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In This List

The Outlook For Corporate Credit Risk; COVID-19 Pandemic And Macroeconomic

Climate Change: Energy Transition Risks and Opportunities for European Public Companies’ Creditworthiness

Fund Financing Through a Credit Lens Credit Risk Factors for Alternative Investment Funds (AIFs)

Case Study: Leveraging a Comprehensive Alternative Investment Funds (AIFs) Scorecard

Industries Most and Least Impacted by COVID-19 from a Probability of Default Perspective – September 2020 Update


The Outlook For Corporate Credit Risk; COVID-19 Pandemic And Macroeconomic

As public companies began to publish financial reports for the first quarter in 2020, investors were getting a first glimpse of how severely the COVID-19 pandemic affected companies worldwide. However, the financial results in the initial few months will not yet show the full extent of the global lockdown, and macroeconomic projections are painting a dire picture of what is yet to come. The full extent of the pandemic fallout on the financial performance of private and public companies will be revealed with a lag and during the course of many months.

To help navigate through these turbulent times, we conducted an analysis of how the credit risk of firm’s may change based on macroeconomic projections. We employ S&P Global Market Intelligence’s Macro-Scenario model, which leverages the historical statistical relationship between macroeconomic conditions and corresponding changes in credit risk to assess the impact of future macroeconomic conditions.[1] In this analysis, we focus on macroeconomic conditions in the United States (U.S.) and assess the potential credit risk impacts for private and public companies across various industries.

Macroeconomic Scenarios

Whilst other recession periods unfolded across many months, the current “sudden stop“ macroeconomic situation is unprecedented in many ways. It is global, driven by both supply and demand shocks, in various ways enforced via the governments-related restrictions, and rapidly changing. Providing relevant and up-to-date macroeconomic projections can thus be challenging and may seem like a never-ending task.

To provide an overview of the range of possible outcomes and gauge industries’ sensitivities to macroeconomic conditions, we analysed multiple economic stress scenarios, as listed in Table 1. As initial baseline scenario, we leverage macroeconomic forecasts for the U.S. in Q2 of 2020, developed by economists at S&P Global Ratings as of April 16 2020. Additionally, we construct two supplementary scenarios which help us gauge the industry credit risk sensitivity. The listed macroeconomic factors are commonly used for stress-testing purposes by banking industry regulators and are also utilized by S&P Global Market Intelligence’s Macro-Scenario model.

Table 1: Macroeconomic Scenarios

Notes: Barrel (bbl), West Texas Intermediate (WTI). Quarterly percentage change represents annualized change over the period.

Source: S&P Global Ratings Economists and S&P Global Market Intelligence. As of April 30, 2020. For illustrative purposes only.

Who Will Feel The Pinch The Most?

As a baseline, we analyse the credit risk profile of different industries in Q4 2019 based on the latest available financials. We employ Probability of Default (PD) Model Fundamentals (PDFN), a statistical model that uses company financials and other socio-economic factors to estimate the credit risk of private and public companies, and calculates median credit risk by industry.[2] Next, we apply Macro-Scenario model and analyse the impact of the selected macroeconomic scenarios by industry sector.

Figure 1 shows the median credit risk by industry for the selected macroeconomic scenarios. [3] The severity of credit risk deterioration in these respective industries is driven by the characteristics of COVID-19 macroeconomic stress. For example, companies and consumers are expected to defer investments and larger purchases in this uncertain environment, which will negatively affect producers of durable consumer products and capital goods. Similarly, a lack of consumer spending will weaken the credit risk profile of companies in the hospitality, automotive, and retail industry. The real estate sector is also especially at risk should macroeconomic conditions significantly deteriorate. Not all industries will feel the impact of COVID-19 so intensely, however. As expected in times of a pandemic, pharmaceuticals and health care industries would not be substantially affected. Utilities and the defence industry are also projected to experience a more modest deterioration of creditworthiness.

