Fraudsters are adapting at machine speed. So why does it still take financial institutions months to deploy new defenses? In this episode of What the F Happened? Fraud and Financial Crime Deconstructed, we explore how agentic AI is closing that gap and changing how fraud and AML solutions are built and deployed.

We dive into how DataVisor’s Vera Code can help organizations:

• Turn requirements into end-to-end fraud and AML solutions

• Build rules, decision flows, and investigator workflows faster

• Adapt defenses as new threats emerge

• Keep human experts in control with transparent, governed AI

The result? Faster deployment, faster adaptation, and more time for fraud teams to focus on stopping criminals—not configuring systems.

Read the blog and the playbook to learn how agentic AI is transforming fraud and AML deployment.

Blog - Introducing Vera Code: The AI Agent That Builds Complete Fraud And AML Programs In Days

Playbook -
Use AI To Deploy Fraud & AML Solutions In Days, Not Months

AI agents are moving beyond chatbots. They can now navigate websites, complete forms, and initiate financial transactions; creating a new challenge for financial institutions: how do you know whether a person or an AI agent is behind a high-value digital interaction?

In this episode of What the F Happened? Fraud and Financial Crime Deconstructed, we explore how behavioral intelligence can help distinguish humans from AI agents and protect digital financial experiences without blocking legitimate automation.

We discuss how modern AI-agent detection can help organizations:

• Identify AI-driven activity through behavioral patterns rather than traditional device fingerprints

• Analyze mouse movements, keystrokes, and other behavioral signals while preserving user privacy

• Distinguish between legitimate customer-approved AI agents and malicious automated activity

• Use behavioral scores as a risk signal to apply the right level of friction at the right time

• Combine AI-agent detection with real-time risk intelligence to prevent account takeover and automated fraud

The key takeaway: as AI agents become part of everyday digital and financial interactions, security systems need to understand not just who is connecting, but how they are behaving.

Want to go deeper? Read the blog to learn how real-time decisioning can help financial institutions detect and stop fraud before the money moves.

Fraud moves in milliseconds. Financial institutions need to make risk decisions just as fast.

In this episode of What the F Happened? Fraud and Financial Crime Deconstructed, we explore the technology and strategies behind real-time decisioning, and how banks can detect and stop fraud before a transaction is completed.

We discuss how modern fraud prevention helps organizations:

• Make risk decisions in milliseconds across instant payment channels

• Combine real-time data enrichment, rules, and machine learning for faster, more accurate detection

• Use unsupervised machine learning to identify coordinated and previously unknown fraud patterns

• Bring fraud and AML intelligence together through shared data and separate workflows

• Modernize fraud prevention with a practical 90-day approach while maintaining governance and explainability

The key takeaway: real-time fraud prevention isn't just about speed. It's about combining intelligence, resilient infrastructure, and strong governance to protect customers without creating unnecessary friction.

Want to go deeper? Explore the accompanying resources and learn how financial institutions can modernize real-time decisioning to prevent fraud before the money moves.

• The Real-Time Decisioning Playbook
• Top 10 Real-Time Decisioning Platforms For Fraud And AML In 2026

• ⁠DEFEND Training