Lincoln University

What you'll study

This programme blends core investment disciplines with contemporary fintech topics. Typical modules cover:

• Financial Markets and Instruments – modern portfolio theory, fixed income, equities, derivatives and market microstructure.
• Quantitative Methods and Financial Econometrics – time series, regression techniques, factor models and back-testing.
• Financial Data Analytics and Programming – Python/R for finance, database access, data cleaning and visualization.
• Algorithmic and High-Frequency Trading – strategy design, execution systems and performance measurement.
• Blockchain, Cryptocurrencies and Digital Assets – distributed ledger technology, token economics and institutional considerations.
• Risk Management and Compliance – market, credit and operational risk plus regulatory frameworks affecting fintech and investment firms.
• Machine Learning Applications in Finance – supervised and unsupervised methods applied to forecasting, classification and anomaly detection.
• Investment Management and Portfolio Construction – asset allocation, performance attribution and portfolio optimisation.
• Capstone Project or Dissertation – an applied research project or industry-linked consultancy that integrates fintech and investment concepts.

The programme is delivered through lectures, practical labs, workshops and a major independent project. Assessment typically combines coursework, programming assignments, case studies and the capstone or dissertation.

Entry requirements

• An undergraduate degree from a recognised institution, usually in finance, economics, mathematics, statistics, computer science, engineering or a closely related discipline. Equivalent professional qualifications and relevant work experience may be considered.
• A minimum academic performance standard as set by the University (applicants with strong quantitative skills are favoured).
• Evidence of quantitative and computing ability: prior coursework in statistics, calculus or programming is advantageous. Applicants without formal computing background may be required to complete bridging study.
• English language proficiency for applicants whose first language is not English, demonstrated by an approved test or equivalent evidence of prior study in English.
• Curriculum vitae and a personal statement outlining motivations and relevant experience; referees may be requested for some applicants.

Career prospects

Graduates are equipped for roles across finance and technology sectors. Common career paths include:

• Investment analyst, portfolio manager or asset management professional
• Quantitative analyst or model developer in banks, hedge funds and trading firms
• Fintech product manager, developer or data scientist
• Risk manager, compliance analyst or regulatory technology (RegTech) specialist
• Roles in digital asset firms, crypto exchanges and custody providers
• Consultancy or advisory positions supporting digital transformation in financial services

Team projects, the capstone and industry engagement are designed to build practical experience and employer-relevant skills, enhancing graduate employability across traditional finance and emerging fintech ventures.

Why study at Lincoln University

• Interdisciplinary focus that brings together finance, data science and technology to reflect how financial services are evolving.
• Small cohort sizes that support close interaction with academic staff and personalised feedback on practical work.
• Practical, hands-on learning through programming labs, trading simulations and an applied capstone project linked to industry problems.
• Access to career development services and industry networks to help with internships, project partnerships and graduate employment pathways.
• Research-informed teaching drawing on staff expertise in finance, econometrics and fintech topics, ensuring course content stays current with sector developments.