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A Table Extraction Solution for Financial Spreading

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1633)


Financial spreading is a necessary exercise for financial institutions to break up the analysis of financial data in making decisions like investment advisories, credit appraisals, and more. It refers to the collection of data from financial statements, where their extraction capabilities are largely manual. In today’s fast-paced banking environment, inefficient manual data extraction is a major obstacle, as it is time-consuming and error-prone. In this paper, we, therefore, address the problem of automatically extracting data for Financial Spreading. More specifically, we propose a solution to extract financial tables including Balance Sheet, Income Statement and Cash Flow Statement from financial reports in Portable Document Format (PDF). First, we propose a new extraction diagram to detect and extract financial tables from documents like annual reports; second, we build a system to extract the table using machine learning and post-processing algorithms; and third, we propose an evaluation method for assessing the performance of the extraction system.


  • Table extraction
  • Deep learning
  • Financial spreading

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    The table’s title and its text are collected, and similar patterns are then merged to create matching patterns. In the real system, many regular expression patterns are designed. One matching pattern is used in the filter to detect a potential page with financial tables. Others are then used to filter these pages into the potential balance sheet, potential income statement, and potential cash flow statement through the respective regular expression filters.

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    The financial tables are presented consecutively, however, in no fixed order.

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    Due to the lack of human resources, only English reports were selected to be able to accurately annotate the table contents.


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Correspondence to Duc-Tuyen Ta .

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Ta, DT., Jendoubi, S., Baelde, A. (2022). A Table Extraction Solution for Financial Spreading. In: Kotsis, G., et al. Database and Expert Systems Applications - DEXA 2022 Workshops. DEXA 2022. Communications in Computer and Information Science, vol 1633. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-14342-7

  • Online ISBN: 978-3-031-14343-4

  • eBook Packages: Computer ScienceComputer Science (R0)