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, ...

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

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 ...

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 ...

In today’s digital world, fraud has become more complex, which means we need smarter ways to detect and prevent it. Generative AI helps with this by looking at large amounts of data in real-time, ...

AI has been used to defraud people through everything from calling voters to faking celebrity giveaways. Now, the US Treasury Department claims machine learning AI has played a critical part in its ...

Mastercard is using AI to help detect and prevent credit card fraud. The company says the tech can flag unusual patterns and block fraudulent transactions. This article is part of "AI in Action," a ...

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

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...