Role-Based Programme
RB1674

AI-Powered Operational Risk

Smarter Risk Identification, Control Monitoring & Incident Management

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Apply AI across Operational Risk activities including risk identification, control assessment, incident management, monitoring, and reporting.
  • Use AI-assisted techniques to analyse process information, incident records, control evidence, risk registers, and operational data more efficiently.
  • Develop structured workflows for Risk & Control Self-Assessments, issue management, loss-event analysis, corrective actions, and escalation.
  • Analyse operational-risk information to identify recurring failures, control weaknesses, emerging risks, concentration areas, and deteriorating indicators.
  • Apply responsible AI practices covering confidentiality, evidence quality, data accuracy, explainability, approvals, and human judgement.

Tools covered

Generative AI AssistantsOperational Risk AnalyticsDocument IntelligenceSpreadsheet AnalysisIncident AnalysisControl AssessmentRisk & Control Self-Assessment SupportKey Risk IndicatorsReporting AssistanceWorkflow Automation

Who should attend

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

Prerequisites & Participant Readiness

  • Working knowledge of risk management, business processes, controls, or audit activities
  • Familiarity with risk registers, operational incidents, control assessments, or risk reporting is helpful
  • Basic spreadsheet and data-analysis skills
  • Basic awareness of Generative AI is helpful
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, automation, and their applications in Operational Risk
  • Identifying AI opportunities across risk assessment, incident analysis, control monitoring, and reporting
  • Understanding AI assistance versus Risk Management and business-owner judgement
  • Recognising limitations related to incomplete data, assumptions, bias, and explainability
Practical activities
  • Mapping the Operational Risk lifecycle to AI-assisted activities
  • Identifying repetitive analytical and documentation tasks suitable for AI support
  • Comparing traditional and AI-assisted Operational Risk workflows

Scenarios

Business Process to RCSA & Risk Treatment Plan

Business Process → AI-Assisted Risk Identification → Risk Statements → Control Mapping → RCSA → Residual Risk → Action Plan → Management Review

Participants analyse a sample business process, identify key operational risks, assess existing controls, determine residual exposure, and prepare a structured risk-treatment plan.

Operational Incident to Risk Reduction Plan

Incident → AI-Assisted Event Analysis → Root-Cause Review → Control Gap → KRI Impact → Corrective Actions → Ownership → Management Report

Participants analyse a simulated operational incident, identify contributing factors and control weaknesses, update related risk indicators, and prepare a management-ready corrective-action and risk-reduction plan.

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