ML tailors banking solutions by analyzing transactions, spending habits, and financial goals. It detects fraud in real time, adapts to threats, and verifies customer identity behaviorally. AI chatbots ...

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

The surge in digital payments and mobile banking has transformed financial services but it has also expanded the fraud landscape. Traditional, rule-based fraud detection methods are increasingly ...

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

Database design and management are essential pillars of success in the financial sector, where efficient data handling and adherence to regulatory standards are critical. The global market for ...

Traditional rule-based systems, once sufficient for detecting simple patterns of fraud, have been overwhelmed by the scale, ...

Swift is planning to roll out new AI-enhanced fraud detection for the global payments industry. It will be available in January 2025. The new capability builds on Swift’s existing Payment Controls ...

Fraud and financial crime remain a significant challenge for UK businesses in 2025. From banks and fintech’s to retailers and telecom providers, organisations are working hard to stay ahead of ...