Navigating the Landscape of Automated Information Extraction for Financial Fund Prospectuses: Survey and Challenges

In the financial sector, a fund prospectus is a critical document mandated by the Securities and Exchange Commission (SEC) that provides vital information about investments to the public. These documents encompass a range of financial concepts that define the fund's operations, including its name and disclaimers associated with periodic reports. Traditionally, the identification of these concepts has been a manual, labour-intensive, and costly task for financial regulators, aimed at ensuring the completeness of information. Automating this process is fraught with challenges, including the lengthy nature of prospectuses, the nuances of financial language, and the scarcity of labelled data for effective model training. This study explores state-of-the-art methods for information extraction, specifically within the context of financial documents. It begins with an overview of information extraction, detailing its definition and various types, such as Named Entity Recognition (NER) and event extraction. The discussion highlights the increasing significance of information extraction in the financial domain and reviews typical application areas. Ultimately, this research seeks to highlight the challenges within existing methods through a comprehensive literature review, emphasizing the need for more effective techniques tailored to the extraction of financial concepts in fund prospectuses. By enhancing and streamlining the extraction process, it aspires to improve efficiency and reduce costs for financial regulators, thereby ensuring more accurate and comprehensive information dissemination.

@article{Xu2025,
  title     = {Navigating the Landscape of Automated Information Extraction for Financial Fund Prospectuses: Survey and Challenges},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {8},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Yuyao Xu and Mohamad Farhan Mohamad Mohsin},
  doi       = {10.14569/IJACSA.2025.0160820},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160820}
}