majority of defaults occur within the first four years after the initial rating. For 'BB' issuers, the majority of defaults take place within six years.

An issuer's credit quality tends to deteriorate in the run-up to an eventual default, and most ratings will transition lower during the path to default. With this deterioration, an issuer is most often rated 'CCC+' or lower immediately prior to a default.

The high default rate in the 'CCC'/'C' category aligns with S&P Global Ratings' criteria for assigning such ratings (see "Criteria For Assigning 'CCC+', 'CCC', 'CCC-', And 'CC' Ratings," published Oct. 1, 2012), as S&P Global Ratings defines a 'CCC' issue as "currently vulnerable to nonpayment, and is dependent upon favorable business, financial, and economic conditions for the obligor to meet its financial commitment on the obligation. In the event of adverse business, financial, or economic conditions, the obligor is not likely to have the capacity to meet its financial commitment on the obligation."

Many of the issuers to which we assign an initial rating of 'CCC+' or lower are those that have previously defaulted, including through a distressed exchange. For the purposes of this study, we treat a rating after a default as a new initial rating for the issuer.

While the 'CCC'/'C' category has the highest default rate among initial rating categories just around 5% of initial ratings are in the 'CCC'/'C' category. Most new ratings are in the 'B' (39%) and 'BB' (18%) rating categories.

Median ratings and the path to default

Defaults of investment-grade issuers (where an issuer was investment grade at the start of the year it defaulted) are becoming more infrequent. There was one investment-grade default in 2024, and the investment-grade defaults that occurred in 2023 were the first ones in four years. In addition, there have been only seven investment-grade defaults since 2010--an average of 0.5 per year.

In the 1981-2010 period, investment-grade defaults were more frequent, averaging 2.9 per year. But they still accounted for a very small portion of defaults.

In the 1981-2024 period, the path for most defaulters toward a default has tended to be a gradual deterioration that accelerated as default neared (see chart 10). The median rating for an issuer seven years before default was 'B+', gradually falling to 'B-' nine months before default and then to 'CCC' about a month before default.

For issuers that defaulted more recently (within the last three years), the path to default has been less steep. Of these more recent defaulters, 95.8% were initially rated speculative grade, and the median rating seven years before default ('B+') was the same as it was for the 1981-2024 period. The median rating for the more recent defaulters deteriorated to 'B' roughly six years before default, before falling to 'CCC+' about a year before default and to 'CCC' two months before default.

The typical path to default diverges for financial services and nonfinancial corporate issuers. For the 1981-2024 period, the median rating for all financial services defaulters seven years before default ('BBB-') was higher than for nonfinancial corporates ('B+') (see charts 11 and 12).

For nonfinancial issuers, defaults are much more common than they are among financial services issuers, and this results in a larger pool of defaulters. In the 44 years covered in this study, 3,217 nonfinancial issuers defaulted, compared with just 339 financial services issuers. Outliers have a greater effect on the default statistics for financial services issuers because of the smaller pool of defaults.

In our annual default rate calculations, we only include defaulters that were rated as of Jan. 1 in the year of default. If S&P Global Ratings withdrew its rating on an issuer before Jan. 1 of the year it defaults, it isn't included in the annual default rate calculation for that year.

Issuers sometimes default after S&P Global Ratings withdraws its rating--we make our best effort to capture these defaults in our database. Historically, 14.8% of defaults are of entities that were no longer rated at the time of default.

Although defaulters that are not rated as of Jan. 1 of a given year are excluded from the one-year annual default rate calculations for that year, they are observed for all years where they had an active rating on Jan. 1. When an issuer emerges from default (including following distressed exchanges), we consider it a separate entity, with a new initial rating after the default event.

Of all of the defaults in our database, 72.0% were rated below 'CCC+' when they defaulted (see chart 13). Very infrequently, an investment-grade rating will default--this accounts for just over 0.5% of all defaults. Of the defaults in 2024, 91.7% were rated 'CCC+' or below when they defaulted. Just two defaults were rated investment grade one year before their default.

