| Nowadays, fraudulent financial reporting has become a big problem which can not be ignored anymore. However, it is difficult to be detected. Using overseas and domestic research results for reference, this paper chooses 68 companies which have fraudulent financial reporting as research object, and then uses statistic method to get 17 ratios from four aspects: audit ratios; financial ratios, cash flow ratios, corporate governance ratios. Finally this paper develops a logit model on the basis of these 17 ratios. The prediction result indicates that the model has a good ability to detect the risk of fraudulent financial reporting in annual reports of China's listed companies. Thus, the model can be applied to the practice effectively. This article is divided into four chapters:The first chapter introduces the background and literature survey of this research, and clarifies the purpose, process and structure of this paper. The second chapter introduces the concept of fraudulent financial reporting, the reasons of fraudulent financial reporting, identifying factors, and identifying models. The third chapter finds identifying factors which can detect the risk of fraudulent reporting effectively. Based on these factors, this paper develops a logit model, and verifies the identifying ability of this model. At last, The conclusion summarizes the result, probes into its academic and practical significance, and points out the limitation and direction of future of this empirical research.The innovations of this paper include two aspects: firstly, this paper adds cash flow ratios to the research; secondly, this paper sets up a model from comprehensive angles. The results of research show that the Logit model can achieve 80.9% accuracy in identifying fraud of the original samples, 68.5% accuracy in identifying fraud of the testing samples. Thus, this model can be used to identify the fraudulent accounting information successfully. The outcome of the research will provide academic and practical support to creditors, investors , government departments. |