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

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

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 ...

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.

Today’s fast-paced online world is underlined by systems that allow it to move that fast. Whether it’s the latest advancements to transport systems, faster internet connections, or more real-time ...

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

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.

The financial sector is anticipated to experience a notable surge in fraudulent activities, leading to projected losses exceeding $40 billion by 2027. This increase marks a significant uptick from ...

RIZAL Commercial Banking Corporation (RCBC) has strengthened its fraud detection and cyber risk management systems as ...

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