A Table Extraction Solution for Financial Spreading

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.