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Sears Strikes Out What Is In Store For Other Retailers In The US

2019 Credit Risk Perspectives Is The Credit Cycle Turning A Fundamentals View

2019 Credit Risk Perspectives Is The Credit Cycle Turning A Market Driven View

Flying Into The Danger Zone; Norwegian Air Shuttle

Credit Analytics Case Study: Hyflux Ltd.

Credit Analysis
Sears Strikes Out What Is In Store For Other Retailers In The US

Nov. 13 2018 — Recently, Sears Holdings Corp. (“Sears”) became yet another retailer in the U.S. that defaulted, and the firm filed for Chapter 11 on October 15, 2018. Similar to other retailers, this former giant could not keep pace with its more agile competitors in a fast-changing landscape. As reported by S&P Global Ratings,1 Sears’s default brings the annual corporate default tally in the U.S. to 37 as of October of this year, making the retail sector the largest contributor with eight defaults to date.

Sears transformed how America shopped and was once the largest retailer and largest employer in the country. However, it gradually fell out of consumers’ favour, and online stores and big box rivals took the helm. Sears' last profitable year was in 2010, and rapidly declining sales and weak cash flow offered the company limited room to improve its operations. Sears dipped into its assets to fund ongoing operations, closing more than 3,000 out of its 4,000 stores between 2011 and 2018. However, continuously negative earnings and a high interest burden prevented Sears from going on without a reorganization. The company’s credit rating by S&P Global Ratings captured this gradual decline in credit quality, deteriorating from ‘A-’ in 2000 to ‘CCC-’ prior to default.2

Only a limited number of companies have assigned credit ratings by a Credit Rating Agency (CRA), leaving out a significant part of the corporate universe. S&P Global Market Intelligence’s Credit Analytics suite includes a range of statistical tools that facilitate an efficient and cost-effective evaluation of a company’s credit quality by generating credit scores3 for both rated and unrated corporates globally. PD Model Fundamentals (PDFN) is a quantitative model that utilizes both financial data from corporates and the most relevant macroeconomic data available to generate probability of default (PD) values over a one- to more than 30-year horizon for corporations of any size. The numerical PD values can be mapped to S&P Global Market Intelligence credit scores (e.g. ‘bbb’), which are based on historical observed default rates extracted from the S&P Global Ratings’ database (available on CreditPro®).

In the analysis that follows, we review the credit risk landscape of retailers in the U.S., and explore which risk factors are the main drivers of PD. We then take a look down the road and assess how possible future macroeconomic scenarios may impact the credit risk of retailers in the U.S.

U.S. Retail Landscape

By leveraging PDFN, we can broaden the view beyond the realm of the CRA-rated universe. Figure 1 shows the distribution of implied credit scores obtained using PDFN for U.S. public retail companies. From 2013 to 2018, the distribution of the credit scores has been gradually shifting toward lower credit scores. In this period, the average credit score shifted from ‘bb+’ to ‘bb’, whilst the percentage of companies in the speculative credit score category (credit score ‘bb+’ and below) increased from 60% to 74%. These trends are symptoms of a change in the risk profile of the U.S. retail industry, which resulted in the bankruptcy of several other big retailers (e.g., Toys “R” US, Inc., RadioShack Corp., and The Bon-Ton Stores, Inc.).

In the second quarter of 2018, 45% of companies in our sample had been assigned a credit rating by S&P Global Ratings. Importantly, whilst a majority (76%) of companies in the investment grade universe do have a CRA rating, the speculative grade is largely unaddressed, with only 35% of companies in our sample having been assigned a credit rating by S&P Global Ratings. The use of statistical models, such as PDFN, assists investors in expanding the analysis and providing a comprehensive overview of credit risk across a wider universe.

Figure 1: Distribution of PDFN credit scores for public companies in the retail sector in the U.S.

Source: S&P Global Market Intelligence (as of October 22, 2018). For illustrative purposes only.
Notes: Public companies in the retail sector in the U.S. (GICS® 2550 and 3010). Distribution of companies based on PDFN credit scores calculated using the latest financial data for each respective period.

Drivers of Default

We further explore which risk factors are the main contributors of the PD for the retail sector. Credit Analytics’ models are equipped with tools, such as contribution analysis, which helps users identify drivers of risk in absolute or relative terms. These tools assess the “weight” or importance of the contribution of each risk factor to the credit risk estimate.

