Presenting insights that tackle the timely issues that senior credit risk professionals face today.
We are in a new era for counterparty risk. Between continued COVID-19 related pressures, environmental, social, and governance risks, and the deep linkages that exist between businesses and their stakeholders across value chains, these intersecting risks call for a sharp focus on counterparty assessment, emphasizing the need for deep and timely data and robust analytical tools.
The stability or change of a credit rating is important for risk management and investment purposes. In this paper, we show how a quantitative model built to statistically match S&P Global Ratings’ ICRs can be used to automate risk surveillance or identify potential investment opportunities by appropriately leveraging the natural existence of mathematical outliers generated by the model.
In this article, we demonstrate the creation of a credit signal that can be used by risk managers to anticipate potential rating moves.
