Modelling the Economic Value of Credit Rating Systems

Determinants of heterogeneity in European credit ratings

“…As more borrowers with too favorable ratings are in the portfolio, the resulting regulatory capital based on these ratings may be inadequate. Jankowitsch et al (2007) show that capital requirements estimated with a lowquality rating system can be more than two percentage points too low compared to the actual risk. This result is driven by the magnitude of the rating error.…”

“…For this analysis, we use a simulation framework that relies on the setup presented in Jankowitsch et al (2007). In principle, low-quality rating systems have two important negative effects on a bank's financial stability.…”

“…For these calibrated values of σ , we simulate the underestimation of the capital holdings by using the base case values presented in Jankowitsch et al (2007) for all other model parameters, i.e., loss given default (LGD) is 45%, borrowers price elasticity (α) is 500, and the risk-free interest rate is 3%. Table 4 sets out the results of this analysis.…”

“…Thus, high degrees of dissimilarity ultimately influence the bank's competitive position (Carey 2001). As a consequence, banks have a natural interest in analyzing the heterogeneity of their ratings to ensure reliable credit assessments of their obligors and avoid the effects of adverse selection (e.g., Jankowitsch et al 2007;Jordão and Stein 2003).…”

The development of a simple and intuitive rating system under Solvency II

“…For instance, a reliable rating model can facilitate an accurate, fair and objective pricing policy; it will offer an objective basis to sell to the re-insurers and due to the more objective pricing it might even reduce the need for reinsurance (Tiller and Tiller, 1995). Jankowitsch et al (2007) show that when financial institutions improve their internal rating system from low accuracy to medium accuracy, the annual return of their portfolio can be increased by 30-40 basis points.…”