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.

• 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

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.

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.

Mar. 06 2019 — Over-the-top video in the Asia-Pacific has been rapidly evolving as OTT players continue to learn and understand the landscape. Industry experts who participated in the Asia Video Industry Association OTT Summit 2019, held February 20 in Singapore, emphasized the importance of relevant content and adaptability of OTT players, particularly in finding the right business model.

According to Media Partners Asia's Vice President Aravind Venugopal, most OTT players that entered the region in 2016 — citing Netflix Inc., HOOQ and iflix — primarily offered a subscription service, whereas PCCW Media Ltd's Viu provided ad-supported content. He said that a year after, each one was trying to figure out what revenue model would work best. It was at that time that sachet pricing, transactional video-on-demand and ad-supported content became more prevalent.

As for 2018, it was said that OTT players moved toward paths through which monetization could continue to grow, and advertising video-on-demand had to be maximized. Venugopal cited that in one of Media Partners Asia's studies, online video platforms that were more ad-focused came out on top. China players such as iQIYI Inc., Tencent Holdings Ltd.'s Tencent Video and Youku Tudou Inc. are able to monetize consumers by adding sachet pricing, as well as allowing customers to purchase magazines or books, or any other offering that would make them stay on the service.

As more OTT services enter the region, finding the most ideal business model to retain and grow viewership can be a challenge. Panelists who were part of the "AVOD vs SVOD vs TVOD: Finding the Right Business Model" discussion, however, agreed there really is not any right model — it is yet to be discovered as OTT players learn more about their respective areas of operation.

Services will have to adapt and should be open to evolving content offerings based on consumers, while also taking regulatory policies into consideration.

In the case of HOOQ, CTO Michael Fleshman highlighted that the company is moving toward using a freemium model, through which consumers may eventually no longer need to register on the site. The OTT player is also trying to maintain simpler packages, with free content very much accessible for everyone.

He also said that HOOQ was initially worried about cannibalizing the subscription video-on-demand business, but as it turns out, engagement is still doing well.

HOOQ recently added linear channels to its offering, and Fleshman emphasized that the OTT service is not shifting but expanding its service so customers will not feel the need to go somewhere else to watch linear channels.

When global OTT player Netflix entered Asia in 2016, it had an international playbook in hand, which made collaborating with local operators a crucial step in learning more about the region. Subscription payment was one of its main concerns and having local partners became beneficial in addressing this.

When asked how the company felt about competitors and what its competitive advantage was in the Asia-Pacific region, Tony Zameczkowski, Netflix's vice president of business development in Asia, said the company sees competition as a good thing.

He also said Netflix's competitive advantage is its platform, content, marketing and partnership. In terms of platform, Zameczkowski elaborated that Netflix provides a "hyper-personalized" service capable of providing recommendations and personalizing the customer's content library.

In terms of content, Zameczkowski acknowledged that the OTT player's local content offering was initially weak. Soon after acquiring various licensing content from producers, however, Netflix started producing original content. The company will continue to invest in relevant titles. In relation to marketing the service, Zameczkowski said that Netflix banks on its titles, part of its promotional strategy.

Partnering with telcos was also very instrumental in establishing Netflix's presence in the region. Likewise, partnering with device manufacturers was important — a different approach for the company, as the Netflix app would normally be included on most devices in U.S. and European markets.

Mar. 04 2019 — Optical fiber, long the backbone for broadband internet, will soon take on additional workload in the form of data backhaul for 5G wireless traffic. That has spurred the two fiber titans among U.S.-based companies to build out even further.

Our analysis of fiber networks held by U.S.-based companies found telcos in control of the three largest fiber networks. AT&T Inc. and Verizon Communications Inc. alone combine for more than 2.2 million route miles, more than half of the total in our survey of publicly available data.

Verizon is jockeying with AT&T to lead the 5G charge in the U.S.

Third on our list is CenturyLink Inc., which nearly doubled its fiber route miles in 2017 with the acquisition of Level 3 as it sharpened its focus on large-scale business functions.

Broadband and multichannel providers Charter Communications Inc., Frontier Communications Corp., Windstream Communications, Inc. and Comcast Corp., take up spots four through seven on our list. Their publicly available data on fiber route miles has been relatively static in recent years, perhaps because they are not under pressure to deliver next-generation wireless networks.

Our analysis is based on recent company filings or data found on corporate websites and is, consequently, an incomplete picture.