A Survey of Deep Learning based Online Transactions Fraud Detection Systems

With the advancement of technology, today most of the modern commerce is relying upon the online banking and cashless payments. Due to adaption of online payment among businesses, the fraud cases are also increasing which cause financial losses to them. Fraudsters are inventing new techniques to perform fraudulent transaction which seem legitimate. Hence, there is an urgent need to develop fraud detection measures which can deal with these fraudsters on real time basis. Deep learning techniques have the capability to detect these fraudulent transactions efficiently and has a huge scope in fraud detection. However, there are many challenges faced by the researchers in online transactions fraud detection because the datasets are not publicly available due to privacy issue of the financial institutions as customers data is sensitive and it can be misused and the datasets which are available are imbalanced. This paper presents a review of deep learning techniques used for online transactions fraud detection. It also provides the information about datasets used by the researchers and the results achieved by them in their research work.