Credit Benchmark operates a contributed data model, focused on gathering credit risk information from the world’s major global banks.
Contributed data models, which aggregate data from multiple market participants, have long created value in financial services. As the model has been proven, contributed data models gathering more confidential datasets, showing results on an anonymised basis, have developed. In securities lending, for example, Data Explorers succeeded in demonstrating the value of industry-sourced benchmarking data to securities lenders and beneficial owners, enabling the company to gather highly market sensitive data, such as open lending positions and margins.
We currently focus on credit risk estimates produced by banks using the Internal Ratings-Based Approach (“IRB”). The Basel framework for banking capital has resulted in many global and national banks adopting IRB (either the foundation or advanced approach) to calculating regulatory capital. Under IRB, banks employ highly qualified credit risk professionals to assess the creditworthiness of the entities with which they do business, generating many thousands of robust entity-level ratings.
Credit Benchmark’s contributed data model unlocks the value of this powerful resource, allowing banks to view their own estimates in the context of a robust industry consensus. We maximise data quality through rigorous data validation and entity mapping techniques. We protect the security and anonymity of individual contributors through industry-leading secure hosting, data processing and data transmission.