Role-Based Programme
RB1672

AI-Powered Operational Risk

Smarter Risk Identification, Control Monitoring & Incident Analysis

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

Programme Objectives

  • Understand how AI can support Operational Risk activities across risk identification, incident analysis, control review, monitoring, and reporting.
  • Explore practical prompting techniques for process-risk assessments, incident summaries, control analysis, root-cause review, and risk documentation.
  • Apply AI to organise operational information, identify recurring patterns, and prepare structured risk-management outputs.
  • Identify opportunities to improve risk visibility, documentation quality, issue tracking, and operational-risk reporting.
  • Recognise confidentiality, evidence quality, policy requirements, regulatory considerations, and human-review responsibilities when using AI.

Tools covered

Generative AI AssistantsAI-Assisted Risk AnalysisDocument IntelligenceSpreadsheet AnalysisIncident SummarisationControl ReviewRisk Register SupportBasic Workflow Automation

Who should attend

  • Operational Risk Analysts
  • Risk Analysts
  • Operational Risk Managers
  • Risk Managers
  • Internal Auditors
  • Enterprise Risk Management Professionals
  • Control Assurance Professionals
  • Business Risk Professionals
  • Process Risk Professionals
  • Governance, Risk & Compliance Professionals
  • Business Continuity Professionals
  • Risk Reporting Professionals
  • Operational Risk Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of operational risk, business processes, controls, or internal audit
  • Familiarity with risk registers, incidents, process issues, or control activities 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 Operational Risk
  • Identifying AI applications across risk identification, incident review, control monitoring, and reporting
  • Understanding AI assistance versus risk-professional judgement and accountability
  • Recognising activities where verified evidence and human review remain mandatory
Practical activities
  • Mapping common Operational Risk activities to potential AI applications
  • Comparing a traditional operational-risk task with an AI-assisted approach

Scenarios

Business Process to Operational Risk Assessment

Business Process → AI-Assisted Risk Identification → Causes → Potential Impacts → Existing Controls → Risk Summary

Participants use AI to analyse a sample business process, identify potential operational risks, map relevant controls, and prepare a structured risk summary for professional review.

Operational Incident to Corrective Action

Incident Information → AI-Assisted Summary → Event Chronology → Root-Cause Themes → Control Gaps → Corrective Actions → Management Brief

Participants use AI to organise a sample operational incident, identify possible contributing factors, and prepare a concise management brief while retaining final risk conclusions and corrective-action decisions with authorised professionals.

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