Unleashing the Power of Predictive Analytics and Machine Learning for Credit Card Fraud Detection

Unleashing the Power of Predictive Analytics and Machine Learning for Credit Card Fraud Detection

Author: Yogesh Madhukar Jadhav
University of Mumbai Institute of Distance & Open Learning (IDOL),
Information Technology, University of Mumbai

Abstract: Credit card fraud has become a prevalent issue in today's digital world, resulting in substantial economic and financial losses. Traditional rule-based fraud detection methods have proven to be ineffective in combating this problem promptly and accurately. Therefore, this research aims to explore the potential of predictive analytics and machine learning techniques in detecting credit card fraud. By utilizing these advanced methods, we can enhance fraud detection accuracy and efficiency, ultimately reducing the impact of fraudulent activities on individuals and financial institutions.

Keywords: Credit card fraud detection, Predictive analytics, Machine learning, Fraud detection methods, Rule-based approaches, Sophisticated fraudulent activities, evaluating fraud detection models, Data collection and preprocessing, Feature engineering techniques, Machine learning algorithms, Model evaluation metrics, Experimental results, Factors affecting accuracy, Enhancing fraud detection efficiency, Ethical and privacy considerations.