Relevance of Big Data to Forensic Accounting

Business organizations lose about 5% of their revenues to fraud each ear, which can exceed 3.5 trillion (USD) worldwide. The existence and persistence of financial statement fraud (FSF) is detrimental to the safety, soundness, and efficiency of the financial markets. This study is intended to improve educational and practical skills of forensic accountants and their audit efficacy in discovering FSF by using Big Data and data analytics and algorithms. We discuss the use of Big Data and data analytics in forensic accounting practices and then examine the desired educational and practical skills of forensic accountants in the age of Big Data. This study gathers opinions from both Chinese academics and practitioners regarding the importance, demand, relevance, benefits, coverage and use of Big Data in forensic accounting education and practices. Results indicate that: (1) the demand for and interest in Big Data/data analytics and forensic accounting will continue to increase; (2) Big Data/data analytics and forensic accounting should be integrated into the business curriculum at both undergraduate and graduate levels; (3) many of the suggested Big Data topics should be integrated into business and accounting curricula and (4) many attributes such as availability of Big Data and Big Data techniques including predictive, descriptive and prescriptive analytics are important in improving forensic accounting education and practice.