Credit Benchmark partners with financial institutions that follow an internal ratings-based (IRB) approach or those that participate in the Comprehensive Capital Analysis and Review (CCAR) process. The underlying inputs from contributors that make up our dataset are subject to a rigorous approval process and standards from regulatory bodies. Credit Benchmark illuminates the work undertaken by these institutions by applying a well-understood “contributed data” business model to credit risk.
We collect a specific measure of credit risk from contributors: a one-year, forward-looking Probability of Default (PD) and forward-looking senior unsecured Loss Given Default (LGD). Contributors have a strong financial incentive to ensure the accuracy of each PD and LGD, leading to a credible market view of credit risk.
The contributed risk estimates are anonymized, aggregated and mapped to the appropriate credit category on the Credit Benchmark Consensus scale. The output, the Credit Benchmark Consensus (CBC), is based on a 21-category (lower case) scale, which can be used as a benchmark for the scales published by the rating agencies.
Credit Benchmark’s coverage is already broader than the Credit Rating Agencies in several key geographies, and each new contributor further accelerates coverage, informational value and use cases. Our business model improves our clients’ ability to manage risk with insight into the universe of unrated organizations that the ‘issuer pay’ model cannot expand to cover.
Currently we publish data on a monthly basis, including historical observations going back to May 2015. Where there are at least 3 separate contributor estimates for the same entity, we calculate and publish simple average PD and LGD estimates. PD estimates can also be mapped into each contributor’s own grading scale to enhance benchmarking.
Our dataset enables Credit Analysts and risk professionals to have access to a new source of information that compliments their own research and provides peer comparisons.
There are a number of use cases for our dataset. Our clients are using CBCs for:
Trend credit monitoring
Defining risk appetite
IFRS9 / CECL