This report analyzes the evolution of supply chain risks over the past two years, ranging from trade policy uncertainty through to the coronavirus pandemic, in the context of credit risk analysis.
Using supply chain data in credit risk analysis
Broadly speaking, credit analysis can be defined as the assessment of the credit health of counterparties and investments, the probability of a firm's default and the creditworthiness of unrated companies.
Credit analysis tools can be useful for financial sector players including banks, insurance firms and portfolio managers as well as non-financial corporates in treasury, financial reporting and merchandise management. In prior research, we have shown a similar set of applications for commercial finance.
Panjiva's supply chain graph, a mathematical representation of a firm's supplier and customer network, can be considered as the "physical twin" of the firm's financial relationships. As a result, the two very much feed into each other. There are at least four ways this can be applied.
Volumes flowing through a company's supply chain provide a real-world guide to its activity in terms of production, inventory management and sales. More details can be found in S&P Global's recent Quantamental Research on the topic. Weakening volumes can be an early sign of emerging financial weakness.
Characteristics of the supply chain can provide an extra layer of insights beyond reported company exposures by geography, product and counterparty shown in financial filings. Geographic exposure can be particularly important in the event of physical risk events such as heavy weather, natural disasters, labor disputes, and of course the COVID-19 outbreak. Panjiva's fundamental research regularly provides event-driven research on that basis.
A volatile supply chain, with rapid turnover in suppliers and buyers or a sudden change in the number of counterparties, may be an early warning that the firm either has suppliers and buyers who are in trouble or that the firm itself is being viewed as a less desirable counterparty financially.
On a more positive tack, longer-term changes in the supply chain structure can also be used to identify the application of corporate strategies such as efficiency measures, reshoring strategies, entry to new markets or the sale of new products.
It is also worth noting that supply chain data, unlikely financial data, is ownership agnostic. In other words, it can be particularly used for privately owned companies or those that are not bound by public company reporting disclosures. A recent example in the agricultural trading space is instructive in this regard, with Cargill Inc. having withdrawn its quarterly reporting.
Global supply chain risks mount ahead of COVID-19
Risks to global supply chains are by no means a new phenomenon, but they have accelerated in the past four years, with two significant developments under the Trump administration. The U.S.-China trade war, as discussed in our extensive history of the topic, reflects a wider geopolitical struggle that is mostly about technology supremacy rather than just the flow of manufacturing jobs.
The main impact so far has been the implementation of tariffs on most U.S. imports from China. Imports of products that have faced 25% duties in a set of lists applied in July, August and September 2018, fell by 30.7% year over year in the 12 months to April 30, Panjiva's analysis shows. Imports covered by 7.5% tariffs, which were initially applied at 15% in September 2019, have fallen by 16.0% over the same period.
The tariffs and associated trade war risks have led firms to face higher costs and to review whether "China+1" strategies are appropriate. From a risk perspective, there are clear signs that relationships are worsening and that an extension of tariffs is possible.
The U.S.-Mexico-Canada Agreement represents a reformation of NAFTA to include sectors that did not exist in 1994, as well as updated appeals procedures. Importantly, though, it also includes new rules-of-origin that may require a recasting of supply chains in manufacturing. This, in turn, may require firms to formulate a whole new set of relationships and may drive a degree of regionalization of supply chains. So far though, there are few signs of that having occurred.
Those are by no means the only areas of trade policy volatility that have brought risks to supply chains with multilateral deals in Asia, the rise of tariffs such as "Make in India," the breakdown of the World Trade Organization appeals process and rising medical protectionism in the wake of COVID-19.
The effects of COVID-19 on global supply chains
Panjiva's shipping data can provide a low-latency, high-frequency oversight of the performance of different industries during the pandemic, particularly for North American markets as well as those with substantial exposure to North America from a second-order perspective.
The impact of the COVID-19 pandemic can be split into four phases from a supply chain perspective.
The first has been the disruption of upstream supply chains due to factory closures. That initially occurred in China before spreading globally. Some of the most extreme examples have been the wholesale industrial closures seen in Mexico and India.
Panjiva's U.S. seaborne import data shows that shipments from China slowed but did not collapse with a 34.5% decline in March being the trough performance, though shipments have continued to decline since. More extreme has been a 66.1% slump in shipments from India to the U.S. in May. Most other regions have seen a downturn of around 20% in shipments to the U.S. in May.
Second has been a collapse in demand. Panjiva's data is structured primarily as products and companies rather than as industries. Nonetheless, the product profile can be closely mapped to industrial sectors with five sectors. Panjiva's data shows that imports linked to the consumer discretionary industry have fallen fastest during the pandemic, counting the three months of imports to May 31 as a baseline on a year over year basis. Consumer discretionary imports fell by 20.2% year over year in the three months to May 31, including a 29.2% slump in May alone.
Imports of materials were the next biggest loser with a 13.6% drop reflecting slower industrial demand. Healthcare surprisingly fell by 10.7% despite government efforts to ensure a steady flow of medical supplies for COVID-19, though there has clearly been a toll on demand for non-COVID-19 related procedures. The slower moving industrial imports have only fallen by 8.7%, while consumer staples were more-or-less unchanged at 0.6%, which is unsurprising given the surge in panic buying.
Within consumer discretionary, all the big six sub-sectors tracked by Panjiva experienced a downturn. The slide in the automotive industry is notable in being around average at a 19.1% decline, but accelerating to a 36.6% slump in May alone.
Imports of household appliances and consumer electronics did better than average with declines of 9.0% and 15.5%, respectively, in the past three months, including a 4.7% rise in household appliances in May alone. That is not necessarily a good thing of course if retailers have over-ordered relative to outcome demand or if manufacturers are channel stuffing in order to maintain factory operations.
In that context, the third phase of impacts from COVID-19 resulting from the uneven reopening of manufacturing and retail operations could be the most significant from a risk perspective. That process is only just getting underway in late May/early June and could take several months to resolve. The relative unknowns of each company's exposure to suppliers and customer dynamics requires a deeper analysis of each supply chain.
The sudden drop in shipments in the automotive industry and the recent recovery in consumer electronics and household appliances make them potentially fruitful sectors for further investigation.
As a side note, the supply chains for other consumer items including furnishings, leisure products (toys) and apparel are relatively simple when compared to those of autos and electronics.
More details regarding the screening process, as well as outline results, are published in Panjiva's research of June 17, which is available here.
Christopher Rogers is a senior researcher at Panjiva, which is a business line of S&P Global Market Intelligence, a division of S&P Global Inc. This content does not constitute investment advice, and the views and opinions expressed in this piece are those of the author and do not necessarily represent the views of S&P Global Market Intelligence. Links are current at the time of publication. S&P Global Market Intelligence is not responsible if those links are unavailable later.