MSc Financial Technology (Fintech), AI and Business Analytics

Recovered from the CourseFinder export (it does not appear in the portal CSVs), this MSc combines the fintech curriculum with a heavier artificial intelligence and analytics load: machine learning for financial prediction, business analytics and visualisation, big-data infrastructure basics, payments and digital banking technology, and the regulatory setting for algorithmic finance. Entry per the source accepts 2:2 degrees across accounting, finance, economics, computing, mathematics or business fields.

The teaching is lab-forward — Python for data work, SQL for storage and querying, and applied model-building against financial datasets, with visualisation delivered through industry-standard BI tools. Project assessments ask students to take a business question from raw data to a defended recommendation, and the capstone supports build-oriented work such as a credit-scoring prototype or a payments-fraud detection study.

Because this course surfaces only in the CourseFinder export, the sheet carries its 2027 intake data and flags it for confirmation against DMU’s live pages before marketing; the £18,450 fee matches the established Financial Technology MSc exactly, suggesting a shared fee band across the fintech family. The title’s breadth is deliberate — it is pitched at business graduates adding technical range, not at software engineers.

Career prospects sit at the strong end of this faculty’s range because analytics demand cuts across every UK sector: realistic entry is analyst-grade at £27,000–£33,000, with fintech and consulting the heaviest hirers and a meaningful minority of employers willing to sponsor after a first year. Before sponsorship, graduates hold Graduate Route permission from this taught award — 18 months where the application lands on or after 1 January 2027, two years for earlier filings — and dependants are excluded on taught routes.