Using AI in a Fraud Investigation – 2026 Update- A/V​

CPE Credit: 2 hours

This course is designed for professionals who want to integrate artificial intelligence technologies into fraud investigation practices. Whether you're in financial auditing, internal auditing or forensic accounting, this course will enhance your skills in detecting, analyzing, and combating fraudulent activities using AI tools. Learn how to harness big data analytics and machine learning algorithms to spot inconsistencies and irregularities in data. This course will include real world applications for the participants to discuss. Join us for an insightful journey into the world of AI-driven fraud investigation and stay ahead in the ever-evolving landscape of fraud prevention. 

Learning Objectives:

Upon completing this course, participants will be able to:

1. Explain the role of artificial intelligence in fraud examinations, including its capabilities, limitations, and relationship to professional judgment throughout the investigative process.

2. Differentiate between appropriate and inappropriate applications of AI during fraud investigations, including data collection, anomaly detection, document analysis, interview preparation, predictive analytics, and link analysis.

3. Apply fraud examination principles to determine when AI-generated information should be corroborated through traditional investigative procedures, documentary evidence, and professional skepticism.

4. Evaluate the legal and evidentiary considerations associated with AI-assisted fraud investigations, including authentication, admissibility, chain of custody, transparency, explainability, and expert witness responsibilities.

5. Identify governance, privacy, cybersecurity, and ethical risks associated with the use of AI in fraud investigations, including data quality, model bias, AI hallucinations, confidential information, and AI poisoning.

6. Recognize practical methods for documenting, validating, and defending AI-assisted investigative procedures in depositions, expert reports, and courtroom testimony.

7. Assess emerging trends in AI-enabled fraud schemes and the corresponding investigative techniques organizations can use to strengthen fraud prevention, detection, and response.