Defaults And Downgrades Rise But Remain Historically Low

In 2022, six financial services entities rated by S&P Global Ratings defaulted, up from four a year earlier (see chart 1). One of these was confidentially rated. Due to the rise in defaults, the 2022 default rate rose slightly to 0.28% from 0.14%, which is comparable to the 2017 level of 0.3% , when seven issuers defaulted.

All of the defaults were speculative-grade at the start of the year, which is similar to trends seen since 2017. Two out of five publicly rated defaults were from Mexico and the other three were from nonbank financial institutions (NBFI). There were no defaults in the U.S. last year. There were also no defaults related to the Russia-Ukraine conflict--all the defaults came from weaknesses specific to the financial institutions.

Half of defaults in 2022 were due to missed interest or principal payments. Regulatory directives and distressed exchanges were other reasons issuers defaulted. While an increase in downgrades from 2021 levels caused the ratio of downgrades to upgrades to increase to 0.61x from 0.53x, this remains lower than the average of 1.93x and maximum of 8.53x seen during 1981-2022.

We identified a clear negative correspondence between ratings and defaults: the higher the issuer credit rating, the lower the observed default frequency. This indicates that credit ratings remain effective indicators of relative credit risk for financial services issuers.

We show the relationship between ratings and defaults with the Gini ratio, which is a measure of the rank-ordering power of ratings over a given time horizon (see table 1). This measure shows the ratio of actual rank-ordering performance to theoretically perfect rank ordering.

In 2022, the one-year Gini coefficient for financial services fell to 87%, down from 89.4% in 2021 (see chart 2), the three-year Gini fell to 83.9% from 95.5%, the five-year Gini fell to 88.1% from 92.5%, and the seven-year Gini remained at 89.5%. These weighted-average Gini ratios are weighted by yearly issuer counts since 1981 (see Appendix III for details).

Comparing financial and nonfinancial annual average Gini coefficients from 1981 to 2022, we see that both sectors see the rank ordering of defaults and ratings decline over time, with a Gini ratio for financials of 80.2% over one year compared to 58.9% over seven years (see table 1). This trend is expected, as longer time horizons allow for more credit deterioration from higher rating levels.

Three financial services issuers rated in the 'BB' rating category one year prior to default defaulted during 2022, and this brought the one-year financial services Gini ratio to 87%, down from 89.4% in 2021 but still above the long-term weighted average of 80.2%.

Table 1

Defaults In 2022

• The speculative-grade default rate for financial services rose to 1.2%, from 0.57% in 2021, as more speculative-grade issuers defaulted.
• There were six defaults in total, five of which were publicly rated by S&P Global Ratings in 2022 and one with a confidential rating.
• Among the entities that defaulted in 2022, the average time to default was 6.7 years from the initial rating, close to the average of 7 years for the issuers that defaulted in 2021.
• In 2022, four out of five publicly rated defaults were rated 'CCC' or below just prior to default and one was rated 'B+'. One year prior to default, three issuers were rated in the 'BB' rating category.

Table 2

Table 3

Financial services issuers tend to see fewer defaults than nonfinancial corporates (see chart 3). In 2022, financial services comprised only 8.5% of total corporate defaults. While the financial services default rate was at 0.28% in 2022, the default rate for nonfinancial corporates was 4.5x higher and reached 1.3%. Even at the worst period of the global financial crisis in 2008-2009, the overall financial services default rate remained below 1.5%.

Defaults of banks and NBFIs can be procyclical, as the sector reflects current macroeconomic conditions. For example, like nonfinancials, financial services experienced more defaults in 2022 than 2021 considering a year of monetary tightening by multiple central banks accompanied by growing macroeconomic uncertainties. Still, also like nonfinancial corporates, 2022 default rates by subsector remain below their long-term averages.

Nonetheless, the financial services default rate rose and was above the default rates of the past two years. Three NBFIs, two banks, and one confidentially rated issuer defaulted, resulting in 2022 default rates of 0.59% and 0.36% for NBFI and banks, respectively. No insurance issuers defaulted in 2022, similar to 2021 and down from one in 2020.

