Abstract
In the financial industry, using of several Machine Learning (ML) algorithms and artificial intelligence (AI) models has simplified the solution and detection of main problems related to its wide landscape. One of the most broadly used techniques of ML is Support Vector Machine (SVM) which owns its specific algorithms appropriated to detect frauds in financial applications. The reason why it is widely used in this field is that it can work well with High Dimensional Data (HDD) in applications where the number of features is greater than number of observations. Also, this technique is less susceptible to overfitting of HDD which makes it suitable for use in these cases.