The COVID-19 pandemic has brought credit risks that are unprecedented in size, are fast-changing and have vastly different manifestations across industries and countries. The uncertainty of impact is driven by epidemiological progression and sociological response.
As institutions attempt to use established, well-developed models to evaluate the current environment, it is clear these are not working adequately.
Internal ratings — an institution’s cornerstone for long-term investment and lending strategies — rely on fundamental, name-level analysis, which cannot be updated at frequencies required to react to and plan for quickly changing developments. Meanwhile, forward-looking measures used in regulatory stress testing or with IFRS 9 impairment often rely on scenarios defined by broad-brushed variables such as unemployment. These scenarios might not be sufficiently differentiated across certain industries (for example, Medical Devices, Hotels, or Transportation); their performances varies in sensitivity to COVID-19 itself.
In this session we explore analytics and data that assess the current-state of credit portfolios, considering loss, downgrade risk, as well as that consider severity and length of this unprecedented economic slowdown across industries and countries.