Automatic extraction of performance indicators from financial statements

We present a method to automatically analyze financial statements for the purpose of recognizing and extracting relevant financial indicators together with its values and its related narratives. We employ a rule-based approach to solve the problem of syntactical and morphological variations contained within the financial text. The information was extracted using a multi-pass scan to process the text in a series of pre-programmed functions. Experiments were carried out to demonstrate the feasibility of the system by deriving the precision and recall scores. The extracted results can be used to construct and augment knowledge bases for a more complex text mining systems.