Default observations for 2024

• Of the 145 corporate defaults in 2024, the majority (97) were of companies in the U.S. and associated tax havens (Bermuda and Cayman Islands). Europe followed with 33 defaults, emerging and frontier markets had 12, and other developed markets had three.
• Distressed exchanges (which are typically selective defaults) accounted for 59.3% of all defaults, much higher than the share attributed to missed interest or principal payments (18.6%). In a distressed exchange, we view an exchange of one or more of the issuer's financial obligations as tantamount to default.
• Various types of bankruptcy filings accounted for 22.1% of all defaults (see table 8 for a list of all of the publicly rated defaulters in 2024, including the reasons for default).
• The largest default in 2024 was that of Lumen Technologies Inc., which accounted for $38.7 billion of the debt affected by defaults during the year.
• Six of the defaulters in 2024 were initially rated investment grade, and five of those six were initially rated in the 'BBB' rating category. (The sixth was initially rated 'A'.)
• Among those six defaulters that were initially rated investment grade, the average time to default--the time between the first rating and the date of default--was 17.4 years, with an associated standard deviation of 14.3 years.
• In contrast, the average time to default for entities that were initially rated speculative grade was 5.4 years, with an associated standard deviation of 6.1 years.
• The issuer with the longest time to default in 2024 was Lumen Technologies. The initial issuer credit rating was 'BB-' on Dec. 31, 1980, more than 43 years before the rating was lowered to 'SD' in March 2024.
• The issuer with the shortest time to default (35 days) was Range Parent Inc., a U.S. issuer from the aerospace/automotive/capital goods/metal sector.

Table 8

Table 9

Quarterly Default Trends

In 2024, quarterly defaults peaked globally in the second quarter (with 37) before slowing slightly in the second half of the year.

However, default rates diverged during this period by region. The quarterly speculative-grade default rate in Europe fell in the second half, while the speculative-grade default rate continued to climb in the U.S. (to 1.8% in the fourth quarter) and in emerging markets (to 0.5% in the fourth quarter) (see charts 14-16).

Lower Ratings Remain Vulnerable To Default

There exists a correlation between initial ratings and time to default (see table 10). Higher initial ratings correspond with both lower rates of default and (for those that do default) a longer amount of time between initial rating and default.

For example, for the entire population of defaulters in this study (1981-2024), 43.2% of issuers initially rated 'CCC+' or lower eventually defaulted (with an average time to default of 2.0 years), while issuers originally rated in the 'B' category had a lower lifetime default rate (21.2%) and a longer average time to default (5.2 years).

By contrast, issuers initially rated in the 'A' category exhibited a much lower lifetime default rate (3.2%), with a much longer average time to default (14.7 years).

The same relationship between initial rating and default is maintained when looking at the post-initial rating (see table 11). Broadly speaking, the average and median times to default for each rating category are longer when based on the initial rating than when they're based on subsequent ratings.

In both cases, the standard deviation of the times to default rises with higher rating levels. This reflects the lower frequency and higher degree of variation among the higher-rated issuers that eventually defaulted.

Of all of the issuers that defaulted in the 1981-2024 period, only eight that were initially rated 'AAA' have defaulted: Macy's Inc., Ally Financial Inc., Ambac Assurance Corp., Mutual Benefit Life Insurance Co., Executive Life Insurance Co. CA, Confederation Life Insurance Co., Motors Liquidation Co. (formerly known as General Motors Corp.), and Eastman Kodak Co. These issuers averaged 18 years between initial rating and default, but with a higher standard deviation than what we see in the other rating categories.

By contrast, issuers that defaulted within one year of an initial rating are highly concentrated in the lowest rating categories. Of the 317 companies that defaulted within 12 months of an initial rating, 94.4% were rated in either the 'B' or 'CCC'/'C' categories (see table 12).

Table 10

Table 11

Table 12

Table 13 shows the number of cumulative defaults for all subsequent ratings (post-initial ratings). The total count is different from table 12 since an issuer typically has multiple post-original ratings, but it can only have one initial rating. Because of this, issuers are generally counted multiple times in table 13.

Times to default in table 13 are from the date that each entity received a unique rating in its path to default. In contrast, table 21 reports transition-to-default rates using the static pool methodology (which calculates movements to default from the beginning of each static pool year).

The data in table 13 also differs from the default rates in table 24, which are based on the static pool methodology. (For more information on methodologies and definitions, see Appendix I.)

Table 13

Over longer time horizons, the incidence of defaults from low rating categories becomes even more pronounced (see table 14). For example, of the 421 defaults recorded in the most recent five-year pool that began January 2020, 97.7% of the defaulters were rated speculative grade on Jan. 1, 2020.

The nine publicly rated investment-grade defaults from this period are listed in table 15. While each of these nine issuers was rated investment grade as of Jan 1, 2020, five of these issuers were speculative grade a year or more before their default.

Table 14

Table 15

The proportion of newly assigned speculative-grade ratings at 'B-' or lower in the U.S. and the U.S. speculative-grade default rate show some correlation historically (see chart 17).

The growth of speculative-grade ratings, particularly ratings of 'B-' or lower, is a sign of the weakening credit quality of the pool of rated issuers, with the growing population of speculative-grade ratings indicating fundamentally higher default risk. The share of new speculative-grade issuers rated 'B-' or lower fell to 46.4% in 2024 from 52.2% the prior year, but that's still much higher than the share during most of the observed 44-year period.

