Mastercard Extortion Discovery Uses AI

Abstract

The issue of Mastercard extortion is a significant concern for financial institutions and credit card corporations across the globe, with annual fraud losses estimated at billions of dollars. Financial institutions suffer reputational harm and financial losses as a result of fraudulent transactions. Consequently, the detection of fraudulent transactions is critical to the survival of the financial sector. This paper presents a proposed system for detecting Mastercard misrepresentations, which classifies exchanges as false or authentic using artificial intelligence (Al) techniques. The proposed approach is predicated on the examination of value- based data, with particular emphasis on factors such as area, time, and exchange sum. To detect fraudulent cases, Al computations are utilized. By implementing the proposed method on a certified Mastercard deception dataset, we achieve high review rates and precision, thereby establishing the method's viability.