MSc Financial Technology

We'll discuss the emerging areas of Digital Currencies and Decentralised Finance (or DeFi). By utilising blockchain and smart contract technologies, DeFi provides a new platform for programmable, automated finance services that remove the reliance on central trust and intermediaries.

We will examine the economics of blockchains, decentralised applications like lending protocols and exchanges, and stablecoins, which are the bridge between decentralised and centralised finance. We will also consider alternative applications like the rise of central bank digital currencies. You will examine critically the welfare and associated risks of these applications, and compare them to traditional financial markets. In a group project, you'll conduct a case study and critically evaluate the design of a DeFi protocol.

In this module, we will demystify Generative AI and illuminate its crucial impact on finance. You will gain insights into various generative models and hone Python and TensorFlow skills, with a focus on financial data management.

Through our pragmatic approach, you will apply key generative AI concepts like Generative Adversarial Networks, Transformer Models, Diffusion models and Natural Language Processing to real-world finance scenarios. As we round off the module, we will project into the future of Generative AI in finance and engage in essential discussions on ethical implications. Our primary goal is to empower you with the know-how and aptitude to leverage Generative AI in finance, enhancing decision-making and pioneering innovative strategies.

The main aim of this module is to introduce students to Finance in general and in particular to modern theories and practices of Asset Pricing and Financial Management.

The key is the modelling and measurement of uncertainty (risk), how investors make decisions in the presence of such uncertainty, and how such behaviours drive both time series and cross-section of asset prices and returns in equilibrium.

This module will provide insights into the ongoing Financial Revolution in the consumer financial services and to showcase how digitalisation transforms the existing financial sector by providing opportunities for new contenders and incumbent actors.

Utilising digital technologies (e.g. Blockchain, Open APIs, Artificial Intelligence, Advanced Analytics), FinTech start-ups successfully venture in traditional financial areas, such as payments, lending, wealth management, investments, trading, and insurance. By increasing the availability of and accessibility to financial services through technology and regulatory changes, the Finech Revolution heralds the financial inclusion of a number of individuals and businesses, who are currently not participating efficiently in the existing financial systems. 

Upon completing this module, you will understand:

• The innovation mechanisms and partnership strategies that characterise the FinTech Revolution
• How emerging technologies change consumer financial services
• The essence of platformisation of the finance sector
• How to design responsibly consumer financial services and ensure their adoption.

Blockchain is a distributed ledger technology that provides proof of ownership and allows for the efficient, secure exchange of ownership. The main aim of this module is to introduce you to technologies behind distributed ledgers in general, and blockchain in particular.

The central topic of the course is understanding blockchain technology and its application to decentralized finance or DeFi. Blockchain is a technology with very special features such as immutability and a high level of security. The advantage of blockchain is that it provides a transactional or verification framework without the need for trust-ensuring central parties (e.g., banks). This reduces transaction costs and lowers the possibility of fraud.

This module is specifically designed to establish a robust programming skillset. This immersive and hands-on module will provide a comprehensive understanding of the Python programming language, with a specific focus on its applications in data analysis and machine learning.

You'll explore the entire spectrum of big data analysis, starting from essential descriptive analysis tasks such as data cleaning, data preparation, data wrangling, and visualisation. You will then progress towards advanced prescriptive analysis elements, including time series analysis and machine learning. We will also explore the essential difference between traditional and big data approaches, and the key data engineering and architectural patterns associated with each.

This module explores cyber security and attacks from different perspectives of hackers, criminal, political, industrial and regulatory perspectives. You'll explore current methods and motivations of types of cyberattacks and defences to ascertain the levels of risk, organisational culture and operational readiness in the impact on personal, operational and organisational performance. We will define the wider context of backup, recovery, escrow, intrusion detection and penetration testing, automated cyber defence systems and other infrastructure and organisational leadership issues including business continuity, insurance, liability, surveillance, security-by-design and emerging new cyber security start-ups and entrepreneurship commercial models in cyber security and intelligence.

You will explore organisational and governmental mandates and developments in security compliance, law and regulations, privacy and ethics, confidentiality, intellectual property, copyright, open-source versus proprietary licensing, trust models and the industrial, country and international standards.

We will examine methods to evaluate impact on costs, benefits and investment decisions for an organisation in communicating cyber risk and business cases through to operational scenarios for monitoring and responding to current and potential types of cyber threats. The module studies current and future technical, social, legal and political developments in Cyber security including narrative engineering, psychological profiling, ethical hacking, quantum cryptography, Artificial Intelligence in cyber security and chip level security and Internet of Things architectures and how this impacts skills, products, services and operational processes and the supply chain and markets.

The module aims to link with current leading standards including Cyber essentials, the UK Government National Cyber Security Centre (NCSC) and international country standards in Asia, America and Europe as well as cyber security standards including; IASME, ISO 27001/2, PCI-DSS, PAS 555 and ISF and the HMG Security Policies and NIST frameworks.