Durham University
Programme and Module Handbook

Postgraduate Programme and Module Handbook 2024-2025

Module LAW48015: ARTIFICIAL INTELLIGENCE AND FINANCE

Department: Law

LAW48015: ARTIFICIAL INTELLIGENCE AND FINANCE

Type Open Level 4 Credits 15 Availability Not available in 2024/2025 Module Cap None.

Prerequisites

  • None

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • To give students a non-technical introduction to the basic features of artificial intelligence (‘AI’) and its impact on the new digital economy;
  • To introduce students to the basic building blocks of the financial system and the fundamental principles of financial regulation;
  • To introduce students to the transformation of finance by (AI) technology (‘FinTech’), creating both risks and opportunities;
  • To encourage students to analyse and discuss case studies that illustrate the opportunities and risks brought by the use of AI in finance;
  • To challenge students to consider how AI is also transforming processes of industry compliance with financial regulation (‘RegTech’) and processes of supervision by financial regulators (‘SupTech’);
  • To introduce students to the wider legal, social, and political debates that surround the regulation of AI in finance at UK, EU, and international levels;
  • To enable students to develop their analytical skills and ability to use lessons learned from different case studies to critically assess the role that (AI-powered) financial regulation and supervision might play in shaping the future of finance.

Content

  • A brief non-technical introduction to AI and algorithmic technologies, including knowledge representation, natural language processing, and machine learning;
  • A general introduction to the financial system, its various components, and the fundamental principles that guide its regulation at UK, EU, and international levels;
  • A discussion of AI and algorithmic technologies as significant drivers of change within the financial system worldwide;
  • A detailed discussion of particular use cases of AI and algorithmic FinTech, including the use of AI and algorithms to automate the provision of financial advice (‘robo-advice’), the use of AI and algorithms to automate trading decisions in the financial markets (‘algorithmic trading’), and the use of AI and algorithms to calculate credit scorings (‘algorithmic credit scoring’);
  • A discussion of how AI is also changing RegTech and SupTech, fundamentally reshaping the interactions between regulators, supervisors, and the financial industry;
  • An introduction to the principles, laws and guidance that may currently apply to AI and algorithmic FinTech at UK, EU, and international levels;
  • A critical discussion—based on the lessons learned from different AI and algorithmic technology case studies—of contemporary and envisioned regulatory and supervisory approaches to AI and finance adopted at UK, EU, and international levels.

Learning Outcomes

Subject-specific Knowledge:
  • students will gain a basic understanding of AI technologies
  • students will gain a basic understanding of the financial system, its basic components and its regulatory principles
  • students will gain an in-depth knowledge of how AI and algorithmic technology are transforming finance, regulatory compliance and supervision
  • students will develop a critical understanding of the existing regulatory and supervisory framework that may apply to AI and algorithmic FinTech at UK, EU, and international levels
  • students will develop a critical understanding of contemporary and envisioned approaches to regulating the use of AI in finance
Subject-specific Skills:
  • students will be able to offer a non-technical explanation of different AI technologies
  • students will be able to identify the basic components and functions of the financial system
  • students will be able to identify and describe the roles played by the UK, EU and international policymaking, regulatory and supervisory bodies responsible for the health of the financial system
  • students will be able to discuss how AI technologies are changing finance, regulatory compliance and supervision
  • students will be able to identify and use the leading primary and secondary sources currently relevant for the regulation of AI technologies and their application in finance
  • students will be able to identify and critically analyse envisioned policy, regulatory and supervisory approaches to AI technologies and their application in finance
  • students will be able to evaluate and engage with the broader legal, social, and political questions raised by the impact of AI technologies in finance
Key Skills:
  • students will be able to write a substantial and well-researched piece of work on specific aspects of AI and financial regulation

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Each teaching session will consist of blended delivery, including lecturing and seminar discussions. The first part of each session will introduce the topic, and the seminar discussions, supported by substantial but targeted reading assignments before each session, will provide a deeper understanding of the issues, and analyse particular use cases of AI in finance in more detail. The readings are selected from both established doctrinal sources as well as cutting-edge scholarship in the area. Lecturing will work from a basic level of doctrinal knowledge and build on that foundation into critical analysis of more difficult and controversial issues within the seminar discussions. This will encourage students to learn the material and develop the ability to discuss it and understand where each aspect of the reading fits in with the relevant debates;
  • The assessment supports the aims of the teaching methods. The essay will assess the ability of the students not only to analyse the subject material but to perform research in the discipline and present a structured, articulate argument on the subject.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
seminars 8 Normally weekly with reading weeks 2 hrs 16
preparation and reading 134
TOTAL 150

Summative Assessment

Component: Summative essay Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
summative essay 3,000 words 100% Y

Formative Assessment:

The formative will consist of writing a review of a selected topical article. Writing the review will help students understand an area of financial regulation as well as how to put forward a coherent argument. The review will be 1000 words in length.


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University