Risk assessment is the cornerstone of credit risk origination, valuation, surveillance, management, and reporting processes regularly performed by risk practitioners at financial and non-financial corporations. At S&P Global Market Intelligence, the Credit Analytics suite allows you to assess credit risk of multiple counterparties in a holistic way, leveraging the speed, scalability, and power of statistical models.
The assessment “philosophy” sits on a continuous spectrum between two stylized extremes:
- Point in Time (PiT): in which the model seeks to capture the dependence of risk on the business cycle by using a daily-updated market-driven signal; a consequence of such an approach is that during an economic downturn there is a general tendency of migration towards worse credit scores;
- Through the Cycle (TtC): in which the model outputs a long-term and stable risk estimate, independent of the business cycle.
A risk management “toolkit” cannot be considered complete without a tool that allows the analyst to explore how future economic scenarios may impact credit risk from a systematic point of view. There is, in fact, a well-known link between business cycle and credit cycle, and ignoring this relationship can otherwise prove costly during periods of economic expansion, or even fatal, during severe recessions, as the latest global financial crisis has bitterly reminded investors. The Macro-Scenario (statistical) model represents the latest addition to the Credit Analytics suite, and enables risk managers and analysts to gauge how a firm’s credit risk may change across both user-defined and pre-defined forward-looking scenarios, based on a set of macro-economic factors. The model can be used as a tool to support expected credit loss calculations required by the new accounting standards (IFRS9 and CECL ) that will become active globally between 2018 and 2021.
 Bank of England, Prudential Regulatory Authority: “Credit risk: internal ratings based approaches”, (CP4/13 - March 2013).
 For example, S&P Global Market Intelligence’s Probability of Default Model Market Signals.
 For example, S&P Global Market Intelligence’s CreditModelTM 2.6.
 See, for example, “Credit Cycles and their role for Macro-Prudential Policy”, November 2011 (European Banking Federation) available here.
 IFRS and CECL stand for International Financial Accounting Standard and Current Expected Credit Loss, respectively.