Text mining financial statements: challenges and opportunities

Georgi Emilov Hristov
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Georgi Emilov Hristov: University of National and World Economy, Sofia, Bulgaria

Innovative Information Technologies for Economy Digitalization (IITED), 2024, issue 1, 196-204

Abstract: This report examines the use of text mining approaches to analyze statutory financial statements, addressing key challenges like specific vocabulary and stop words. Through a case study on General Electric's consolidated statutory financial statement, it demonstrates the complexities that need to be managed in order to extract useful information from unstructured text (financial disclosures). The results demonstrate that using off-the-shelf, well known Python library (NLTK) is not sufficient when text mining statutory financial statements.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:nwe:iitfed:y:2024:i:1:p:196-204

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