The publicly rated financial services defaults in 2022 were:

• Mexico-based NBFI Credito Real S.A.B. de C.V. SOFOM E.N.R., which failed to pay principal on swiss franc 170 million senior notes due Feb. 9, 2022.
• Singapore-based nonoperating holding company Mulhacen Pte. Ltd., which announced the completion of a bond restructuring that we considered a distressed transaction and tantamount to a default since bondholders have received less than they were originally promised and in the form of a more junior, longer-dated instrument.
• Mexico-based NBFI Unifin Financiera S.A.B. de C.V., which announced that it won't make interest and principal payments on all its debt--except on its non-recourse private securitizations--until it reaches a debt restructuring agreement.
• Turkiston Bank, which had its banking license revoked by the Central Bank of Uzbekistan. The company has said it will start proceedings to settle obligations to creditors in accordance with bankruptcy legislation.
• European-based Corestate Capital Holding S.A., which missed the repayment of its convertible bond on the maturity date of Nov. 28, 2022.

Defaults across all financial institutions in 2022 were below the long-term averages since 1981, as well as more recent 10-year averages (see table 4). The 10-year averages for banks, NBFIs, and insurance companies were 0.40%, 0.66%, and 0.06%, respectively, versus close to the 1.8% level for nonfinancials. The insurance default rate average remains the lowest among financial and nonfinancial companies for 1981-2022.

Table 4

Financial Services Rating Trends In 2022

Ratings on financial services companies have become more stable in the past 10 years, as only 16.8% of entities had a change of rating in 2022, compared to 24.6% 10 years earlier (see table 5).

In general, financial services tended to see more downgrades than upgrades, with 29 out of the past 42 years with a downgrade-to-upgrade ratio above one. But in recent years, upgrades have generally outpaced downgrades.

Downgrades started to slightly rise to 3.7%, from 3.6% in 2021, amid rising macroeconomic risks across regions and sectors. But upgrades remained higher than downgrades, finishing 2022 at 6.1% of financial services entities rated at the start of the year, down from 6.8% in 2021.

Despite the higher downgrade-to-upgrade ratio, credit stability--which indicates the share of unchanged ratings--was 83% in 2022, compared to 84% in 2021. The metric has been above 80% over the past four years, having previously not reached that level since 1985.

Persistent inflation, tighter funding conditions, and lower economic growth impacted the credit performance of rated financial institutions in 2022. The largest share of financial services downgrades in the year came from NBFIs (46%), followed by banks (33%), and insurance companies (21%). In 2021, banks led in downgrades. From a regional perspective, 52% of downgrades came from emerging and frontier markets, up from 31% a year earlier.

Rising interest rates made it more difficult for NBFIs to transfer higher rates to their borrowers and increased funding costs. For banks, rising rates led to increase in net interest margins that offset higher provisions and expenses. For insurance companies, higher rates have required careful management, but over time they might spur higher investment returns for the industry. Asset liquidity issues, heightened by weak liability structures in times of stress, have historically been a main cause of insurer failure, especially for life insurers.

Table 5

Banks

Banks comprised the largest of the three financial services sectors in 2022, with 825 issuers at the start of the year. The stability rate was slightly lower in 2022 at 81.1%, compared to 83.1% in 2021, primarily because of more rating withdrawals. The year also saw some increase in upgrades (to 7.6% from 7.5%) and a sharp decrease in downgrades (3.3% from 4.8%). However, the default rate increased slightly, to 0.36% from 0.24% (see Appendix I for detailed statistics by sector).

Both of the publicly rated bank defaults in 2022 came from Asia (Singapore and Uzbekistan). There were no defaults or bank downgrades in the U.S. last year. Emerging and frontier market banks accounted for 76% of downgrades in 2022, followed by Europe with 17%.

On the one hand, solid profitability due to higher net interest income helped banks in developed markets to absorb higher operating and credit costs. On the other hand, in 2022 major central banks in emerging and frontier markets were tightening monetary policy faster than initially expected, which made global liquidity scarcer and more expensive.

The negative bias for rated issuers across emerging and frontier markets was due to high interest rates, persistent inflation, and weakening demand that put some pressure on banks' asset quality. A few issuers benefited from this situation, mainly in commodity exporting countries, thanks to lower cost of risk and higher interest rates. Elsewhere in emerging and frontier markets, profitability remained under pressure.

Europe contributed to the overall credit performance improvement last year as the number of downgrades decreased in 2022 compared to 2021. In 2022, our ratings bias remained stable in Europe, but we cannot disregard more negative outlooks emerging given sizable downside risks to our macro projections (see "Global Bank Outlook 2023: Greater Divergence Ahead," Nov. 17, 2022).

