Vericent Insights

Rule-based fraud systems generate false positives that cost institutions billions and erode customer trust. Machine learning changes the logic entirely. Here is how.

GDPR, EU AI Act, and fraud detection AI now converge into one compliance challenge. Learn what regulators require, and how privacy-preserving techniques resolve the tension.

Account takeover bypasses passwords entirely. Behavioural anomaly detection flags the attacker before the first fraudulent transaction. See how and why it matters now.

156 jurisdictions now classify fraud as a top money laundering risk. Discover why AML and fraud detection are converging in 2026, and how AI is the integration layer.

Real-time fraud monitoring stops fraud before funds leaves. Batch processing detects it after. In 2026, that timing gap costs your organisation, here is the evidence.

Synthetic identity fraud is becoming a major financial crime risk in 2026. Learn how Graph Neural Networks detect fraud networks that traditional rule engines miss with data, implementation realities, and governance implications.

False positives in fraud detection create hidden operational and customer costs. Learn why AI-driven fraud monitoring is replacing legacy rule-based systems.

The EU AI Act becomes enforceable on 2 August 2026. Learn what fraud detection and compliance teams must do to meet AI governance, transparency, and deployer obligations.

Discover how agentic AI is transforming fraud detection in 2026 through autonomous investigations, adaptive threat response, and AI governance frameworks. Learn the benefits, risks, and compliance strategies financial institutions need to deploy agentic AI securely.

Discover how deepfake fraud is evolving in 2026 and why AI anomaly detection is becoming the last line of defence against synthetic identity fraud and AI-powered cyber threats.