A white paper on real time credit risk monitoring and assessing global events for risk signals around the clock has just been released. The author, RAGE, deploys a multi-dimensional approach for generating a Real Time Credit Risk signal – a combination of semantic analysis techniques using a unique semantic analysis engine, statistical models, and fundamental analysis of companies and the environment they operate in. This interesting news came to us from Gnomes National News Service in their article, “Continuous Credit Risk Monitoring, a new paradigm in the age of Big Data.”
The RAGE Big Data engine systematically and continuously assesses credit risk of borrowers, customers, and third party partners. Every 24 hours, it processes over a million items and interprets them using a context specific ‘lens’ for each company being monitored. This is some powerful semantic analysis going on.
Semantic technology requires a special knowledge of terminology and coding to reduce errors. Access Innovations, developer of the M.A.I. machine-assisted indexing system and specializing in complex coding, tagging, and indexing, provides a range of services that deliver tag integrity.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.
