This program begins with a one-week intensive boot camp (Sessions 1–4) structured as a combination of blended learning and evening sessions during the first week of classes that provide a structured foundation in AI for financial services, including Foundations of AI and Financial Data Literacy, Prompt Engineering and Explainability, AI Prototype Development, and Financial Services AI Requirements. The boot camp is followed by four weeks of blended learning and weekly evening sessions (sessions 5-8) that cover AI Ethics and Risk Management, Data Governance for AI, AI Security and Auditability, and one project-related module. After the class sessions are completed, students will spend six weeks working with a financial institution on an industry-focused project. The project will use AI prompting to build an AI agentic prototype to support one of the following areas: AI in Risk Management, AI in Sales and Marketing, AI in Technology and Operations, AI to Support Regulatory Compliance, and AI in Investment Research.
- Frame and refine a real-world AI problem within its organisational and ecosystem context;
- Assess feasibility across data, technological, operational, regulatory, and stakeholder dimensions;
- Design and prototype an AI-enabled solution aligned with strategic objectives;
- Apply responsible AI principles, including governance, transparency, fairness, and risk management;
- Develop a practical implementation and adoption roadmap;
- Articulate a clear value proposition supported by analytical evidence;
- Critically evaluate the broader ecosystem implications of AI deployment.