We divide the companies in deciles based on their PD and construct financial ratios for a median company in each decile. Next, we calculate PDs for each median company and evaluate associated absolute contributions of each risk factor.

Figure 2 shows the absolute contribution of each risk factor for a median retail company, a median retail company in the top decile, and a median retail company in the bottom decile. Note that absolute contributions for each company add to 100% to facilitate comparability, however, their nominal values are scaled by PD values and are, thus, markedly different.

Figure 2: Overview of absolute contribution of credit risk drivers for public companies in the retail sector in the U.S.

Source: S&P Global Market Intelligence (as of October 22, 2018). For illustrative purposes only.
Notes: Public companies in the retail sector in the U.S. (GICS® 2550 and 3010).

Efficiency and profitability represent important drivers of PD, directly reflecting an operating environment of low margins in the retail sector. Together with company size, these three risk factors represent roughly 50% of the PD value. In addition, low margins also limit available funds to respond to unexpected expenses and investment opportunities, resulting in restricted financial flexibility. However, the current macroeconomic environment for retail companies in the U.S. is favourable, and represents a small part of the PD value. On average, these companies have sustainable capital structures and sufficient liquidity, resulting in the limited contribution of these factors to PD.

For retail companies with high credit risk (bottom decile denoted in red in Figure 2), the company size, whilst still important, is no longer the only dominant factor. Factors like profitability, sales growth, and debt service capacity grow in importance and represent key factors when determining the credit quality of riskier retail companies.

View Down the Road

Next, we review how future economic scenarios may impact the credit risk of the public companies within the U.S. retail sector from a systematic point of view. The Credit Analytics Macro-Scenario model enables risk managers and analysts to gauge how a firm’s credit risk may change across both user-defined and pre-defined forward-looking scenarios, based on a set of macroeconomic factors. The model is trained on S&P Global Ratings’ credit ratings and leverages the historical statistical relationship observed between changes in credit ratings and corresponding macroeconomic conditions to explore what future scenarios may look like.

In Figure 3, we analyse the impact of different macroeconomic scenarios on companies with various credit scores. We depict relative changes in PD to directly demonstrate, in numerical terms, the impact on the expected loss calculation and, in turn, credit risk exposure. As a baseline prediction, we apply macroeconomic forecasts for the U.S. in 2019, developed by economists at S&P Global Ratings. We observe an increase in one-year PDs across all credit scores, suggesting a possibility of further deterioration of creditworthiness in the U.S. retail sector. Additionally, we evaluate the influence of two downturn scenarios: a mild recession scenario and a global recession scenario, which are based on economic trends during the early 2000s recession and the great recession of 2008, respectively. The downturn scenarios show proportionally larger increases in PDs, in accordance with the severity of each recession scenario.

Figure 2: Relative change of PD in the retail sector in the U.S. under various macroeconomic scenarios

Source: S&P Global Market Intelligence (as of October 22, 2018). For illustrative purposes only.
Notes: Macro-Scenario model captures the average tendency of all companies with the same creditworthiness profiles to transition to a different creditworthiness level (or remain at the same level) under a given macroeconomic condition, and does not take into account company-specific characteristics.

S&P Global Market Intelligence’s Credit Analytics suite helps users unlock relevant credit risk information to perform an overview of a company’s creditworthiness and undertake an insightful deep-dive analysis. All model inputs can be easily adjusted to perform sensitivity analysis for selected financial ratios, or to conduct a stress-test exercise using a fully-adjusted set of financials. The Macro-Scenario model integrates with standalone credit risk models and provides a forward-looking tool to help support expected credit loss calculations required by the new accounting standards: International Financial Reporting Standards 9 (IFRS 9) and the Financial Accounting Standards Board’s (FASB) Current Expected Credit Loss (CECL).

S&P Global Market Intelligence leverages leading experience in developing credit risk models to achieve a high level of accuracy and robust out-of-sample model performance. The integration of Credit Analytics’ models into the S&P Capital IQ platform enables users to access a global pre-scored database with more than 45,000 public companies and almost 700,000 private companies, obtain PD values for single or multiple companies, and perform a scenario analysis.

1 S&P Global Ratings: “Default, Transition, and Recovery: The Global Corporate Default Tally Jumps To 68 After Two U.S. Retailers And One Russian Bank Default This Week”, October 18, 2018.
2 S&P Global Ratings: “Credit FAQ: Credit Implications Of Sears Holdings Corp.'s Bankruptcy Filing For Retailers, REITs, CMBS, And Our Recovery Analysis”, October 17, 2018.
3 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit model scores from the credit ratings issued by S&P Global Ratings.
4 Numbers as of September 15, 2018.

