blog Market Intelligence /marketintelligence/en/news-insights/blog/managing-trade-credit-exposures-in-times-of-crisis-impact-of-covid19-and-an-oil-price-war content esgSubNav

In This List

Managing Trade Credit Exposures in Times of Crisis Impact of COVID-19 and an Oil Price War


Navigating Private Credit: Payment-in-Kind And Credit Risk Under Macro-Economic And Climate-Related Scenarios


Harnessing the Power of Quantum Computing in Derivatives Trading and Risk Management


Net Zero 2050: How Climate Risk May Reshape the FTSE 100


From Royal Courts to Muddy Fields: Hunter Boot Ltd. goes into administration.

Managing Trade Credit Exposures in Times of Crisis Impact of COVID-19 and an Oil Price War

Staying on top of trade credit exposure is fundamental for companies to help manage working capital and mitigate liquidity issues. This aspect of supply chain management and treasury operations is even more crucial during periods of market volatility and stressed economic conditions. As we saw, for example, many companies within the Oil and Gas industry became insolvent and filed for bankruptcy[1] during the first half of 2020, a time that was characterized by COVID-19 and an oil price war. This period of disruption offers a valuable timeframe to test how an exposure management tool could perform, helping companies assess their exposures to counterparties and minimize losses in the event of defaults.

In this case study, we show how our MaxLimit framework, available via Credit Analytics  would have performed between January 15, 2020 and June 22, 2020 to assess the recommended maximum exposure for a portfolio of 1,056 public companies in the U.S. Oil and Gas industry. Maximum exposure refers to the total amount of all exposures for a customer (i.e., the total of all payment receivables, invoices, bills, and other trade exposures).

The case study was developed by: (i) maintaining a constant loss capacity of $1 million USD on the total exposure of this portfolio, which is the maximum loss the supplier can tolerate from the exposure losses, and (ii) using a benchmark for the credit risk assessment that is the median probability of default (PD) of this portfolio calculated using our PD Model Market Signals (PDMS).[2] PDMS is a point-in-time credit risk model that dynamically assigns timely flags to anticipate deteriorations in a counterparty’s creditworthiness based on market sentiments and uncertainties, enabling companies to quickly take action when conditions worsen. Using PDMS with MaxLimit during this specific stressed timeframe, we show how a user is able to anticipate market uncertainties and manage exposures prior to major industry events.

Table 1: Key Oil and Gas Industry Events



31 Jan. 2020

6 Mar. 2020

9 Mar. 2020

13 Apr. 2020

20 Apr. 2020

Industry Key Events*

China slowdown

OPEC+ disagreement

Saudi Arabia oil price cut

OPEC+ agreement

Oil price drop

* Please note, only the above key events were selected for the purposes of this article.

Source: S&P Global Market Intelligence, August 10, 2020. For illustrative purposes only.

The initial worldwide spread of COVID-19 resulted in a sudden stop to the global economy and the imposition of travel restrictions between and within major oil-consuming countries, triggering a significant drop in global demand for oil. The resulting oversupply led oil markets into a severe supply-demand imbalance entering the second quarter of 2020.[3] While Saudi Arabia and Russia could not initially agree on production cuts, the oil price war between the two countries came to an end on April 13, 2020 when the Organization of the Petroleum Exporting Countries (OPEC), amongst other oil producing nations, agreed to collectively reduce supply. On April 20, 2020, the market saw the price of oil drop to the lowest value ever recorded in history.

During the period between January 2020 and May 2020, the credit risk for most companies within the Oil and Gas industry had risen, the payment behavior at an industry level had slowed, and the size of business had decreased. A series of key events were captured by the MaxLimit framework, as shown in Figure 1. The three relevant risk dimensions − credit risk, industry payment behavior, and business size − were considered and embedded in the calculation of the exposure limit.

Figure 1: MaxLimit Exposure for the Portfolio of Oil and Gas Companies

Risk Aversion scenarios were used to embed different levels of supplier uncertainty into the assessment of the exposure.[4] This case study looked at three different levels: Low, Mid, and High Risk Aversion. As shown in Figure 1, for each level of Risk Aversion, the MaxLimit framework reassessed and adjusted in a timely manner the exposure before each key industry event. This was done by considering the three relevant risk dimensions mentioned above: credit risk, industry payment behavior, and business size. Prior to each event, the exposure was shown to align with the deterioration in creditworthiness of the portfolio. The Low and High Risk Aversion bounds provide the user an additional tool to manage the exposure within different levels of uncertainty.

In summary, MaxLimit dynamically reallocates the exposure in a timely manner based on a counterparty’s risk dimensions and a supplier’s risk appetite, leveraging PDMS to capture market sentiments and uncertainties to anticipate key events. The current challenges in the global economy highlight the importance of having proper mechanisms in place in order to monitor and set appropriate exposure limits for counterparties.

[1] “Oil price collapse driving more producers to brink of bankruptcy”, S&P Global Ratings, March 13, 2020.

[2] “Credit Risk: Identifying Early Warning Signals in the Oil and Gas Industry”, S&P Global Market Intelligence, April 27, 2020.

[3] “Global Supply-Demand Mismatch is a Major Disruption to Energy Markets”, S&P Global Ratings, June 8, 2020.

[4] “MaxLimit: A Dynamic Tool for Managing Exposures”, S&P Global Market Intelligence, August 24, 2020.


Learn more about Credit Analytics
Request Demo