AI & Machine Learning in Financial Services

Imperial College Business School

How long?

  • 3 days
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Imperial College Business School

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About the course

AI and Machine Learning for Financial Services is a three-day programme that explores the role of emerging algorithmic techniques on financial decisions. Drawing on knowledge from Imperial College Business School faculty, industry experts, case studies and your peers, you will apply key elements of artificial intelligence (AI) and machine learning to your organisation, increasing the efficiency and accuracy of decision making.

Through this immersive, hands-on programme you will gain an understanding of the fundamentals of AI and machine learning and how they apply to financial functions such as fraud detection, lending processes, asset management, risk assessment, regulatory compliance and beyond.

You will walk away prepared to implement what you’ve learnt, ensuring your organisation is maximising the value of its live and historic data.

Learning outcomes

Gain a good understanding of the main concepts of AI and machine learning

Understand how to operationalise AI and machine learning

Be able to identify key areas to apply AI and machine learning techniques within your teams and workplace

Be able to appreciate the advantages that AI and machine learning techniques can add to various portfolio and risk management strategies

Programme content

Before you arrive

Upon registration, you will be able to access our online hub. Here you will find a range of reading and activities to prepare you before you arrive with us on campus. The Hub will also provide you with the opportunity to meet fellow participants virtually, kickstarting your networking.

Day 1

Overview, Expectations & Introductions

Russell Miller, Director of Learning Solutions & Innovations at Imperial College Business School

Machine Learning Fundamentals

Marcin Kacperczyk, Professor of Finance at Imperial College Business School

Marcin will introduce some fundamental concepts and methodologies of machine learning. We start with the big picture before exploring in more depth some of the key concepts that will support your learning on Day 2.

Machine Learning Fundamentals

Marcin Kacperczyk, Professor of Finance at Imperial College Business School

Continuation of the morning session

The IT Organisation: Operationalising AI & ML

Deeph Chana, Professor of Practice at Imperial College Business School

The barriers to entry are much lower than assumed (and getting lower). What are the main requirements your technology and IT teams need to consider?

Network Drinks

Join your colleagues at the end of day 1 for a chat over drinks and canapés

Day 2

Machine Learning for Portfolio Management

Paolo Zaffaroni, Professor in Financial Econometrics at Imperial College Business School

Understand how AI and Machine Learning solutions are improving investment decisions, allowing organisations to manage their financial assets, reducing costs and ultimately increasing revenues.

Machine Learning for Risk Management

Enrico Biffis, Associate Professor of Actuarial Finance at Imperial College Business School

Risk management is a complex system. We will be looking at dependency patterns and the importance of capturing their sequential evolution.

Machine Learning for Systematic Strategies

Andrea Buraschi, Professor of Finance at Imperial College Business School

We answer the question of how Big Data and Commodity Trading Advisor (CTA) are shaping the investment landscape.

Day 3

Deep Learning Algorithms

Pierre Dangauthier, Head of Quantitative Analytics at Smarkets

We explore the importance of using available data in Machine Learning and make the case for the role of human guidance and intuition in its application.

Regulatory Risks of AI Products: A pensions example

David Miles, Professor of Financial Economics at Imperial College Business School As the European Commission pledges to attempt to regulate AI, experts are sceptical about how to frame the AI legal framework. In this session, David will explain the impact of AI regulation for financial service firms using a pensions example.

Investing in AI – The next big thing?

London is one of the global hot spots for FinTech and tech funding. The adoption of disruptive and innovative technologies such as the application of AI/ML has attracted the top tier investors and FinTech founders. Discover where the smart money is going and meet active investors in this space.

Reflection & Consolidation & Certificates

Russell Miller, Director of Learning Solutions & Innovations at Imperial College Business School

Who should attend

This programme is designed for professionals working in the financial services industry, including members of the exchanges and regulatory agencies, and executives who make decisions that affect financial results. To get the most from the three intensive days, you will need a good grounding in finance and statistical techniques.

Trust the experts

Enrico Biffis

Summary Enrico Biffis is Associate Professor of Actuarial Finance at Imperial College Business School, a fellow of the Pensions Institute in London, and a member of the Munich Risk and Insurance Centre at LMU Munich. His areas of expertise are risk analysis and asset-liability management, with a...


Andrea Buraschi

Summary Personal web page Professor Buraschi’s research interests are in the fields of Financial Economics, Asset Pricing and Derivatives, and Financial Econometrics. Professor Buraschi has previously held at The University of Chicago Booth School of Business as a Visiting Professor of Finance...


Marcin Kacperczyk

Summary Private Website


Paolo Zaffaroni

Summary   Paolo is Professor in Financial Econometrics at Imperial College Business School. He has a summa cum laude degree in economic statistics from Roma and holds a PhD  in Econometrics  from the London School of Economics. He is also  teaching at the University of Rome La Sapienza  and  ha...


Pierre Dangauthier

Pierre Dangauthier is the head of Quantitative Analytics at Smarkets, one of the leading betting exchanges. He is specialized in systematic market making and machine learning. He received a Ph.D. degree in statistical learning in 2007 from INRIA for a joint work with Microsoft Research Cambridge...


Deeph Chana

Deeph has extensive experience of working on world leading STEM in academia, industry and government. He is Professor of Practice within Imperial's Business School, Deputy Director of the Institute for Security Science Technology and is co-founder of the UK-Goverment funded Research Institute in ...


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AI & Machine Learning in Financial Services

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AI & Machine Learning in Financial Services at Imperial College Business School

3490 GBP $4,477

Jun 17—19, 2020

London, United Kingdom


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