Government agencies face increasingly sophisticated security challenges in a world driven by digital transformation.

Abstract: Credit card fraud detection remains a critical challenge in the financial industry, demanding robust, scalable, and adaptive solutions. This paper explores the existing research landscape, ...

Abstract: In online advertising, click fraud poses a significant challenge, draining budgets and threatening the industry’s integrity by redirecting funds away from legitimate advertisers. Despite ...

Retailers are implementing AI through software companies like Happy Returns and Narvar to detect return fraud and issue ...

A Data Science and Machine Learning project for detecting fraudulent financial transactions using customer behavior analysis and classification models. - ...

Archer Materials (ASX: AXE) has completed the next stage of its quantum machine learning (QML) fraud detection project after successfully testing and benchmarking a quantum neural network (QNN) model ...

Fraud Detection in Banking is a Machine Learning project that identifies fraudulent transactions using historical banking data. It applies data preprocessing, exploratory data analysis, and a Random ...

Deepfake fraud attempts jumped more than 1,300% in 2024 according to Pindrop’s analysis of 1.2 billion calls, moving fro ...

Revolut just built what might be the most ambitious AI model purpose-built for banking. Called PRAGMA, short for PRe-trained Banking Foundation Model, it’s a series of transformer-based models ...

DataVisor, the AI-native real-time decisioning platform for fraud and financial crime prevention, today announced that its customer, NASA Federal Credit Union (NASA FCU), won the Celent Model Risk ...

Artificial Intelligence and Machine Learning are among the most discussed buzzwords in the realm of technology in contemporary times. The applications of these technologies range from voice assistance ...