Fraud has become more common over the last few decades, as major corporations like WorldCom, Enron, and Satyam have gained notoriety for their dishonest financial reporting techniques. Internal and external auditors identify only a small portion of fraud incidents as such, there is a growing emphasis on automated techniques for identifying fraudulent financial statements. Accordingly, the main objective of this research is to investigate the impact of data analytics tools viz data visualization using Microsoft Power BI by auditors in fraud detection. An experiment of 49 participants was conducted to examine the research hypotheses and fulfill the research objective. The experiment results revealed that data visualization led to a timely fraud detection than traditional methods. Also, the use of data visualization led to more accurate fraud detection with regards to locating the potential fraud and the magnitude of the potential fraud as well. Hence, his research leads to practical follow-up steps that would serve as a guideline for forensic accounting auditors and to focus on areas of potential fraud. In order to develop a better fraud detection visualization tool, future researchers, auditors, law enforcement organizations, and regulators can benefit greatly from the knowledge this research provides. Also, auditing professionals that embrace big data, data analytics, and artificial intelligence (AI) to stay ahead of the competition can take advantage of many opportunities in this quickly changing, disruptive, but ultimately beneficial environment