This course presents a comprehensive vision of fraud investigation and forensic auditing assisted by Artificial Intelligence, combining methodological foundations, evidence analysis and technological techniques applied to the identification, investigation and documentation of possible fraudulent conduct. It starts from the essential concepts of fraud, its elements, warning signs and responsibilities, to develop an orderly investigation methodology based on objectivity, planning, traceability and adequate management of hypotheses and evidence.
The program addresses the collection, preservation and analysis of evidence, including digital evidence and chain of custody, and subsequently incorporates AI tools for anomaly detection, data forensics, intelligent document processing, communications analysis using Natural Language Processing and investigative interview techniques. It also develops the analysis of financial and accounting frauds, including identification of unusual transactions, relationships, conflicts of interest and complex schemes.
A core component is the practical and responsible use of AI: generative AI, prompt engineering, automation, network visualization, continuous monitoring, and analysis of large volumes of information. The course further incorporates the new threats associated with deepfakes and examines the governance, ethics, privacy, transparency, explainability, and human oversight required to use these technologies safely.
