WCSE

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.

Index Terms— big data, forensic, audit, fraud, detection

Bambang Leo Handoko, Ameliya Rosita, Nada Ayuanda, Adelia Yulma Budiarto
Accounting Department, Faculty of Economic and Communication, Bina Nusantara University, INDONESIA

[Download]

Cite: Bambang Leo Handoko, Ameliya Rosita, Nada Ayuanda, Adelia Yulma Budiarto, "The Impact of Big Data Analytics and Forensic Audit in Fraud Detection, " Proceedings of 2022 the 12th International Workshop on Computer Science and Engineering (WCSE 2022), pp. 67-71, June 24-27, 2022.