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Credit Analytics Case Study The Bon-Ton Stores, Inc

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Credit Analysis
2019 Credit Risk Perspectives Is The Credit Cycle Turning A Fundamentals View

Mar. 15 2019 — On November 20, 2018, a joint event hosted by S&P Global Market Intelligence and S&P Global Ratings took place in London, focusing on credit risk and 2019 perspectives.

Pascal Hartwig, Credit Product Specialist, and I provided a review of the latest trends observed across non-financial corporate firms through the lens of S&P Global Market Intelligence’s statistical models.1 In particular, Pascal focused on the outputs produced by a statistical model that uses market information to estimate credit risk of public companies.

I focused on an analysis of how different Brexit scenarios may impact the credit risk of European Union (EU) private companies that are included on S&P Capital IQ platform.

Before, this, I looked at the evolution of their credit risk profile from 2013 to 2017, as shown in Figure 1. Scores were generated via Credit Analytics’ PD Model Fundamentals Private, a statistical model that uses company financials and other socio-economic factors to estimate the PD of private companies globally. Credit scores are mapped to PD values, which are based on/derived from S&P Global Ratings Observed Default Rates.

Figure 1: EU private company scores generated by PD Model Fundamentals Private, between 2013 and 2017.

Source: S&P Global Market Intelligence.2 As of October 2018.

For any given year, the distribution of credit scores of EU private companies is concentrated below the ‘a’ level, due to the large number of small revenue and unrated firms on the S&P Capital IQ platform. An overall improvement of the risk profile is visible, with the score distribution moving leftwards between 2013 and 2017. A similar picture is visible when comparing companies by country or industry sector,3 confirming that there were no clear signs of a turning point in the credit cycle of private companies in any EU country or industry sector. However, this view is backward looking and does not take into account the potential effects of an imminent and major political and economic event in the (short) history of the EU: Brexit.

To this purpose, S&P Global Market Intelligence has developed a statistical model: the Credit Analytics Macro-scenario model enables users to study how potential future macroeconomic scenarios may affect the evolution of the credit risk profile of EU private companies. This model was developed by looking at the historical evolution of S&P Global Ratings’ rated companies under different macroeconomic conditions, and can be applied to smaller companies after the PD is mapped to a S&P Global Market Intelligence credit score.

“Soft Brexit” (Figure 2): This scenario is based on the baseline forecast made by economists at S&P Global Ratings and is characterized by a gentle slow-down of economic growth, a progressive monetary policy tightening, and low yet volatile stock-market growth.4

Figure 2: “Soft Brexit” macro scenario.5

Source: S&P Global Ratings Economists. As of October 2018.

Applying the Macro-scenario model, we analyze the evolution of the credit risk profile of EU companies over a three-year period from 2018 to 2020, by industry sector and by country:

  • Sector Analysis (Figure 3):
    • The median credit risk score within specific industry sectors (Aerospace & Defense, Pharmaceuticals, Telecoms, Utilities, and Real Estate) shows a good degree of resilience, rising by less than half a notch by 2020 and remaining comfortably below the ‘b+’ threshold.
    • The median credit score of the Retail and Consumer Products sectors, however, is severely impacted, breaching the high risk threshold (here defined at the ‘b-’ level).
    • The remaining industry sectors show various dynamics, but essentially remain within the intermediate risk band (here defined between the ‘b+’ and the ‘b-’ level).

Figure 3: “Soft Brexit” impact on the median credit risk level of EU private companies, by industry.

Source: S&P Global Market Intelligence. As of October 2018.

  • Country Analysis (Figure 4):
    • Although the median credit risk score may not change significantly in certain countries, the associated default rates need to be adjusted for the impact of the credit cycle.6 The “spider-web plot” shows the median PD values for private companies within EU countries, adjusted for the credit cycle. Here we include only countries with a minimum number of private companies within the Credit Analytics pre-scored database, to ensure a robust statistical analysis.
    • Countries are ordered by increasing level of median PD, moving clock-wise from Netherlands to Greece.
    • Under a soft Brexit scenario, the PD of UK private companies increases between 2018 and 2020, but still remains below the yellow threshold (corresponding to a ‘b+’ level).
    • Interestingly, Italian private companies suffer more than their Spanish peers, albeit starting from a slightly lower PD level in 2017.

