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, ...

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

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 ...

A surge in digital payment technologies has been paralleled by an equally rapid increase in credit card fraud. This research field explores multifaceted approaches that combine advanced analytics, ...

Digitalisation has rapidly changed the face of industry and business. Businesses have increasingly integrated modern technologies into their operations to improve real-time activity. However, ...

Srinubabu Kilaru said Bringing version control and CI/CD into data pipelines changed how quickly we could respond to policy ...

Rodney Drake, Chief Strategy Officer at Valid Systems, advocates AI-powered risk and fraud solutions for FI's and fintechs. Fraud isn’t static. It learns, adapts and evolves just as quickly as the ...

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 ...

With businesses collecting and analyzing vast amounts of data to personalize experiences and improve operations, the need for robust cybersecurity measures has never been greater. However, the more ...

When embedded within a case management framework, Agentic AI can detect subtle anomalies, highlight inconsistencies, and surface patterns traditional systems miss.