Detection of Fraudulent Financial Statements Based on BP Neural Network
Mei Guo-ping · Systems Engineering · 2009
Considering the characteristics of fraudulent financial statements(FFS),this paper designs a FFS detection model based on BP neural network.To carry out the experiment,we choose 44 FFS according to the auditing reports and 44 true financial statements according to some specific standards during 1999-2002 as training data set.Similarly,73 FFS and 99 true financial statements during 2003-2006 are chosen as testing data set.Ten financial ratios are chosen as detection variables.We train the model by using training data set and apply the trained model to the testing data set,good experimental results are obtained.