Fintech Programme

Imperial College Business School

How long?

  • from 2 days
  • online, in person

Imperial College Business School


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Who should attend

This programme is designed for mid to senior-level professionals wanting to gain an understating of how the fintech ecosystem operates. Participants come from all over the world and hold an interest in strategy and innovation, working in industries such as construction, professional services and finance. An understating of finance principles would be advantageous however no banking experience is required.

About the course

This immersive two-day Fintech programme develops a hands-on understanding of the different elements of fintech and how they are disrupting financial and banking sectors. The programme introduces participants to the origins of banking and explores how digital transformation has remodelled the sector, creating alternative finance models and a new wave of digital banks.

Participants will gain insights into the different elements of fintech such as APIs, blockchain and machine learning, and how they can be applied to various financial and banking scenarios. Imperial College Business School finance faculty and fintech industry leaders will blend academic thinking with technological discovery to give a holistic understanding of how the fintech ecosystem operates.

Learning outcomes

Undertake a deep-dive into how fintech is innovating the banking sector

Understand the regulatory conditions for fintech and digital banks

Understand at a high-level how algorithms such as machine learning operate and how they can be applied to finance

Through data visualisation, understand how blockchain is changing the financial services industry

Programme content

Day 1

Introduction to FinTech

José-Luis Peydró, Professor of Finance at Imperial College Business School This session will provide an overview of the changing FinTech ecosystem with a special focus on how FinTech affects the banking industry. To understand the disruption in banking one first needs to understand the main pillars of banks. What is the origin of banking? What has led to the current form of banks? Thus, understanding the strengths and weaknesses of banks can help us isolate the areas where one could see disruption. We will start the session by studying banks in their traditional form and then move on to FinTech where we will examine new business models and their potential to change the intermediation landscape.

Alternative Finance

Helene Panzarino, Programme Co-Director at Imperial College London In the age of the Internet and social networking, banks have lost their monopoly on finance. A growing number of Crowdfunding operators, P2P lenders, and investment-based platforms allow businesses and consumers to access capital on favourable terms, and with much less red tape. However, as the alternative finance industry matures, existing operators have been arguing for greater regulatory oversight to act as a barrier to entry for new platforms. What does the future hold?

Alternative Finance

Helene Panzarino, Programme Co-Director at Imperial College London with Tom Britton GapCap, Co-founder SyndicateRoom, Non-Executive Director UK Business Angel Association

Digital Banks

Helene Panzarino, Programme Co-Director at Imperial College London with Jason Maude, Chief Technology Advocate at Starling Bank Today, there is a growing trend towards digital banks, in this module we talk about the strengths of the digital banks and how they differ from the normal banks. Also, we explore the challenges normal banks face in their digital transition

Programme drinks reception

Day 2

Finance and Machine Learning

Stephen Hansen, Associate Professor of Economics at Imperial College Business School This session introduces the main approaches to finance based on machine learning techniques. I will argue that machine learning revolves around the problem of prediction, while many economic applications revolve around parameter estimation. Thus, a crucial element in successfully applying machine learning to finance requires finding relevant tasks. At the same time, machine learning algorithms can be applied naively or their output can be misinterpreted. The class aims to make them conceptually easier to use by providing a crisper understanding of how these algorithms work, where they succeed, and where they can fail—and thus where they can be most usefully applied.

Finance and Machine Learning (continued)

Stephen Hansen, Associate Professor of Economics at Imperial College Business School

Robo Advising Demo platform

Tom Stevens, Chief Commercial Officer at ETFmatic ETFmatic is a platform that enables anyone to easily convert their savings into diversified investments. Tom will showcase how the platform works and how relevant this type of technology is for the Fintech world.


Alfonso Delgado, Emerging Tech Consultant and Computer Science Ph.D. student at Imperial College London A blockchain is usually described as a distributed ledger – a database of records shared by all clients that have access to it. This description is not incorrect, but it leaves a lot to be desired. It’s like calling a car a “horseless carriage” or a handheld personal computer a “smartphone.” A blockchain is really a computer – a finite-state machine. Currently, it is not a very good computer. It is very slow, it is not exact, and it is also very expensive. But, it is a truly global computer that does not reside in any particular physical or virtual machine. And, very importantly, it allows anonymous users to share their private computing power and memory capacity for a fee. With the hindsight knowledge of how fundamentally computers have changed the world, we can ask: Does blockchain have the potential to fundamentally change the financial services industry?

BitCoin demonstration at the Data Observatory

Philip Nadler, Consultant for the Data Science Institute at Imperial College London The KPMG Data Observatory (DO), the largest of its kind in Europe, features an enveloping circular wall of 64 monitors powered by 32 computers facilitating 313 degrees of surround vision. Opened in November 2015, The DO provides an opportunity for academics and industry to visualise data in a way that uncovers new insights and promotes the communication of complex data sets and analysis in an immersive and multi-dimensional environment. Designed, built by, and housed within the Data Science Institute, the DO will enable decision-makers to derive new implications and actions from interrogating data sets in an innovative, unique environment.

Wrap up and programme close


Helene Panzarino

As both an independent business consultant working on a one-to-one basis and as part of a team on larger access to finance programmes, workshops and seminars, Helene has worked with both start-up and high growth small and medium sized businesses. She has worked extensively with intermediaries, ad...

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 ...

José - Luis Peydró

José-Luis Peydró is ICREA Professor of Economics at UPF, Barcelona GSE Research Professor, CREI Research Associate, Professor of Finance at Imperial College London, and CEPR Research Fellow. His research on Banking and Systemic Risk has been published in the top journals in Economics and Finance...

Stephen Hansen

Stephen Hansen is an Associate Professor of Economics at the University of Oxford and a Fellow of University College. He received his BSc Econometrics and Mathematical Economics and PhD in Economics from the London School of Economics. Previously he was Assistant then Associate Professor at Pompe...

Jason Maude

Jason is a developer, coach, debater and public speaker. He has over a decade of experience working in the financial sector, primarily in creating and delivering software. He is passionate about building teams and explaining complex technical concepts to those who are convinced that they won't be...

Tom Stevens

Tom is a strong Business Development professional and analyst with a demonstrated history of working in and founding tech startups. Post studying law and economics at the University of Otago in New Zealand, Tom moved to Madrid where he helped successful Spanish startup "We Are Knitters" enter and...

Philip Nadler

Philip is a Ph.D. Candidate at the Department of Computing and a consultant for the Data Science Institute at Imperial College London. His research interests lay in the combination of econometric and machine learning methodology to explore new possibilities for statistical inference. Philip’s res...

Alfonso Delgado De Molina Rius

Alfonso Delgado de Molina Rius está cursando estudios de doctorado en el Imperial College London (departamento de Ciencias de la Computación), en donde investiga la intersección del Derecho, la Economía y las Ciencias Informáticas. Sus investigaciones más recientes se centran en los “split contr...

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Fintech Programme at Imperial College Business School

From  1800 GBP$2,357

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