Applications of Generative AI in Fintech (FIN536)

FIN536 Applications of Generative AI in Fintech moves beyond ChatGPT and prompt engineering to practical applications of generative AI using modern tools and techniques. Students will understand the theoretical foundations of generative AI and possess applied competencies beyond conversational AI usage. This course is a practical, beginner-friendly course that equips finance and fintech students with applied digital capabilities increasingly expected in organisations where automation, GenAI-assisted operations, and rapid prototyping are becoming standard. Building on foundational concepts, the course moves beyond chatbot-based use of generative AI (such as ChatGPT and prompt engineering) to focus on embedding GenAI into real workflows, automations, and simple digital tools that address concrete business needs. Rather than learning programming in a traditional, syntax-first manner, students leverage modern generative AI tools — from no-code platforms to AI coding agents — to automate tasks, analyse information, and rapidly translate business ideas into working digital solutions. By the end of the course, students will be able to apply GenAI to enhance productivity, build simple business applications, and contribute to AI-enabled transformation in financial services — capabilities increasingly expected in today’s technology-augmented finance roles.

• Introduction to Generative AI
• Beyond ChatGPT and Prompt Engineering: Shift toward Applied GenAI Systems
• Open vs Closed Large Language Models (LLMs)
• How Generative AI Reasons and Fails: Context windows, hallucinations, bias, uncertainty, and reliability in decision-making
• GenAI Tooling Landscape
• No-Code Workflow Automation and Orchestration
• JavaScript Fundamentals for Generative AI
• Using AI Coding Agents for JavaScript Development
• Preparing External Knowledge for Generative AI
• Retrieval, Grounding, and Context Injection
• Connecting Generative AI to Tools and Systems (Model Context Protocol)
• Prototyping End-to-End GenAI Solutions

• Appraise the core concepts, capabilities, and limitations of generative AI systems
• Assess AI models, coding agents, and workflow tools for their roles in practical automation pipelines for finance-related tasks
• Evaluate the suitability of different generative AI tools, platforms, and deployment approaches for specific use cases
• Combine data extraction and transformation processes to prepare external content for effective use by generative AI systems (e.g. web-scraping, OCR)
• Create AI-assisted analyses, summaries, and insights from financial and business data to support decision-making
• Design and prototype functional digital solutions, or process automations, that address real-world finance and business needs