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

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, ...

“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 ...

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 ...

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

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 ...

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 ...

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

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 ...