Abstract
This paper aims to detect plausible frauds of financial companies via text analysis of annual and quarterly reports of China's listed companies. The Management Discussion and Analysis (MD&A) is digitized as vectors. The empirical results indicate that compared with various vector indexes, the bag-of-words (BoW) model and machine learning algorithm have a prediction effect and the ability to recognize frauds where the BoW model can correctly recognize 77% of the fraud reports. This would be helpful for audit authorities to identify fraud reports.
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