可读性
财务报表
质量(理念)
匹配(统计)
财务分析
业务
国家(计算机科学)
财务
相似性(几何)
经济
会计
计算机科学
人工智能
哲学
统计
审计
数学
认识论
算法
图像(数学)
程序设计语言
作者
Jing Li,Nan Li,Tongshui Xia,Jinjin Guo
标识
DOI:10.1016/j.econmod.2023.106428
摘要
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.
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