Figure 4: “Soft Brexit” impact on the median credit risk level of EU private companies, by country.

Source: S&P Global Market Intelligence. As of October 2018.

“Hard Brexit” (Figure 5): This scenario is extracted from the 2018 Stress-Testing exercise of the European Banking Authority (EBA) and the Bank of England.7 Under this scenario, both the EU and UK may go into a recession similar to the 2008 global crisis. Arguably, this may seem a harsh scenario for the whole of the EU, but a recent report by the Bank of England warned that a disorderly Brexit may trigger a UK crisis worse than 2008.8

Figure 5: “Hard Brexit” macro scenario.9

Sources:”2018 EU-wide stress test – methodological note” (European Banking Authority, November 2017) and “Stress Testing the UK Banking system: 2018 guidance for participating banks and building societies“ (Bank of England, March 2018).

Also in this case, we apply the Macro-scenario model to analyze the evolution of the credit risk profile of EU companies over the same three-year period, by industry sector and by country:

  • Sector Analysis (Figure 6):
    • Despite all industry sectors being severely impacted, the Pharmaceuticals and Utilities sectors remain below the ‘b+’ level (yellow threshold).
    • Conversely, the Airlines and Energy sectors join Retail and Consumer Products in the “danger zone” above the ‘b-’ level (red threshold).
    • The remaining industry sectors will either move into or remain within the intermediate risk band (here defined between the ‘b+’ and the ‘b-’ level).

Figure 6: “Hard Brexit” impact on the median credit risk level of EU private companies, by industry.

Source: S&P Global Market Intelligence. As of October 2018.

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  • Country Analysis (Figure 7):
    • Under a hard Brexit scenario, the PD of UK private companies increases between 2017 and 2020, entering the intermediate risk band and suffering even more than its Irish peers.
    • Notably, by 2020 the French private sector may suffer more than the Italian private sector, reaching the attention threshold (here shown as a red circle, and corresponding to a ‘b-’ level).
    • While it is hard to do an exact like-for-like comparison, it is worth noting that our conclusions are broadly aligned with the findings from the 48 banks participating in the 2018 stress-testing exercise, as recently published by the EBA:10 the major share of 2018-2020 new credit risk losses in the stressed scenario will concentrate among counterparties in the UK, Italy, France, Spain, and Germany (leaving aside the usual suspects, such as Greece, Portugal, etc.).

Figure 7: “Hard Brexit” impact on the median credit risk level of EU private companies, by country.

Source: S&P Global Market Intelligence. As of October 2018.

In conclusion: In Europe, the private companies’ credit risk landscape does not yet signal a distinct turning point, however Brexit may act as a pivot point and a catalyst for a credit cycle inversion, with an intensity that will be dependent on the Brexit type of landing (i.e., soft versus hard).

1 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence.
2 Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit scores from the credit ratings issued by S&P Global Ratings.
3 Not shown here.
4 Measured via Gross Domestic Product (GDP) Growth, Long-term / Short-term (L/S) European Central Bank Interest Rate Spread, and FTSE100 or STOXX50 stock market growth, respectively.
5 Macroeconomic forecast for 2018-2020 (end of year) by economists at S&P Global Ratings; the baseline case assumes the UK and the EU will reach a Brexit deal (e.g. a “soft Brexit”).
6 When the credit cycle deteriorates (improves), default rates are expected to increase (decrease).
7 Source: “2018 EU-wide stress test – methodological note” (EBA, November 2017) and “Stress Testing the UK Banking system: 2018 guidance for participating banks and building societies”. (Bank of England, March 2018).
8 Source: “EU withdrawal scenarios and monetary and financial stability – A response to the House of Commons Treasury Committee”. (Bank of England, November 2018).
9 As a hard Brexit scenario, we adopt the stressed scenario included in the 2018 stress testing exercise and defined by the EBA and the Bank of England.
10 See, for example, Figure 18 in “2018 EU-Wide Stress Test Result” (EBA November 2018), found at:https://eba.europa.eu/documents/10180/2419200/2018-EU-wide-stress-test-Results.pdf

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2019 Credit Risk Perspectives: Is The Credit Cycle Turning? A Market-Driven View

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Credit Analysis
2019 Credit Risk Perspectives Is The Credit Cycle Turning A Market Driven View

Mar. 15 2019 — On November 20, 2018, a joint event hosted by S&P Global Market Intelligence and S&P Global Ratings took place in London, focusing on credit risk and 2019 perspectives.

