Many factors innuence a learning process and the performance of a learned classiier. In this paper we investigate the performance eeects of class distribution in the training set. We also study diierent methods of measuring performance based on cost models and the performance eeects of training class distribution with respect to the diierent cost models. Observations from these eeects help us d...

As the usage of credit card has increased the credit card fraud has also increased dramatically. Existing fraud detection techniques are not capable to detect fraud at the time when transaction is in progress. Improvement in existing fraud detection is necessary. In this paper Hidden Markov model is used to detect the fraud when transaction is in progress. Here is shown that hidden markov model...

Credit Card Fraud is one of the biggest threats to business establishments today. This paper presents a cascade artificial neural network for the recognition of credit card fraud detection. This system aims at attaining a very high recognition rate and a very high reliability, In other words, excellent recognition performance of credit card fraud detection was obtained. Then, One solution was p...

As credit card becomes the most popular payment mode particularly in online sector, fraudu- lent activities using technologies are rapidly increasing as a result. The purpose of this work is to develop novel system for fraud detection based on sequential modeling data, attention mechanism Long Short Term Mem- ory(LSTM) deep Recurrent Neural Networks(RNN) and Synthetic Minority Oversampling Tech...

Due to the dramatic increase of fraud which results in loss of billions of dollars worldwide each year, several modern techniques in detecting fraud are continually evolved and applied to many business fields. Fraud detection involves monitoring the behaviour of populations of users in order to estimate, detect, or avoid undesirable behaviour. Undesirable behaviour is a broad term including mis...

Credit card usage has been increased tremendously because of the popularity of E-commerce. As the usage of credit card grows the occurrence of fraudulent transactions also increases, thus comes the stipulation of fraud detection. Detection of fraudulent transaction using credit card plays a vital role in financial institutions. In the proposed work, fraud detection is done with data mining appr...

www.philadelphiafed.org R eports in the popular press and policymakers’ concerns about student loans have greatly intensified in recent years because of rising student loan balances and defaults. Even greater cause for concern arose as student loans outstanding passed credit card debt to become the single largest nonmortgage household debt in 2012. Worries about the risk of massive default have...

1 Background Credit cards have been widely used in the USA. The industry has matured so much that most households hold many credit cards and most consumers use credit cards as means of payment. They usually maintain their records on credit cards. In the USA, a total amount of credit card balances is about $700 billion. Because of the wide usage of credit cards, the term of cards is becoming a m...

Outlier detection is useful for credit card fraud detection. Due to drastic increase in digital frauds, there is a lot of financial losses and therefore various techniques are developed for fraud detection and applied to diverse business fields. In high-dimensional data, outlier detection presents some challenges because of increment of dimensionality. In this paper, the proposed model aims to ...

This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incomin...