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Finance, digital platforms and regulation for the next generation of banking
Online or on campus
Financial technology is reshaping how money moves, risk is priced and customers bank. Brigant's MSc Fintech unites capital markets literacy with digital products, data science methods and regulatory competence. You will analyse payment rails and open banking, build quantitative credit and fraud models, evaluate distributed ledger applications with sober engineering and legal scrutiny, and design fintech products with unit economics that survive regulation. Graduates leave able to speak both the language of the trading floor and the product engineering room. MSc Financial Technology is taught as one award, not a list of unrelated modules. The published length is 24 months, and the credit total is 36. Students move from Financial Markets, Institutions & Fintech Landscapes through Financial Markets, Institutions & Fintech Landscapes; Corporate Finance & Valuation for Digital Assets; Programming & Data Analysis for Fintech; Payments Systems, Banking & Open Finance; Blockchain, Distributed Ledgers & Tokenisation; Machine Learning for Finance & Credit Risk, and finish on MSc Fintech Capstone Project. Each course has a question, a method, and a submission. In this field, students read a set of figures, build a small case, and state which assumption moves the result. Reading is financial statements, a recognition note, and a risk report. The artefact a marker expects is a recommendation that separates the decision, the numbers, and the risk. The award is built so that a graduate can do the following in practice: Map fintech value chains in payments, lending, wealth and market infrastructure Apply machine learning responsibly to credit, fraud and personalisation Assess blockchain and tokenisation use cases for technical and regulatory fit Teaching assumes the student can read a source, attempt a problem before the seminar, and revise after feedback. Attendance at live seminars is part of the design. The capstone or final course must use the methods of the earlier courses; a project that ignores them does not pass. This course does not confer an accounting, audit, or financial-services licence. The pages for each course name the topics that are examined. Those topics are the syllabus. A brochure line is not a substitute for them.
Modules reference UK FCA, PSD2/open banking, and Basel-aligned risk thinking without reducing the degree to a compliance checklist. Guest practitioners from payments, challenger banks and market infrastructure firms join seminars. Capstone projects may partner with fintech firms under data governance agreements.
Faculty spotlight
Dr. Priya Sharma teaches ML for credit risk; Professor Daniel Mensah specialises in payment systems and financial inclusion technology.
Study online
Online tuition is free. Online examinations are free. There is no exam fee for online study.
On-campus study
Prefer to learn at our Edinburgh campus? Campus tuition and campus examinations are charged. The published campus price is on each programme page.
| Code | Course | Credits · hours |
|---|---|---|
| FT501 | Financial Markets, Institutions & Fintech Landscapes Financial Markets, Institutions & Fintech Landscapes (FT501) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can read a set of figures, build a small case, and state which assumption moves the result, using Financial Markets, Institutions & Fintech Landscapes as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses financial statements, a recognition note, and a risk report. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation that separates the decision, the numbers, and the risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer an accounting, audit, or financial-services licence.
| 3 · 30 h |
| FT502 | Corporate Finance & Valuation for Digital Assets Corporate Finance & Valuation for Digital Assets (FT502) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can read a set of figures, build a small case, and state which assumption moves the result, using Corporate Finance & Valuation for Digital Assets as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses financial statements, a recognition note, and a risk report. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation that separates the decision, the numbers, and the risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer an accounting, audit, or financial-services licence.
| 3 · 30 h |
| FT503 | Programming & Data Analysis for Fintech Programming & Data Analysis for Fintech (FT503) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Programming & Data Analysis for Fintech as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| FT504 | Payments Systems, Banking & Open Finance Payments Systems, Banking & Open Finance (FT504) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can read a set of figures, build a small case, and state which assumption moves the result, using Payments Systems, Banking & Open Finance as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses financial statements, a recognition note, and a risk report. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation that separates the decision, the numbers, and the risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer an accounting, audit, or financial-services licence.
