Financial Technology with Data Science

Mathematical Sciences

Taught

MSc

Taught

MSc

Overview
Application Timeline
Tuition
Requirements
Modules
About
Subject Area Information
Career
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Overview

The Financial Technology MSc program explores innovations like crowdfunding and cryptocurrencies, equipping students with skills in technology implementation and data analysis. It targets individuals with backgrounds in computer science, engineering, or numerate sciences. The program emphasizes industry engagement and real-world project experience.

Application Timeline

September 1, 2025
Start date
April 10, 2026
Today

Tuition

Year 1

Year 1

Student categories	Study
Student categories	Full-time	Part-time
England	£18,400	£9,200
Northern Ireland	£18,400	£9,200
Scotland	£18,400	£9,200
Wales	£18,400	£9,200
Channel Islands	£18,400	£9,200
EU	£35,500	N/A
International	£35,500	N/A

Requirements

Entry Requirements:

Language Requirements

Language requirements information is currently unavailable.

Modules

Modules is currently unavailable

Please check back later for updates.

About

Introduction to Financial Technology Innovations

Recent advancements in financial technologies have transformed spending, saving, borrowing, and investing. Key developments include:

Crowdfunding
Cryptocurrencies
Automated trading
Alipay

These innovations enable financial services companies to leverage data for personalized offerings, while tech giants and startups disrupt traditional banking models.

Program Overview

This MSc program provides an opportunity to engage with the financial technology sector. Key features include:

Learning design features of various financial technology applications.
Developing skills in implementation,

...

Subject Area Information

Financial mathematics is a specialized field that combines mathematical theories and methods with financial practice to solve problems in finance. This discipline is essential for understanding and modeling financial markets, managing financial risks, and making informed investment decisions.

Typical Course Structure

1. Introduction to Financial Mathematics
2. Probability and Statistics for Finance
3. Derivatives and Risk Management
4. Fixed Income Securities
5. Portfolio Theory and Asset Pricing
6. Numerical Methods in Finance
7. Financial Econometrics
8. Advanced Topics in Financial Mathematics

Typical Skills Acquired

Understanding fundamental financial concepts
Calculating present and future values
Analyzing financial data
Modeling uncertainty
Valuing derivative securities
Designing hedging strategies
Valuing fixed income securities
Constructing optimal portfolios
Implementing numerical algorithms
Analyzing financial time series data
Understanding complex financial instruments
Proficiency in programming languages such as Python, R, or MATLAB

Career

Graduates of financial mathematics programs can pursue a variety of careers in the finance industry, leveraging their strong foundation in mathematics, finance, and computational techniques.

Potential Professions

Quantitative Analyst (Quant)
Developing and implementing complex financial models to support trading and risk management.
Risk Manager
Identifying and mitigating financial risks for banks, investment firms, and corporations.
Financial Engineer
Designing new financial products and strategies using advanced mathematical techniques.
Investment Analyst
Analyzing financial data to make investment recommendations.
Actuary
Assessing financial risks in the insurance and pension industries.
Data Scientist
Applying statistical and computational methods to analyze financial data and inform business decisions.

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