BSc (Hons) FinTech with Data Analytics Bachelor's degree at Westminster

The rapid growth of data and its increasing complexity require businesses to adopt efficient computing solutions for data management and analysis. This module equips you with essential skills to design and implement data-driven applications that support business operations, including planning, customer management, and decision-making. You'll learn to work with modern tools such as Python, SQL, and Excel for data processing, storage, and retrieval, gaining hands-on experience in solving real-worl

The module provides you with knowledge and an understanding of finance, financial markets and institutions to build financial and digital literacy skills. You'll acquire knowledge of money management, debt and credit, budgeting, saving and investing. Hands-on training will be provided on the Bloomberg database and you will explore how Excel skills can be applied to solve a variety of financial problems. You will also progress to understand the role of the central banks, functions of different ty

This module provides you with knowledge of the fundamental concepts and analytical tools required for exploring current practices in finance. Emphasis is placed on developing an understanding of contemporary theoretical frameworks and their applications to a broad range of business problems faced by corporations and investing organisations.

The module equips you with the necessary mathematical and numeracy skills required for this finance degree. It is designed to provide you with a sound knowledge of mathematical techniques and their applications in different areas of finance, such as investment decisions, financial markets and risk management. Topics covered include: basic algebra, functions and graphs; solving systems of equations; exponents and logarithms; financial mathematics (time value of money); linear algebra (matrices);

This module develops an understanding of the historical perspectives of FinTech. Theories, design and structure of each of the core elements of a FinTech macrostructure will be examined, namely: Artificial Intelligence, Blockchain, Cloud Computing and Big Data. We aim to explore the nature of the disruption to businesses from these technologies and the emergence of new business models in financial services. The study is grounded in theory, with practical examples to demonstrate the role and rele

This module introduces you to how Entrepreneurship has taken place in the FinTech sector. You will learn about the various business models that ventures in FinTechs adopt. You will study the entrepreneurial mindset, how ideas can be generated and how you can develop a suitable business model canvas with a viable value proposition. You will explore FinTech organisations, their valuations, management and control features. You will also examine how start-up FinTechs are financed from start-ups to t

This module will develop a deep knowledge of well-established financial, computational and statistical theories and methods for solving a variety of business problems. Learning will lead to the synthesis of the knowledge base and skills to demonstrate how statistics, databases and software packages and libraries (Excel, Python etc) are being used to calculate, model and visualise financial data to inform business decision-making.

A study of financial market microstructure examines how markets are organised and function. The financial market theory focuses on the structure of the asset exchanges and trading platforms (including knowledge of displayed and dark pools), price discovery processes and the determinants of spreads and quotes, intra-day trading behaviour, and transaction costs. Your learning will enable you to gain insights into questions such as market efficiency, market stability, and the sources of volatility.

This module provides the basic understanding and knowledge of statistical and econometrics techniques commonly used in financial markets. It aims to develop an understanding of financial theory and to teach students how to apply different financial and analytical techniques to solve a range of problems in the following contexts: financial markets, investment decision-making and risk management. Emphasis is placed on developing a working knowledge and understanding of the following methods: proba

This model provides learning about the principles and applications of Cryptocurrencies and Blockchain Technology. You will be taught how to use relational and non-relational database management systems (SQL and NoSQL). The module provides hands-on skills in the areas of data acquisition, cleansing and loading. Leveraging this knowledge base, you'll move on to examine Blockchain technology and relate this learning to applications in Cryptocurrencies. Building upon this technology, you'll develop

This module explores how to effectively manage the range of operations functions drawing from the traditional and digital perspectives. It considers the business process; the supply chain; operational strategic alignment; systems integration; and the management of information, quality, demand, capacity and resources. It covers aspects of electronic and mobile services, commerce and business; sustainability; innovation and design in products and services; and developments in technology and system

In this module, you'll analyse and evaluate the rapid proliferation of data, with a focus on the fundamental principles of big data management. The course will develop a deeper understanding of the key characteristics of big data – namely, volume, variety, velocity, veracity, value, and variability. The size and complexity of big data present significant challenges in storage, search, sharing, transfer, analysis, and visualisation. You'll critically examine the reliability, validity, and signifi

This module provides you with advanced econometric and financial modelling techniques essential for rigorous data analysis in FinTech environments. Building on foundational statistics, you'll master sophisticated econometric methods, including panel data analysis, advanced cross-sectional models, instrumental variables, difference-in-differences, and causal inference techniques. The module emphasises the practical application of advanced econometric methods to address real-world FinTech research

The module provides you with learning in advanced mathematical and statistical models for analysing large datasets within business and finance contexts. Techniques taught in this module will enable you to critically analyse and evaluate the reliability and validity of information and data. You will learn how to select from a range of mathematical models to forecast future trends and optimise decisions for business and finance. The use of Python and/or R programming languages constitutes an integ

The module is designed to provide a comprehensive and detailed knowledge of investments and an understanding of modern portfolio theory. Particular emphasis on the module is to develop a critical understanding of the nature and organisation of common financial investments, namely money market instruments, equities and government and corporate bonds.