How big data analytics is used in forensic accounting and auditing

Abstract

In this study, we investigate the application of big data analytics in forensic accounting and auditing. Big data technology mediates the connection between awareness and plans to use for fraud detection. We made an effort to assess how big data might be used in forensic accounting and auditing practices. Design/methodology This research is based on systematic literature review, and it provides a thorough understanding of the existing literature on big data research in forensic accounting and auditing. The research was gathered through peer-reviewed literature using current (post-2014) articles. Results/findings The model for corporate auditing has changed. Managers at the organization are proactively identifying and resolving internal abnormalities and discrepancies prior to an external audit using conventional audit techniques. Known white-collar crimes at several publicly traded corporations have led to a high demand for forensic accountants. Big data analytics is a key tool for spotting fraud patterns. Students should be encouraged to develop skills in data generation, sharing, analytics, mining, reporting, and storage because big data analytics is essential to business education. Practical implications and conclusions The study's conclusions can be applied to the forensic accounting industry to assist in the development of Big Data fraud-fighting technology. Big data analytics and forensic accounting should be covered in accounting curricula. By offering different perspectives on big data and its practical implications in accounting practice, this research contributes to the body of published knowledge. As more companies use big data, the need to update the accounting curriculum is highlighted because success now requires a distinct set of skills. Future research should involve interviewing and surveying accountants, auditors, and other members of the financial services industry, which will be difficult but necessary.