Curriculum
- 6 Sections
- 34 Lessons
- 1 Day
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- The Rise of Data-Driven Finance6
- 1.1Evolution from descriptive to predictive & prescriptive finance
- 1.2Digital finance stack — ERP + BI + ML + RPA
- 1.3Role of data governance, automation, and real-time analytics
- 1.4Key enablers: Big Data, Cloud, APIs, and Generative AI in finance
- 1.5Finance 4.0 framework — agility, accuracy, and automation
- 1.6Quick diagnostic – Assess organization’s data maturity across FP&A, risk, and fraud functions
- AI in Financial Forecasting & Scenario Planning7
- 2.1Time-series forecasting (ARIMA, Prophet, LSTM)
- 2.2AI-based demand and revenue projections
- 2.3Rolling forecasts vs. static budgets
- 2.4Scenario and sensitivity modelling using ML insights
- 2.5AI-driven cost variance and working capital optimization
- 2.6Case Example: Unilever & Microsoft — AI-powered financial forecasting reducing variance error by 20%
- 2.7Exercise: Build a simple regression-based forecasting model in Excel/Python to predict quarterly revenue or expenses
- AI/ML in Financial Risk Analytics7
- 3.1Predictive risk scoring and anomaly detection
- 3.2Credit default prediction using supervised learning models
- 3.3Stress testing and Monte Carlo simulations
- 3.4Early warning signals for liquidity and exposure management
- 3.5Linking ESG data to financial risk modelling
- 3.6Example: JP Morgan & HDFC Bank — AI models for risk scoring and liquidity forecasting
- 3.7Exercise: Analyze risk datasets to flag potential exposure patterns and suggest mitigation actions
- AI in Fraud Detection & Compliance Monitoring7
- 4.1Transaction anomaly detection using clustering and NLP
- 4.2Outlier detection in payments and expense claims
- 4.3Continuous control monitoring (CCM) and forensic analytics
- 4.4Reinforcement learning for adaptive fraud models
- 4.5AI-based KYC, AML, and compliance monitoring systems
- 4.6Case Example: Mastercard’s AI-led fraud prevention and PayPal’s real-time anomaly systems
- 4.7Fraud detection Challenge — Identify outliers in sample payment data using AI pattern rules
- Building the Intelligent Finance Function5
- 5.1AI-augmented FP&A and cognitive decision support
- 5.2Human + Machine collaboration for financial insight generation
- 5.3Integrating ML pipelines into finance workflows
- 5.4Data visualization for storytelling — Power BI, Tableau, and GenAI dashboard
- 5.5Group activity – Design a “Smart Finance CoE” framework for their organization
- Action Planning & Digital Roadmap2