Economics MSc
Artificial Intelligence in Finance ACCFIN5230
- Academic Session: 2026-27
- School: Adam Smith Business School
- Credits: 10
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 2
- Available to Visiting Students: No
- Collaborative Online International Learning: No
- Curriculum For Life: No
Short Description
The course provides an introduction to the main artificial intelligence (AI) algorithms and present its applications in Finance.
Timetable
Course is delivered over 2 weeks, comprising of 10 hours of lectures and 2 hours of tutorials.
Excluded Courses
None
Co-requisites
None
Assessment
1. Written Assignment, including Essay; Individual; 1300 words; 75%; ILOs 1-4.
2. Oral assessment & presentation; Group; 10 minutes; 25%; ILOs 1-5.
Are reassessment opportunities available for all summative assessments? No
It is the default expectation that all courses will offer opportunities for reassessment or deferred assessment. Where it is not possible to offer this in some assessment components, the grade achieved at the first attempt will be counted towards the final course grade, and any exceptions for this course are described below.
[No exceptions]
Course Aims
The overall aim of the course is to introduce the main algorithms of AI and inform the students about is applications in Finance. The course aims to introduce Neural Networks, evolutionary programming, meta-heuristics and deep learning to students. The advantages and disadvantages of AI in Finance will be discussed along with its applications through a series of case studies and research papers.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
1. Understand, explain and critically assess the main Neural Networks algorithms.
2. Understand, explain and critically assess the main evolutionary programming algorithms.
3. Understand and critically assess the applications of Neural Networks, evolutionary programming, meta-heuristics in Finance.
4. Understand and critically assess the concept of deep learning in Finance applications
5. Work collaboratively in a group to develop team working skills by producing a combined piece of coursework.