You are building an NLP system for noisy financial text such as earnings call transcripts, analyst notes, and internal commentary. The text includes speaker changes, abbreviations, OCR errors, ticker symbols, and domain-specific phrases that make manual review slow and inconsistent. The goal is to turn this text into structured signals that analysts can search, filter, and act on.
How would you design a system to extract actionable insights from noisy financial text?
