Outsmarting Fraud in the Age of AI: Highlights from Microblink’s Panel at Money 20/20
Money 20/20 USA in Las Vegas is well underway, and Microblink was proud to help kick the event off with a panel that brought some of the brightest minds in fraud prevention together. Titled “The Hateful Eight: Obstacles to Fraud and Their Solutions” (Shout out to all you Tarantino fans out there!) the session explored how modern fraud has evolved and how companies are responding with smarter, AI-driven strategies. Moderated by our CEO Hartley Thompson III, the panel included Kelley Andersen, Senior Director of Product at Microsoft, Yuliya Kazakevich, Global Head of Merchant Risk for CashApp and Lyanna Liu, Senior Manager, Risk Management at SoFi.
Below are some of the key takeaways from the panel.
Building Trust and Speed in Payments
The panel opened by framing the challenge of how to balance speed and trust in high-volume payment networks. One key strategy discussed for designing merchant onboarding processes is to allow low-risk merchants to move quickly while applying friction to risky actors. On the consumer side, they emphasized tools such as in-app scam warnings and other proactive measures to help detect and prevent fraud before it happens. Looking ahead, the discussion highlighted the importance of building trustworthy ecosystems and expanding AI capabilities to protect both merchants and consumers.
Scaling Fraud Prevention Across Ecosystems
Participants also discussed how companies can leverage data and AI to build proactive, scalable fraud prevention ecosystems, focusing on both monetary and non-monetary activity. By combining machine learning, self-serve recovery processes, and cross-platform intelligence, organizations can reuse successful strategies across products and fraud types, creating a cohesive, long-term approach to fraud prevention.
AI: Both a Tool and a Threat
Another key theme was AI’s dual role in payments: it enables faster fraud detection but at the same time also empowers fraudsters. From deepfakes to synthetic identities and fake storefronts, AI can accelerate fraudulent activities. Companies are countering this by using AI to detect AI, employing explainable, transparent, and fair systems that prioritize accuracy and trust over speed. AI can help verify merchants, spot inconsistencies, and generate actionable insights, allowing human teams to focus on higher-risk cases.
Managing Risk Across Payment Methods
Emerging payment types like Buy Now, Pay Later (BNPL) and digital wallets bring layered risks, including credit risk, consumer fraud, and merchant fraud. Effective mitigation relies on sharing data across ecosystems to link merchant and consumer signals, detect collusion, and prevent fraud before it escalates.
Lessons in Scaling and Strategy
The panel highlighted key strategies for building fraud teams that remain proactive, flexible, and data-driven. These include:
- Clearly defining mission and KPIs to focus resources on what matters most.
- Encouraging cross-functional collaboration across data science, engineering, product management, and operations.
- Building flexible systems that can accommodate new vendors, products, and threats.
- Fostering a culture of continuous learning and human oversight to adapt to evolving fraud tactics.
The Human Element Matters
While AI is undoubtedly a key aspect of modern fraud prevention, the discussion emphasized the importance of continuous human feedback. Every onboarding event, transaction, and decision should feed into the next cycle of learning, ensuring systems evolve alongside emerging threats.
The panel reinforced that fraud prevention is both a science and an ecosystem exercise. Organizations that combine AI, cross-ecosystem data sharing, and human judgment are better positioned to outsmart increasingly sophisticated fraudsters while keeping legitimate users moving smoothly through digital payment systems. To learn more about how Microblink can play a role in helping your organization secure transactions and fight fraud, get in touch today.
