Research published in the International Journal of Information and Communication Technology suggests that machine learning tools might be used to detect and so combat financial fraud. According to ...

Overview: AI in financial services uses machine learning and automation to analyze data in real time, improving speed, accuracy, and decision-making across bank ...

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...

The review reports that blockchain-enhanced federated learning systems typically achieve slightly lower raw accuracy than ...

Kinil Doshi is a Senior VP at Citibank and a fintech expert in banking compliance and risk management with two decades of experience. In this article, I want to explore AI applications in fraud ...

Fighting fraud is like playing a game of cat and mouse. But what if the 'mouse' could learn the cat's every move? Machine learning in fraud detection creates a system that constantly gets better at ...

Abstract: Fraud in supply chain operations poses significant risks to businesses, including financial losses, operational inefficiencies, and erosion of stakeholder trust. With the increasing ...

AI continues to gain momentum, and according to a recent report by Accenture, the technology is predicted to add $1.2 trillion in value to the financial sector by 2035. As the head of a platform that ...

The Fast Company Executive Board is a private, fee-based network of influential leaders, experts, executives, and entrepreneurs who share their insights with our audience. BY Matt Swann The rise of ...

Fraud detection is a high-stakes game of cat and mouse, with retail businesses continually adapting to outsmart increasingly sophisticated fraudsters. As ecommerce losses from online payment fraud ...