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

“Fraud detection today is about precision, not just protection. The ability to differentiate legitimate customers from ...

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

TransUnion LLC has introduced a major upgrade to its Device Risk fraud-detection platform, adding new capabilities designed ...

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, ...

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 ...

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

Srinubabu Kilaru said Bringing version control and CI/CD into data pipelines changed how quickly we could respond to policy ...

Fraud detection is no longer enough to protect today’s financial ecosystem. As digital transactions increase, banks require ...

Discover the 7 best fraud detection systems for enterprises in 2025. Learn about their features, pricing, and how they help combat digital and identity fraud in the ever-evolving threat landscape.

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 ...