Finance And Data Analytics BSc (Hons)

In choosing to study this course, you will receive rigorous training in areas such as econometrics for finance, programming with Python, theoretical finance, and computational methods. 

You will have the opportunity to study cutting- edge topics such as data mining, machine learning, financial data visualisation, and financial technology. You will be able to combine your knowledge of finance, programming in Python, and analytics to solve finance problems and generate insights.

The BSc Finance and Data Analytics blends together the areas of finance and data analytics and equips you with the knowledge, skills, and abilities to follow a range of careers, e.g. finance and consulting.

The first year equips you with the foundational knowledge of finance and introduces you to Python, the programming language. The second year develops your understanding of advanced finance theories and their implications for the industry. 

You will learn to use Python and industry-leading datasets to empirically test finance theories. You will also learn to use data visualisation techniques to communicate your insights with the audience.

During the third year, you will deepen your knowledge of the finance industry and have the opportunity to take cutting-edge modules such as Data Mining and Machine Learning. 

You will also develop a range of transferable skills, including flexibility, problem-solving ability, commercial awareness, and communication, which are highly valued by employers.

Studying Finance with Data Analytics at Liverpool will enable you to reach your full potential as you will benefit from our range of industry links and research expertise in addition to being exposed to our cutting-edge curriculum, the state-of-the-art computer room, and innovative teaching methodologies.

What You'll Learn:

• Corporate finance
• Financial markets
• Financial econometrics
• Python programming
• Data mining and machine learning
• Data visualisation
• Database management
• Computational methods
• Corporate reporting and analysis
• Financial technology

Syllabus:

• Year 1:
• In the first year of study, you will acquire the foundational knowledge of accounting, finance, and data analytics. During this year, you will learn about the key concepts and datasets and their implications for decision-making. You will also begin to develop an expertise in the area of data analytics and computational methods by using Python to write computer codes to solve finance problems. In addition to your technical abilities, you will also develop key employability skills that will be important in your future career.
• Compulsory Modules
• Introduction To Financial Accounting (acfi101)
• Quantitative Methods For Accounting And Finance (acfi111)
• Introduction To Finance (acfi103)
• Introduction To The Graduate Recruitment Process (ulms170)
• Skills For The Finance Professional (acfi118)
• Data Analytics (acfi130)
• Economics Of Risk And Uncertainty (acfi131)
• Computational Methods (acfi132)
• Year 2:
• In the second year of study, you will build upon the foundations of the first year to learn about advanced finance theories and evaluate their implications for the business world. You will also develop the ability to not only theoretically evaluate key concepts but also to leverage financial datasets to evaluate their empirical relevance. In so doing, you will improve your analytical skills and learn to use Tableau to prepare insightful visual elements. You will achieve this goal by combining your knowledge of finance theory, programming, and econometrics.
• Compulsory Modules
• Econometrics For Finance 1 (acfi225)
• Financial Reporting And Analysis (acfi220)
• Ethics And Regulations In Finance (acfi230)
• Theory Of Finance I (acfi231)
• Database Management (acfi232)
• Econometrics For Finance Ii (acfi233)
• Theory Of Finance Ii (acfi234)
• Financial Data Visualisation (acfi235)
• Year 3:
• In the final year, you will have the opportunity to develop your understanding of the key players of the financial sector, their business models, the key asset classes in financial markets and the impact of technology on the finance sector. You will also have the opportunity to further develop your Python programming skills by learning about topics such as data mining and machine learning. Furthermore, you will have the unique opportunity to put your knowledge of finance, Python programming, and data analytics to practice by completing a year-long research project analysing a substantive finance issue. This is a great opportunity to develop and demonstrate key skills desired by graduate employers.
• In semester one, you will select one module out of the following list: (ACFI317),  (ACFI319), (ACFI331).
• In semester two, you will select two modules out of the following list: (ACFI311), (ACFI320), (ACFI332), (ACFI333).
• Compulsory Modules
• Derivative Securities (acfi310)
• Financial Risk Management (acfi342)
• Banking And The Financial System (acfi330)
• Project In Finance (acfi318)
• Optional Modules
• Issues In Development Finance (acfi317)
• Financial Crises And Defaults (acfi319)
• Behavioural Finance (acfi311)
• Corporate Governance (acfi320)
• Financial Technology (acfi332)
• Institutional Investors And Alternative Investments (acfi333)
• Data Mining And Machine Learning (acfi331)