State-of-the-art strategy in machine learning for credit card fraud detection

State-of-the-art strategy in machine learning for credit card fraud detection

K. Jyothsna Vyshnavi*1, B. Srinadh2, B. Bhargav Naidu3, M. Akshay4, Ms. V. L. Sowjanya5

[1-4] B. Tech Student, 5Assistant Professor, LIET

[1,2,3,4,5] Computer Science and Systems Engineering, Lendi Institute of Engineering and Technology, Vizianagaram

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Abstract - People can use credit cards for online transactions as it provides an efficient and easy-to-use facility. With the increase in usage of credit cards, the capacity of credit card misuse has also enhanced. Credit card frauds cause significant financial losses for both credit card holders and financial companies. In this research study, the main aim is to detect such frauds, including the accessibility of public data, high-class imbalance data, the changes in fraud nature, and high rates of false alarm. The main focus has been to apply the recent development of machine learning algorithms for this purpose. Comparative analysis of machine learning algorithms was performed to find efficient outcomes. A comprehensive empirical analysis has been carried out by applying variations in the number of hidden layers, epochs and applying the latest models.

Key Words:   Credit Card Fraud, Machine Learning, Fraud Detection, Algorithm Comparison, Financial Security