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

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

“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 ...

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 ...

The Federal Reserve is racing to contain a new kind of systemic risk, one that does not start with bad loans or exotic ...

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

Proactive monitoring tools, such as a third-party hotline platform and data analytics, coupled with employee engagement and a ...

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.

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 ...