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If you aspire to lead the future of finance, our MSc Financial Technologies and Artificial Intelligence (AI) is designed for you. The programme’s versatile curriculum will open doors to many high-value professions at the intersection of finance and technology, where expertise in AI and financial innovation is increasingly rewarded.
MSc Financial Technologies and AI is a unique programme that combines classical quantitative finance techniques with cutting-edge developments in financial technology and big data analysis, including machine learning and AI. The curriculum bridges financial theory with practical applications in quantitative trading, risk management, and forecasting. Graduates can pursue prestigious roles such as quantitative traders, risk managers, data scientists, and financial researchers at leading investment banks, hedge funds, and FinTech firms.
Programme overview
Main Subject
Finance
Degree
MSc
Study Level
Masters
Study Mode
On Campus
If you aspire to lead the future of finance, our MSc Financial Technologies and Artificial Intelligence (AI) is designed for you. The programme’s versatile curriculum will open doors to many high-value professions at the intersection of finance and technology, where expertise in AI and financial innovation is increasingly rewarded.
MSc Financial Technologies and AI is a unique programme that combines classical quantitative finance techniques with cutting-edge developments in financial technology and big data analysis, including machine learning and AI. The curriculum bridges financial theory with practical applications in quantitative trading, risk management, and forecasting. Graduates can pursue prestigious roles such as quantitative traders, risk managers, data scientists, and financial researchers at leading investment banks, hedge funds, and FinTech firms.
Admission Requirements
2.7+
58+
176+
4.5+
6.5+
Academic requirements 2:2 Hons degree (UK or equivalent) in Finance/Economics with strong quantitative components, or STEM (Mathematics, Engineering, Physics, Computer and Data Science, and related disciplines).
Students with other business, social and natural science related degrees are encouraged to apply, provided they can demonstrate strong quantitative skills.
We assess applicants based on their overall academic performance, typically putting more emphasis on strong results in quantitative modules. Relevant work experience and/or significant programming skills are also viewed favourably.
Financial Technologies and AI MSc
Lancaster University Management School, Lancaster University, Lancaster, GB, Bailrigg, United Kingdom
12 monthsProgramme duration
30,000 GBPTuition Fee/year
2Scholarships
SepStarting Month
Programme overview
Main Subject
Finance
Degree
MSc
Study Level
Masters
Study Mode
On Campus
MSc Financial Technologies and AI is a unique programme that combines classical quantitative finance techniques with cutting-edge developments in financial technology and big data analysis, including machine learning and AI. The curriculum bridges financial theory with practical applications in quantitative trading, risk management, and forecasting. Graduates can pursue prestigious roles such as quantitative traders, risk managers, data scientists, and financial researchers at leading investment banks, hedge funds, and FinTech firms.
Programme overview
Main Subject
Finance
Degree
MSc
Study Level
Masters
Study Mode
On Campus
MSc Financial Technologies and AI is a unique programme that combines classical quantitative finance techniques with cutting-edge developments in financial technology and big data analysis, including machine learning and AI. The curriculum bridges financial theory with practical applications in quantitative trading, risk management, and forecasting. Graduates can pursue prestigious roles such as quantitative traders, risk managers, data scientists, and financial researchers at leading investment banks, hedge funds, and FinTech firms.
Admission Requirements
2:2 Hons degree (UK or equivalent) in Finance/Economics with strong quantitative components, or STEM (Mathematics, Engineering, Physics, Computer and Data Science, and related disciplines).
Students with other business, social and natural science related degrees are encouraged to apply, provided they can demonstrate strong quantitative skills.
We assess applicants based on their overall academic performance, typically putting more emphasis on strong results in quantitative modules. Relevant work experience and/or significant programming skills are also viewed favourably.
Tuition fees
Domestic
International
Scholarships
Management School Master's Excellence Scholarship
Value
20% tuition fee waiver
Deadline
31 Aug 2026
Application requirements
QS Event Attendance is NOT required
Entry requirements
You must be admitted to this school to be awarded
Postgraduate International Regional Scholarship
Value
$10000
Deadline
31 Aug 2026
Application requirements
QS Event Attendance is NOT required
Entry requirements
You must be admitted to this school to be awarded
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