The Impact of Big Data Analytics and Forensic Audit in Fraud Detection

Abstract

The high number of fraud cases that occur, causes a large amount of losses to be borne by the company as well as investors and creditors. Based on this, we are looking for an effective method to detect fraud. This study aims to analyze the effect of big data analytics on forensic audits and fraud detection. In addition, this study was conducted with the aim of analyzing the effect of forensic auditing as a mediating variable on fraud detection. This research was conducted using a quantitative approach with a survey method by distributing questionnaires. The respondents of this study are auditors who work in public accounting firms. Statistical testing in this study is in the form of Structural Equation Modeling (SEM) using the smart PLS 3 application. The results of this study indicate that big data analytics has a positive effect on forensic audits. This research also proves that big data and forensic audit each have a positive effect on fraud detection. In addition, this study also proves that forensic audit moderates/strengthens the effect of big data analytics on fraud detection.