Insurance

Insurance is the second largest sector, starting 2022 with 787 issuers. Insurance issuers saw the fewest downgrades among financial services in 2022, with 1.7% lowered (down from 1.9% the previous year), and 6% raised (up from 5.2%). Insurance also tends to have the highest stability rates, with 87.6% of ratings unchanged in 2022, and a historical average of 78.9%.

Insurers are clearly exposed to macroeconomic and financial market pressures, but enhanced risk management practices over the past decade (for example, a focus on asset/liability management, strategic asset allocation, and sector and obligor concentration limits), combined with capital buffers and product redesign, have led to ratings stability, even in recent times of stress.

In 2022, the U.S. led downgrades in insurance sectors such as property/casualty, life, and mutual insurance as higher inflation and supply chain disruptions weighed on underwriting results. Over the second half of 2022, pressure mounted on some insurance sectors as higher interest rates weakened balance sheets and our view of capital adequacy.

NBFI

NBFI is the smallest of the three sectors, with 511 issuers at the start of the year. However, it saw the highest year-on-year growth of the rated portfolio in 2022 since mid-1990s. NBFI experienced the fewest upgrades as a percentage of the population, with 3.9% (down from 8.4%), and was the only sector where downgrades increased, rising to 7.6% in 2022 from 4.5% in 2021. Defaults rose to 0.6% from 0.2%.

Combined, the U.S. and emerging and frontier markets (primarily Greater China including Hong Kong, Macau and Taiwan) accounted for 34 out of 38 downgrades from NBFI in 2022, equally split between the two regions. Surging funding costs in 2022 limited companies' refinancing options.

NBFIs are vulnerable to disruptions in funding access given geopolitical tensions, slowing economies, and spiking interest rates. These entities tend to rely more on market funding and don't benefit from access to central bank credit lines. For them, tighter financing conditions may in some cases prove more challenging even if many have used the past years of abundant market liquidity to push out debt maturities.

Investment-Grade Issuers Account For The Largest Share Of Financial Institutions

Financial services issuers accounted for 2,053 rated issuers globally at the start of 2022 while nonfinancial accounted for 4,989 rated issuers. As of Jan. 1, 2023, 77% of financial services issuers are rated investment-grade, compared with just 39% of nonfinancial issuers.

In the last 10 and 20 years, the percentage of investment-grade financial institutions fell 10% and 20% respectively. However, the largest share remained 'A' rated issuers, which account for 39% of the financial services rated universe, followed by 'BBB' issuers at 28%, and 'BB' at 12%. There are only three 'AAA' issuers, which has gradually decreased from 112 in 1995.

Financial services entities rated by S&P Global Ratings, including the bank, NBFIs, and insurance sectors (for definitions refer to Appendix I), have maintained a median rating level of 'BBB+' since 2014. This is despite increasing global pressures and uncertainty from rising geopolitical risks, tighter financing conditions, and inflation.

The median rating of nonfinancial companies was speculative-grade at 'BB'. The insurance sector had the highest median rating of 'A' while banks and NBFIs had median ratings of 'BBB+' and 'BBB', respectively. In the last 42 years, the sharpest decline in the median rating was for banks (from 'AA') followed by NBFIs (from 'A'). However, since 2016 the median ratings have been stable for all of the rated financials services sectors.

Financial services in the U.S. and emerging and frontier market regions have a higher number of speculative-grade issuers: Emerging and frontier markets account for 53.6% of speculative-grade issuers, compared to 29.5% from the U.S., 11.8% from Europe, and 5.1% from other developed markets.

Many issuers in emerging and frontier markets have weaker creditworthiness compared to better positioned players in the more developed markets. The concentration in the low-investment-grade and speculative-grade categories in emerging and frontier markets also largely owes to lower sovereign credit ratings.

Although sovereign ratings don't act as a ceiling on issuer credit ratings, an issuer rated higher than the sovereign must be able to withstand a sovereign default. For example, government-related entities are typically more subject to country risk and negative sovereign intervention risk than private-sector entities, since they usually have direct links to governments. Some of the issuers have explicit or implicit links to the respective sovereign or have an eligible guarantee from a parent or sovereign. In all cases, the issuer credit rating is subject to any sovereign-related considerations.

In the U.S., the number of speculative-grade financial services reflects the larger proportion of speculative-grade NBFIs (41% of U.S. NBFIs are speculative-grade). In Europe, 52% of speculative-grade issuers are banks, and in other developed markets, 66% are NBFIs.