Giorgio Baldassarri, Global Head of the Analytic Development Group, and I provided a review of the latest trends observed across non-financial corporate firms through the lens of S&P Global Market Intelligence’s statistical models.1 In particular, Giorgio focused on the analysis of the evolution of the credit risk profile of European Union companies between 2013 and 2017, and how this may change under various Brexit scenario.

I started with an overview of key trends of the credit risk of public companies at a global level, before diving deeper into regional and industry sector-specific performance and pointing out some key drivers of country- and industry-level risk. Credit Analytics Probability of Default (PD) Market Signals model was used to derive these statistics. This is a structural model (enhanced Merton approach) that produces PD values for all public corporates and financial institutions globally. Credit scores are mapped to PD values, which are derived from S&P Global Ratings observed default rates (ODRs).

From January 2018 to October 2018, we saw an increase in the underlying PD values generated by PD Market Signals across all regional S&P Broad Market Indices (BMIs), as shown in Figure 1. For Asia Pacific, Europe, and North America, the overall increase was primarily driven by the significant shift in February 2018, which saw an increase in the PD between 100% to 300% on a relative basis. The main mover on an absolute basis was Latin America, which had a PD increase of over 0.35 percentage points.

Figure 1: BMI Benchmark Median credit scores generated by PD Market Signals, between January 1 and October 1, 2018.

Source: S&P Global Market Intelligence. As of October 2018.

Moving to the S&P Europe BMI in Figure 2, we can further isolate three of the main drivers behind the overall increase in PDs (this time measured on a relative basis), namely Netherlands, France, and Austria. Among these, the Netherlands had the most prominent increase between August and October. Again, one can identify the significant increase in the PDs in February, ranging from 150% to 230%, across all three countries. Towards July, we saw the spread between the three outliers shrink significantly. In August and September, however, the S&P Europe BMI began to decrease again, whilst all three of our focus countries were either increasing in risk (Netherlands, from a 150% level in the beginning of August to a 330% level at the end of September) or remaining relatively constant (France and Austria).

Figure 2: European Benchmark Median PD scores generated by PD Market Signals model, between January 1 and October 1, 2018.

Source: S&P Global Market Intelligence. As of October 2018.

In the emerging markets, Turkey, United Arab Emirates (UAE), and Qatar were the most prominent outliers from the S&P Mid-East and Africa BMI. As visible in Figure 3, the S&P Mid-East and Africa BMI saw less volatility throughout 2018 and was just slightly above its start value as of October. Two of the main drivers behind this increase were the PDs of the country benchmarks for Turkey and the UAE. Turkey, especially, stood out: the PD of its public companies performed in line with the S&P Mid-East and Africa BMI until mid-April, when it increased significantly and showed high volatility until October. On the other hand, the benchmark for Qatar decreased by over 60% between May and October.

Figure 3: S&P Mid-East and Africa BMI Median PD scores generated by PD Market Signals, between January 1 and October 1, 2018.

Source: S&P Global Market Intelligence. As of October 2018.

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We then looked at different industries in Europe. As shown in Figure 4, the main shift in S&P BMIs occurred in February, with most industries staying on a similar level for the remaining period. The main outliers were the S&P Industrials, Materials, and, in particular, Consumer Discretionary Europe, Middle East, and Africa (EMEA) BMIs. The S&P Energy BMI saw some of the highest volatility, but was able to decrease significantly throughout September. At the same time, the Materials sector saw a continuous default risk increase from the beginning of June, finishing at an absolute median PD level of slightly over 1% when compared to the start of the year.

Figure 4: S&P EMEA Industry BMI Median PD scores generated by PD Market Signals, between January 1 and October 1, 2018.

Source: S&P Global Market Intelligence. As of October 2018.

In conclusion, looking at the public companies, Latin America, Asia Pacific, and Europe pointed towards an increase of credit risk between January 2018 and October 2018, amid heightened tensions due to the current U.S. policy towards Latin-American countries, the U.S./China trade war, and Brexit uncertainty.

1 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence.

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2019 Credit Risk Perspectives: Is The Credit Cycle Turning? A Fundamentals View

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Credit Analysis
Flying Into The Danger Zone; Norwegian Air Shuttle

Highlights

This analysis was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global. This is not investment advice or a stock suggestion.

