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CFTE

Generative AI for Private Banking in Financial Services

  • up to 6 weeks
  • Intermediate

This course is designed to help private banking professionals understand how to harness Generative AI to augment their operations and offer hyper-personalised banking experiences. Participants will gain in-depth knowledge of generative AI, understand its applications and underlying mechanisms, and learn about global trends and know how to integrate AI in their organisations.

  • Generative AI fundamentals
  • Client personalisation
  • Portfolio management
  • Fraud detection
  • Risk management

Overview

The course covers the fundamentals of generative AI, the landscape of generative AI in private banking, current and future applications, risk management, and regulation. Participants will learn to apply generative AI techniques to develop highly personalized banking experiences, optimize portfolio management, strengthen fraud detection, and enhance client advisory services. The course includes hands-on projects, case studies, and industry expert interviews to provide practical insights and real-world applications.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Professional Certification
    upon course completion
  • Self-paced
    course format
  • Live classes
    delivered online

Who is this course for?

Relationship Managers

Professionals responsible for managing client relationships and providing personalized banking services.

Investment Advisors

Experts who offer investment advice and strategies to clients, aiming to optimize their portfolios.

Wealth Managers

Specialists in managing the financial assets of high-net-worth individuals, focusing on long-term wealth growth.

This course equips finance professionals with the knowledge and skills to leverage generative AI in private banking. Key benefits include mastering AI fundamentals, enhancing client personalization, optimizing portfolio management, and strengthening fraud detection. Ideal for professionals in private banking, this course will help you stay competitive and advance your career.

Pre-Requisites

1 / 3

  • Basic understanding of private banking operations

  • Familiarity with financial services industry

  • Interest in AI and its applications in finance

What will you learn?

Week 1: Generative AI Fundamentals
This week explores the definition, the inner mechanisms, and the evolution of Generative AI.
Day 1: Definition of Generative AI
Understanding what Generative AI is and its basic principles.
Day 2: Differences between traditional Machine Learning and Generative AI
Comparing traditional machine learning techniques with generative AI.
Day 3: Transformers: a revolutionary breakthrough
Exploring the role of transformers in generative AI.
Day 4: Scaling transformers
Understanding how transformers can be scaled for better performance.
Day 5: LLMs as a new human/machine interface
Learning about Large Language Models (LLMs) and their applications.
Week 2: The Landscape of Generative AI
This week discusses the Generative AI landscape and key players such as infrastructure providers, model providers and application providers.
Day 6: Model providers
Identifying key model providers in the generative AI space.
Day 7: Infrastructure providers
Understanding the role of infrastructure providers in generative AI.
Day 8: Application providers
Exploring various application providers and their offerings.
Day 9: Hands-on project: Getting started with ChatGPT and Customer Personas
Practical project to get started with ChatGPT and create customer personas.
Day 10: Hands-on project: Analysing & extracting information from PDF Reports with AI
Using AI to analyze and extract information from PDF reports.
Week 3: Current landscape of Generative AI in Private Banking
This week delves into the Private Banking domain and compare traditional approaches with AI-driven methods.
Day 11: Introduction and background of Private Banking
Overview of the private banking sector and its key characteristics.
Day 12: Challenges in Private Banking
Identifying the main challenges faced by private banking.
Day 13: Traditional approaches vs AI-driven approaches in Private Banking
Comparing traditional methods with AI-driven approaches in private banking.
Day 14: Current landscape of Generative AI in Private Banking
Exploring the current use of generative AI in private banking.
Day 15: Expert interview: TBC
Interview with an industry expert on generative AI in private banking.
Week 4: Applications and use cases of Generative AI in Private banking
This week discusses Generative AI applications and current initiatives and use cases in Private Banking.
Day 16: Applications of Generative AI in Private Banking (1/2)
Exploring various applications of generative AI in private banking.
Day 17: Applications of Generative AI in Private Banking (2/2)
Continuing the exploration of generative AI applications in private banking.
Day 18: Case studies (1/2)
Reviewing case studies of generative AI in private banking.
Day 19: Case studies (2/2)
Continuing the review of case studies in generative AI.
Day 20: Expert interview (TBC)
Interview with an industry expert on generative AI applications.
Week 5: From Theory to Practice: Practical Approach
This week focuses on practical applications of generative AI tools in Private Banking.
Day 21: Navigate key Generative AI tools
Learning to navigate and use key generative AI tools.
Day 22: Understanding the Prompt Engineering
Understanding the concept and techniques of prompt engineering.
Day 23: Use case
Exploring a practical use case of generative AI.
Day 24: Use case
Continuing the exploration of practical use cases.
Day 25: Use case
Further exploration of practical use cases.
Day 26: Use case
Final exploration of practical use cases.
Week 6: Opportunity and risk in Private banking
This week examines the advantages and key success factors of implementing AI in Private Banking and teaches the privacy and data usage in Generative AI in Private Banking.
Day 27: Advantages / Key Success Factors of AI implementation in Private Banking
Identifying the advantages and key success factors of AI implementation.
Day 28: Impact and assessment
Assessing the impact of AI in private banking.
Day 29: Data, Risk, Privacy and Ethical considerations
Understanding data, risk, privacy, and ethical considerations in AI.
Day 30: Changes in skills
Exploring the changes in skills required for AI implementation.

What learners say about this course

  • “The content was really relevant. I really liked that it gave a lot of examples on how AI can be applied in the industry, the companies that are successful implementing AI and high level view on what AI is really about.”

    Magdalene Loh

    Senior Vice President and Head of Innovation at Prudential Singapore

  • “The interviews covered in the course introduced the insights that are very important from those with 20+ years experience professionals.”

    Priscilla Cournede

    Deputy Director at Life Reinsurance at Covéa

  • “Since I finished the course, I raised suggestions to my team to integrate different technologies and AI in the different parts of the organisation.”

    Goh Theng Kiat

    Chief Customer Officer at Prudential Singapore

Meet your instructors

  • Huy Nguyen Trieu

    CEO, The Disruptive Group

    Huy Nguyen Trieu is an entrepreneur, academic, and investor who is passionate about building and growing businesses, especially in changing environments. This led him from a tech CEO in New York to Managing Director in London investment banks to Founding Partner of an accelerator in Hong Kong and now co-founder of a global knowledge platform in Fintech.

  • Philip Watson

    Head, Platform Development & Innovation, Citi Wealth

    Philip Watson is a highly accomplished financial services professional with over 20 years of experience in wealth management. He is a recognized expert in innovation, digital leadership, product knowledge, data and analytics, and has extensive experience working with emerging technologies, including artificial intelligence (AI).

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£270