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COVID-19, Automation and ESG Expected to Dominate the Credit Scene in 2022


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COVID-19, Automation and ESG Expected to Dominate the Credit Scene in 2022

This article is written and published by S&P Global Market Intelligence, a division independent from S&P Global Ratings.

2021 has proven to be a very interesting year. As of the fourth quarter, the S&P 500 had jumped more than 25% since January, with energy leading all sectors due to increases in crude oil and fuel prices caused by rising demand and limited supply growth.[1] Strong corporate earnings also boosted stock prices and stoked a risk-on sentiment that is expected to continue into 2022. In addition, three important topics were in the spotlight: COVID-19 and variants, automation and climate change.

The impact of COVID-19 on the global economy has been unique, as it has not only affected demand, but also cross-border supply chains, which will continue to weigh on the creditworthiness of some sectors. The emergence of the new omicron variant is a stark reminder that the impact of the pandemic is far from over.   

The pace of technological disruption was supercharged by the pandemic, and there is now an even greater push to become digitally resilient to remain competitive. Credit and risk management teams are no exception. From dynamic financial spreading tools to cloud-based storage, a host of capabilities are being actively deployed to help streamline and automate risk assessment processes to improve efficiencies and stay ahead of the curve.

Climate-related risk is increasingly a focus of governments and regulators across the globe. Central banks and regulators are exploring mandatory climate risk disclosures and climate stress testing, while the Network for Greening of the Financial System (NGFS) supports integrating climate risk into financial stability monitoring and supervision. Consequently, financial institutions are focused on disclosure and management of climate change impacts.

This blog touches on these three areas in more detail.

1. COVID-19 Can’t Be Ignored

As we head into 2022, we see:[2]

Improving, but still vulnerable credit markets with largely positive credit momentum, reflecting favorable financing conditions and a powerful economic recovery. This could be derailed if persistently high inflation pushes central banks to aggressively tighten monetary policy, triggering significant market volatility and repricing risks. New COVID-19 variants could also undermine confidence and recovery prospects. The weakest areas of credit markets — often still highly sensitive to the ongoing impact of the pandemic — are most exposed, particularly highly leveraged corporates and some emerging markets.

Fewer downgrades and low default rates with robust economic growth and largely favorable funding conditions, pointing to a steady overall ratings performance. However, persistent supply chain disruptions and high input costs could weigh on growth and ratchet up the pressure on so-far resilient corporate margins. Inflationary pressures are clouding the outlook for emerging markets still grappling with the pandemic. Leverage continues to build up in the riskiest parts of the credit markets, leaving them exposed to shifts in market sentiment.

Risk of aftershocks from inflation and high global debt pose significant risks. Persistent inflation, tied to supply disruptions and soaring energy prices, could trigger wage inflation and push major central banks, the Fed in particular, to hike rates sooner and faster. This could generate market volatility, likely amplified by elevated global debt levels. New variants could weaken the global economic recovery, as could China's policy and economic developments. Beyond COVID-19, credit markets face significant longer-term uncertainties around energy transition, cyber risk and evolving financial systems in an increasingly digital economy.

2.    Automation Takes Hold

Credit and risk management professionals face numerous challenges every day, increasing the need to work faster and smarter than ever before. This has driven many firms to look at ways to digitize their credit risk workflows to help improve efficiencies. To look at some of the trends reshaping credit risk practices, we conducted a survey[3] to gather insights from over 200 professionals in countries around the world to see what steps they were taking before the COVID-19 pandemic took hold and how this unprecedented time has accelerated change. We found that:

Digitization efforts started well before COVID-19 given the growing push for credit and risk management teams to improve operating procedures and the efficiency and quality of decision making. 75% of respondents were already working on digitization efforts before the pandemic hit to capitalize on a range of benefits, including enhanced risk control and management, improved efficiencies and better early warning systems.

The pandemic underscored the need for more timely and granular data as credit and risk professionals were challenged by the lack of essential information at the start of the pandemic, especially when it came to assessing small- and medium-sized enterprises. This spurred firms to consider a range of new approaches on the data front, including combining alternative and traditional data, using data mining and machine-learning techniques to extract new and deeper insights and upgrading platforms for faster data delivery.