Variation By Industry: Leisure Time/Media Led Default Rates

There were defaults in 2024 in nearly all of the sectors we track, but they were heavily concentrated in the consumer/service sector (33 defaults). Seven sectors had a 2024 default rate above 2%, and eight sectors had a 2024 default rate that was above its long-term weighted average (see table 16).

Table 16

The leisure time/media sector led all sectors with a 4.9% default rate in 2024, which was above its 3.4% long-term weighted average but an improvement on the 5.6% default rate in 2023. Consumer-facing sectors--including leisure time/media as well as the consumer/service sector--confronted challenges related to shifting demand as consumers adjusted their spending in response to inflation.

There's also greater default risk in the leisure time/media sector than in other sectors since it has the highest concentration of speculative-grade issuers.

Notably, the health care/chemicals sector saw the biggest gap between its 2024 default rate and its historical average (4.5% and 1.7%, respectively). Elevated costs from staffing shortages and higher debt burdens have strained the credit quality of many of the sector's lower-rated issuers.

As for sectors with improving default rates, the biggest surprises were the energy and natural resources sector (where the default rate fell to 1.1% in 2024, well below the 3.0% long-term average) and the transportation sector (where the default rate fell to 2.0% in 2024 from 3.6%).

Across sectors, the share of issuers that were rated speculative grade varied widely. Leisure time/media had the highest concentration of speculative-grade issuers (82.5%), while the insurance sector had the lowest (10.9%) (see chart 18).

To some extent, sectors with a higher concentration of speculative-grade issuers can be expected to exhibit higher default rates over time. In five sectors, the share of speculative-grade ratings has grown over the past decade: insurance, utilities, consumer/service, health care/chemicals, and leisure time/media.

Broad-sector default rates reflect some of the difference between the rating distributions within financial and nonfinancial sectors (see table 17). The speculative-grade share of nonfinancial corporate issuers has tended to be higher than that of financial services issuers. This is reflected in the higher average default rate for nonfinancial companies--including over the one-, three, and 10-year horizons--than for financial services companies. The 0.52% one-year average default rate for the financial services sector is considerably lower than the 1.87% default rate for the nonfinancial sector.

In addition, the annual default rate for financial services companies has remained below 2% since 1990 (and below 1% for the past 15 years), while the default rate for nonfinancial companies was above 1% in 14 of the past 15 years (see chart 19). The gap in default rates between financial and nonfinancial issuers is even wider over longer time horizons (see chart 20).

Table 17

Table 18

Table 19

Variations By Region

While slowing economic growth, rising interest rates, and tighter financing conditions were common themes for corporate credit globally in 2023 and 2024, default rate trends varied by region. For example, in 2024, the U.S. had the highest speculative-grade default rate of the regions we track, at 5.1% (up 0.6 percentage points from 2023), compared with Europe's 4.5% default rate (which was up a more modest 0.9 percentage points).

But this could be an example of the impact of sustained high interest rates and the increased use of distressed exchanges--the U.S. default rate was higher despite resilient U.S. economic growth (compared with sub-1% growth in Europe).

The speculative-grade default rate for emerging and frontier markets fell 1.0 percentage points in 2024, to 1.2% (see chart 21).

Speculative-grade issuers continued to represent a higher share of rated issuers in the U.S. than they do globally. At the end of 2024, 53.7% of rated issuers in the U.S. were speculative grade, versus 43.9% in Europe and 47.6% globally (see charts 22-24).

Transition And Cumulative Default Rates Demonstrate Ratings Performance

Transition rates, which measure the change in a rating (including both upgrades and downgrades) over a given horizon, are another useful measure of ratings performance. Rating transition rates show that higher ratings tend to be more stable while speculative-grade ratings generally experience more volatility.

Transition rates in 2024 continued to show a strong rank-ordering relationship between ratings and credit risk (see table 20). For instance, 93.7% of issuers rated 'A' at the beginning of 2024 were still rated 'A' at the end of the year, while the comparable share for issuers rated 'B' was only 79.3%. The inverse relationship between higher ratings and defaults can be seen across time horizons and regions.

Transition tables also include default rates for a given time horizon. The default rates in these tables show the rank-ordering power of ratings. There were no defaults in 2024 of issuers rated 'A' or above--the 15th consecutive year with no defaults from these higher rating levels.

Occasional exceptions are usually due to outliers within smaller sample sizes or due to rare default events. For example, even though the default rate for the 'BBB' category among emerging and frontier markets issuers (0.2%) was higher than the corresponding default rate for the 'BB' category in 2024, the relationship still holds globally, where the 'BB' category default rate (0.2%) exceeded the 'BBB' category default rate (0.1%).

