Structured Data Extraction and Regulatory Narrative Generation: Machine Learning Models for Automated Financial Reporting and Disclosure

Authors

  • Xiaojing Wang Professor of Electrical and Computer Engineering, University of Illinois Urbana-Champaign

Keywords:

structured data extraction, regulatory narrative generation, machine learning models, automated financial reporting

Abstract

Reliability, automation, and accuracy in financial reporting have become more pertinent than ever with rising regulatory requirements, rapid expansion in business activity, and increasing complexities, as these require analysis of larger volumes of financial data than ever before. Artificial intelligence (AI) could be a savior in this world to drive efficient, automated, and compliant financial reporting.

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Published

30-06-2026

How to Cite

[1]
“Structured Data Extraction and Regulatory Narrative Generation: Machine Learning Models for Automated Financial Reporting and Disclosure”, J. Computational Intel. & Robotics, vol. 6, no. 1, pp. 1–8, Jun. 2026, Accessed: Jun. 05, 2026. [Online]. Available: https://www.thesciencebrigade.com/jcir/article/view/731