Earnings Management on New Fraud Diamond and Financial Statement Fraud in Indonesian Infrastructure Firms

Abstract

Financial statement fraud in Indonesia’s infrastructure sector poses significant risks due to complex accounting practices. The New Fraud Diamond framework offers a robust approach to detecting fraud, but its application in this context, moderated by earnings management. This study investigates the direct effects of financial stability, financial targets, monitoring effectiveness, earnings growth, and change in directors on financial statement fraud, and examines earnings management’s moderating role. Using panel data regression and Moderated Regression Analysis, we analyzed 90 firm-year observations from 15 IDX-listed infrastructure firms (2018–2023). The Beneish M-Score measured fraud, while proxies like financial stability and Return on Assets captured independent variables. Financial stability and earnings growth significantly increase fraud risk (p < 0.050), while monitoring effectiveness unexpectedly worsens it. Earnings management strengthens these relationships for stability and growth. The New Fraud Diamond model, enhanced by Moderated Regression Analysis, effectively detects fraud in Indonesian infrastructure firms. Strengthened governance is needed to address monitoring weaknesses. Future research should explore additional fraud predictors.