Credit card fraud falls broadly into two categories: behavioural fraud and application fraud. Application fraud occurs when individuals obtain new credit cards from issuing companies using false personal information and then spend as much as possible in a short space of time. However, most credit card fraud is behavioural and occurs when details of legitimate cards have been obtained fraudulent...

Billions of dollars of loss are caused every year due to fraudulent credit card transactions. The design of efficient fraud detection algorithms is key for reducing these losses, and more and more algorithms rely on advanced machine learning techniques to assist fraud investigators. The design of fraud detection algorithms is however particularly challenging due to non stationary distribution o...

We study carding shops that sell stolen credit and debit card information online. By bypassing the anti-scrapping mechanisms they use, we find that the prices of cards depend heavily on factors such as the issuing bank, country of origin, and whether the card can be used in brick-and-mortar stores or not. Almost 70% of cards sold by these outfits are priced at or below the cost banks incur in r...

We introduce a new approach to anomaly detection based on extreme value theory statistics. Our method improves detection accuracy by replacing binary feature thresholds with anomaly scores and by modeling the tail region of the distribution where anomalies occur. It requires no optimization or tuning and provides insights into results. This work describes the Extreme Value Theory-Anomaly Detect...

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...

To deal with credit card fraud, a detection model based on Class Weighted Support Vector Machine was established. Due to large-scale and high dimensions of data, Principal Component Analysis (PCA) was adopted firstly to screen out the main factors from a great deal of indicative attributes in order to reduce the training dimension of SVM effectively. Then according to the characteristics of cre...

This research examines whether temporal orientation moderates the impact of compulsive buying tendencies (CBT) on credit card debt. Participants completed the consideration of future consequences scale, a compulsive buying scale, and reported their credit card debt. Results revealed that CBT mediated the relationship between concern with immediate consequences and credit card debt, and high con...

Substantial losses from credit card fraud are forcing retail industry executives to reevaluate the effectiveness of their ability to prevent this type of crime. In 1992, management at Tops Appliance City Inc. decided to reassess its own fraud prevention program in an attempt to prevent future losses. An analysis of the Tops' problem pointed out the need to differentiate legitimate from illegiti...

A hybrid influence diagram is a compact graphical and numerical representation of a decision problem under uncertainty that includes both discrete and continuous chance variables. These models can be used by businesses to detect online credit card transactions that may be fraudulent. By creating decision rules based on merchandise value and additional address and product characteristics, the in...