A new academic study argues that fraud detection systems must evolve beyond accuracy-focused prediction tools into ...

“Fraud detection today is about precision, not just protection. The ability to differentiate legitimate customers from suspicious activity in milliseconds is what separates high-performing businesses ...

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

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

A surge in digital payment technologies has been paralleled by an equally rapid increase in credit card fraud. This research field explores multifaceted approaches that combine advanced analytics, ...

Overview: AI-powered fraud detection tools are rapidly being adopted by banks and fintechs to block scams and reduce losses.New platforms combine machine learni ...

Fraud detection is no longer enough to protect today’s financial ecosystem. As digital transactions increase, banks require systems that can assess risk with precision.

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

Ravelin, a machine learning fraud detection company based in London, has raised approximately $3.7 million (£3M) in funding to support its growing global client base. The finance round was led by ...

This raises the question: is TransUnion poised for further growth, or has the market already accounted for its potential? TransUnion's recent upgrade arrives at a pivotal moment, with many analysts ...