The Number Of Rated Financial Services Grew Materially In The Past 42 Years

Since 1981, the rated universe of financial services has grown materially. In the 1980s and 1990s, the number of banks and insurance companies flourished. In the past 20 years, the number of financial services issuers grew by 35% primarily due to NBFIs and insurance companies. Banks have adjusted to rising capital and new regulatory requirements since the global financial crisis. Heightened regulatory requirements for banks led to the closure of weaker banks or market consolidation, which contributed to the decline in the number of rated banks.

NBFIs has shown continued growth as new nonbank lenders, finance companies, and business development companies have entered the market. At the same time, the number of banks and insurance companies contracted to 790 banks (2006 levels) and 765 insurers (2007 levels) from the peaks of 885 banks (in 2015) and 866 insurers (in 2016) (see chart 8).

At the end of 2022, 34% of NBFIs were rated speculative-grade, compared with 26% of banks and just 11% of insurers (see chart 8). NBFIs tend to be unregulated or more lightly regulated than banks and tend not to benefit from central bank access. As a result, they are generally rated lower than regulated banks and insurance companies.

The share of banks rated investment-grade rose to 74% as of Dec. 31, 2022, from 68% at the end of 2016. The credit quality in the banking sector has continually improved in the past several years as banks have strengthened balance sheets and expanded bail-in-eligible capital reserves amid favorable economic trends (see chart 9).

Meanwhile, the number of investment-grade insurers has been strong at 87.5% in the last five years, although it's been below 90% since 2013. Insurers are less exposed to confidence sensitivity than banks but are not immune.

2022 Transition Rates And Ratings Performance

An analysis of transition rates in 2022 suggests that ratings behavior remains consistent with long-term trends, showing a negative correspondence between ratings and the observed frequency of default.

Investment-grade financial services issuers globally tend to exhibit greater ratings stability (as measured by the frequency of rating transitions) than their speculative-grade counterparts (see table 6). For instance, 94.87% of issuers rated 'A' at the beginning of 2022 were still rated 'A' as of Dec. 31, 2022, whereas the comparable share for issuers rated 'B' was only 76.61%.

Table 6

No 'AAA' rated financial institutions were downgraded in 2022. However, the number of 'AAA' rated financial institutions has been dwindling in recent years. For example, at the start of 2008, before the global financial crisis, the number of 'AAA' rated financial services issuers totaled 74 globally. By the beginning of 2023, just three 'AAA' rated financial services issuers remained.

All three entities are government-related entities, which allows S&P Global Ratings to rate them equivalently to or give additional notches of support from the respective parent:

• Nederlandse Waterschapsbank N.V. (Netherlands): The issuer credit rating (ICR) is in line with our sovereign rating on the Dutch government (AAA/Stable/A-1+) as we expect the latter would remain willing and able to provide extraordinary support to the bank as needed. The bank's stand-alone credit profile (SACP) is five notches below the ICR at 'a+', reflecting its leading position as a lender to Dutch public authorities, which grants it better asset quality than traditional commercial banks and an extremely strong capital base.

• Public Sector Pension Investment Board (Canada): the SACP of 'aaa' reflects our view of the fund's operational independence from the Government of Canada, high operational effectiveness, well-diversified portfolio, strong liquidity position, management and governance, and low leverage. In addition, the 'AAA' ICR reflects our opinion of a moderately high likelihood that the Canadian government would provide extraordinary support in the event of financial distress.

• Zuercher Kantonalbank (Switzerland): ZKB benefits from its close ties, including full ownership and a statutory guarantee, with the financially strong Canton of Zurich (AAA/Stable/--). ZKB materially benefits from its superior stand-alone creditworthiness in conjunction with the full ownership by and extremely high likelihood of timely and sufficient support from the Canton, if ever needed.

Annual Default Rates And Ratings Performance

All of our ratings performance studies have found a clear correlation between ratings and defaults: The higher the rating, the lower the observed frequency of default, and vice versa. Over each time span, lower ratings correspond to higher default rates.

We found that the same was true when we broke out the data by rating as well as by region. As the Gini ratios show, the ability of financial services ratings to serve as effective measures of relative risk remains intact, particularly across larger pools of issuers.

Many default studies, including this one, also look at transition rates, which gauge the degree to which ratings move--either up or down--over a particular time. Transition studies have repeatedly confirmed that higher ratings tend to be more stable and speculative-grade ratings generally experience more volatility.