Feb. 13 2019 — The headwinds are picking up for Norwegian Air Shuttle ASA (“Norwegian”), the eighth largest airline in Europe. The carrier has been battling with rising fuels costs, increased competition from legacy carriers, and persistent aircraft operational issues. Norwegian’s problems are a continuation of what have been turbulent months for budget airlines in Europe resulting in a collapse of Primera Air, based in Denmark, near-default of WOW air, Iceland’s budget carrier, and most recently bankruptcy of Germania.

When we pull back the curtain and review the creditworthiness of European airlines to explore further some of the causes for Norwegian’s turbulent period, we see Norwegian’s business strategy and financial structure have made the carrier highly exposed. Coupled with the traditionally slow winter season, the airline may have to navigate through the storm clouds forming on the horizon.

A View From Above

S&P Global Market Intelligence has developed CreditModelTM Corporates 2.6 (CM2.6), a statistical model trained on credit ratings from our sister division, S&P Global Ratings. The model combines multiple financial ratios to generate a quantitative credit score and offers an automated solution to efficiently assess the credit risk of both public and private companies globally.1 Within CreditModel, the airline industry is treated as a separate global sub-model to better encompass the unique characteristics of this industry.

Figure 1 shows the overview of S&P Global Market Intelligence credit scores obtained using CreditModel for European airlines. Norwegian’s weak position translate into the weakest credit score among its competitors. The implied ‘ccc+’ credit score suggests that Norwegian is vulnerable to adverse business, financial, or economic conditions, and its financial commitments appear to be unsustainable in the long term. In addition to Norwegian, Flybe and Croatian Airlines rank among the riskiest carriers in Europe and share a similar credit risk assessment. The airlines with the best credit scores are also Europe’s biggest airlines (Lufthansa, Ryanair, International Airlines Group (IAG), and easyJet). The exception among the top five European airlines is Air France-KLM, which is crippled by labour disputes and its inability to reshape operations and improve performance.

Figure 1: Credit Risk Radar of European Airspace
Overview of credit scores for European airlines

Source: S&P Global Market Intelligence. For illustrative purposes only.
Note: IAG operates under the British Airways, Iberia, Vueling, LEVEL, IAG Cargo, Avios, and Aer Lingus brands. (January 3, 2019)

S&P Global Market Intelligence’s sister division, S&P Global Ratings, issued an industry outlook for airlines in 2019 noting that the industry is poised for stability.2 It stated the global air traffic remains strong and is growing above its average rate at more than 6% annually. The report also cited rising interest rates dampening market liquidity while increasing the cost of debt refinancing and aircraft leases. Oil prices are expected to settle, and any further gradual increases in oil prices are expected to be compensated by rising airfares and fees. The most significant risks for airlines are geopolitical. Potential downside scenarios include a crisis in the Middle East or other disruptions in oil, causing oil prices to spike. The possibility of trade wars and uncertainty surrounding the Brexit withdrawal agreement represent additional sources of potential disruption or weakening in travel demand.

Flying into the danger zone

Although Norwegian has so far dismissed any notion of financial distress as speculation, it has simultaneously implemented a series of changes to prevent further turbulence.3 The airline announced a $230mm cost-saving program that included discontinuing selected routes, refinancing new aircraft deliveries, divesting a portion of the existing fleet, and offering promotional fares to passengers to shore up liquidity.

In Figure 2, we rank Norwegian’s financial ratios within the global airline industry and benchmark them against a selected set of competitor European budget carriers (Ryanair, easyJet, and Wizz Air). Through this chart, we can conclude that Norwegian’s underlying problems are persistent and the company’s financial results are weak. Norwegian’s business model of rapid growth and a debt-heavy capital structure have resulted in severe stress for its financials. Norwegian ranks among the bottom 10% of the worst airlines in the industry on debt coverage ratios, margins, and profitability. This is in sharp contrast to other European budget carriers, which are often ranked among the best in the industry. On the flip side, Norwegian’s high level of owned assets represents its strong suit and gives the carrier some flexibility to adjust its operations and improve performance in the future.

Figure 2: Flying at Low Altitude
Norwegian’s financial ratios are among the worst in the industry

Source: S&P Global Market Intelligence. For illustrative purposes only. (January 3, 2019)
Note: Presented financial ratios are used in CreditModelTM Corporates 2.6 (Airlines) to generate quantitative credit score in Figure 1.

