| CODE | CIS3400 | ||||||||||||
| TITLE | Introduction to Fintech | ||||||||||||
| UM LEVEL | 03 - Years 2, 3, 4 in Modular Undergraduate Course | ||||||||||||
| MQF LEVEL | 6 | ||||||||||||
| ECTS CREDITS | 5 | ||||||||||||
| DEPARTMENT | Computer Information Systems | ||||||||||||
| DESCRIPTION | "Fintech" is a broad term that is used to describe the application of AI, Machine Learning, Cloud-based tools, open-source software and other kinds technology to improve finance, banking and investing. Fintech has the potential to disrupt today's financial systems. Fintech, an abbreviation for financial technology, is one of the hottest new trends in the digital age. It promises to radically changing the way we live and conduct business. Study-unit Aims: The aims of the study-unit are to: i) Introduce the best practices, standards, techniques, and concepts for obtaining data; ii) Use case studies to clean obtained data and use best practices to share the data; iii) Differentiate between different algorithms that can be applied to explore and learn more about the data; iv) Evaluate which is the best Machine Learning algorithm to apply depending on the type of data available; v) Apply visualisation best practises to present interesting conclusions drawn from the data. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: • Describe the technologies underlying cryptocurrencies and Blockchains (DLTs); • Design smart contracts and decentralized applications; • Understand AI and Machine Learning principles and assess their impact on traditional banking and payment industries; • Apply machine learning in robo-advising and FinTech; • Engage in the process of FinTech innovation. 2. Skills By the end of the study-unit the student will be able to: 1) Discuss and critically analyse outcomes from use-cases covering current open problems in the field; 2) Search for state of the art techniques to solve domain specific problems; 3) Present a solution using proper visualisation tools; 4) Analytical skills: Develop analytical skills by applying machine learning techniques to a dataset; 5) Assessment Skills: Use industry standard techniques to evaluate the performance of the algorithm chosen; 6) Communications skills: Use techniques to share data with colleagues and present findings to a non-technical audience effectively. Main Text/s and any supplementary readings: - Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction by Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder, Princeton University Press, ISBN-13: 978-0691171692. - Ethereum: Blockchains, Digital Assets, Smart Contracts, Decentralized Autonomous Organizations by Henning Diedrich, CreateSpace Independent Publishing Platform, ISBN-13: 978-1523930470. - Blockchain Applications: A Hands-on Approach. by Arshdeep Bahga and Vijay Madisetti, Vpt, ISBN-13: 978-0996025560. - The Fintech Book - the Financial Technology Handbook for Investors, Entrepreneurs and Visionaries Paperback – 1 Apr 2016, by Susanne Chishti (Author), Janos Barberis. ISBN-13: 978-1119218876. |
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| ADDITIONAL NOTES | Pre-Requisite Study-unit: CIS3187 | ||||||||||||
| STUDY-UNIT TYPE | Lecture, Independent Study & Tutorial | ||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | John M. Abela (Co-ord.) Vincent Vella |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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