Some issuers default after S&P Global Ratings no longer rates them. We make our best effort to capture such defaults in the database, and we include an entity in the annual default rate calculations if it was rated as of Jan. 1 in the year of default. If, however, S&P Global Ratings withdrew the rating prior to Jan. 1 of the year of default, we do not include the issuer in the default rate calculation in that year.

Although defaulters that are not rated (NR) are not always captured in the default rate calculations for the year of default, we do capture them in the longer-term cumulative default rate statistics, which are tied back to the year in which defaulters were last rated.

The path to default for financial services has been more gradual in recent years

Financial services entities typically exhibit lower average default rates and account for fewer defaults annually than nonfinancial entities. However, the path to default for financial issuers can be relatively swift. Financial institutions are typically more confidence-sensitive than nonfinancial companies, and the loss of confidence from stakeholders (such as counterparties or funding sources) can contribute to a rapid decline in liquidity and credit quality.

From 1981-2022, financial institutions that defaulted had a median rating of 'BBB-' seven years prior to default, and the median rating remained investment-grade (at 'BBB-') until just over five years prior to default. From that point, the defaulters experienced a relatively steep descent into default, with the median rating dropping to 'B+' one year prior to default.

In contrast, financial entities that defaulted over the past 12 quarters (2020-2022) typically experienced a much more gradual path to default from a much lower rating level. These issuers had a median rating of 'B+' seven years prior to default, and this median fell to 'B' over 3.5 years prior to default (see chart 10). Notably, the trailing-12-quarter median default rate for financial entities is based on a much smaller subsample of just 15 issuers, while the full history (1981-2022) covers 321 issuers.

Financial services entities with higher initial ratings, should they default, tend to show a longer time between the initial rating and the eventual default. The time to default for a defaulting issuer generally correlates with the initial rating.

For example, for the entire pool of defaulters (1981-2022), the average time to default for financial entities that were originally rated in the 'AA' category was 13.56 years from initial rating, while those initially rated in the 'B' category defaulted on average 4.14 years later (see table 7). Note that the standard deviation of the time to default is also generally smaller for lower ratings.

We treat cases where an issuer emerges from a prior default (including from distressed exchanges), as a separate entity, with a new initial rating that is first recorded after the default event.

Table 7

While no financial services issuer has ever defaulted from the 'AAA' rating level over a one-year horizon throughout the 42-year span of our study, there have been five financial services entities that eventually defaulted after receiving an initial rating of 'AAA'.

One of these was Ally Financial Inc., formerly known as GMAC Financial, a subsidiary of General Motors Corp. The issuer credit rating on this company was lowered to 'SD' from 'CC' following a distressed debt exchange in December 2008. While this issuer was initially rated 'AAA', it was downgraded to 'AA+' in 1981, more than 27 years in advance of its eventual default in 2008. While GMAC Financial was an NBFI at the time of default, the reorganized entity, Ally Financial Inc., has since become a bank holding company.

The four other 'AAA' rated defaulters were from the insurance sector. These insurers' defaults occurred as their asset values fell or as liabilities climbed following recession periods.

Three North American life insurers (Mutual Benefit Life Insurance Co., Executive Life Insurance Co. CA, and Confederation Life Insurance Co.) defaulted from 1992-1994 because of a combination of illiquid assets and insufficient liquidity to meet maturing liabilities.

These companies had asset portfolios with heavy concentrations of speculative-grade bonds, real estate investments, or commercial real estate loans, which lost value and were increasingly illiquid following the 1991-1992 U.S. recession. As policyholders lost confidence in these insurers, they accelerated withdrawals, which exacerbated the companies' inabilities to meet liabilities.

The remaining defaulter was bond insurer Ambac Assurance Corp., which was downgraded to 'SD' in 2009 due to financial weakness through exposure to the U.S. subprime housing sector.

These insurers' defaults occurred as their asset values fell or as liabilities climbed following recessions. S&P Global Ratings subsequently made adjustments to global insurance criteria to address the issues that caused these failures, including through the introduction of the capital model in 1994 and, more recently, through updates to most of the criteria for financial services companies following the global financial crisis.

