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 ...

The survey polled 88 financial crime professionals, confirm that AI is no longer a fringe technology but a foundational element ...

Although AI has introduced a new threat in the world of payments fraud, it has also emerged as the analytical backbone of next-generation fraud mitigation systems.

Launching a digital wallet today involves far more than enabling payments. As the digital wallet trends 2026 show high adoption of digital wallets, so do the challenges like increasingly sophisticated ...

In the fast-moving digital landscape, where gig workers expect instant payouts and companies handle millions of microtransactions daily, the need for robust real-time fraud detection has never been ...

Artificial intelligence (AI), like any technology, can be misused. Malicious actors intent on committing fraud can use AI to create more realistic deceptions at a much faster clip. How has the threat ...

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, ...

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

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, ...