Social Media (SM) are the most widespread and rapid data generation applications on the
Internet increase the study of these data. However, the efficient processing of such massive …

Credit risk is the risk of financial loss when a borrower fails to meet the financial commitment.
While there are many factors that constitute credit risk, due diligence while giving loan (credit …

Detecting frauds in credit card transactions is perhaps one of the best testbeds for
computational intelligence algorithms. In fact, this problem involves a number of relevant …

Supervised learning techniques are widely employed in credit card fraud detection, as they
make use of the assumption that fraudulent patterns can be learned from an analysis of past …

Due to the growing volume of electronic payments, the monetary strain of credit-card fraud is
turning into a substantial challenge for financial institutions and service providers, thus …

Credit card fraud events take place frequently and then result in huge financial losses.
Criminals can use some technologies such as Trojan or Phishing to steal the information of …

In order to improve the performance of any machine learning model, it is important to focus
more on the data itself instead of continuously develo** new algorithms. This is exactly the …

Abstract The Data Big Bang that the development of the ICTs has raised is providing us with
a stream of fresh and digitized data related to how people, companies and other …

This study proposes a framework for fraud detection in the auto insurance industry by using
predictive models. The feature selection is performed utilizing a publicly available car …

Every year billions of Euros are lost worldwide due to credit card fraud. Thus, forcing
financial institutions to continuously improve their fraud detection systems. In recent years …