AI & Monte Carlo Simulation for Investment Decisions

This 5day course empowers finance professionals across all functions with the skills to use Artificial Intelligence and Monte Carlo Simulation for enhanced decisionmaking. By integrating AIdriven analysis with advanced probabilistic modeling, participants will explore how to assess uncertainty, forecast outcomes, evaluate risk exposure, and optimize financial decisions in dynamic environments. Realworld applications across investment, treasury, and financial control functions are emphasized throughout.

TRAINING TOPICS

• Monte Carlo simulation principles in financial modeling
• AI integration into forecasting, scenario planning, and simulations
• Risk quantification using probabilistic distributions and stress testing
• AIpowered scenario generation (LLMs, GANs, diffusion models)
• Treasury and liquidity forecasting under uncertainty
• ValueatRisk (VaR), CVaR, and tailrisk modelling
• ESG, macroeconomic, and geopolitical scenario simulations
• Cloud computing, Python/GPU tools for largescale simulation
• AI in credit risk, cash flow modeling, and insurance underwriting
• Governance, model risk management, and ethical AI in finance

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO:

• Apply Monte Carlo simulation to support financial, treasury, and investment decisions
• Use AI models to generate dynamic scenarios and improve forecast accuracy
• Quantify risk and optimize portfolios using AIenhanced metrics
• Simulate ESG and macroeconomic shocks to assess resilience
• Build financial dashboards integrating simulation outputs
• Use Python as a user or AI platforms for simulation and automation
• Evaluate simulation assumptions, transparency, and regulatory compliance
• Implement AI models that align with internal audit and risk governance policies

TRAINING IS TAILORED TO

• Corporate finance, investment, and treasury teams
• Risk, compliance, and internal audit professionals
• Financial planning, FP&A, and budgeting managers
• Credit analysts, insurance and actuarial departments
• Financial controllers and CFO office advisors
• Fintech and digital transformation leaders in finance

TRAINING METHODOLOGY

• Expertled interactive sessions blending theory and handson practice
• Reallife case studies from global financial institutions
• Guided labs using Python, Excel, and AI tools
• Group simulations and peer collaboration
• Scenariobased forecasting challenges
• Interactive dashboards and visualization building
• Live demonstrations of AI & Monte Carlo integration
• Postcourse toolkit with models and templates

DAY ONE:

INTRODUCTION TO AI AND MONTE CARLO IN FINANCE

• Key financial decisions under uncertainty
• Monte Carlo principles: distributions, iterations, randomness
• Introduction to AI tools in forecasting and decision support
• Risk vs uncertainty: finance applications
• Handson: Building a basic Monte Carlo model in Excel
• Use cases in budgeting, capital planning, credit risk

DAY TWO:

ADVANCED MONTE CARLO MODELING IN FINANCE

• Scenario generation: macro, market, and business drivers
• Applications in liquidity risk, project valuation, and FX exposure
• ValueatRisk, Expected Shortfall, and tail event modelling
• Monte Carlo in insurance claims and credit stress testing
• Forecasting balance sheet and P&L scenarios
• Handson: Multivariable Monte Carlo simulation using Python or Excel

DAY THREE:

AIENHANCED SIMULATIONS & FINANCIAL OPTIMIZATION

• Generative AI models for scenario planning (ChatGPT, GANs, etc.)
• Using AI to forecast revenue, expenses, and working capital
• AIassisted portfolio riskadjusted returns and stress testing
• Automating simulations with AI pipelines and tools
• Use of AI in audit sampling, anomaly detection, and controls testing
• Handson: Use an AI platform (nocode/lowcode) to run forecasts

DAY FOUR:

APPLICATIONS IN RISK, TREASURY & STRATEGIC FINANCE

• Monte Carlo for liquidity forecasting and treasury cash flow stress tests
• Corporate finance: AIdriven project appraisal under uncertainty
• Integration into enterprise risk management (ERM) frameworks
• ESG, geopolitical risk and supply chain uncertainty simulation
• Reallife case studies across sectors (banking, corporates, insurance)
• Handson: Stress testing financial KPIs with AI & simulations

DAY FIVE:

BUILDING YOUR OWN AIMONTE CARLO TOOLKIT

• Governance: assumptions, transparency, ethics in AIdriven models
• Dashboarding and communicating risk visually to executives
• Regulatory alignment: IFRS, Basel, Solvency, ESG reporting
• Group project: build and present your own AI + simulation model
• Review of tools: Python, Excel, Knime, Power BI, ChatGPT
• Strategic roadmap for AI adoption in your financial department