Figure 1: Macro-Scenario Credit Risk Radar

Notes: Median credit score for each respective industry. Industries highlighted in red are projected to experience the highest relative and absolute increase in credit risk across all three scenarios. Industries highlighted in green are projected to experience the lowest relative and absolute increase in credit risk across all three scenarios.

Source: S&P Global Market Intelligence. As of April 30, 2020. For illustrative purposes only.

Point-In-Time Adjusted Default Rates

The Macro-Scenario model produces a through-the-cycle (TTC) assessment of the average tendency of companies to transition to a different credit score, in addition to changes in TTC credit risk assessment, i.e. credit risk transition, the default rates for each credit category will likely change as well. To reflect the point-in-time (PIT) characteristics, the Macro-Scenario model incorporates a PIT adjustment to reflect current credit risk conditions. This adjustment leverages PD Model Market Signals, a structural market-driven model, to incorporate a market-implied view into the comprehensive PIT assessment of credit risk.

Figure 2 shows the PIT assessment of the credit risk profile by industry. As a baseline, we use the median credit score by industry in Q4 2019 and apply the macroeconomic forecasts developed by S&P Global Ratings to calculate TTC credit risk changes due to credit transition. Then we also apply PIT adjustment to obtain the most current assessment of the probability of default.[4]

As a result of a severe market decline, the PIT adjustment significantly increases the credit risk profile of all industries. Proportionally most affected are durable construction materials, industrial products, service industry (hotels, restaurants, airlines), and real estate. Those industries are also among some of the industries with the riskiest credit risk profile. On the other side of the spectrum, market-implied PIT credit risk adjustments are less severe for non-durable consumer products, pharmaceuticals, healthcare, and telecoms.

Figure 2: Point-in-Time Macro-Scenario Credit Risk Profiles

Notes: Median probability of default for each respective industry. Credit risk doubles with every horizontal gridline.

Source: S&P Global Market Intelligence. As of April 30, 2020. For illustrative purposes only.

Implications for Calculations of Expected Credit Losses

The current macroeconomic forecasts suggest that the increase in credit risk is projected to be substantial across many industries. This could have major implications for the calculation of the expected credit losses (ECL) and other risk-based capital measures, and has potential to severely affect companies’ financial statements.

Recently, the International Accounting Standards Board provided guidance on applying calculation of expected credit losses in the light of current uncertainty resulting from the COVID-19 pandemic.[5] The International Financial Reporting Standards 9 (IFRS 9) are principle-based, and entities should not apply the ECL calculations mechanistically. Rather, entities can use the flexibility inherent in IFRS 9 to, for example, give due weights to long-term TTC credit transition and PIT market-derived information.

Those who will perform the stress test should take into account both the macroeconomic effects of COVID-19, and the impact of potentially significant government support measures being undertaken. These support measures vary by country and include a range of different payment moratoriums, government guarantees, and monetary policy interventions. The Basel Committee on Banking Supervision has also agreed that the risk-reducing effects of the various extraordinary support measures should be fully recognised in risk-based capital requirements.[6] For example, payment moratorium periods can be excluded from the number of days past due, and the assessment of unlikeliness to pay should be based rescheduled payments.



[1] S&P Global Market Intelligence: “Macro-Scenario Model”, White Paper, December 2019

[2] S&P Global Market Intelligence: “PD Model Fundamentals - Public Corporates”, White Paper, February 2020; S&P Global Market Intelligence: “PD Model Fundamentals – Private Corporates”, White Paper, February 2020

[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 PD credit model scores from the credit ratings issued by S&P Global Ratings.

[4] The PIT adjustments is calculated using median benchmark PD levels generated by Probability of Default Model Market Signals in the last three months vs in the last year.

[5] International Financial Reporting Standards Foundation: “IFRS 9 and covid-19”, March 27 2020

[6] The Bank for International Settlements, Basel Committee on Banking Supervision: “Measures to reflect the impact of Covid-19”, April 2020

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