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Keywords: Credit Card Fraud Detection, Machine Learning, Deep Learning, Streaming Transaction Data, Behavioural Pattern Analysis.
ABSTRACT
Credit card frauds are easy and friendly targets. E-commerce and many other online sites have increased the online payment modes, increasing the risk for online frauds. Increase in fraud rates, researchers started using different machine learning methods to detect and analyse frauds in online transactions. The main aim of the paper is to design and develop a novel fraud detection method for Streaming Transaction Data, with an objective, to analyse the past transaction details of the customers and extract the behavioural patterns. Where cardholders are clustered into different groups based on their transaction amount. Then using sliding window strategy to aggregate the transaction made by the cardholders from different groups so that the behavioural pattern of the groups can be extracted respectively. Later different classifiers are trained over the groups separately. And then the classifier with better rating score can be chosen to be one of the best methods to predict frauds. Thus, followed by a feedback mechanism to solve the problem of concept drift. In this paper, we worked with European credit card fraud dataset.
1. INTRODUCTION: Fraud detection involves in monitoring the activities of the populations of users to avoid objectionable behavior which consists of fraud and defaulting. This has been a very relevant problem that demands the attention of communities such as machine learning and data science where the solution of this problem can be automated. As this kind of problem is particularly challenging in a learning perspective, as it is characterized by various factors such as class imbalance. The number of valid transactions far outnumbered fraudulent ones and also the transaction pattern changes in statistical properties over the course of time. Thus, in real world examples, the massive streams of payment requests are been quickly scanned by the automatic tools that determine which transaction to be authorized in order to prevent the performance of the fraud detection overtime As for many banks which has retained high profitable customers has been the number one business goal, these banking frauds poses a significant threat at different banks but in terms of substantial financial losses, trust and credibility has been a concerning issue for both banks and...