Since 2011, S&P Global Ratings has further updated and revised the methodology and assumptions that it applies to determine the ratings on financial services companies. Rating methodologies and assumptions were revised in 2011 and 2019 (including a capital model update) for bond insurance, in 2013 and 2019 for insurance companies (including life, health, and property/casualty), in 2014 for NBFIs, and in 2015 and 2019 for mortgage insurance.

For banks, S&P Global Ratings updated its rating methodology and assumptions in 2011. The revised criteria also consider the relationship of the banking industry in a country to its financial system as a whole.

The banking industry country risk assessment (BICRA) criteria were also updated in 2011, providing a framework to compare global banking systems, including the role of government supervision, regulation, and systemwide support programs. We use BICRA to determine a bank's anchor, the starting point in assigning an ICR.

In December 2021, S&P published revised criteria for financial institutions, which enhanced the consistency of our terminology and approaches, to incorporate relevant developments since the publication of the previous articles (including newer or emerging risks), and to enable S&P Global Ratings to communicate more clearly on the drivers of rating changes.

On Dec. 6, 2021, S&P Global Ratings published a request for comment (RFC) on proposed changes to its risk-based capital adequacy methodology for insurers and reinsurers. We have completed our review of the substantial volume of feedback received. On May 9, 2023, we issued a subsequent RFC, which incorporated market feedback (see "Request For Comment: Insurer Risk-Based Capital Adequacy--Methodology And Assumptions," May 9, 2023).

Higher-rated entities had fewer defaults than lower-rated ones

The lower frequency of default among higher-rated entities and higher rate of default among lower-rated entities remains true over time (see chart 11).

The relationship between default rates and ratings is most apparent through the cumulative rates, with the lowest rating categories exhibiting default rates far in excess of those in the investment-grade categories.

The lowest investment-grade rating category, 'BBB', has a one-year weighted long-term average default rate (since 1981) of 0.21%. The average default rate more than doubles to 0.59% for the 'BB' category and rises further to 2.37% for the 'B' category, and 16.89% for the 'CCC'/'C' category.

The speculative-grade default rate for the 'B' category dropped to 0.46% in 2022, while it rose for 'BB' and 'CCC/C' to 0.72% and 13.6%, respectively. The 'BB' rate is higher than its long-term weighted average of 0.59%, while the rates for 'B' and 'CCC/C' are lower than their respective long-term weighted averages of 2.4% and 16.9% respectively.

For financial services, the pool of issuers rated in each speculative-grade rating category is often relatively small, particularly for the 'CCC'/'C' category. As of Jan. 1, 2023, speculative-grade ratings accounted for only 23% of financial services issuers, and the 'CCC'/'C' category accounted for roughly 1%.

Given the small base of ratings (particularly in earlier years), the default rate for entities rated 'CCC'/'C' has climbed as high as 100% (in 1982, when there was only one financial issuer rated 'CCC'/'C' at the beginning of the year) while the 'B' category default rate peaked at 25% in 1982 (with one default) (see table 8).

Table 8

By contrast, the relationship is slightly more discontinuous when we examine rating transitions across modifiers (the plus or minus after a rating) or by sector, but these variations are likely a result of sample size considerations, and we do not consider them significant (see table 9 for default rates by rating modifier and Appendix I for default rates by sector).

Additionally, when examining default rates by rating modifier, we see a few higher-than-expected default rates for some investment-grade ratings in certain years. For instance, in 1983, the default rate for 'BBB-' rated financial issuers climbed to 16.67%. Notably, this rate reflected the default of just one issuer, and the default rate for the 'BBB' category as a whole in 1983 was just 3.8%.

Since 1981, no financial services issuers rated 'AAA' or 'AA+' have defaulted over a one-year horizon. However, over this period, three financial services issuers rated either 'AA' or 'AA-' defaulted:

• General American Life Insurance Co.: After aggressively growing its guaranteed investment contract product line in prior years, the company did not have sufficient liquidity and was taken under administrative supervision in 1999, following a spike in surrender rates on the contracts.
• Lehman Brothers Inc.: The company filed for Chapter 11 bankruptcy protection in 2008 following the deterioration of its U.S. subprime housing assets.
• BluePoint Re: This company was taken over by its regulatory authority in 2008 as projected losses mounted on subprime and second-lien residential mortgage-backed security and asset-backed security collateralized debt obligations that it had reinsured.

In the last six years, however, there have been no defaults from investment-grade financial services issuers. In the last 10 years, there was only one default, from 'BBB', and in the last 13 years, there were only two defaults from all investment-grade financial institutions.

