The business world has been introduced to a number of unexpected challenges in the past couple of years. Some of these challenges, like credit risk management, were trending even before the pandemics and have only become more significant because of it.
At the same time, the pressure for achieving growth has not decreased. On the contrary, it is only becoming stronger. Therefore, growth is often sought in new and developing markets, which are the markets characterized with low availability of information. This unavailability sets credit risk as one of today’s central risks.
Besides lack of data, some major difficulties in getting the required information in order to execute a proper credit risk assessment are knowing where to source data from and being aware of international and unilateral sanctions. In addition, there is no common international standard for company information. For example, some countries have adopted the International Financial Reporting Standards and others use the Generally Accepted Accounting Principles (GAAP). Furthermore, some countries require less disclosure than others, or have adopted a different order of listing the line items.
Bureau Van Dijk, the analytics company of Moody’s, has issued an article which explains the way their programs help organizations in managing their credit risk more efficiently. Some of the options offered by their tool which goes by the name of Orbis are: standardized financials, quantitative scores, qualitative scores and corporate ownership structures. All these data were necessary for conducting an effective risk analysis then, and more importantly, now.
One of interesting option that Orbis offers is the access to information on corporate ownership structures. It can help mitigate the risk of doing business with sanctioned companies or entities. For example, In April 2018, OFAC added 12 Russian nationals to its Specially Designated Nationals (SDN) sanctions list for allegedly interfering with the 2016 US election. Orbis identified 1300 companies that became sanctioned by extension through their ownership chains to the 12 Russian nationals. 90% of these companies were registered outside of the US. These companies did not appear on any sanctions lists. Regardless, if a company traded with them, it would receive a fine.
The crisis presented itself as a powerful exogenous shock at the end of a largely benign global credit cycle. Both supply and demand were equally suppressed, suddenly. Credit risk levels during the pandemics have increased for numerous reasons. Conventional data sources typically used in credit-risk assessments became obsolete overnight. Because of lack of information regarding the collaborators during lockdowns, many frauds have been made. One example is the recent case of the Sicilian William Cerbo, who has made a fortune during the Italian lockdown. With the help of an accountant, he managed to open 24 companies, which he used for trading with everyday goods, from Sicilian oranges to synthetic grass. He was buying and re-selling these goods without paying his suppliers, blaming it on low liquidity because of the pandemics or on the movement restrictions. This way, in only a couple of months, he managed to trick almost 60 companies.
As a response, credit risk management solutions have been updated as well. Creative approaches to acquire and utilize high-frequency data are the order of the day.
All industry trends that are supercharged by the pandemic are connected with digitalization. For credit risk management systems and processes, this has boosted the amount of data that companies need to incorporate into their systems for counterparty assessment.
Furthermore, creditworthiness estimation considers the types of sector and subsector more than before, since the pandemics influenced sectors to a greater degree than previous recessions. Certain industries, such as food distributors, did better in the crisis and struggled to meet rising demand. Others, such as telecommunications and pharmaceuticals, were little affected. But certain sectors—such as travel, transportation, tourism, and hospitality—have been severely challenged.
The before mentioned qualitative factors are the secondary option to counter the shortage of more concrete financial data. Operating-model characteristics are among the qualitative factors that can predict future effects. Some are relevant for all sectors, such as seasonality or reliance on lockdown-disrupted suppliers, markets, and customers. Others will be sector specific, such as the respective shares of domestic versus international customers in parts of the hotel and hospitality sector.
If there is one thing that companies should have learned during this past few years, it is that there is a growing need to place risk management firmly at the center of company plans rather than as a supporting function. Inserting risk management in the central spot is a serious undertaking. Creating an effective credit risk management requires consistency, reorganization, education, taking advantage of technology, resource sharing and rigorous use of information. Internally, the company needs to educate employees about higher standards of transparency, increase their awareness and keep processes clearly described, frequently reviewed and easily available.
