Role-Based Programme
RB1678

AI-Powered Financial Risk

Smarter Exposure Analysis, Risk Monitoring & Financial Decision Support

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

Programme Objectives

  • Apply AI across Financial Risk activities including exposure identification, financial analysis, risk monitoring, scenario assessment, limit review, and reporting.
  • Use AI-assisted techniques to analyse financial data, risk reports, market information, liquidity indicators, and exposure records more efficiently.
  • Develop structured workflows for identifying financial risks, assessing impact, monitoring limits, analysing scenarios, and escalating exceptions.
  • Analyse structured and unstructured information to identify concentration, liquidity, market, funding, and financial-performance risks.
  • Apply responsible AI practices covering financial confidentiality, data quality, model limitations, explainability, approvals, and human judgement.

Tools covered

Generative AI AssistantsFinancial Risk AnalyticsSpreadsheet AnalysisDocument IntelligenceScenario AnalysisStress Testing SupportRisk ScoringExposure AnalysisManagement ReportingWorkflow Automation

Who should attend

  • Financial Risk Analysts
  • Financial Risk Managers
  • Risk Management Professionals
  • Enterprise Risk Professionals
  • Market Risk Professionals
  • Liquidity Risk Professionals
  • Treasury Risk Professionals
  • Finance Risk Professionals
  • Risk Analysts
  • Internal Auditors
  • Risk Assurance Professionals
  • Financial Controls Professionals
  • Risk Reporting Professionals
  • Risk & Internal Audit Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of finance, financial risk, treasury, accounting, or risk-management activities
  • Familiarity with financial statements, exposures, risk reports, or financial-performance data is helpful
  • Basic spreadsheet and financial-analysis skills
  • Basic awareness of Generative AI is helpful
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, predictive techniques, and automation in Financial Risk
  • Identifying AI applications across exposure analysis, monitoring, scenario analysis, and reporting
  • Understanding AI assistance versus authorised financial-risk judgement and decision-making
  • Recognising model, data-quality, bias, and explainability risks in AI-assisted financial analysis
Practical activities
  • Mapping the Financial Risk lifecycle to AI-assisted activities
  • Identifying repetitive analytical and reporting tasks suitable for AI support
  • Comparing traditional and AI-assisted financial-risk workflows

Scenarios

Financial Exposure to Risk Assessment

Financial Data → AI-Assisted Exposure Analysis → Risk Identification → Sensitivity Analysis → Limits & Indicators → Mitigation Options → Management Review

Participants analyse sample financial information, identify major exposures and risk drivers, test sensitivities, review limits, and prepare a structured Financial Risk assessment for management.

Financial Risk Portfolio to Stress-Tested Management Report

Portfolio & Liquidity Data → AI Analysis → Concentrations → Stress Scenarios → Limit Exceptions → Early Warning Indicators → Priority Actions → Executive Report

Participants combine sample financial-risk information to identify concentrations, liquidity concerns, and potential limit issues, run structured scenarios, and prepare a management-ready report highlighting key risks and actions.

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