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Summary
Enhancing company data, even when structured and cleaned, proves challenging without mapping it to industry-standard identifiers like S&P Global’s CapIQ IDs or various BECRS IDs. But entity mapping is a complex process for data engineering and analyst teams across industries.
Creating accurate mappings from company entities in one database to identifiers in an external one presents deep technical challenges due to the limited amount of contextual information and frequent name similarities, including among entities within the same corporate hierarchy. While fuzzy matching and rules-based mapping are common solutions, their reliance on semantic similarities limits their effectiveness.
Introducing AI-powered entity linking—a revolutionary approach that considers not only the submitted entity but also its associated data and the content of the target database. This innovative technology offers a more effective and powerful mapping capability.
Join us in this session as we explore AI entity mapping, including the Kensho Link solution, and its seamless integration with other S&P Global datasets. Discover how it addresses user initiatives such as:
- CRM clean-up
- Platform integrations
- Security master file enhancement
Speaker
Lance Risi
Lead, Product Management & Development
Lance has been with S&P Global for 25 years, primarily working on the industry leading Cross Reference mapping solution for clients around the globe.
Jonathan Leibowitz
Associate Manager, Business Development
Jonathan Leibowitz is the Commercial Lead for Kensho's Financial Data Management & Linking Solutions.
David Bender
Product Manager, Kensho Link
David is a product manager at Kensho Technologies (an S&P Global company) where he leads Kensho Link, an AI-powered entity linking tool.
Moderator
Taylor Richardson
Associate Manager, Business Development
Taylor Richardson is an Associate Manager of Business Development at Kensho Technologies.
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