MSc Finance with AI

Module 1: Mastering Finance (30 credits)

Develop advanced knowledge of the key financial principles and strategies that underpin corporate and investment decision-making, and apply them to real-world scenarios rather than textbook abstractions.

❚ Financial institutions, markets and instruments

❚ Capital structure and its impact on the firm

❚ Capital budgeting techniques and investment appraisal

❚ Financial analysis and planning

❚ Financial risk and portfolio management

 

Module 2: Finance and Machine Learning (30 credits)

Build practical competence across the financial data pipeline. You will collect, transform, visualise and analyse financial data using advanced statistical methods and machine learning techniques — and critically evaluate the ethics of doing so.

❚ Data collection and transformation

❚ Data visualisation for financial audiences

❚ Foundational and advanced statistical methods in finance

❚ Applying machine learning techniques to analyse and predict financial trends

❚ Interpreting model output and its limitations

❚ Ethical considerations in financial data analytics

 

Module 3: Next Gen Finance (30 credits)

Develop a critical overview of how financial technologies are reshaping national and global finance, and the systematic knowledge to evaluate the regulatory and ethical frameworks governing them.

❚ Fintech and financial technology innovations

❚ Regulatory frameworks relating to fintech

❚ Sustainable finance and reporting

❚ Ethical principles and decision-making in finance

❚ Environmental, social and governance (ESG) factors

 

Module 4: AI for Business and Professional Practice (30 credits)

Build a critical, practical command of artificial intelligence and its responsible use in professional work. You will learn what current AI can and cannot do, use and evaluate AI tools and workflows in a finance and data analytics context, and design an AI-enabled solution proposal. No coding, model development or deployment expertise is required.

❚ AI literacy: generative AI, machine learning, automation, predictive analytics, large language models and intelligent agents

❚ Prompt design, AI-assisted research, source checking, hallucination, reliability and bias

❚ AI-supported analysis and decision-making with human-in-the-loop judgement

❚ Responsible AI: privacy, GDPR, intellectual property, transparency, explainability, inclusion and accountability

❚ AI-enabled solution planning: problem framing, stakeholder analysis, workflow mapping, risk controls and success measures

 

Module 5: Learning without Limits (30 credits)

Take ownership of your own professional development. You will analyse industry skill trends, map the capabilities you already hold against those the market is demanding, and build an authentic professional identity that communicates your value to employers and collaborators.

❚ Analysing sector reports and future-of-skills research (e.g. World Economic Forum)

❚ Sector-specific versus transferable skills across industries

❚ Recognising learning from work, volunteering and micro-credentials

❚ Skills mapping, peer feedback and reflective video diaries

❚ Personal branding: elevator pitches, LinkedIn, digital portfolios, vlogs and podcasts

 

Module 6: Impact Project (30 credits)

Take full ownership of a self-directed consultancy, business analysis, or entrepreneurship project. This is your opportunity to apply everything you have learned to a real challenge that is independent, career-focused, and tailored to your future goals.

❚ Applied research methods and evidence-based decision-making

❚ Project scoping, management, and impact-driven outcomes

❚ 3,000-word plan or report, accompanied by either a 5-minute video or a voice-over presentation

❚ Translate project experience into career growth and employability