In efforts to help assist financial companies and auditors, two Virginia Tech professors are developing software that will allow for a more advanced way to detect fraud. other information, can raise ...

Fraud detection already relies heavily on non-financial signals such as IP address, device fingerprinting, geolocation and behavioural biometrics. When linked with AML monitoring, these signals become ...

DataVisor, the world's leading AI-powered fraud and risk management platform, released its 2026 Fraud & AML Executive Report, revealing an AI Readiness Gap between rising concern over AI-driven fraud ...

In today’s rapidly evolving digital landscape, fraud and financial crime have become increasingly complex and create pervasive issues for organizations of all sizes and specialties. As a result, ...

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 ...

What’s driving the rise in digital fraud? The global payments landscape appears more dynamic and complex than ever before. As e-commerce spending accelerates toward an estimated $8.1 trillion by 2028, ...

Deepfake and continuous identity protection programs must therefore be framed not as experimental controls, but as ROI-driven investments.

The most convincing media you see online could be an AI-generated fake. Last May, nefarious marketers used deepfake tech to steal the likenesses of famous people, running ads online and making it ...

With AI technology, payment fraud and fraud prevention have become more complex and sophisticated. Both financial data owners and businesses that accept illegal payments are directly affected by ...

HHS’ Office of the Inspector General has issued a report urging CMS to develop a set of best practices for its Medicare contractors on detecting fraud associated with electronic health records. The ...