Author: Edoardo Giovannini, Research Analyst Intern, FNA
In the context of the coronavirus pandemic (COVID-19), it is important that central banks monitor credit risk with new methods. Understanding how credit risk will move during the next few years is crucial to prevent non-performing-loans (NPL) from negatively affecting the financial system or the real economy. Recently, the ECB stated that banks “should identify and record any significant increase in credit risk at an early stage” . This poses a unique challenge for banks, as they need to be able to model and estimate their credit risk provisions by integrating reliable IFRS 9 baseline scenarios with detailed forecasts. Furthermore, central banks need to be able to evaluate those models and estimations.
To understand how credit risk will move during 2021-2023, it would be useful to understand what happened to credit takers during the COVID-19 pandemic: when did they stop working? For how long? How has this affected their sales, lay-offs, and hires?
We know that Small and Medium Enterprises (SMEs) are the backbone of every national and international economy (they account for 99% of the businesses in EU and US) (Altman et al., 2008; ECB, 2013; USTR, 2021). Their peculiarities create special challenges from the credit risk perspective: they suffer the most from economic crises, they are the quickest to suffer losses, and they (usually) cannot escape national regulation, or taxes (Bartik et al., 2020). In short, we can say SMEs face higher levels of uncertainty than larger companies, amplified during economic and financial crises. This has to be accounted for when calculating safe credit risk estimates.
Here at FNA, in our quest for safer and sounder financial systems, we asked ourselves the question “What will be the impact of the pandemic on SMEs and their credit worthiness?”.
We decided to build a dashboard to discover useful insights about Small and Medium Enterprises (SMEs) during the coronavirus pandemic, the SMEs Watcher. We drew useful data from the Future of Business Survey (FoBS), developed by Facebook, OECD and the World Bank. The survey was monthly run from May 2020 to October 2020, complemented with further semi-annual additions, and aggregated at country level for privacy concerns.
The following is a snapshot from our SMEs Watcher map; it shows at a glance the distribution of non-operating SMEs during September 2020:
Most countries were heavily affected by the pandemic, but the worst results are expected to come from Africa and SouthEast Asia and, in general, from emerging countries.
Intuitively, this negatively relates to SMEs that have bank loans or credit in their balance sheets:
SMEs in developing countries show a tendency to not have bank loans or credit facilities.
Let’s take a look at individual countries. The Italian SMEs job market shows two lay-off waves, June 2020 and October 2020:
For the purposes of credit risk analysis, it is useful to know how sales moved during the pandemic. Let’s take the United States of America from, June 2020 to October 2020:
At least 45% of SMEs experienced lower sales, compared to sales from the same month in 2019, with a descending trend in H2 2020.
Of course, because of the worldwide pandemic, all countries experienced marked declines in sales; the effect on business survival should also account for government financial assistance. Looking at US and AUS trends, American SMEs received less and less financial assistance over time, while Australia always stayed above the best level reached in the US:
The SMEs Watcher dashboard gives both a broad idea of how SMEs fared during the COVID-19 pandemic, and country-level detail that could be used as an input in comparative macroeconomic studies; or it could be integrated with country-wide granular loan data to more accurately forecast credit risk insights for the following years.
All this information is available for visualization and download on our dashboard, SMEs Watcher, within the FNA G20 Lab.
Contact us at firstname.lastname@example.org immediately to gain access to our dashboard or for more information!