Sample size is an important consideration when analyzing transition rates. Subsets of issuers pooled by rating, region, or sector, for example, can become quite small.

For the 1981-2024 period, higher ratings have shown greater stability, on average (see table 21). When analyzing transition matrices that present averages computed over multiple static pools, the standard deviations associated with each transition point in the matrix can be large relative to averages.

One example of the greater stability of higher ratings is that issuers rated 'AAA' were still rated 'AAA' one year later 87.3% of the time, while just 45.1% of issuers in the 'CCC'/'C' category were still rated in that category one year later. This relationship between higher ratings and greater ratings stability holds even over longer time horizons and when broken out by region (see tables 21-22).

The relationship is more discontinuous when we examine rating transitions across rating levels--these variations are, in part, a result of sample sizes (see table 23). For example, 'AA+' rated issuers were still rated 'AA+' one year later 80.9% of the time, while 81.3% of 'AA' rated issuers were still rated 'AA' one year later. In this case, the 'AA+' figure is derived from a much smaller sample than the 'AA' figure is derived from.

Generally, the highest proportions of rating changes for either a rating category or rating level occur at adjacent rating categories and rating levels. Small sample sizes can result in historical default rates that seem counterintuitive. But these default rates do not imply that, for example, 'AAA' rated companies are riskier than 'AA+' rated companies, but rather that both are highly unlikely to default (see tables 24-26 and chart 25).

Table 20

Table 21

Table 22

Table 23

Table 24

Table 25

Table 26

Gini Ratios And Lorenz Curves

A quantitative analysis of the performance of S&P Global Ratings' corporate ratings shows that they continue to correlate with default risk across several time horizons. As one measure of ratings performance, the cumulative share of defaulters was plotted against the cumulative share of issuers by rating in a Lorenz curve to visually render the accuracy of its rank ordering (for definitions and methodology, refer to Appendix II).

Over the long term, the global weighted average Gini coefficient was 82.9% over the one-year horizon, 75.1% over three years, 71.7% over five years, and 69.2% over seven years (see table 27). If the rank ordering of ratings had little predictive value, the cumulative share of defaulting corporate entities and the cumulative share of all entities at each rating would be nearly the same, producing a Gini ratio of zero.

In line with expectations, the Gini coefficients decline over time because longer time horizons allow for greater credit deterioration among higher-rated entities. For example, in the one-year global Lorenz curve, 96.9% of defaults occurred in the speculative-grade categories, which constituted just 41.2% of all corporate ratings (see charts 26-29).

One-year Gini coefficients appear to be broadly cyclical and negatively correlated with default rates (see chart 30). In an economic downturn, the risk that higher-rated issuers will experience rapid credit deterioration rises; in periods with high default rates, there tends to be greater variation in the distribution of issuer ratings prior to default--and this reduces the Gini ratio.

Table 27

Table 28

Appendix I: Methodology And Definitions

This long-term corporate default and rating transition study uses the CreditPro database of long-term local currency issuer credit ratings. The analysis excludes public information ("pi") ratings and ratings based on the guarantee of another company or government entity. We also do not include short-term issuer credit ratings.

S&P Global Ratings does not require all issuers with rated debt to have an issuer credit rating. Therefore, if an issuer has rated debt but not an issuer credit rating, we assign a proxy rating so that the CreditPro corporate dataset accurately represents the complete universe of ratings. The local currency senior unsecured rating is the preferred debt rating used for the proxy because it is usually consistent with the issuer credit rating. In a small number of cases, we use the subordinated debt rating or the senior secured rating as the proxy.

An S&P Global Ratings issuer credit rating is a forward-looking opinion about an obligor's overall creditworthiness. This opinion focuses on the obligor's capacity and willingness to meet its financial commitments as they come due. It does not apply to any specific financial obligation because it does not take into account the nature and provisions of any single obligation, its standing in bankruptcy or liquidation, statutory preferences, or the legality and enforceability of the obligation. Counterparty credit ratings, corporate credit ratings, and sovereign credit ratings are all forms of issuer credit ratings. Issuer credit ratings can be either long-term or short-term.

Our ongoing enhancement of the database used to generate this study could lead to outcomes that differ to some degree from those reported in previous studies. However, this poses no continuity problem because each study reports statistics back to Dec. 31, 1980. Therefore, each annual default study is self-contained and effectively supersedes all previous versions.

Issuers included in this study

This study analyzes the rating histories of 23,831 issuers that S&P Global Ratings rated as of Dec. 31, 1980, or that were first rated between that date and Dec. 31, 2024. These include industrials, utilities, financial institutions, and insurance companies around the world with long-term local currency ratings. Structured finance vehicles, public-sector issuers, and sovereign issuers are the subjects of separate default and transition studies, and we exclude them from this study.

