Fraud Detection Using Fraud Hexagon Model in Top Index Shares of KOMPAS 100

Abstract

The company's performance is reflected in the financial statements that they prepare each period. This triggers fraud management, namely fraudulent financial statements. There are several approaches to detecting fraud, one of which is the Fraud Hexagon approach. Our research uses the Fraud Hexagon approach with a sample of companies going public on the Indonesia Stock Exchange which are included in the top index of KOMPAS 100. Our research is a causal quantitative study, we use statistical data analysis to test hypotheses. Our results state that capability and collusion have a significant effect on detecting fraudulent financial statements, while other variables do not have a significant effect.