Markit is adopting the Industry Classification Benchmark (ICB) from Dow Jones Indexes and FTSE Group. ICB will be implemented across Markit’s entire range of entities across all asset classes. Markit’s involvement will also help to enhance ICB’s coverage of the current 40,000 equities by expanding into around 5,000 credit default swap reference entities and bond issuing entities. This information is covered in Markit’s Reference Entity Database (RED), which will now follow ICB guidelines providing a four-tier classification structure.
A-Team Insight Blogs
Markit Adopts and Enhances ICB Codes for Credit Markets
Recorded Webinar: Adverse media screening – how to cut exposure to criminal activity, from money laundering to human trafficking
Screening for adverse media coverage of counterparties presents an incredible opportunity for financial institutions to limit risk exposures and identify bad actors early. It is required by regulations such as the EU’s sixth Anti-Money Laundering Directive (AML 6), and is one of the most effective ways to steer clear of potential connections with sanctioned activity...
Data monetisation, data strategy to drive business outcomes, data discovery and intelligence, the power of data lineage, how to deliver an ESG data strategy and, necessarily, regulatory reporting challenges and the data management response, are just some of the key topics that leading capital markets’ participants and innovative solutions vendors will discuss at A-Team Group’s...
Now in its 5th year, the RegTech Summit in NYC explores how the North American financial services industry can leverage technology to drive innovation, cut costs and support regulatory change.
Sourcing entity data and ensuring efficient and effective entity data management is a challenge for many financial institutions as volumes of data rise, more regulations require entity data in reporting, and the fight again financial crime is escalated by bad actors using increasingly sophisticated techniques to attack processes and systems. That said, based on best...