In this study, the insurance industry includes life insurance, health insurance, property/casualty insurance, reinsurance, bond insurance, mortgage insurance, and title insurance. In addition to these subsectors, this study groups insurance service providers (such as insurance brokers and third-party administrators that are rated according to corporate criteria) with the insurance industry.

To avoid overcounting, we exclude subsidiaries with debt that is fully guaranteed by a parent or with default risk that is considered identical to that of a parent. The latter are companies with obligations that are not legally guaranteed by a parent but that have operating or financing activities that are so inextricably entwined with those of the parent that it would be impossible to imagine the default of one and not the other. At times, however, some of these subsidiaries might not yet have been covered by a parent's guarantee, or the relationship that combines the default risk of parent and subsidiary might have come to an end or might not have begun. We included such subsidiaries for the period during which they had a distinct and separate risk of default.

Issuers with withdrawn ratings

S&P Global Ratings withdraws ratings when an entity's entire debt is paid off or when the program or programs rated are terminated and the relevant debt extinguished. Others are withdrawn because of a lack of cooperation, particularly when a company is experiencing financial difficulties and refuses to provide all the information needed to continue surveillance on the ratings, or at the entity's request. For the purposes of this study, a corporate rating may also be withdrawn as a result of mergers and acquisitions.

Definition of default

An obligor rated 'SD' (selective default) or 'D' (default) is in default on one or more of its financial obligations, including rated and unrated financial obligations but excluding hybrid instruments classified as regulatory capital or in nonpayment according to terms. An obligor is considered in default unless S&P Global Ratings believes that such payments will be made within five business days of the due date in the absence of a stated grace period, or within the earlier of the stated grace period or 30 calendar days.

A 'D' rating is assigned when S&P Global Ratings believes that the default will be a general default and that the obligor will fail to pay all or substantially all of its obligations as they come due. An 'SD' rating is assigned when S&P Global Ratings believes that the obligor has selectively defaulted on a specific issue or class of obligations but will continue to meet its payment obligations on other issues or classes of obligations in a timely manner. S&P Global Ratings lowers its rating on an obligor to 'D' or 'SD' if the obligor is conducting a distressed exchange offer.

'R' (regulatory intervention) indicates that an obligor is under regulatory supervision owing to its financial condition. This does not necessarily indicate a default event, but during the period of regulatory supervision, the regulators may have the power to favor one class of obligations over others or pay some obligations and not others. Preferred stock is not considered a financial obligation; thus, a missed preferred stock dividend is not normally equated with default. On July 5, 2020, we removed the 'R' symbol from all rating scales.

We deem 'D', 'SD', and 'R' issuer ratings to be defaults for the purposes of this study. A default is assumed to take place on the earliest of:

• The date S&P Global Ratings revised the rating(s) to 'D', 'SD', or 'R';
• The date a debt payment was missed;
• The date a distressed exchange offer was announced; or
• The date the debtor filed for, or was forced into, bankruptcy.

When an issuer defaults, it is not uncommon for S&P Global Ratings to subsequently withdraw the 'D' rating. For the purposes of this study, if an issuer defaults, we end its rating history at 'D'. If any defaulting entity reemerges from bankruptcy--or otherwise restructures its defaulted debt instruments, thereby reestablishing regular, timely payment of all its debts--we reenter this issuer into the database as a new entity. Its rating history after the default event is included in all calculations as entirely separate from its experience leading up to its earlier default.

Many practitioners use statistics from this default study to estimate the "probability of default" and "probability of rating transition." It is important to note that S&P Global Ratings' credit ratings do not imply a specific probability of default.

Regional definitions

Within this study, tables and charts are often presented using specific geographic regions. Like most of our studies, issuer ratings included in this study are classified by the geographic location in which each entity is incorporated. Some locations can be included in multiple regions, and S&P Global Ratings does not have corporate ratings within every location. The regions covered in this study are:

U.S. and tax havens:  U.S., Bermuda, and Cayman Islands

Other developed:  Australia, Brunei Darussalam, Canada, Israel, Japan, Republic of Korea, New Zealand, and Singapore

Europe:  Austria, Belgium, British Virgin Islands, Bulgaria, Channel Islands, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Gibraltar, Greece, Guernsey, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, and the U.K.

