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

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

Research published in the International Journal of Information and Communication Technology suggests that machine learning tools might be used to detect and so combat financial fraud. According to ...

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, ...

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 ...

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

Fighting fraud is like playing a game of cat and mouse. But what if the 'mouse' could learn the cat's every move? Machine learning in fraud detection creates a system that constantly gets better at ...

Fraud detection is a high-stakes game of cat and mouse, with retail businesses continually adapting to outsmart increasingly sophisticated fraudsters. As ecommerce losses from online payment fraud ...