Fundamentals of Practical AI for Investment Management Firms

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AI is a technology whose time has come. A combination of abundant data and ever more powerful computing are providing fertile conditions for the rapid development and implementation of AI across investment management and the financial services industry more broadly.” Director, Business: Risk, Culture & Resilience at The Investment Association

The global economic impact of AI is forecast by McKinsey & Co. in excess of $19 trillion p.a and commonly divided by the AI sector into two broad areas: 1. enterprise use cases improving existing processes and 2. labour or individual productivity with some overlap (see below).

This will be a practical style course, pushing through the hype to real-world use cases and context of attendees. Alignment to attendee context will be made further effective by providing options for member / attendee pre-briefings and bringing to the course non-confidential problems and project which can be worked through during the training to integrate as much of attendee context into the training (e.g. specific issues, concerns, problems etc.)

Key Learning Objectives:

• Learn the fundamentals and distinguish between generative and non-generative AI, broader data science and traditional statistical improvement approaches in the context of investment management support functions.
• Learn simple methods and tools to decide which parts of your function, process or role AI can have the best impact while minimising risks.
• Become familiar with AI tools and methods you can use in your role and which could best help your productivity.
• Discuss AI case studies for investment management support functions and learn lessons
• Have 1:1 clinics with experts and work through how AI can help specific challenges and opportunities you are facing in your role.
• Practice using some basic AI tools.

1pm-5:30pm

• Introduction to generative and non-generative AI: What is generative AI? How does it work? What is non-generative AI? How are they currently used in functions supporting investment management?
• Quality in AI. How to maximise the impact and minimise risks of AI. Learn practical tools, methods, and proven frameworks for identifying which parts of your function AI can have a high-impact, how to assess and manage or mitigate risks of AI.
• How can we customise and use Large Language Models (LLMs) like Chat GPT as co-pilots for productivity? What are their capabilities and limitations and what can be done to address them?
• Case Study (TBC): e.g. Growth private equity value creation. Using AI to accelerate portfolio company growth and valuations.
• AI clinic (optional for those who wish to use it): on a 1:1 basic work through applying AI to a  challenge or opportunity in your function
• Hands-on practice: Practise select generative AI tools
• Best practices and takeaways: Get valuable insights into what it takes to start to successfully use AI in your role and get measurable productivity improvements.

Dr Tillman Weyde is a Reader at the Department of Computer Science, City, University of London, a member of the Research Centre for Adaptive Computing and Machine Learning and of the Data Science Institute at City, University of London and Director of Artificial Intelligence & Data Science at equitably.ai. He manages data scientists working at equitably.ai, captures leading edge AI research from universities, and works to apply them to solve business problems through AI. He has published 150+ peer reviewed papers, has won research grants from national and international institutions along with companies and has been awarded several awards for research and developed award winning software.

John Paul Danaee is Director of Project Management and Quality at equitably.ai.

He specialises in application of proven quality methods to de-risk and maximise the impact of AI including AI use case and business case development, AI impact assessment, AI risk management and AI programme design and governance. He regularly speaks and writes about AI. He has delivered webinars for Department for Business & Trade, moderated AI panels for Bayes Business School and has been  commissioned by editor of Quality World Magazine to write “a practical guide for using quality competencies in enterprise artificial intelligence: how quality can reduce risks and maximise the impact of artificial intelligence”.

He has 30+ years of experience combining investments, performance improvement and marketing across asset management, financial services and technology internationally (UK, Australia, US, Europe etc.). His investment expertise includes roles covering company stock exchange listings (IPOs) and private equity in HSBC Group and KPMG. He has a master’s in finance and investments and has conducted research into mid-market private equity at Bayes Business School, City University of London, supported by the British Private Equity & Venture Capital Association (BVCA).

He views AI through the prism of performance improvement where he has delivered some 20 enterprise-wide improvement projects and initiatives in companies including mid-market private equity portfolio companies and companies of HSBC Group internationally. He practises agile principles, is certified in LEAN Six Sigma as a Master Black Belt coach and has been admitted as a Chartered Quality Professional by the Chartered Quality Institute.

This course is primarily designed for those in support functions in asset management and in particular those in: Sales and marketing, Product development, client Services, relationship management and investor relations, research and analysis, operations and admin, IT and HR.

IA Member £395.00 +VAT
Non-Member £545.00 +VAT

Pay using a credit card online, or if you wish to be invoiced please email your full details to: Training@theia.org

PLEASE NOTE: Full payment for the course must be made prior to the course commencement date.

• Any cancellation must be made in writing.
• For all cancellation received 15-30 days prior to the course start date, 50% of the course fee is still payable.
• No refund is given for a cancellation made 14 days or less prior to the commencement of a course.
• Transferring from one course to another is treated as a cancellation.
• You can substitute one delegate for another at no additional cost. In this instance, please give two business days’ notice.

Hybrid Training Courses:

Hybrid deliveries of our training allows participants on our courses the option to attend in-person here from our offices at Camomile Court, or you can attend virtually via MS Teams.

Please be advised a training course could change from hybrid delivery to solely virtual delivery. In such an event, we will inform delegates at least one week prior to the course delivery date.

There are a limited number of in-person spaces available on this course and this will be allocated on a first come first served basis.