Emerging markets in this study consist of the following subregions:

Asia-Pacific:  Bangladesh, Bhutan, China, Fiji, Hong Kong, India, Indonesia, Macao Special Administrative Region of China, Malaysia, Mongolia, Pakistan, Papua New Guinea, Philippines, Serbia, Sri Lanka, Taiwan, Thailand, British Indian Ocean Territory, and Vietnam

EMEA:  Angola, Armenia, Azerbaijan, Bahrain, Belarus, Bosnia and Herzegovina, Bulgaria, Cote d'Ivoire, Croatia, Cyprus, Egypt, Estonia, Gabon, Georgia, Ghana, Hungary, Jordan, Kazakhstan, Kenya, Kuwait, Latvia, Lebanon, Lithuania, Mauritius, Montenegro, Morocco, Namibia, Nigeria, Oman, Poland, Qatar, Moldova, Romania, Russia, Saudi Arabia, Slovakia, South Africa, Tunisia, Turkiye, Ukraine, United Arab Emirates, and Uzbekistan

Latin America and Caribbean:  Argentina, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Honduras, Jamaica, Mexico, Panama, Paraguay, Peru, Trinidad and Tobago, and Uruguay

Frontier markets in this study consist of the following subregions:

Asia-Pacific:  Cambodia and Marshall Islands

EMEA:  Iraq, Liberia, Syria, and Togo

Latin America and Caribbean:  Aruba, Bahamas, Curacao, Netherlands Antilles*, Turks and Caicos Islands, and Venezuela

*The Netherlands Antilles was dissolved in 2010.

Calculations

Static pool methodology.  S&P Global Ratings Credit Research & Insights conducts its default studies on the basis of groupings called static pools. For the purposes of this study, we form static pools by grouping issuers (for example, by rating category) at the beginning of each year, quarter, or month that the database covers. Each static pool is followed from that point forward. All companies included in the study are assigned to one or more static pools. When an issuer defaults, we assign that default to all of the static pools to which the issuer belonged.

We use the static pool methodology to avoid certain pitfalls in estimating default rates, such as by ensuring that default rates account for rating migration and allowing for default rates to be calculated across multiperiod time horizons. Some methods for calculating default and rating transition rates might charge defaults against only the initial rating on the issuer, ignoring more recent rating changes that supply more current information. Other methods may calculate default rates using only the most recent year's default and rating data, which may yield comparatively low default rates during periods of high rating activity because they ignore prior years' default activity.

The pools are static in the sense that their membership remains constant over time. Each static pool can be interpreted as a buy-and-hold portfolio. Because errors, if any, are corrected by every new update and because the criteria for inclusion or exclusion of companies in the default study are subject to minor revisions as time goes by, it is not possible to compare static pools across different studies. Therefore, every update revises results back to the same starting date of Dec. 31, 1980, so as to avoid continuity problems.

Entities that have had ratings withdrawn--that is, revised to not rated (NR)--are surveilled with the aim of capturing a potential default. Because static pools include only entities with active ratings as of the beginning date of a given pool, we exclude companies with withdrawn ratings, as well as those that have defaulted, from subsequent static pools. If the rating on an entity is withdrawn after the start date of a particular static pool and the entity subsequently defaults, we will include the entity in that static pool as a defaulter and categorize it in the rating category of which it was a member at that time.

For instance, the 1981 static pool consists of all companies rated as of 12:00:01 a.m. on Jan. 1, 1981. Adding those companies first rated in 1981 to the surviving members (those still actively rated and not in default) of the 1981 static pool forms the 1982 static pool. All rating changes that took place are reflected in the newly formed 1982 static pool through the ratings on these entities as of 12:00:01 a.m. on Jan. 1, 1982. We used the same method to form static pools for 1983-2024. From Jan. 1, 1981-Dec. 31, 2024, a total of 23,831 first-time-rated organizations were added to form new static pools, while we excluded 3,556 defaulting companies and 13,432 companies that are no longer rated (NR).

Consider the following example: An issuer is originally rated 'BB' in mid-1986 and is downgraded to 'B' in 1988. This is followed by a rating withdrawal in 1990 and a default in 1993. We would include this hypothetical company in the 1987 and 1988 pools with the 'BB' rating, which was the rating on the issuer at the beginning of those years. Likewise, it would be included in the 1989 and 1990 pools with the 'B' rating. It would not be part of the 1986 pool because it was not rated as of the first day of that year, and it would not be included in any pool after the last day of 1990 because the rating had been withdrawn by then. Yet each of the four pools in which this company was included (1987-1990) would record its 1993 default at the appropriate time horizon.

Default rate calculation.  We calculated annual default rates for each static pool, first in units and later as percentages with respect to the number of issuers in each rating category. We combined these percentages to obtain cumulative default rates for the 44 years the study covers (see tables 24-26 and 30-32).

