Role-Based Programme
RB1696

AI-Powered Fraud Risk & Financial Crime

Smarter Detection, Investigation Support & Control Monitoring

IMAGE REQUIRED
Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how AI can support Fraud Risk and Financial Crime activities across risk identification, alert review, investigation support, control monitoring, and reporting.
  • Explore practical prompting techniques for reviewing suspicious patterns, analysing case information, summarising evidence, and preparing structured risk outputs.
  • Apply AI to organise fraud-related information, identify anomalies and recurring patterns, and support case documentation.
  • Identify opportunities to improve review efficiency, consistency, issue visibility, and risk-monitoring effectiveness.
  • Recognise confidentiality, evidence quality, legal and regulatory requirements, data privacy, and human-review responsibilities when using AI.

Tools covered

Generative AI AssistantsAI-Assisted Risk AnalysisDocument IntelligenceSpreadsheet AnalysisAnomaly ReviewCase SummarisationControl MonitoringBasic Workflow Automation

Who should attend

  • Fraud Risk Analysts
  • Fraud Prevention Executives
  • Financial Crime Analysts
  • Internal Auditors
  • Risk Analysts
  • Operational Risk Professionals
  • Compliance Professionals
  • AML Support Professionals
  • Investigation Support Professionals
  • Control Assurance Professionals
  • Risk Managers
  • Audit Managers
  • Fraud & Financial Crime Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of fraud risk, financial crime, audit, compliance, or risk-management processes
  • Familiarity with transactions, case reviews, controls, alerts, or investigation documentation is helpful
  • Basic computer and spreadsheet skills
  • No AI or programming knowledge required
  • No previous Generative AI experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to fraud-risk and financial-crime functions
  • Identifying AI applications across detection support, alert review, case analysis, documentation, and reporting
  • Understanding AI assistance versus investigator, auditor, compliance, and risk-professional judgement
  • Recognising activities where evidence, legal requirements, and human validation remain mandatory
Practical activities
  • Mapping common Fraud Risk and Financial Crime activities to potential AI applications
  • Comparing a traditional case-review task with an AI-assisted approach

Scenarios

Transaction Anomalies to Fraud-Risk Review

Transaction Data → AI-Assisted Pattern Review → Red Flags → Context Check → Control Review → Escalation Summary

Participants use AI to review sample transaction information, identify unusual patterns, organise relevant facts, and prepare a structured escalation summary without treating anomalies as proof of wrongdoing.

Fraud Case Information to Management Brief

Case Notes + Supporting Documents → AI Summarisation → Chronology → Evidence Gaps → Key Risks → Actions → Management Brief

Participants use AI to organise a sample fraud case, structure the chronology, identify missing information, and prepare a concise management-ready brief while retaining all investigative conclusions with authorised professionals.

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