Credit Portfolio Risk: Consensus Data Fills in the Blanks
Investors in credit portfolios make extensive use of credit agency ratings and market-driven risk models. But some segments are faced with less visibility and a lack of public ratings, while credit portfolio management models are only as good as the credit risk data available to them. This paper reviews a data-driven framework for portfolio risk analysis and discusses practical applications of consensus credit risk estimates.
Credit Correlations: Avoiding Unnecessary Risks
With default risks expected to rise in 2023, correlations between those risks are increasingly important for credit portfolio management. Exposures to different sectors – that normally diversify the portfolio – may show a simultaneous increase in risk during difficult economic conditions. This paper shows how Consensus credit data can be used to estimate credit correlations between regions, countries, industries, and sectors.
Credit Consensus Ratings and Risk Sharing Portfolios
Risk sharing transactions are a rapidly growing asset class, and have provided attractive returns over the past decade. As corporate credit becomes more unstable, emerging risks – and opportunities – highlight the need for comprehensive credit data for accurate transaction pricing. This paper details how Credit Consensus Ratings and Aggregates provide a detailed map of the credit market risk-reward landscape, including possible anomalies.
Credit Consensus Ratings & Risk Sharing
For investors in Risk Sharing products, transparency is key. This report uses Credit Consensus Ratings to compare a single bank’s view of a typical risk sharing portfolio with the broader bank peer group view of the same portfolios. This unique dataset can be used for industry trend tracking, portfolio analytics, and single name assessments.
