The emergence and continued reliance on the Internet and related technologies has
resulted in the generation of large amounts of data that can be made available for analyses …

Credit risk assessment is a crucial element in credit risk management. With the extensive
research on consumer credit risk assessment in recent decades, the abundance of literature …

With the continuous emergence of various network attacks, it is becoming more and more
important to ensure the security of the network. Intrusion detection, as one of the important …

Data augmentation is an important procedure in deep learning. GAN-based data
augmentation can be utilized in many domains. For instance, in the credit card fraud domain …

The existence of class imbalance in a dataset can greatly bias the classifier towards majority
classification. This discrepancy can pose a serious problem for deep learning models, which …

Customer credit scoring is a dynamic interactive process. Simply designing the static reward
function for deep reinforcement learning may be difficult to guide an agent to adapt to the …

The expanding availability of data in the financial sector promises to take the performance of
machine learning models to a new level. However, given the high business value and …

Automatic credit scoring, a crucial risk management tool for banks and financial institutes,
has attracted much attention in the past few decades. As such, various approaches have …

The goal of credit scoring is to identify abnormalities, aiding decision making and
maintaining the order of financial transactions. Due to the small number of default records …

Credit scoring is an effective tool for banks or lending institutions to identify potential bad
lenders and creditworthy applicants. Boosting ensemble approaches have made appealing …