AI Strategies Against Fraud and Scams

Jun 3, 2025

Lecture on Combating Fraud and Scams with Artificial Intelligence

Introduction

  • Presenter: Aaron Klene, Miriam K. Carliner Chair and Senior Fellow in Economic Studies
  • Focus: Use of artificial intelligence (AI) to combat fraud and scams
  • Personal anecdote: Experienced a scam with fake tickets at a Grateful Dead show
  • Context: Transition from physical to electronic fraud with the rise of electronic money and transactions
  • Objective: Protect vulnerable individuals (e.g., parents) and enhance system efficiency

Panelists

  1. Brian Boats

    • Title: Risk Lead at Block
    • Focus: Machine learning and AI in risk management

  2. Kip Wayne Scott

    • Title: Executive Director of Global AI Policy at JP Morgan Chase
    • Focus: Integration of AI in fraud prevention

  3. Kelly Thompson Cochran

    • Title: Deputy Director and Chief Program Officer of Finreg Labs
    • Focus: Research on fraud, scams, and AI

Key Points Discussed

Nature of Fraud and Scams

  • Fraud and scams are age-old problems, evolving with technology
  • Scammers are using sophisticated methods, including generative AI for fake documents
  • Need to stay ahead with technology, as it is a cat-and-mouse game

AI in Fraud Detection

  • Brian Boats: Block utilizes AI and machine learning for real-time scam detection

    • Issue targeted warnings to consumers
    • High effectiveness in scam prevention

  • Kip Wayne Scott: Importance of AI in scaling fraud detection across financial institutions

    • Collaborative efforts (e.g., National Fraud and Scams Prevention Task Force)

Challenges in Fraud Detection

  • Kelly Thompson Cochran: Difficulty in scams due to consumer belief in legitimacy
  • AI Role: Identifying patterns, anomaly detection, and distinguishing fraud from scams
  • Policy frameworks often lag behind evolving technology

Consumer Role and Responsibility

  • Educating consumers about scams
  • Implementing systems to allow reporting and reimbursement (e.g., Cash App)

Regulatory and Policy Implications

  • Existing frameworks (e.g., EFTA, Reg E) do not fully align with current challenges
  • Importance of federal involvement and holistic ecosystem approach
  • Need for updated policy enabling technology-driven solutions

Feedback Mechanisms

  • Leveraging consumer reports to improve AI model training
  • Enhancing fraud detection by reducing false positives and improving information sharing

Future Directions

  • Privacy and Consent: Balancing consumer privacy with fraud prevention
    • Consumers' stated versus revealed preferences
  • Regulatory Improvements: Need for cross-sectoral standards and improved collaboration

Conclusion

  • Takeaway: Continuous adaptation and vigilance are key to combating fraud
  • Emphasis on both technological and policy advancements to protect consumers
  • Encouragement for ongoing collaboration among stakeholders

These notes provide a comprehensive overview of the discussion on using AI to combat fraud and scams, highlighting the perspectives of different experts and the implications for policy and practice.

Full transcript