Fintech course overview
This immersive two-day Imperial Fintech course 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.
For the virtual Fintech programme, you will have access to the learning platform from the programme start date, giving you an opportunity to familiarise yourself with the learning platform and prepare for the live sessions and programme ahead. Live sessions will begin on 17th June 2021.
Fintech Banking Programme
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.
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.
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
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This on-campus programme accounts for 2 days worth of training time.
This virtual programme accounts for 20 hours worth of training time.
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.
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?
Helene Panzarino, Programme Co-Director at Imperial College London with Tom Britton GapCap, Co-founder SyndicateRoom, Non-Executive Director UK Business Angel Association
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
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
Teaching sessions begin on 24th November 2020. You will have access to the learning platform from 17th November 2020. There will be no formal teaching between these dates, though you will have the opportunity to familiarise yourself with the learning platform and prepare for the programme.
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Deeph Chana has extensive experience of working on world-leading STEM in academia, industry and government and brings a wealth of knowledge and expertise to Imperial Executive Education Programmes. He is the Programme Co-Director of the Imperial Fintech: Foundations, Applications and Impact programme and Professor of Practice within Imperial College Business School. Deeph is also Deputy Director of the Institute for Security Science Technology, co-founder of the UK-Government funded Research Institute in Trustworthy Industrial Control Systems and Imperial's FinTech Network of Excellence.
Originally a commercial banker, Helene is a highly experienced FinTech Programme Director, exited entrepreneur, educator and author. Her most recent role was MD of the global Rainmaking Colab FinTech Programme, a world-first, post-accelerator programme for Series A+ FinTechs and Tier 1 financial institutions. Responsible for the inaugural programme of education and events for Innovate Finance, Helene is also an Associate Director of the LIBF Digital Banking Centre, the Lead Fellow and creator on a world-first FinTech Pathway in a Masters in Tech Entrepreneurship Degree for UCL, and co-creator and lead delivery partner on the Imperial College FinTech Executive Education Programme.
José-Luis Peydró is Professor of Finance at Imperial College Business School. José-Luis is currently an advisor for organisations such as the Bank of Spain and the European Central Bank on topics such as non-banks, shadow banks, fintech, systematic risk, financial crises, macroeconomics, and credit and monetary policy.
Stephen is an Associate Professor of Economics at Imperial College Business School. He regularly advises central banks on organisational economics and monetary policy. Stephen’s research focuses on unstructured data sources and machine learning methods.
Alfonso Delgado De Molina Rius
Alfonso is an Emerging Tech Consultant and Computer Science Ph.D. student at Imperial College London. He is the founder of the Oxford Fintech & SmartLaw Society and is involved in various initiatives in the digital space, such as Emerchain Capital (a VC firm) and Uinspire (a social enterprise). He also works with organisations in helping streamline business processes across financial institutions.
Jason is the Chief Technology Advocate at Starling Bank. Jason is an expert in data architecture, spending most of his time creating and delivering software for Starling Bank platform. Starling Bank is a digital, mobile-only challenger bank based in the United Kingdom, operating current accounts, and business banking.
Tom is the Chief Commercial Officer for ETFmatic and has worked in the Fintech space founding Tech startups. ETFmatic provides customers with an easy way to manage their investment goals. ETFmatic uses index-based investment strategies and Exchange Traded Funds (ETFs) to construct and manage unique investment portfolios tailored to customers' personal preferences and circumstances.
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 research is funded by industry partners, thus the work is related and applied to the new field of cryptocurrencies and distributed ledger technology, taking advantage of the interdisciplinary nature of the research.
"Insightful perspectives on the impact of FinTech on Banking supported by real examples from leading FinTechs companies; made extra special by sharing with a diverse group of delegates."
"An excellent course with some high profile presenters from the Finance sector, elements applicable across the sector and with a good mix of attendees."
Attending the two-week Fintech Virtual Programme was definitely a good use of my time during lockdown amid the everchanging market environment during the pandemic. The course was well structured - with introduction of key concept of fintech followed by a deeper dive in subtopics. As a working professional in the Financial service sector, the course deepened my understanding of the Fintech horizon. It is also very interesting to hear different prospects from other students from various backgrounds. I will definitely try to attend another virtual course in the future with Imperial College if possible.