Existing analytical approaches came under pressure given the wave of non-performing exposures seen during the pandemic. Many credit and risk management professionals focused on enhancing their early warning systems to quickly identify potential problems, updating models to better estimate probabilities of default and monitoring portfolios in a more granular manner with back-testing exercises and internal ratings–based models.

Steps to Aid Digitization

As we continue to enhance our product line in response to market needs, we have looked at ways to make it easier for machines to perform additional tasks for improved speed and scalability. In doing so, we understand that:

Machine-based activities won’t replace the need for subjective judgement in credit analysis. For example, RatingsXpress®: Research on Xpressfeed™ provides bulk access to credit research from S&P Global Ratings for textual data analysis, enabling users to:

  • Skim a large volume of articles.
  • Create alpha signals for investments, plus custom metrics and benchmarks.
  • Identify emerging themes affecting credit, such as the mentions of “COVID-19” language in earnings call transcripts and ratings reports.
  • Provide an early warning indicator via custom filters on keywords.

This product complements RatingsDirect®, which is the official desktop offering for S&P Global Ratings credit ratings and research. RatingsDirect enables users to uncover deep insights within the data with visualization and other analytical tools — providing the all-important “why” behind the numbers.

New product features are needed to support automation. Ease of use, timeliness, and completeness are always important, as are:

  • Consistent and standardized metrics since automated algorithms don’t use subjective judgment. For example, our RatingsXpress: Scores and Factors database, which provides the underlying risk factors for S&P Global Ratings credit ratings, supports peer comparisons across different industries and geographies.
  • Clear organization of information for easy retrieval since machines tend to assign equal weights to content unless there is a way to categorize textual data according to similarities and importance. For example, machines can easily find and read the Outlook and Creditwatch sections contained within ratings reports published by S&P Global Credit Ratings and form an aggregated industry view.
  • Linking and integrating content sets since credit risk assessments often draw on multiple datasets. For example, our financial statement data can be automatically linked to a range of formulas in our models, such as the calculation for loss given default. 

3. Climate Change Moves to Center Stage

Natural disasters as the result of climate change are increasing in both intensity and frequency, resulting in significant financial losses for companies. This is bringing several issues to the forefront.

There are two important types of climate-related risks that need to be evaluated: physical and transitional. Physical risks refer to either acute physical hazards, such as more frequent and extreme weather events (e.g., storms, hurricanes and floods), or the chronic and longer-term effects of climate change, such as changing weather patterns and sea level rise. Transition risks refer to the costs associated with the market, technological, policy, legal and reputational risks associated with moving to a low-carbon economy. For example, market risks due to reduced demand for higher-carbon products or policy and legal risks due to increased operating costs from government actions to increase the price of carbon.

 There is emerging consensus among financial regulators regarding the need to assess the risks and opportunities posed by the move to a greener economy. Many regulators have already introduced, or are in the process of introducing, climate-related stress testing exercises for financial institutions, which is important to test the resilience to climate shocks. Regulators are starting to be mindful about the burden posed on financial institutions, especially for modelling risks and opportunities. For example, the Bank of England's guidelines call for a deep-dive analysis for the biggest exposures/large-revenue companies in a portfolio and an aggregate view for the remainder.

There is a critical need for clear definitions and common standards across the globe on climate data, reporting and scenario analysis. Clarity and consistency will contribute to a better understanding of the risks and opportunities inherent in the transition.

This is a nascent field and new approaches are needed. One such solution is Climate Credit Analytics, developed by S&P Global Market Intelligence and Oliver Wyman.[4] This powerful capability translates climate scenarios into drivers of financial performance tailored to specific industries, such as production volumes, fuel costs and capital expenditures. These drivers are then used to forecast complete company financial statements under various climate scenarios and assess potential changes in counterparty credit scores and probabilities of default.[5] 

It will be important to watch these three areas as 2022 progresses to understand the short- and long-term effects on the global economy and credit markets.


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[1] “Insight Weekly: US stock performance; banks' M&A risk; COVID-19 vaccine makers' earnings”, November 30, 2021,

[2] Comments from “COVID-19 Impact: Key Takeaways from Our Articles”, December 1, 2021,

[3] See “Digitization in Credit Risk Management” report at

[4] Oliver Wyman is a global management consulting firm and is not an affiliate of S&P Global, or any of its divisions.

[5] 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.