In an era defined by economic volatility and unforeseen global events, banks face an unprecedented challenge in accurately forecasting risk. Traditional econometric models often struggle to capture the complex, non-linear relationships that drive market disruptions and macroeconomic shocks. This training course is designed to address that gap, providing a strategic framework for financial professionals to move beyond conventional methods and embrace the power of artificial intelligence in risk management. By integrating advanced AI techniques, organizations can develop more dynamic and robust stress testing and scenario analysis capabilities.

This immersive 5-day program is a practical journey into AI-powered financial modeling, equipping participants with the skills to predict, analyze, and mitigate the impact of macroeconomic shocks. You will learn to build, validate, and interpret sophisticated models that not only satisfy regulatory requirements but also provide critical, forward-looking insights for strategic decision-making. The course transforms complex data into actionable intelligence, empowering you to navigate uncertainty and strengthen your institution's resilience in a rapidly changing world.

Duration: 5 Days

Target Audience

• Risk Analysts
• Quantitative Modelers
• Financial Regulators and Supervisors
• Credit Officers
• Portfolio Managers
• Chief Risk Officers (CROs)
• Financial Data Scientists
• Senior Executives in Banking
• Treasury Professionals
• Economic Research Analysts

Objectives

• Understand the fundamental concepts of macroeconomic shocks and their impact on banking.
• Learn to integrate AI and machine learning into traditional scenario analysis frameworks.
• Apply data-driven techniques to forecast and model a range of economic scenarios.
• Utilize AI to assess the impact of shocks on credit portfolios and market risk.
• Develop and validate robust AI models for stress testing and regulatory compliance.
• Interpret model outputs and translate complex findings into strategic business insights.
• Evaluate the ethical considerations and limitations of using AI in risk modeling.
• Design and execute a complete end-to-end scenario modeling project with AI tools.
• Communicate complex scenario findings effectively to executive leadership and regulators.

Module 1: Fundamentals of Macroeconomic Shocks & Banking Risk

• Defining and classifying different types of macroeconomic shocks.
• Understanding the transmission channels of shocks into banking risks.
• Comparing and contrasting traditional econometric approaches versus AI-driven methods.
• Exploring historical case studies of financial crises and their root causes.
• Identifying key risk types: credit, market, liquidity, and operational risk.

Module 2: Introduction to AI for Financial Modeling

• Overview of key machine learning concepts and algorithms.
• The role of supervised and unsupervised learning in risk analysis.
• Data preprocessing, cleaning, and preparation for financial datasets.
• Selecting appropriate AI models for different risk modeling challenges.
• Understanding the trade-offs between model complexity and interpretability.

Module 3: Data Sourcing and Feature Engineering

• Identifying and sourcing relevant internal and external data.
• Working with unstructured data, such as news articles and social media.
• Creating powerful, predictive features from raw financial data.
• Handling time-series data, including stationarity and seasonal components.
• Leveraging external APIs for real-time economic indicators.

Module 4: Building Predictive Models for Economic Variables

• Applying time-series forecasting models to key macroeconomic variables.
• Using regression and classification models to predict economic outcomes.
• Generating plausible economic scenarios using probabilistic methods.
• Backtesting predictive models to ensure their reliability and accuracy.
• Fine-tuning model parameters to optimize forecasting performance.

Module 5: Stress Testing and Portfolio Impact Analysis

• Integrating AI models into existing stress testing frameworks.
• Modeling the impact of shocks on credit risk and default probabilities.
• Assessing market risk exposure under extreme market conditions.
• Simulating portfolio-level losses and capital requirements.
• Running sensitivity analysis to identify key risk drivers.

Module 6: Regulatory Compliance and Model Validation

• Understanding the regulatory landscape for stress testing (e.g., Basel III, CCAR).
• Documenting AI models for regulatory submission and audit.
• Implementing robust model validation and governance frameworks.
• Performing sensitivity analysis and backtesting on AI-driven stress tests.
• Ensuring model fairness and mitigating potential biases.

Module 7: Advanced Scenario Simulation Techniques

• A deep dive into Monte Carlo simulation for complex risk scenarios.
• Using Generative Adversarial Networks (GANs) to create synthetic, realistic data.
• Exploring causal inference to understand the true impact of shocks.
• Building dynamic models that adapt to changing economic conditions.
• Combining expert judgment with AI-driven insights for hybrid scenarios.

Module 8: Interpreting and Communicating Model Results

• Techniques for visualizing complex, multi-dimensional model outputs.
• Translating technical findings into clear, strategic business insights.
• Presenting compelling dashboards and reports to executive leadership.
• Communicating model assumptions and limitations to a non-technical audience.
• Developing narrative descriptions for scenario outcomes.

Module 9: Capstone Project: End-to-End Scenario Modeling

• Participants work in teams on a simulated macroeconomic shock event.
• The project covers data gathering, model building, and stress testing.
• Teams will present their findings and strategic recommendations to a mock executive committee.
• The project emphasizes collaboration, communication, and practical application.
• Reviewing and critiquing peer models and presentations.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.