| 3 · 30 h |
| Code | Course | Credits · hours |
|---|---|---|
| FT505 | Blockchain, Distributed Ledgers & Tokenisation Blockchain, Distributed Ledgers & Tokenisation (FT505) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can read a set of figures, build a small case, and state which assumption moves the result, using Blockchain, Distributed Ledgers & Tokenisation as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses financial statements, a recognition note, and a risk report. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation that separates the decision, the numbers, and the risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer an accounting, audit, or financial-services licence.
| 3 · 30 h |
| FT506 | Machine Learning for Finance & Credit Risk Machine Learning for Finance & Credit Risk (FT506) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Machine Learning for Finance & Credit Risk as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| FT507 | Cybersecurity, Fraud & Operational Resilience Cybersecurity, Fraud & Operational Resilience (FT507) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can map one named system, write a threat model, and specify the controls that would stop the most likely path, using Cybersecurity, Fraud & Operational Resilience as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses control catalogues, incident write-ups, and a short technical standard. Seminar time is for the decision, not for reading the materials aloud. Assessment is a defensive design with a test plan and a statement of residual risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| FT508 | RegTech, Compliance & Financial Regulation RegTech, Compliance & Financial Regulation (FT508) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can read a set of figures, build a small case, and state which assumption moves the result, using RegTech, Compliance & Financial Regulation as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses financial statements, a recognition note, and a risk report. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation that separates the decision, the numbers, and the risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer an accounting, audit, or financial-services licence.
| 3 · 30 h |
| Code | Course | Credits · hours |
|---|---|---|
| FT601 | Fintech Product Strategy & Venture Economics Fintech Product Strategy & Venture Economics (FT601) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can read a set of figures, build a small case, and state which assumption moves the result, using Fintech Product Strategy & Venture Economics as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses financial statements, a recognition note, and a risk report. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation that separates the decision, the numbers, and the risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer an accounting, audit, or financial-services licence.
| 3 · 30 h |
| FT602 | Ethics, Inclusion & Sustainable Finance Technology Ethics, Inclusion & Sustainable Finance Technology (FT602) is a 3-credit course on MSc Financial Technology, with 30 notional learning hours. By the end, students can read a set of figures, build a small case, and state which assumption moves the result, using Ethics, Inclusion & Sustainable Finance Technology as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses financial statements, a recognition note, and a risk report. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation that separates the decision, the numbers, and the risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer an accounting, audit, or financial-services licence.
| 3 · 30 h |
| FT603 | MSc Fintech Capstone Project MSc Fintech Capstone Project (FT603) is a 6-credit course on MSc Financial Technology, with 60 notional learning hours. By the end, students can read a set of figures, build a small case, and state which assumption moves the result, using MSc Fintech Capstone Project as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses financial statements, a recognition note, and a risk report. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation that separates the decision, the numbers, and the risk. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer an accounting, audit, or financial-services licence.
| 6 · 60 h |
Modules are assessed through a published mix of coursework, applied projects, and examinations. Exam windows are announced in advance so students in other time zones are not forced into overnight sittings. Alternative arrangements are available where documented.
The published duration is 24 months. Teaching language: English. Actual time-to-complete depends on mode and any recognised prior learning.
You may study this award fully online from your country, or — where published — on campus at Brigant. Online study does not require a student visa. Campus study may.
Degree tuition for this award is published as £0 / tuition-free on the online pathway. Examination or administrative fees may apply at checkout — never an annual tuition invoice. Check the Fees page for any extras.
Requirements are grouped on this page (academic, English, documents). Equivalent qualifications are considered. English may be waived after prior English-medium study.
Assessment is typically a mix of coursework, projects, and examinations. Doctoral awards include a thesis or dissertation and an oral examination. Details sit in the programme specification and module outlines.
Recognition of the award for local employment, professional licence, or ministry attestation is decided by your employer or regulator. University of Brigant publishes verification pages for certificates. We do not claim automatic equivalence in every country.
Start an application on this website. Progress is saved from the first step. Admissions: admissions@brigant.uk.
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