Faster, Higher, Farther

Norwegian has undergone a rapid expansion in recent years, introducing new routes and flying over longer distances. Between 2008 and 2018, the carrier quadrupled its fleet from 40 to 164 planes.4 This enabled it to fly more passengers and become the third largest budget airline in Europe, behind Ryanair and easyJet. However, unlike its low-cost rivals, Norwegian ventured into budget long-haul flights. After establishing its new base at London Gatwick, it started operating services to the U.S., South-East Asia, and South America.

As a result of this expansion, Norwegian’s capacity as measured by available seat kilometres (ASK) and traffic as measured by revenue passenger kilometres (RPK) grew nine-fold between 2008 and 2018, as depicted in Figure 3. By offering deeply discounted fares, the carrier was able to attract more passengers and significantly grow its revenues, which were expected to reach $5bn in 2018. However, to be able to support this rapid growth, Norwegian accumulated a significant amount of debt and highly increased its financial leverage. This rising debt is putting Norwegian under pressure to secure enough liquidity to repay maturing debt obligations.

Figure 3: Shooting for the Stars
Norwegian’s rapid growth propelled by debt

Source: S&P Global Market Intelligence. All figures are converted into U.S. dollars using historic exchange rates. Figures for 2018 are estimated based on annualized YTD 2018 figures. For illustrative purposes only. (January 3, 2019)

Norwegian’s strategy to outpace growing debt obligations by driving revenue growth is coming under pressure. The data tells us that expansion to the long-haul market and the undercutting of competitors to gain market share proved to be costly and negatively impacted Norwegian’s bottom line. Operational performance, measured as unit revenue (passenger revenue per ASK) and yield (passenger revenue per RPK), have been slipping continuously since 2008, as depicted in Figure 4. Negative free operating cash flow required Norwegian to continuously find new sources of capital to finance its operations, and profitability suffered. The carrier was able to ride a tailwind of low oil prices and cheap financing for a while, however, the winds seem to be turning.

Figure 4: Gravitational Pull
Slipping operational and financial performance

Source: S&P Global Market Intelligence, Norwegian Air Shuttle ASA: “Annual Report 2017”, Norwegian Air Shuttle ASA: “Interim report - Third quarter 2018”. Figures for 2018 are estimated based on annualized YTD 2018 figures. For illustrative purposes only. (January 3, 2019)

Norwegian’s plan to outrun a looming mountain of debt obligations is resulting in a turbulent flight. While growing its top line, the carrier has been unable to convert increased capacity and traffic into consistent profit. With a stable industry outlook and cost-cutting measures in place, Norwegian lives to fly another day. However, any additional operational issues or adverse macroeconomic developments could send Norwegian deep into the danger zone.

Learn more about S&P Global Market Intelligence’s Credit Analytics models.
Learn more about S&P Global Market Intelligence’s RatingsDirect®.

S&P Global Market Intelligence leverages leading experience in developing credit risk models to achieve a high level of accuracy and robust out-of-sample model performance. The integration of Credit Analytics’ models into the S&P Capital IQ platform enables users to access a global pre-scored database with more than 45,000 public companies and almost 700,000 private companies, obtain credit scores for single or multiple companies, and perform scenario analysis.

S&P Global Market Intelligence’s RatingsDirect® product is the official desktop source for S&P Global Ratings’ credit ratings and research. S&P Global Ratings’ research cited in this blog is available on RatingsDirect®.

1 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD credit model scores from the credit ratings issued by S&P Global Ratings.
2 S&P Global Ratings: “Industry Top Trends 2019: Transportation”, November 14, 2018. https://www.capitaliq.com/CIQDotNet/CreditResearch/viewPDF.aspx?pdfId=36541&from=Research.
3 Norwegian Air Shuttle ASA, “Update from Norwegian Air Shuttle ASA”, press release, December 24, 2018 (accessed January 3, 2019), https://media.uk.norwegian.com/pressreleases/update-from-norwegian-air-shuttle-asa-2817995.
4 Norwegian Air Shuttle ASA: “Investor Presentation Norwegian Air Shuttle”, September 2018.

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Tesla Contemplates Going Private; But Who Is Going to Power Its Batteries

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Sears Strikes Out What Is In Store For Other Retailers In The US

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Credit Analysis
Credit Analytics Case Study: Hyflux Ltd.

