AI is giving fraudsters a powerful new playbook. From cloning voices and creating synthetic identities to deploying autonomous scam agents, criminals are using increasingly sophisticated tools to scale financial crime and bypass traditional defenses.

In this episode of What the F Happened? Fraud and Financial Crime Deconstructed, we explore how AI is transforming fraud and what financial institutions need to do to stay ahead.

In this episode, we cover:

• How AI-powered scams use deepfakes, voice cloning, and social engineering.

• How synthetic identities and fake documents bypass KYC checks.

• How agentic AI enables large-scale, automated fraud operations.

• Why traditional identity verification is no longer enough.

• How behavioral analytics, device intelligence, and graph analysis strengthen fraud prevention.

Tune in to understand the evolving threat landscape and what it takes to fight back.

E-book: AI Tools Fraudsters Use In 2026

Defend Training: https://www.datavisor.com/defend-training/

Fraud is no longer moving at human speed. As fraudsters deploy AI agents that can adapt, evade defenses, and attack at machine speed, financial institutions are turning to AI to fight back.

In this episode of What the F Happened? Fraud and Financial Crime Deconstructed, we explore the new AI arms race in financial crime; from sub-30-millisecond fraud decisions to agentic attacks that can change tactics in real time. We also look at how DataVisor’s Vera Code can rapidly build and adapt fraud and AML defenses, while dEdge uses device intelligence and behavioral signals to distinguish real humans from AI agents.

The result? A new approach to fraud prevention where defenses can evolve as quickly as the threats themselves.

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

Financial crime is entering a new era where AI agents can operate at machine speed and fraudsters and defenders are increasingly using AI against each other.

In this episode of 'What the F Happened? Fraud and Financial Crime Deconstructed', we explore:

• How AI agents automate fraud, from reconnaissance and synthetic identities to social engineering and stolen funds.

• Why polymorphic attacks and adaptive AI are making traditional, rule-based defenses less effective.

• How financial institutions can redesign fraud and AML workflows around AI agents and real-time detection.

• What the future of AI vs. AI means for fraud prevention, digital identity, and financial security.

Read the Blog and watch the Webinar for more insights on Agentic AI attacks.

• The Fraud And AML Guide To Agentic AI Attacks

• DEFEND WEBINAR | Agentic AI In Action: The Playbook From Best-Performing Fraud And Risk Teams

• ⁠DEFEND Training
  

As financial institutions put AI agents to work across fraud and AML, regulators will want to know more than what the technology can do. Can you explain its decisions, prove it was properly tested, reconstruct what happened, and show where human accountability begins and ends?

We break down the governance questions CROs and CCOs need to address as agentic AI takes on more responsibility, including levels of autonomy, human oversight, explainability, audit trails, and what it takes to make AI-driven decisions defensible.

Go deeper:

• The CRO & CCO’s Guide to Agentic AI
  https://www.datavisor.com/intelligence-center/ebooks/the-cro-cco-guide-to-agentic-ai

• What CROs & CCOs Need to Know About Agentic AI
  https://www.datavisor.com/blog/what-cro-cco-need-to-know-about-agentic-ai

Chapters

00:00 The agentic AI governance challenge
02:45 Why traditional governance falls short
04:53 When AI risks compound
07:23 Five levels of AI autonomy
10:30 The explainability problem
11:09 How AI explanations fail
12:51 From signal to evidence
13:37 The Plain English Test
14:56 Building an exam-ready audit trail
16:30 Why human overrides matter
17:36 Governance by design
18:10 Knowledge Graphs and evidence
19:03 Governing a digital workforce
20:10 The risk of automation bias

Fraud happens in real time. Your fraud prevention needs to keep up.

In this episode of What the F Happened? Fraud and Financial Crime Deconstructed, we explore what it takes for financial institutions to make fast, intelligent fraud decisions without adding friction for legitimate customers or compromising security.

From processing thousands of transactions per second to connecting risk signals across payment channels, we break down how modern fraud prevention infrastructure helps organizations:

• Make real-time risk decisions at enterprise scale

• Detect suspicious behavior as it happens, not after the damage is done

• Connect risk signals across cards, ACH, wires, RTP, wallets, and P2P

• Maintain performance during transaction spikes and coordinated attacks

• Balance stronger fraud prevention with a seamless customer experience

The takeaway? Effective real-time fraud prevention isn't just about having a smarter model. It requires an infrastructure built to deliver speed, intelligence, and resilience when it matters most.

Explore the accompanying blog and ebook for a closer look at the strategies and infrastructure behind high-speed fraud prevention.

High Speed Fraud Prevention At Enterprise Scale

High Speed Fraud Prevention