ABSTRACT : This paper proposes a solution to the Kaggle competition: "IEE-Fraud Detection", whose objective is to detect fraudulent transactions in a customer and transactional dataset collected by an E-commerce site to construct a transaction confirmation system via text messaging of the payment services company Vesta Corporation. Exploratory analysis of the data and different modeling approaches are shown, selecting the most appropriate results for anomaly detection.