Role-Based Programme
RB1677

AI-Powered Financial Risk

Smarter Exposure Analysis, Risk Monitoring & Decision Support

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Financial Risk activities across exposure identification, analysis, monitoring, scenario assessment, and reporting.
  • Apply AI-assisted techniques to analyse financial data, risk indicators, liquidity information, market exposures, and supporting documents.
  • Use structured prompting for financial-risk assessment, variance analysis, scenario evaluation, trend identification, and management reporting.
  • Explore AI-supported approaches for identifying emerging financial risks, unusual movements, concentration areas, and potential stress points.
  • Build responsible AI-assisted Financial Risk workflows while maintaining data confidentiality, calculation accuracy, governance, professional judgement, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisFinancial Risk AnalysisScenario AnalysisRisk Reporting AIWorkflow Automation

Who should attend

  • Financial Risk Analysts
  • Risk Analysts
  • Financial Risk Managers
  • Treasury Risk Professionals
  • Market Risk Professionals
  • Liquidity Risk Professionals
  • Enterprise Risk Management Professionals
  • Finance Risk Professionals
  • Internal Auditors
  • Risk Management Executives
  • Financial Control Professionals
  • Governance, Risk & Compliance Professionals
  • Risk Managers
  • Financial Risk Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of Financial Risk, Finance, Treasury, or Risk Management
  • Familiarity with financial statements, exposures, cash flows, risk indicators, or management reports is helpful
  • Basic computer, spreadsheet, and document-handling skills
  • No AI or programming knowledge required
  • No previous AI training required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Financial Risk
  • Identifying AI applications across exposure analysis, monitoring, scenario review, and reporting
  • Understanding AI assistance versus financial-risk and management judgement
  • Recognising limitations such as inaccurate calculations, hallucinations, incomplete data, and unsupported conclusions
Practical activities
  • Mapping a typical Financial Risk workflow
  • Identifying repetitive and information-intensive activities suitable for AI assistance
  • Comparing a traditional financial-risk task with an AI-assisted approach

Scenarios

Financial Exposure to Risk Assessment

Financial Data → AI-Assisted Exposure Identification → Risk Categories → Liquidity / Market Sensitivity → Scenario Analysis → Risk Summary → Management Review

Participants use AI to analyse sample financial information, identify major exposure areas, test selected scenarios, and prepare a structured Financial Risk assessment for authorised review.

Financial Risk Data to Early-Warning Report

Risk Indicators → AI Analysis → Threshold Breaches → Unusual Movements → Concentration Areas → Early-Warning Actions → Management Report

Participants use AI to analyse sample Financial Risk indicators, identify emerging concerns and exceptions, and prepare a concise management report with follow-up priorities.

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