Kelvin Du , Yazhi Zhao , Rui Mao , Frank Xing , Erik Cambria
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This survey presents an in-depth review of the transformative role of Natural Language Processing (NLP) in finance, highlighting its impact on ten major financial applications: (1) financial sentiment analysis, (2) financial narrative processing, (3) financial forecasting, (4) portfolio management, (5) question answering, virtual assistant and chatbot, (6) risk management, (7) regulatory compliance monitoring, (8) Environmental, Social, Governance (ESG) and sustainable finance, (9) explainable artificial intelligence (XAI) in finance and (10) NLP for digital assets. With the integration of vast amounts of unstructured financial data and advanced NLP techniques, the study explores how NLP enables data-driven decision-making and innovation in the financial sector, alongside the limitations and challenges. By providing a comprehensive analysis of NLP applications combining both academic and industrial perspectives, this study postulates the future trends and evolution of financial services. It introduces a unique review framework to understand the interaction of financial data and NLP technologies systematically and outlines the key drivers, transformations, and emerging areas in this field. This survey targets researchers, practitioners, and professionals, aiming to close their knowledge gap by highlighting the significance and future direction of NLP in enhancing financial services.
期刊介绍:
Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.