Issuer-weighted default rates.  All default rates that appear in this study are based on the number of issuers rather than the dollar amounts affected by defaults or rating changes. Although dollar amounts provide information about the portion of the market that is affected by defaults or rating changes, issuer-weighted averages are more useful measures of the performance of ratings.

Average cumulative default rate calculation.  The cumulative default rates in this study average the experience of all static pools by first calculating marginal default rates for each possible time horizon and for each static pool, weight-averaging the marginal default rates conditional on survival (survivors being nondefaulters) and accumulating the average conditional marginal default rates (see tables 24-26 and 30-32). We calculated conditional default rates by dividing the number of issuers in a static pool that default at a specific time horizon by the number of issuers that survived (did not default) to that point in time. Weights are based on the number of issuers in each static pool. Cumulative default rates are one minus the product of the proportion of survivors (nondefaulters).

For instance, in table 32, the weighted average first-year default rate for all speculative-grade-rated companies for all 44 pools was 3.5%, meaning that an average of 96.5% survived one year. Similarly, the second- and third-year conditional marginal averages--shown in the "Summary statistics" section at the bottom portion of the table--were 3.4% for the first 44 pools (96.6% of those companies that did not default in the first year survived the second year) and 3.0% for the first 43 pools (97.0% of those companies that did not default by the second year survived the third year), respectively. Multiplying 96.5% by 96.6% results in a 93.2% survival rate to the end of the second year, which leads to a two-year average cumulative default rate of 6.8%. Multiplying 93.2% by 97.0% results in a 90.4% survival rate to the end of the third year, which results in a three-year average cumulative default rate of 9.5%.

Transition analysis.  Transition rates compare issuer credit ratings at the beginning of a period with ratings at the end of the period. To compute one-year rating transition rates by rating category, we compared the rating on each entity at the end of a particular year with the rating at the beginning of the same year. An issuer that remained rated for more than one year was counted as many times as the number of years it was rated.

For instance, an issuer continually rated from the middle of 1984 to the middle of 1991 would appear in the seven consecutive one-year transition matrices from 1985-1991. If the rating on the issuer was withdrawn in the middle of 1991, it would be included in the column representing transitions to NR in the 1991 transition matrix. Similarly, if it defaulted in the middle of 1991, it would be included in the column representing transitions to 'D' in the 1991 one-year transition matrix.

All 1981 static pool members still rated on Jan. 1, 2024, had 44 one-year transitions, while companies first rated on Jan. 1, 2024, had only one. Table 29 displays the summary of one-year transitions in the investment-grade and speculative-grade rating categories. Each one-year transition matrix displays all rating movements between letter categories from the beginning of the year through year-end. For each rating listed in the matrix's leftmost column, there are nine ratios listed in the rows, corresponding to the ratings from 'AAA' to 'D', plus an entry for NR (see table 22).

The only ratings considered in these calculations are those on entities at the beginning of each static pool and those at the end. All rating changes that occur in between are ignored. For example, if an entity was rated 'A' on Jan. 1, 2024, and was downgraded to 'BBB' in the middle of the year and then upgraded to 'A' later in the year (with no other subsequent rating changes), this entity would be included only in the percentage of issuers that began the year as 'A' that ended the year as 'A'. This also applies to transition matrices that span longer time horizons. If an issuer defaults or if the rating on the issuer is withdrawn in the middle of the year, then it would be considered rated 'D' or not rated as of Dec. 31 of that particular year.

Table 29

Multiyear transitions.  Multiyear transitions were also calculated for periods of two up to 20 years. In this case, we compared the rating at the beginning of the multiyear period with the rating at the end. For example, three-year transition matrices were the result of comparing ratings at the beginning of the years 1981-2022 with the ratings at the end of the years 1983-2024. Otherwise, the methodology was identical to that used for single-year transitions.

We calculated average transition matrices on the basis of the multiyear matrices just described. These average matrices are a true summary, the ratios of which represent the historical incidence of the ratings listed in the first column changing to the ones listed in the top row over the course of the multiyear period (see tables 33-40). Transition matrices that present averages over multiple time horizons are also calculated as issuer-weighted averages.

Rating modifiers.  We use rating modifiers (plus and minus signs) to calculate upgrade and downgrade percentages, as well as the magnitude of rating changes, throughout this study. However, some transition tables may use full rating categories for practical reasons. In other words, the use of a rating category suggests that transitions, for example, to 'AA' from 'AA-' or to 'BBB+' from 'BBB-', are not considered to be rating transitions because the rating remained within the rating category.

Comparing transition rates with default rates.  Rating transition rates may be compared with the marginal and cumulative default rates described in the previous sections. For example, the one-year default rate column of table 24 is equivalent to column 'D' of the average one-year transition matrix in table 21, as well as the cumulative average in the "Summary statistics" of the one-year column in table 32.

