"Generative AI and Identity Fraud"

Content
5 modules

Rating

Course length
2 hours

Instructor
Caroline Smith

Released
18 Dec 2025

Price
Free

Description

The Generative AI and Identity Fraud course explores the growing intersection between advanced generative technologies and evolving identity-based fraud threats. As fraudsters adopt AI-powered tools to create realistic fake identities, mimic voices and faces, and execute sophisticated social engineering attacks, fraud prevention professionals must adapt rapidly to defend the customer journey.

This course provides a deep dive into the techniques and technologies used to facilitate GenAI-powered identity fraud, including synthetic identity creation, deepfake impersonation, phishing campaigns, and fraudulent websites. Learners will learn how these tools bypass traditional verification systems and how emerging detection methods such as behavioral biometrics, device intelligence, and real-time analytics are evolving in response. The course also examines regulatory and ethical considerations, including transparency, fairness, and AI accountability.

Who Should Enroll?

  • Fraud Prevention and Risk Professionals tasked with protecting customer identity and transaction integrity.
  • Financial Institutions, eCommerce Merchants, and Fintech Platforms seeking to strengthen defenses against GenAI-enabled fraud.
  • Compliance and Regulatory Staff needing awareness of AI-driven risks in KYC, AML, and data privacy frameworks.
  • Analysts and Investigators focused on detecting, mitigating, and preventing identity fraud.

Program Details

  • Program Level: Intermediate
  • Program Field of Study: Specialized Knowledge
  • Program Delivery Method: QAS Self-Study
  • CPE Credits: 1.5
  • Advanced Preparation and/or Pre-requisites: Fraud Essentials is recommended.

For more information regarding any concerns, please email us at [email protected]

Refunds and cancellations are determined on a case-by-case basis. Cancellations and requests for refunds must be communicated in writing to [email protected]. Refunds will not be issued once a course has been started. Additionally, courses must be completed within one year of purchase.

Logo and Guidelines: QAS Self Study - NASBA Registry

Merchant Risk Council is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org 

Course Created: 09/23/2025

 

Objectives

  • Identify how generative AI technologies are being exploited in modern identity fraud schemes.
  • Explain the limitations of traditional fraud detection systems.
  • Describe how generative AI enables new forms of identity fraud.
  • Explain how AI tools enhance account takeover and impersonation tactics.
  • Recognize how generative AI is being used in real-world identity fraud cases.
  • Describe the risks posed by cross-border GenAI-enabled fraud.
  • Identify advanced detection methods for combating GenAIbased identity fraud.
  • Explain the importance of layered authentication strategies and real-time monitoring in defending against AI-enhanced identity threats.
  • Understand the regulatory implications of using AI in fraud detection.
  • Identify compliance risks posed by generative AI and how to align fraud prevention strategies with data privacy, transparency, and legal defensibility
  • Recognize emerging GenAI fraud threats and how LLMs may be weaponized at scale.
  •  Identify tools, training, and strategies to prepare teams and build ethical, adaptive AI defenses.

Certificate

By completing/passing this course, you will attain the certificate MRC Education Certificate of Completion

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Program Materials
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Consent to Information Sharing
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Generative AI and Identity Fraud
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Generative AI and Identity Fraud | Final Exam
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