Fraud is a common phenomenon in business. Prevention by detecting significant fraud in financial statements has always been the focus of investors, legislators, standardizers, managers and auditors. The present age is called the information age, and what leads to power and success is information. Data mining is a bridge between statistics, computer science, artificial intelligence, modeling, machine learning and visual loading of data, which in the process of extracting valid, previously unknown, understandable and reliable information from large databases is possible. It can be used in decision-making in important business activities such as improving the quality of information usefulness by detecting financial fraud.
The present study provides the necessary evidence for investigating data mining in financial statement fraud by using historical documents using library documents and based on the background and research of researchers.