However, the two-year default rate column in table 24 is not the same as column 'D' of the average two-year transition matrix in table 34. This difference results from the different methods of calculating default rates. The default rates in table 34 are calculated as not conditional on survival, while those in table 24 are average default rates conditional on survival. The two-year default rates in table 24 are calculated in the same way as those in the cumulative average section for the two-year column in table 32, while those in the 'D' column of table 34 are equivalent to adding up all the defaults behind the two-year column's annual default rates in table 32, divided by the sum of all the issuers in table 32 for the years 1981-2024.

The links between transition matrices and average cumulative default rates are best illustrated through tables 30-32. The default rates in the columns of these tables, associated with each static pool year, are calculated in the same way as they would be for individual years' one-year transition matrices. Tables 30, 31, and 32 are broken out by the broadest rating classifications (all rated, investment grade, and speculative grade). These tables can also be constructed for each rating category.

As an example, the two-year column of table 32 shows the two-year default rates (not conditional on survival) for each static pool. These are calculated in the same way as the default column in table 20, though table 20 shows the one-year default rates for each rating category for 2024 exclusively. In the summary section at the bottom of tables 30-32, the first row shows the issuer-weighted averages of the marginal default rates. These marginal averages are then used to calculate the cumulative average default rates in the row directly beneath them, as explained in the "Average cumulative default rate" section above. These default rates are the same that appear in table 24 and are average cumulative default rates conditional on survival.

Standard deviations.  Many of the tables and charts in this study display averages of default rates, transition rates, and Gini ratios. Often these are issuer-weighted averages. Prior studies have shown that fluctuations within default rates and transitions can vary greatly depending on many circumstances specific to particular time frames, industries, and geographic regions. As a supplement to many of the averages and time series presented in this study, standard deviations are also shown to provide a gauge of the dispersion of data behind these averages.

For the transition matrices in tables 21-23 and 33-44, the standard deviation for each cell in a given matrix is a weighted standard deviation, calculated using the data from each of the underlying cohort years that contribute to the averages, weighted by that cohort year's issuer base for each rating level.

For the Gini ratios in tables 2, 27, and 28, the standard deviations are derived from the time series of Gini ratios for all of their constituent annual cohorts. As an example, the standard deviation applied to the seven-year weighted average global Gini ratio in table 2 (5.3%) was calculated from the time series of all available seven-year Gini ratios by cohort. In this case, these are the seven-year Gini ratios from the 1981 cohort through the 2018 seven-year cohort. We calculated standard deviations for Gini ratios in this study as the standard deviations of a sample, and not those of a population.

Time sample.  This study limits the reporting of default rates to the 15-year time horizon. However, the data was gathered for 44 years, and all calculations are based on the rating experience of that period. In addition, average default statistics become less reliable at longer time horizons as the sample size becomes smaller and the cyclical nature of default rates has a bigger effect on averages.

Table 30

Table 31

Table 32

Table 33

Table 34

Table 35

Table 36

Table 37

Table 38

Table 39

Table 40

Table 41

Table 42

Table 43

Table 44

Appendix II: Gini Methodology

We utilize the Lorenz curve, a graphical representation of the proportionality of a distribution, as one measure of ratings performance, and we summarize this via the Gini coefficient. For this study, the Lorenz curve is plotted with the x-axis showing the cumulative share of issuers, arranged by rating, while the y-axis represents the cumulative share of defaulters, also arranged by rating. For both axes of the Lorenz curve, the observations are ordered from the low end of the ratings scale ('CCC'/'C') to the high end ('AAA').

As an example, if 'CCC'/'C' rated entities made up 10% of the total population of issuers at the start of the time frame examined (x-axis) and 50% of the defaulters (y-axis), then the coordinate (10, 50) would be the first point on the curve. If S&P Global Ratings' corporate ratings only randomly approximated default risk, the Lorenz curve would fall along the diagonal. Its Gini coefficient--which is a summary statistic of the Lorenz curve--would thus be zero. If corporate ratings were perfectly rank ordered so that all defaults occurred only among the lowest-rated entities, the curve would capture all of the area above the diagonal on the graph (the ideal curve), and its Gini coefficient would be 1 (see chart 31).

The procedure for calculating the Gini coefficients is illustrated in chart 31: 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 total of area A plus area B. In other words, the Gini coefficient captures the extent to which actual ratings accuracy diverges from the random scenario and aspires to the ideal scenario.

Related Research

• S&P Global Ratings Definitions, Dec. 2, 2024
• Default, Transition, and Recovery: U.S. Recovery Study: Loan Recoveries Persist Below Their Trend, Dec. 15, 2023