Fraud Detection Technique in Credit Card Transactions using Convolutional Neural Network

Abstract

Cashless transactions such as online transactions, credit card transactions, and mobile wallet are becoming more and
more popular in financial transactions nowadays. With increased number of such cashless transaction, fraudulent transactions are also
increasing. Fraud can be detected by analyzing spending behavior of customers (users) from previous transaction data. If any deviation
is noticed in spending behavior from available patterns, there may be chance of fraudulent transaction. To detect fraud behavior, bank
and credit card companies are using various methods of data mining such as decision tree, rule based mining, neural network, fuzzy
clustering approach, hidden markov model or hybrid approach of these methods. In this paper we have used Convolutional neural
network with SMOTE. We have transformed original features into new features.