Risk Management: Internal Controls & Fraud Prevention - Part 3 Webinar

To provide CPAs and other finance professionals with a practical understanding of AI-related risks and third-party considerations, enabling them to strengthen risk oversight, evaluate emerging threats, and support effective governance in technology-driven environments.

• The intersection of risk management and AI, including:
  – Foundation models
  – Generative AI
  – Agentic AI
• Third party risks and SOC reports
• The convergence of cyber risks and AI in 2026

Rosemary Ferrero, CPA

To provide CPAs and other finance professionals with a practical understanding of AI-related risks and third-party considerations, enabling them to strengthen risk oversight, evaluate emerging threats, and support effective governance in technology-driven environments.

DETAILED LEARNING OBJECTIVES

• Understand the role and structure of AI foundation models

• Evaluate key considerations when selecting AI models

• Identify risks associated with third-party AI vendors

• Differentiate levels of AI risk tolerance and implementation approaches

• Understand characteristics of agentic AI systems

• Recognize challenges in monitoring complex AI systems

• Identify benefits of AI in risk management and fraud detection

• Understand AI applications in predictive modeling and anomaly detection

• Recognize limitations of AI including data silos and integration challenges

• Evaluate ethical and transparency concerns in AI systems

• Understand components of third-party risk management programs

• Identify tools used to assess third-party controls including SOC reports

• Differentiate between SOC 1 and SOC 2 reports

• Understand enhancements introduced under SSAE 18

• Recognize trust services criteria used in SOC 2 reporting

• Identify key categories such as security, availability, and confidentiality

• Understand emerging AI-related cyber threats such as prompt injection

• Recognize risks associated with data poisoning in AI systems

• Evaluate risks posed by adversarial AI technologies

• Understand vendor dependency and lock-in risks

• Assess the intersection of AI and cybersecurity risk management

• Recognize the importance of governance across the AI lifecycle

• Understand monitoring and control requirements for AI-driven systems

• Evaluate enterprise risks arising from AI adoption

• The intersection of risk management and AI, including:
  – Foundation models
  – Generative AI
  – Agentic AI
• Third party risks and SOC reports
• The convergence of cyber risks and AI in 2026

Rosemary Ferrero, CPA