Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings…
Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings and stock movements, while rarer events such as credit-rating changes, product approvals, and labor issues are harder to capture at scale. Synthetic generation can help fill those gaps for trading research, risk modeling, and surveillance…
