Targeting fraud today: a real-time, integrated approach

How can banks detect fraud before a payment is authorised? And how can they keep pace with increasingly sophisticated artificial intelligence-enabled attacks? Fraudsters are exploiting fragmented systems, real-time payments and AI-powered tactics to evade traditional controls. But many institutions still rely on reactive, rules-based approaches that struggle to identify threats before losses occur.

This Chartis/INETCO case study explores how a tier two bank transformed its fraud strategy, moving from siloed monitoring to real-time, AI-driven detection and prevention.

Key insights include:

• Why traditional fraud controls are struggling against modern attack techniques
• How real-time transaction intelligence can improve detection and reduce false positives
• How one bank used AI-driven fraud prevention to stop high-risk transactions before losses occurred.

This tier two bank case study makes intriguing reading for fraud, financial crime and payments leaders, risk managers and technology teams responsible for fraud prevention.

Download the case study to learn how leading institutions are adapting to the next generation of fraud threats.