The world of global finance, banking and financial services is changing rapidly with the emergence of financial technologies, commonly referred to as FinTech. FinTech is also the term which encompasses the disruption of traditional functions: payments, capital raising, remittances, consumer banking, B2B banking and much more. Over the last few years, FinTech has allowed for new mediums of finance, from micro-payments over mobile apps, P2P lending and spending integrated into social media, new electronic methods of institutions trade, through to robo-advisors helping to make decisions about investment portfolios to name a few. This course provides students with the latest practical knowledge on FinTech, enabling students to understand the underlying reasons of why change was needed, and through industry case studies, understand how disruptive technologies have helped to create a new ecosystem. We are only at the early stages of FinTech, thus students will need to prepare themselves with a deeper understanding of Financial Technology.

Machine learning, Big Data and Artificial Intelligence are rapidly becoming key pillars to help financial organisations make more accurate and timely decisions, and to uncover previously undiscovered patterns and relationships with data. This is highly impactful for the Financial Industry as a whole, due to the immense amount of financial data being transacted daily. Machine learning uses computers to run scientific models that forecast future behaviours, outcomes, and trends, and has given birth to new-age algorithmic trading, robo-advisors, and improved understanding of human behaviour in the capital marketplace. This course will give students clearer understanding of the fundamentals of machine learning theory, combined with practical scenarios and hands-on exercises. The course will also draw from numerous case studies and applications, so that students also learn how to build and apply their own algorithms to real life situations.

This course introduces students to the concepts and techniques in making business financial decisions. The course focuses on the following issues concerning corporate financial managers. These include the decision over the means of financing (Financing Decision), the selection of investment projects (Capital Budgeting), and the making of short-term financial decisions (Current Asset Management). Such knowledge should be helpful to students to explore into other Finance subject areas such as Investments, Personal Financial Planning, Banking, Real Estates, Insurance, Derivatives, International Finance, and Risk Management. Although the corporate perspective will be adopted throughout the course, it will become apparent that the theories, concepts, and techniques are applicable to personal and public financial decision-making. Upon completion of the course, students are expected to gain an appreciation of the role of the financial discipline in the overall economic decision-making process.

This course analyses different principles in the valuation of financial assets including common, preferred stocks and bonds. The development of portfolio concepts and capital market theories are introduced. The issue of market efficiency is investigated while asset pricing models are discussed. Techniques on performance evaluation are introduced and performance of mutual funds is also examined. After completing this course, students should be able to perform sound investment and portfolio analysis.

The course is designed to provide a gentle, yet intense, introduction to programming using Python and R for students with little or no prior experience in programming. The course will focus on planning and organizing programs in Business and Data Analytics, as well as the grammar of the Python and R programming languages. In the current era of Big Data, the capabilities of a language/platform/tools to perform big data processing and generating quick insights are important to business to remain competitive in the market. This quick and dynamic insight (which changes very frequently) is valuable to the organizations. Python and R languages are selected in this course because they are the most popular options for big data processing due to their simple usage and wide set of data processing libraries. They are also preferred for making scalable applications and can be easily integrated with web applications.

With the rise of disruptive technology, particularly in the area of FinTech, new concepts in the use of money, payments, identity, and security need to be looked at through a new lens. Under the rapidly changing landscape, it’s important for an organization to respond early and effectively to ride the wave and take advantage of the new opportunities. Through workshops, round-table discussions, case studies and sharing from expert industry practitioners, the course widens and deepens students’ understanding of the rapidly changing landscape and the impact of Blockchain on the traditional financial industry. Students will develop new insights and perspectives, grab the opportunities from blockchain and cryptocurrency, and harness new technologies to take the financial industry to the next level.

This course enables students to understand the fundamental concepts in derivatives and risk management and their applications. Derivatives have been used extensively in hedging, arbitrage, speculation, and the design of financial products. Executives with knowledge in derivatives can better assess the risk of a business entity. Precautions of using derivatives are also emphasised. Besides application of derivatives in risk management, other techniques in risk management are introduced. In the global environment of business, risk management is an indispensable tool for business managers. Students will be able to apply the concepts in this course to real-world situations after the completion of this course.

The ecosystem for conducting business is changing rapidly towards a digital economy with the emergence of FinTech. This has introduced new attack surfaces, where financial systems are now one of the most targeted industries by criminals. While open platforms brings easier access to financial services and enhanced customer experience, an organization needs to balance the openness with being secure. As cyber attacks become more frequent and widespread, financial losses and data breaches result in the need for regulators to take closer notice; all these put pressure on financial institutions to act and comply. This course will provide students with a practical perspective on cybersecurity and privacy, enabling them to understand the key security and information protection issues under the broad umbrella of FinTech. This course will also cover the latest regulations such as EU’s General Data Protection Regulation (GDPR) and industry compliance frameworks on security and privacy.