Exploring Machine Learning for Credit Card Fraud Detection from a Philippine Perspective

This study examines how machine learning (ML) techniques are applied in the Philippine setting to identify credit card fraud. This research aims to provide insights into the effectiveness of ML techniques in fraud detection, focusing on customizing ML algorithms to the distinct patterns and dynamics of credit card fraud in the Philippines, considering the nation's unique economic, technological, and social milieu. The research assesses the efficacy of different machine learning (ML) models using available data on credit card fraud occurrences and suggests improving fraud detection systems in Philippine financial institutions through ML integration. It also examines the opportunities and difficulties of using ML-driven fraud detection techniques in the Philippine financial industry.