Table 9

Average Transition Tables And Cumulative Default Rates

This study--in line with previous default studies--confirms that over the long term (1981-2022), higher ratings are more stable than lower ratings. For financial services entities, the highest rating categories of 'AAA', 'AA', and 'A' each displayed stability rates of 87% or higher for a one-year horizon.

Of these three rating categories, the 'A' category had the highest stability rate, at 89.6%, meaning that 89.6% of 'A' rated issuers remained within that rating category over one year. The stability rates for the 'AAA' and 'AA' categories were slightly lower but still very high at 87.1% and 87.7%, respectively.

In comparison, ratings in the 'B' category had a notably lower stability rate of 76.4% over one year (see table 10).

When we examine rating transitions by modifier, the general relationship between rating and stability tends to hold (see table 11). For example, 'A+' rated issuers were still rated 'A+' one year later 80% of the time, and 'A-' rated issuers were still rated 'A-' one year later 78.8% of the time.

These long-term relationships also broadly hold when transition rates are calculated over longer time horizons and when broken out by region (see table 12), though we do see some exceptions, largely due to sample size considerations, which we do not consider significant.

Over the long term (1981-2022), heightened ratings stability is broadly consistent with higher ratings. A key observation when analyzing transition matrices that present averages computed over multiple static pools is that the standard deviations associated with each transition point in the matrix are large relative to the averages (outside of stability rates).

Table 10

Table 11

Table 12

Lower Ratings Are Consistent With Higher Default Vulnerability

Lower ratings continue to exhibit higher default rates over each time span (for example, as in the one- to 15-year time horizons shown in table 13). This generally holds true across regions as well, though some exceptions occur when the number of defaults is low or when the underlying population of issuers is very small--such as among the highest and lowest rating categories, or at the rating modifier level (see tables 14 and 15).

Investment-grade issuers seldom default, so the number of defaults among these rating categories is particularly low. This small sample size can result in historical default rates that appear counterintuitive.

The cumulative default rates by rating modifier do not imply, for example, that 'AAA' rated companies are riskier than 'AA+' rated companies over a horizon of less than 10 years, but rather that both are highly unlikely to default. By rating modifier, each of the ratings from 'AAA' to 'A-' exhibits a 15-year cumulative default rate below 2.0%

Table 13

Table 14

Table 15

Gini Ratios And Lorenz Curves

A quantitative analysis of the performance of S&P Global Ratings' credit ratings shows that ratings on financial services issuers correlate with the level of default risk across several time horizons. To measure ratings performance, we plotted the cumulative share of defaulters against the cumulative share of issuers by rating in a Lorenz curve to visually render the accuracy of the rank ordering (see Appendix III). Over the long term, the global weighted-average one-year Gini coefficient for banks is 83.5%, followed by insurance (74.5%), and NBFIs (73.6%) (see table 16).

Table 16

As expected, the Gini coefficients decline over time because longer time horizons allow for greater opportunity for credit degradation among higher-rated entities. For example, in the one-year global Lorenz curve, 83.2% of defaults occurred in the speculative-grade category, while speculative-grade ratings constituted only 18.3% of all financial services ratings. In the five-year Lorenz curve, speculative-grade issuers constituted 65% of defaulters and only 17.1% of the entire sample.

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 (see charts 12-14). The quick deterioration of Gini ratios also reflects issuers' vulnerability to a loss of confidence, even among highly rated entities.

Among the three financial services sectors, insurance companies exhibit Gini ratios that are lower over three or more years, which reflects, in part, fewer insurance companies that eventually defaulted.

Appendix I: Detailed Default And Transition Statistics By Financial Services Sector

Bank rating action trends and ratings performance

Table 17

Table 18

Table 19

Table 20

Table 21

Table 22

Table 23

Table 24

Nonbank financial institutions rating action trends and ratings performance

Table 25

Table 26

Table 27

Table 28

Table 29

Table 30

Table 31

Table 32

Insurance rating action trends and ratings performance

Table 33

Table 34

Table 35

Table 36

Table 37

Table 38

Table 39

Table 40

Appendix II: 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. The 'pi' qualifier was used to indicate ratings that were based on an analysis of an issuer's published financial information, as well as additional information in the public domain. We discontinued use of 'pi' ratings as of December 2014.

We also do not include short-term issuer 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-level rating used for the proxy because this rating 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 consider 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 is self-contained and effectively supersedes all previous versions.

