Textual analysis and detection of financial fraud: Evidence from Chinese manufacturing firms

Jing Li, Nan Li, Tongshui Xia and Jinjin Guo

Economic Modelling, 2023, vol. 126, issue C

Abstract: With the increasing complexity of financial statement manipulation, relying solely on quantitative financial data may not effectively detect financial fraud. While textual analysis can provide additional insight, little research has been conducted on its multiple dimensions. Using 579 listed Chinese manufacturing firms in 2020, we select readability, forward-looking, similarity, matching degree, and positive and negative sentiment indicators from textual language structure, quality, and expression of management discussion and analysis texts, in combination with financial indicators, to detect financial fraud. Our findings indicate that fraudulent firms tend to be overly cautious in their financial reporting, express fewer positive sentiments, and conceal financial fraud by increasing the complexity of their annual reports and using more degree adverbs to modify forward-looking information. This study also highlights the importance of considering textual language expression in detecting financial fraud in state-owned and non-state-owned firms.

Keywords: textual analysis; Financial fraud; Language structure; Language quality; Language expression (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:126:y:2023:i:c:s0264999323002407

DOI: 10.1016/j.econmod.2023.106428

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