The recent turmoil experienced by global financial markets is characterized by highly volatile conditions that can quickly turn financially robust companies and financial institutions into weak ones, prone to default.
In these conditions, it is critical that firms carefully monitor the evolution of the creditworthiness of their counterparties, by early screening and filtering of those clients or business partners that are less certain to fulfill previously agreed commitments in the future.
To do this, firms require access to an accurate econometric model that captures all relevant risks when calculating a counterparty's probability of default (PD) and/or distance to default (DD). Such a model can help firms take timely action (for example, reducing business with a single company or a portfolio of companies when market conditions worsen) and make informed decisions on a daily basis on their (potential) business partners.Traditionally, “structural PD models” have found wide application in the industry because they can produce reliable and early warning signals useful for credit surveillance or quick initial screening. Structural models' transparent mathematical framework links a firm’s creditworthiness to market movements and their intuitive economic interpretation facilitates the analysis of a firm’s transactions (increased borrowing, share repurchases, acquisition of another firm, etc.).
However, current industry-standard structural models have severe limitations that lead to puzzling and/or user-unfriendly signals. They can be misleading because:
- Abrupt market movement generates excessively volatile PD values or counter-intuitive phenomena (namely an increasing PD when leverage decreases rapidly).
- Country and industry risk dimensions may not be appropriately reflected, leading to possible overestimation/underestimation of a firm's creditworthiness.
- PD values are often floored at the sovereign rating (that is, they don't move lower than the PD implied by the sovereign rating). This masks valuable information about the behavior of a company's PD below the floor (whether it is still improving, or has started deteriorating, for example).
S&P Global Market Intelligence’s PD Model Market Signals
S&P Global Market Intelligence has recently developed PD Model Market Signals for both corporates and financial institutions (including insurance companies), a structural model that produces PD values over a one- to five-year horizon for all public corporates and financial institutions, globally. PD Model Market Signals builds on a traditional structural framework with several enhancements that tackle the issues mentioned above.