Nov. 02 2018 — Hyflux Ltd. (Hyflux) is a Singaporean water utility company, which announced on 22 May 2018 that it had applied to the Singaporean High Court to begin a court-supervised process of debt and business reorganization.1 S&P Global Market Intelligence’s Fundamental Probability of Default (Fundamental PD) increased nearly nine-fold from 0.5046% (an implied credit score of bb+)2 to 4.5233% (an implied credit score of b) between fiscal year (FY) 2016 and FY 2017. Since FY 2017, the Q1 2018 Fundamental PD increased by approximately 4% to 4.7275% and the company has not filed any further public accounts since entering court supervision.

Hyflux experienced a period of rapid sales growth expansion over the course of 2016 with sales year-on-year (y-o-y) growing from 38.5% in Q4 2015, to peak at a high of 152.48% in Q3 2016. However, over the course of 2017 sales growth slowed and the company began to struggle to service its debt facilities. From mid-2016 the company’s current liabilities/net worth exceeded 100% and would continue to rise until in mid-2018 where it would stand at 141.5%.

Exhibit 1: Fundamental PD Escalation

Source: S&P Global Market Intelligence as of July 24, 2018. For illustrative purposes only.

Business Description
Hyflux provides various solutions in water and energy areas worldwide. The company operates through two segments, Municipal and Industrial. The Municipal segment supplies a range of infrastructure solutions, including water, power, and waste-to-energy to municipalities and governments. The Industrial segment supplies infrastructure solutions for water to industrial customers. The company provides seawater desalination, raw water purification, wastewater cleaning, water recycling, water reclamation, and pure water production services to municipal and industrial clients, as well as to home consumers; and filtration and purification products. It also designs, constructs, owns, operates, and sells water treatment, seawater desalination, wastewater treatment, and water recycling plants under service concession arrangements; and sells oxygen-rich water and related products and services. In addition, the company designs, constructs, owns, operates, and sells power plants and waste-to-energy plants; trades in the electricity markets; and sells retail electricity contracts. Hyflux was founded in 1989 and is headquartered in Singapore.

Fundamental Probability of Default Analysis
The analysis of S&P Global Market Intelligence’s one-year Fundamental PD reveals Hyflux had consistent implied credit scores in the bb+/bbb- range over the course of 2016.3 In the time after FY2016 the Fundamental PD rose consecutively for 5 periods until the company applied for court supervision in May 2018. It is therefore possible to detect the deteriorating credit quality of Hyflux as early as 12 months before the credit event in 2018. Prior to Q2 2017, the company had been below the global water utility industry median one-year PD consistently since 2010 with a single exception in 2015. The escalation of company PD levels in 2017 therefore show a significant increase in company risk levels on an absolute basis but also when compared to that of its global peers.

Fundamental PDs produced over the course of 2017 and into H1 2018 highlights several areas of financial risk elements which were driving risk levels continually higher. As of Q1 2018, the company had a financial risk assessment from PD Fundamentals as highly leveraged. Over the course of 2016, sales growth became negative and moved from a high point of 152.5% y-o-y sales growth in Q3 2016 to a low of -53.48% y-o-y sales growth in Q3 2017. This contraction in sales revenues led to a situation where the company was under increasingly constrained liquidity. Over the same period, the company’s current liabilities/net worth rose from 57.2% in Q3 2016 up to 141.52% as of Q1 2018, demonstrating the increasingly fragile state the company was in with respect to its liabilities. EBIT Interest Coverage fell from 3.05x in Q3 2016 down to -1.61x as of Q1 2018 while EBITDA margins fell into negative territory over the course of 2017 and stood at -24% as of Q1 2018. The combination of these factors – declining sales revenues, increasing leverage and erosion of profit margins, prompted the company to enter into court supervised debt restructuring conversations.

Exhibit 2: Fundamental Probability of Default Contribution Analysis

Source: S&P Global Market Intelligence as of June 28, 2018. For illustrative purposes only.

Exhibit 3: Key Developments

Source: S&P Global Market Intelligence as of October 29, 2018. For illustrative purposes only.

1 Source:The Business Times, Hyflux seeks court protection to reorganise business, debt, as published on May 23, 2018.
https://www.businesstimes.com.sg/companies-markets/hyflux-seeks-court-protection-to-reorganise-business-debt .
2 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD scores from the credit ratings used by S&P Global Ratings.
3 S&P Capital IQ platform as of October 29, 2018.

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