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Using NLP: Entities and Their Relationships from Unstructured Financial Documents
Analysts can now spend far less time collecting and understanding data manually.
Primer has created two ready-to-use NLP Models that structure information from financial documents, making it simple to extract insights.
Analysts in financial organizations are faced with the task of analyzing massive amounts of data in order to make critical decisions involving risk, compliance, customer experience, and investments. To overcome the difficulties of unstructured data, Primer offers Finance Entity Recognition and Finance Relation Extraction. FER Relex can scan documents, identify all products that a company has, identify all revenue/financial metrics for an organization that investors need to know, and more.