- Highlights
- Leverage data on the aliases for entities and individuals to support enhanced due diligence with client onboarding, KYC, and AML workflows
- Access over 75 global sanction lists, including the dates the individual or entity first appeared and last appeared on the list
- Identify direct relationships, parent hierarchy relationships, and affiliated entities
- Feed Coverage
Country/Region Count Type Start Date Europe Region 350 Entities 2002 United Kingdom 350 Entities 2000 United Nations 350 Entities 2001 United States 8,240 Entities 1981 Australia 1,800 Entities 2003 - Feed Details
- Monitor the entities (companies and individuals) on U.S. and global economic sanctions lists with FactSet Global Sanctions. This data set monitors the U.S. Treasury’s Office of Foreign Assets Control (OFAC) sanctions lists and other restricted lists maintained by global authorities (e.g., Great Britain, United Nations, and European Union). Identified with FactSet symbology, the entities that appear on these lists are further analyzed to identify related entities as well as the connecting relationship.
- Firm Information
- FactSet creates data and technology solutions for investment professionals around the world, providing instant access to financial data and analytics that investors use to make crucial decisions. We combine our unique proprietary datasets, your in-house data, and third-party unstructured data to help you see and seize opportunity sooner.
- Data/Documents
- Community Discussion
Today we would like to inform you that we have made a major update for our emotional data API and released version 3 in February 2019. Additionally, to general improvements of stability and redundancy we have added some new and very interesting data sets. For more information just visit our websi...
We conducted a survey on Alternative Data demand during the https://advantage.factset.com/factset-buy-side-forum-tokyo-2019 FactSet Buy-Side Forum Tokyo last week. Not surprisingly, ESG tops the list among 18 categories as Japanese financial institutions began integrating ESG investment strategie...
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Working with Japanese Earnings Call Transcripts: StanfordNLP What open-source packages are you using in the NLP space? I had always found Python’s NLTK package easy to use. A recent https://medium.com/analytics-vidhya/introduction-to-stanfordnlp-an-nlp-library-for-53-languages-with-python-code-d7...
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