Financial Data

Financial data analysis is undergoing a rapid transformation driven by advancements in machine learning and natural language processing. Current research focuses on developing sophisticated models, including large language models (LLMs), XGBoost, and various neural network architectures, to improve tasks such as credit risk prediction, financial distress forecasting, and the generation of synthetic financial data for regulatory purposes. This work addresses challenges like data scarcity, missing values, and the need for explainable models, ultimately aiming to enhance decision-making in finance, improve regulatory oversight, and facilitate more robust economic analysis.