An Early Warning Study on Disclosure Fraud Detection Based on Corporate Governance
Shinong Wu · Management Sciences in China · 2006
This paper collects a sample of 192 A-share listed companies committing disclosure fraud spanning from 2001 to 2005 and the corresponding 192 matched companies. Based on financial indicators and corporate governance indicators, the paper develops two disclosure fraud detection models by applying the Logistic regression and hybrid BP neural network method respectively. The empirical results show that corporate governance indicators help to improve the efficiency of the prediction model. Moreover, the hybrid BP neural network model dominates the Logistic regression model.