Data Analytics to Detect Anomalies and Fraud Using the SAFT-PT File

Anomalies' detection and investigation on fraud have been, in recent years, one of the auditing emerging areasIn external auditing, fraud detection the detection of fraud requires adequate and sufficient evidence to provide a high, though not absolute, assurance that the financial statements are free from fraud or material misstatement. Internal auditing aims at identifying the risk of fraud, defining strategies to prevent and anticipate internal control needs. The use of data nalytics and extraction software to analyze millions of records and to apply advanced techniques that highlight severe outliers, unwanted inliers, repetitions, or other patterns, is recommended in International Standards on Auditing. This paper presents the context of appropriate analytical methods for anomalies' and fraud detection, demonstrates and systematizes their application through the analysis of the SAFT-PT file, taking six months of sales in an Small Enterprise and analyzes and discusses the results, proposing improvements in internal control. This paper is intended to contribute to the demystification of the complexity of the analyzes, evidencing the opportunity to repeat tasks with identical data.