Learning Objectives:

  • Define Generative AI and its core technologies.

  • Explain the applications of Generative AI in banking.

  • Understand the challenges and risks of Generative AI adoption.

6.1 What is Generative AI?

Generative AI refers to AI models that can generate new content—text, images, code, or data—based on training data. The HKU SPACE certificate programme provides a comprehensive introduction to Generative AI for banking and finance .

Key technologies include:

  • Generative Adversarial Networks (GANs): Two neural networks competing to generate realistic data.

  • Variational Autoencoders (VAEs): Models that learn data distributions and generate new samples.

  • Transformer Models: The architecture behind ChatGPT and other LLMs.

6.2 Applications in Banking

The HKU SPACE course covers practical applications of Generative AI in banking and compliance :

  • Documentation: Document drafting, translation, review, and writing.

  • Financial Pitching Presentations: Creating automated presentations.

  • Financial Analysis: Automated financial analysis and reporting.

  • Customer Service and Personalisation: Chatbots and virtual assistants.

  • Credit Scoring and Risk Assessment: Enhanced loan approval processes.

  • Compliance: AML compliance, financial compliance, and risk modelling.

6.3 Current Trends and Challenges

The HKU SPACE course covers current trends and challenges :

  • Large Language Models (LLMs): Development of major LLMs and open-source LLMs.

  • Large Reasoning Models: ChatGPT o1 and o1 pro in financial services.

  • Large Action Models: AI agents performing actions in banking.

  • Implementation Challenges: Practical challenges in implementing Generative AI in banking.

 

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