Abstract
Our research seeks to determine whether the detection of potential fraud in China-listed U.S. companies could be measured by the U.S. M-Score and F-Score models. Then, we group the data for 18 pairs of companies to make a t-test defined as the average difference between firms' M-scores or F-scores before and after the fraud. Moreover, more detailed information about these companies, financial fraud methods and motives, and ways to prevent financial fraud. Through our preliminary research, these two U.S. detection models can be used to detect financial fraud for Chinese-listed U.S. companies in statistical significance. With this premise, we also do an additional t-test to prove the standing adverse effects of committing fraud on firms.
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