In the world, financial frauds have presented a serious problem for organizations, mostly caused by lack of controls and, in turn, technological advances have opened doors to carry out frauds that are difficult to detect in time. Thus, since the creation of technology processing cores, patterns that suggest fraud or suspicious actions have been detected. Therefore, the purpose of this article is the analysis of case studies of Machine Learning used in financial fraud. Methodologically it begins with a detailed review of the use of Machine Learning in different areas, and then directly analyzes the information in the financial area. It is concluded that intelligent systems help detect financial fraud.