BUS7013 - Emerging Technologies in Finance

Objectives:

On successful completion of the module, students will be able to:

1 - Define and explain key emerging technologies, including blockchain, artificial intelligence and machine learning and their application in finance
2 - Assess how AI and machine learning are transforming financial processes, including risk management, fraud detection, customer service and investment strategies
3 - Explore various use cases and applications of blockchain technology in finance, such as digital currencies, smart contracts and supply chain finance
4 - Evaluate the impact of emerging technologies on traditional financial services and business models
5 - Engage in collaborative activities and projects to solve complex problems related to the integration of emerging technologies in finance.

Content:

The content of a module on emerging technologies in finance should cover a broad range of topics to provide students with a comprehensive understanding of the subject. The following is an indicative list of module content:

1. Introduction to Emerging Technologies in Finance

- Definition and scope of emerging technologies, Historical context of technology adoption in finance. An overview of key emerging technologies: blockchain, artificial intelligence, machine learning and their application in finance.

2. Artificial Intelligence (AI) and Machine Learning (ML) in Finance

- Introduction to AI and ML; Applications in finance: risk management, fraud detection, credit scoring and customer service; Algorithmic trading and robo-advisors; Explainability and ethical considerations in AI.

3. Applications of blockchain technology in finance, such as digital currencies, smart contracts and supply chain finance.

4. Case studies and practical applications on the integration of emerging technologies in finance.

Learning and Teaching Information:

The objective of our learning and teaching methods in this module is to explore the emerging technologies in finance. This is achieved by incorporating evidence-based and research-informed teaching practices, incorporating real-world finance examples, case studies and practical applications.

In doing that, in the workshop-based delivery a combination of problem-based learning and action learning will be embedded throughout the module, allowing students to apply their knowledge and skills to the current trends in financial technologies. This provides an opportunity to apply theoretical concepts to practical problems and develop critical thinking and problem-solving skills with the prudent application of the artificial intelligence, machine learning and blockchain technologies. The indicative module content provides a balance between theoretical concepts and practical applications, ensuring that students gain both a solid understanding of the emerging technologies in finance and the ability to apply them in real-world scenario.

Workshops
Hours: 40
Intended Group Size: Cohort

Guided independent study
Hours: 260

Further Detail Relating to Assessment

Designing an individual or group project on creating a financial technology solution can be a highly effective way for students to apply their theoretical knowledge to real-world scenarios.

Students will work independently to design and present a financial technology solution. This will involve identifying and addressing a specific challenge or opportunity within the financial industry. The project will involve comprehensive research, innovative thinking and the development of a detailed report.

Students may also work in groups to tackle a larger or more complex challenge/opportunity. Groups will collaborate to design and present their solution, dividing tasks according to each member’s expertise and interests.

Thereafter, the individual or group will select appropriate technologies for the solution and then design the overall architecture of the financial technology solution.

Both individual and group projects begin with a proposal that finalises group members and outlines the problem or opportunity, proposed solution and technologies to be used. The proposal must be submitted for review by week 5 and the module tutor will provide feedback to ensure the project scope is appropriate and achievable. The module tutor will then approve proposals the following week in a dedicated assessment workshop.

Formative feedback on module activities will be present throughout the module.

Full details are available in the Module Handbook.

Assessment:

001 Individual or group project on designing a Financial Technology solution. 5000 words or equivalent. End of term 1. 100%

Fact File

Module Coordinator - Efan Johnson
Level - 7
Credit Value - 30
Pre-Requisites - NONE
Semester(s) Offered - 7T1

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