Information Extraction from Financial Tables: Application and Evaluation of a Machine Learning Approach in Annual Reports

Abstract

In recent years, specialized deep-learning models have demonstrated promising results in extracting table information from PDFs. In addition, multi-module solutions have been developed to process complex PDF documents and optimally align the extraction techniques to the different document components. Furthermore, Large Language Models (LLMs) have shown a comprehensive language understanding. However, the performance of these new possibilities has not yet been validated in an end-to-end process on a dataset of annual reports.