Issuers included in this study

This study analyzes the rating histories of 5,600 financial institutions that S&P Global Ratings rated as of Dec. 31, 1980, or that were first rated between that date and Dec. 31, 2022. These include banks, nonbank 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, we review the defaults, rating transitions, and ratings performance of financial services broadly, in the following sectors:

• Banks: bank holding companies, bank subsidiaries, savings and loans, credit unions, and government-related entities;
• Nonbank financial institutions (NBFIs): a loose grouping of highly diverse companies, including broker-dealers, asset managers, finance companies, financial market infrastructure companies, and other financial entities that share some common features; and
• Insurance: life insurance, health insurance, property/casualty insurance, reinsurance, bond insurance, mortgage insurance, insurance brokers, and title insurance, as well as insurance-related service providers.

We calculated default and transition rates based on the number of issuers in the sample period. The default rates 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.

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. For the purposes of this study, a corporate rating may also be withdrawn as a result of mergers and acquisitions. 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.

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, excluding hybrid instruments classified as regulatory capital or in nonpayment according to terms. An obligor is considered to be 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 to pay some obligations and not others. While the 'R' rating was in place during the many of the years covered in this study, it was removed from all ratings scales on July 5, 2019 (see "S&P Global Ratings Definitions," Nov. 10, 2021).

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 often present specific geographic regions. Some countries can be included in multiple regions, and S&P Global Ratings does not have corporate ratings within every country. The regions covered in this study are:

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

Other developed:  Australia, Brunei Darussalam, Canada, Israel, Japan, Republic of Korea, New Zealand, 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, Republic of Moldova, Monaco, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, and the U.K.

Emerging markets:

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

EMEA (Europe, the Middle East, and Africa).   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, Republic of 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:

Asia-Pacific.   Cambodia and Marshall Islands

EMEA.   Liberia, Syrian Arab Republic, and Togo

Latin America and Caribbean.   Aruba, Bahamas, Curacao, Netherlands Antilles (dissolved in 2010), Turks and Caicos Islands, and Venezuela

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 (by rating category, for example) 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 back to all of the static pools to which the issuer belonged.

We use the static pools to avoid certain pitfalls in estimating default rates, ensuring that default rates account for rating migration and can 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--are surveilled with the aim of capturing a potential default. Because static pools only include 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 it in that static pool as a default 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 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 1983-2022. From Jan. 1, 1981, to Dec. 31, 2022, a total of 5,509 first-time-rated financial services entities were added to form new static pools, while we excluded 321 defaulting companies and 3,242 companies that were no longer rated.

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 40 years the study covers (see chart 11 and tables 13-15, 22-23, 30-31, and 38-39).

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. 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).

Transition analysis

Transition rates compare issuer 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 to 1991. If the rating on the issuer was withdrawn in the middle of 1991, it would be included in the column representing transitions to not rated ("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, 2022, had 42 one-year transitions, while companies first rated on Jan. 1, 2022, had only one. Table 6 displays the summary of one-year transitions in the investment-grade and speculative-grade rating categories in 2022. 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 12).

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 rated 'A' on Jan. 1, 2022, 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 at 'A' and ended the year at 'A'. This also applies to transition matrices that span longer time horizons. If an issuer defaults or if the issuer rating 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.

Multiyear transitions

Multiyear transitions were also calculated for periods of two up to 10 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 1981-2020 with the ratings at the end of the years 1983-2022. Otherwise, our approach 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 10, 19, 27, and 35). 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 to, for example, 'AA-' from 'AA' or to 'BBB-' from 'BBB+' are not considered to be rating transitions because the rating remained within the rating category.

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 in 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.

Time sample

This update limits the reporting of default rates to the 15-year time horizon. However, we gathered the data for 42 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.

Appendix III: Gini Methodology

To measure relative ratings performance, we utilize the Lorenz curve as a graphical representation of the proportionality of a distribution, 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 24).

The procedure for calculating the Gini coefficients 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 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 Criteria And Research

Related Criteria

• Request for Comment: Insurer Risk-Based Capital Adequacy--Methodology And Assumptions, May 9, 2023
• Banking Industry Country Risk Assessment Methodology And Assumptions, Dec. 9, 2021
• Financial Institutions Rating Methodology, Dec. 9, 2021
• S&P Global Ratings Definitions, Nov. 10, 2021
• Insurers Rating Methodology, July 1, 2019

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