Fraud investigation is entering a new operating reality. Evidence volumes have outgrown manual review, schemes now run through digital channels at machine speed, and the investigator who cannot deploy AI across the case lifecycle works slower, sees less and reports later than the fraud demands. This two-day programme takes you through the complete AI-enabled investigation lifecycle, from allegation intake and triage through planning, evidence collection, document and transaction analysis, interviews, evidence evaluation and defensible reporting. You work hands-on with AI at every stage: extracting facts from whistleblower complaints, generating testable fraud hypotheses, mapping collusion networks, pressure-testing findings against alternative explanations and converting case files into board-ready reports. The programme closes with the governance layer that makes all of this defensible, covering data privacy, legal privilege, evidence admissibility, hallucination risk and the professional scepticism required to keep human judgement in command of the machine.

Learning Objectives

* Explain how artificial intelligence can support the complete fraud investigation lifecycle.
* Use AI to assess allegations, develop investigation plans and prioritise investigative activities.
* Apply AI tools to analyse documents, transactions, communications and digital evidence.
* Use generative AI to support interviews, evidence evaluation and case analysis.
* Identify legal, ethical, privacy and evidentiary risks associated with AI-assisted investigations.
* Produce clear, evidence-based investigation reports using AI while maintaining professional judgement.