In today's complex and interconnected financial world, traditional methods of credit risk scenario design often fail to capture the full range of potential future uncertainties. This training course is engineered to empower risk professionals with the knowledge and tools to leverage Generative AI (GenAI) for creating more dynamic, realistic, and comprehensive stress testing scenarios. By moving beyond a limited set of historical assumptions, participants will learn how to generate an endless array of plausible scenarios, ensuring their portfolios are truly resilient against unforeseen economic shocks.

This program provides a practical, hands-on approach to integrating GenAI into the core of the credit risk management framework. Participants will explore how large language models and other generative techniques can be used to synthesize macroeconomic narratives, simulate market movements, and create nuanced risk events that challenge traditional models. The course is a strategic investment for financial institutions aiming to elevate their stress testing capabilities, comply with evolving regulatory expectations, and gain a significant competitive advantage through more intelligent and forward-looking risk analysis.

Duration: 10 days

Target Audience:

• Credit Risk Managers
• Stress Testing Analysts
• Financial Modelers
• Data Scientists in Finance
• Risk Officers
• Quantitative Analysts
• Portfolio Managers
• Internal Audit Professionals
• Treasury Professionals
• Regulatory Compliance Officers

Objectives:

• Understand the core concepts of Generative AI and its application in risk management.
• Learn how to use GenAI to create rich and realistic credit risk scenarios.
• Master the process of generating both macroeconomic and idiosyncratic risk narratives.
• Develop a framework for validating and interpreting GenAI-generated scenarios.
• Integrate GenAI tools into existing stress testing and risk modeling workflows.
• Ensure scenarios are diverse, plausible, and compliant with regulatory standards.
• Overcome the ethical and governance challenges of using GenAI in a regulated environment.
• Enhance the speed, accuracy, and comprehensiveness of your stress testing.
• Build a forward-looking and adaptive risk management culture.
• Identify and mitigate potential risks associated with AI-generated data.

Course Modules:

Module 1: The AI-Powered Risk Revolution

• Understanding the limitations of traditional scenario analysis
• An introduction to Generative AI and its core capabilities
• The business case for using GenAI in risk management
• Key types of generative models (e.g., GPT, diffusion models)
• A high-level overview of the GenAI workflow

Module 2: Foundational Concepts of Generative AI

• How large language models (LLMs) work
• Understanding the concepts of prompts and fine-tuning
• The importance of context and conditioning in scenario generation
• The difference between deterministic and probabilistic models
• An overview of key platforms and APIs

Module 3: Designing Macroeconomic Scenarios with GenAI

• Using GenAI to create rich and detailed economic narratives
• Generating plausible stories of inflation, recession, and geopolitical shocks
• Integrating financial data and economic indicators into prompts
• The role of human-in-the-loop for refining narratives
• Case studies on generating a global downturn scenario

Module 4: Simulating Market Movements with AI

• Using GenAI to create realistic simulations of asset price changes
• Generating correlated movements across different markets
• Incorporating volatility and liquidity shocks into the scenario
• Validating the statistical properties of the simulated data
• The use of conditional generation for specific market events

Module 5: Creating Idiosyncratic Risk Scenarios

• Leveraging GenAI to generate scenarios for specific sectors or counterparties
• Creating plausible narratives for operational failures or reputational crises
• Simulating the impact of a cyberattack or a supply chain disruption
• The use of GenAI for reverse stress testing
• Ensuring the scenarios are relevant and material

Module 6: Data and Infrastructure for GenAI Risk Models

• Identifying and sourcing the right data for model training
• The importance of a clean and well-structured data pipeline
• Setting up the technical infrastructure for GenAI (e.g., cloud platforms)
• Managing the computational resources and costs
• Integrating with existing risk systems and data warehouses

Module 7: Prompt Engineering for Risk Scenarios

• The art and science of writing effective prompts
• Techniques for guiding GenAI to generate desired outcomes
• Using structured prompts for consistency and control
• The importance of context and historical data in prompting
• Advanced prompting strategies for complex scenarios

Module 8: Validating and Calibrating GenAI Scenarios

• Developing a framework for scenario plausibility
• Using quantitative methods to validate model outputs
• Comparing GenAI-generated scenarios with traditional ones
• The importance of expert judgment and peer review
• The role of backtesting and historical analysis

Module 9: Integrating GenAI into the Stress Testing Cycle

• Automating the scenario generation process
• The role of GenAI in the annual stress test
• Using GenAI for ad-hoc and real-time analysis
• Streamlining the reporting and documentation of scenarios
• A step-by-step guide to a GenAI-augmented stress test

Module 10: Ethical AI and Governance in Risk Management

• Addressing the risks of "hallucinations" and biased outputs
• The importance of explainability and transparency in AI models
• Establishing a governance framework for GenAI use
• Ensuring compliance with regulatory expectations for AI
• The role of human oversight in all stages of the process

Module 11: GenAI for Portfolio-Specific Stress Tests

• Tailoring scenarios to the specific composition of a credit portfolio
• Generating scenarios that target specific sectors or regions
• Simulating the impact on a loan-by-loan basis
• Using GenAI to create a comprehensive risk heat map
• The benefits of granular scenario analysis

Module 12: GenAI for Regulatory Reporting

• Using GenAI to generate the narratives for regulatory submissions
• Ensuring the scenarios meet the requirements of regulators
• Automating the creation of supporting documentation
• The role of GenAI in capital planning and capital adequacy
• Case studies on regulatory compliance

Module 13: Advanced GenAI Techniques

• An introduction to generative adversarial networks (GANs) for risk data
• The potential of diffusion models for scenario generation
• Fine-tuning open-source LLMs for a specific financial context
• The use of multimodal GenAI for combining text and data
• The future of generative models in finance

Module 14: Practical Application and Hands-on Labs

• A guided project on creating a full-scale risk scenario
• Using a GenAI platform to generate macroeconomic narratives
• Simulating a market downturn for a hypothetical portfolio
• Troubleshooting common challenges in GenAI implementation
• Peer review and feedback sessions on generated scenarios

Module 15: The Future of Risk Management

• The convergence of AI, data, and risk
• The long-term implications of GenAI for the finance industry
• How GenAI will change the role of risk professionals
• The rise of autonomous risk systems
• Anticipating the next wave of technological disruption

Module 16: Strategic Action Planning

• Creating a customized roadmap for GenAI adoption
• Identifying key stakeholders and securing buy-in
• Developing a phased implementation strategy
• Measuring the ROI and business impact of the investment
• Final Q&A and course wrap-up

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 10 working days before commencement of the training.