A Financial Fraud Detection Model Based on Organizational Impression Management Strategy

Abstract

Financial fraud misleads investors into making wrong decisions based on incorrect information, especially for listed companies’ financial statements fraud. It damages investors’ interests, disturbs the economic order, and creates a crisis of trust, which is extremely harmful. Therefore, it is of great significance to build an effective financial fraud detection model for listed companies. This study uses a sample of 126 Chinese listed companies from 2013 to 2017 to examine the relationship between two organizational impression management strategies (promotion strategy and defense strategy) and financial fraud using the integrated learning methods. This study innovatively analyzes financial fraud using social media data and annual reports’ readability data as non-financial features. The results show that companies implementing the defensive/protective strategy were more likely to commit financial fraud. In addition, the average number of tables in a company’s annual report can significantly help researchers to judge fraud.