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 machine learning breakthrough outperforms traditional methods by reducing false positives and minimizing cases needing further inspection, crucial for sectors like Medicare and credit card fraud ...

Kinil Doshi is a Senior VP at Citibank and a fintech expert in banking compliance and risk management with two decades of experience. In this article, I want to explore AI applications in fraud ...

Launching a digital wallet today involves far more than enabling payments. As the digital wallet trends 2026 show high adoption of digital wallets, so do the challenges like increasingly sophisticated ...

The evolution of telecommunication technologies not only enhances social interactions but also inadvertently fosters an environment for telecom fraud. Graph-like data generated from traceable ...

Customs revenue represents a major source of funding for most governments. Accordingly, customs administrations worldwide have promoted advanced analytics techniques to detect fraud and enhance ...

Quick Summary Looking to detect and prevent financial and digital fraud more effectively? Discover the 7 best fraud detection systems for enterprises in 2026 that leverage advanced analytics, machine ...

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

In an era where insurance fraud drains billions from the global economy annually, a groundbreaking study by researchers Chetan Sasidhar Ravi introduces advanced hybrid machine learning (ML) techniques ...

Services Australia is trialling machine learning to detect potential instances of identity theft affecting Centrelink customers, with the goal of stopping payments from being rerouted. The agency was ...