AI in Banking

The course covers the main applications of AI and how it can be applied to Banking.

Who can benefit from this program?

There are no pre-requisites but the course is mainly designed for people working in:

• Banking.

• IT.

• Payments companies.

• Public sector, given the public policy aspects of Banking.

• Academia.

• Fintech Leaders.

• Digital Banking Managers.

• Banking Heads.

• Start-up Leaders.

OUTLINE OF THE WORKSHOP. 

DAY 1. 

New technologies in Banking: how intensely have new technologies penetrated the Banking industry? 

AI: 

• What is AI.

• The AI Ecosystems.

• AI Use Cases.

• AI opportunities.

  • AI Risks

  • Black box AI: A suggested sandbox regulatory approach for Black BoxAI.

  • Why should banks become AI-first? Benefits.

  • Risks for banks to use AI.

  • What might the AI-bank of the future look like?

  • What obstacles prevent banks from deploying AI capabilities at scale?

  • How can banks transform to become AI-first?

    Applications of AI in Banking:

    • Front office (conversational banking)

    • Middle office (fraud detection and risk management)

    • Underwriting

    • Key use cases for transforming the front and middle office using the technology.

The recent hype for AI: overview of ChatGPT and other AI-based tools.

How do they work and how should we use them? 

Business Case 1

DAY 2 

AI in Banking: 

• Winning strategies used by financial institutions that are leveraging AI to transform their entire organizations.

• How banks can best capture the AI opportunity, including considerations oninternal culture, staffing, operations, and data.

  
  

How can Data Science and Artificial Intelligence (AI) help drive Financial Inclusion in the Philippines and beyond? 

How can AI be used to identify fraud in monetary transactions? 

How can Data Science and AI be relevant in the areas of Decision-Making and Business Processes?