Role-Based Programme
RB1676

AI-Powered Financial Risk

Smarter Risk Analysis, Monitoring & Financial Decision Support

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

Programme Objectives

  • Understand how AI can support Financial Risk activities across risk identification, financial analysis, monitoring, exception review, and reporting.
  • Explore practical prompting techniques for financial-risk assessment, trend analysis, scenario review, exception identification, and management summaries.
  • Apply AI to organise financial information, identify relevant risk indicators, and prepare structured risk outputs.
  • Identify opportunities to improve analysis efficiency, consistency, documentation quality, and financial-risk visibility.
  • Recognise confidentiality, financial-data accuracy, model limitations, regulatory requirements, and human-review responsibilities when using AI.

Tools covered

Generative AI AssistantsAI-Assisted Financial Risk AnalysisDocument IntelligenceSpreadsheet AnalysisFinancial Data SummarisationRisk MonitoringException TrackingBasic Workflow Automation

Who should attend

  • Financial Risk Analysts
  • Risk Analysts
  • Risk Managers
  • Finance Risk Professionals
  • Internal Auditors
  • Treasury Risk Professionals
  • Market Risk Support Professionals
  • Liquidity Risk Professionals
  • Enterprise Risk Management Professionals
  • Financial Control Professionals
  • Risk Reporting Professionals
  • Control Assurance Professionals
  • Financial Risk Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of finance, risk management, accounting, or financial analysis
  • Familiarity with financial statements, risk indicators, budgets, forecasts, or management reports 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 Financial Risk
  • Identifying AI applications across financial analysis, monitoring, reporting, and risk review
  • Understanding AI assistance versus Finance and Risk professional judgement
  • Recognising activities where validated financial data and human review remain mandatory
Practical activities
  • Mapping common Financial Risk activities to potential AI applications
  • Comparing a traditional financial-risk task with an AI-assisted approach

Scenarios

Financial Information to Risk Assessment

Financial Data → AI-Assisted Trend Review → Risk Indicators → Exposure Analysis → Potential Impact → Risk Summary

Participants use AI to organise sample financial information, identify relevant trends and potential risk indicators, and prepare a structured Financial Risk summary for professional review.

Financial Risk Indicators to Management Brief

Risk Metrics + Variances + Thresholds → AI Review → Exceptions → Scenario Observations → Actions → Management Brief

Participants use AI to review sample financial-risk indicators, identify exceptions and emerging concerns, and prepare a concise management brief while retaining final risk decisions with authorised professionals.

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