Discriminatory Power of Consensus Ratings
This analysis evaluates how Credit Benchmark’s Credit Consensus Ratings (CCR) compare to S&P Global Ratings in identifying default risk at the time of S&P’s default declarations.
November 12, 2025
This analysis evaluates how Credit Benchmark’s Credit Consensus Ratings (CCR) compare to S&P Global Ratings in identifying default risk at the time of S&P’s default declarations.
Most credit portfolios carry significant unrated exposure—middle-market borrowers, private credit holdings, counterparties—where internal assessments are your only risk view. That’s perfectly manageable until regulators start
Model owners, validation teams, CROs, IFRS 9 stakeholders, and audit professionals face mounting pressure to demonstrate that credit risk models are accurate, defensible, and aligned
Recent banking failures around the globe have exposed fundamental weaknesses in how financial institutions manage counterparty credit risk: The 2022 UK Gilt liquidity crisis showed
Internal credit risk models remain essential, but they are no longer sufficient on their own. Today’s environment is marked by greater market volatility, increasing regulatory
Risk officers today are managing credit portfolios in an increasingly volatile market. Effective portfolio oversight requires forward-looking, consensus-based intelligence.
Rising bond spreads will lift private credit spreads, requiring sharper borrower oversight – Credit Benchmark provides vital risk insight.
Traditional CVA pricing often relies on incomplete or proxy data—especially for unrated or private counterparties—leading to inaccuracies in capital, risk, and pricing decisions.
The SRT market is large, growing, and complex. Learn how SRT investors are leveraging Credit Benchmark’s bank-sourced default risk estimates to evaluate these transactions, manage portfolio risk and optimize swap structures.
A credit rating transition matrix shows, for a group of companies, the proportion that migrate from one credit rating category to another over a set time period. For example it could show the proportion of firms with rating AA that migrate to AAA, A, BBB, BB, B and C, plus those that remain in the AA rating category, in the course of a single year. For some use cases, it also includes a Default column to show the proportion of firms that default.
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