Financial Natural Language Processing

Financial Natural Language Processing (FinNLP) applies NLP techniques to analyze textual financial data, aiming to improve decision-making and risk management in finance. Current research focuses on adapting and developing large language models (LLMs), often incorporating time-series data, for tasks such as sentiment analysis, risk detection, and price prediction; this includes creating specialized FinLLMs and multilingual models to address data scarcity in certain languages and domains. The field's significance lies in its potential to enhance the accuracy and efficiency of financial analysis, leading to better investment strategies, improved risk assessment, and more robust regulatory oversight.