This course aims to equip students with a comprehensive and profound understanding of Financial Technology’s core principles, preparing to navigate, contribute to, and thrive in this ever-evolving domain; prepare students to delve deeply into the dynamic intersection of finance and technology, exploring the revolutionary transformations shaping the world of global finance, banking, and financial services.

In this course, students will discover the disruptive potential of FinTech and Web3.0, revealing its power to redefine a multitude of financial sectors, including payments, capital raising, remittances, consumer banking, and B2B banking. In addition, students will be introduced to a myriad of innovative financial mediums such as micro-payments via mobile apps, P2P lending platforms, integrated social media spending, and the intelligence of robo-advisors optimizing investment decisions, among others.

Real-world case studies will be a cornerstone of this course’s learning approach, enhancing students’ understanding with practical insights and illustrating the transformative impact of disruptive technologies in creating a new, improved financial ecosystem. These carefully selected cases will not only unveil the intrinsic necessity driving the evolution of the financial landscape but also elucidate the practical methodologies and technologies underpinning this transformation.

This course focuses on the application of machine learning in the financial services industry. It aims to equip students with the necessary skills and expertise to utilize machine learning algorithms and techniques in finance. The course covers the fundamentals of machine learning and explores its application in areas such as stock market forecasting, asset valuation, risk and fraud detection, portfolio management (robo-advisors), and sentiment analysis. Additionally, participants will learn about the factors and steps involved in deploying machine learning models for production use. By gaining knowledge in these areas, students will be prepared to navigate the evolving landscape of the financial services industry and harness the power of machine learning to drive innovation and create value.

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, bonds and virtual assets.  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 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 programming language.

In the current era of Big Data, the capabilities of a language/platform/tool 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 language is selected in this course because it is the most popular option for big data processing due to its simple usage and wide set of data processing libraries. It is also preferred for making scalable applications and can be easily integrated with web applications.

This course aims at providing a thorough understanding and hands-on experience in blockchain technology and its applications in financial industry, especially with respect to virtual assets (cryptocurrencies, NFTs) and smart contracts. This course will traverse the core concepts of blockchain protocol, encompassing an array of essential operations and practical engagements crucial for mastering blockchain technology. The course will start by unraveling the fundamental principles of blockchain protocol. Students will explore the mechanics of creating nodes on blockchain network, establishing and managing accounts, securely unlocking accounts, and delving into the mining process. In addition, this couse will decipher oracles and understanding their role in connecting the blockchain with real-world data, exploring layer 2 solutions like sidechains and state channels for scaling blockchain networks, immersing in the interaction between wallets, decentralized applications (dApps), and the blockchain.

Interactive sessions, workshops, real-world case studies, and sharing from seasoned industry practitioners will facilitate a holistic understanding of blockchain technology and virtual assets. These sessions aim to foster a deep understanding of how blockchain technology can revolutionize not just the financial industry but various other sectors, preparing participants to harness blockchain technology for practical and innovative solutions.

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.

As the global marketplace swiftly transitions towards a digital economy, the rise of financial technology (FinTech) and conducive governmental initiatives are at the forefront. This evolution, while catalyzing easier access to financial services and enriching customer experiences, also beckons a surge in criminal targeting, given the financial system’s lucrative nature. Open platforms, despite their myriad advantages, necessitate a delicate balance between accessibility and security to mitigate the burgeoning threats. The escalating frequency and scope of cyber-attacks not only accrue financial losses but also draw heightened regulatory scrutiny, thereby exerting pressure on financial institutions to bolster their cybersecurity measures and ensure compliance.

This course is designed to equip students with a pragmatic understanding of cybersecurity and privacy within the FinTech realm. Through a blend of theoretical knowledge and real-world insights, students will delve into the pivotal security and information protection challenges enveloping the FinTech sector. Additionally, the course provides a comprehensive overview of contemporary regulations and industry compliance frameworks, including the European Union’s General Data Protection Regulation (GDPR). Students will garner an understanding of the regulatory landscape, enabling them to navigate and adhere to the stringent security and privacy mandates that govern the financial technology ecosystem. Through a blend of case studies, interactive discussions, and practical exercises, students will be well-versed in devising and implementing robust cybersecurity strategies, ensuring not only organizational resilience but also fostering a culture of privacy and trust amidst digital transformation.