Abstract Machine learning and data mining techniques have been used extensively in order
to detect credit card frauds. However, most studies consider credit card transactions as …

Credit card frauds are at an ever-increasing rate and have become a major problem in the
financial sector. Because of these frauds, card users are hesitant in making purchases and …

Due to the increasing digitalization of banking services and the predominance of mobile
banking applications, the rate of credit card payments is increasing every year, among …

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 …

In the peer to peer (P2P) lending platform, investors hope to maximize their return while
minimizing the risk through a comprehensive understanding of the P2P market. A low and …

With the explosion of data in recent times, Machine learning has emerged as one of the most
important methodical approaches to observe significant insights from the vast amount of …

Every year, billions of dollars are lost due to credit card fraud, causing huge losses for users
and the financial industry. This kind of illicit activity is perhaps the most common and the one …

For aiding computer security experts in their work, log files are a crucial piece of information.
Especially the time domain is of interest, since sometimes, timestamps are the only linking …

In this paper we consider a challenging problem of learning discriminative vector
representations for event sequences generated by real-world users. Vector representations …

In this dissertation, we develop and discuss several loan evaluation methods to guide the
investment decisions for peer-to-peer (P2P) lending. In evaluating loans, credit scoring and …