Revenue Segmentation: Financial Analysis and Regulatory Transparency Webinar
Join our Enterprise Data specialists whilst they present the latest content set under the Company Research umbrella. In this session we will provide details of our Company Revenue Segmentation aligned to the Bloomberg Industry Classification System (BICS).
• BICS classifies every company to level 4 - Sub Industry, and where appropriate it classifies companies at more granular levels such as Segment Level - Levels 5 to 7
• Coverage includes 50K Public Companies
• 17 years of history available, which includes both active and inactive companies
• Use cases include calculating the revenue exposure of a portfolio based on BICS segments, screening companies to exclude and include specific segments for ESG investment mandates, identifying the particular segments which enable companies to be EU taxonomy eligible
• The Revenue Segmentation product provides identifiers which allow easy integration with other datasets
Speakers
Sundeep Agrawal
Research Data Product Manager
Bloomberg
Sundeep Agrawal is a Research Data Product Manager at Bloomberg. Prior to joining Bloomberg LP, Sundeep spent 18 years on the buy side at different hedge funds as a portfolio manager and research analyst investing in credit and equities. Earlier in his career he worked in the Fixed Income division at Lehman Brothers. Sundeep received his MBA from New York University’s Stern School of Business, an MS in Systems Engineering from The University of Texas at Austin and a BS in Electronics Engineering from Delhi Institute of Technology, India.
JUAN VIEIRO
Data Specialist
BLOOMBERG L.P.
Juan Vieiro is a data specialist working with the quant and data science community to build data and technology solutions. Juan has over 20 years of experience in enterprise data distribution and management with a focus on Quant & Systematic workflows.
Maris Serzans
Data Scientist
Bloomberg
Maris Serzans is a data scientist at Bloomberg, specialising in quant research data and alternative data. Maris has experience in fintech in the context of data engineering and data science, and a background in theoretical physics at University of Oxford.