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University of Exeter Business School

Advanced Financial Technology

Module titleAdvanced Financial Technology
Module codeBEEM062
Academic year2023/4
Credits15
Module staff

Dr Jack Rogers (Convenor)

Duration: Term123
Duration: Weeks

11

Number students taking module (anticipated)

30

Module description

This module builds on BEEM061 Fundamentals of Financial Technology, but goes deeper into exploring how blockchain, big data, machine learning and AI are re-shaping Finance. With direct input from industry practitioners, you will examine the economics and environmental impact of bitcoin mining, appraise the merits and drawbacks of existing blockchains, and examine in depth how bitcoin works by studying the bitcoin whitepaper and its protocol. New use cases that allow secure identity management and micropayments will also be introduced. On completion of this module, you will be highly proficient at critically evaluating current and future developments in FinTech, and highly competent in the practical aspects of programming in useful languages like Python.

Module aims - intentions of the module

This module aims to consolidate the analytical, technical and strategic foundation laid out on the BEEM061 Fundamentals of Financial Technology module. You will continue to an advanced level of understanding how bitcoin, and hence all blockchain and smart contract applications work. The theory behind how these systems work will continue to be applied in real case studies, and you will be trained into a competent multi-disciplinary FinTech specialist. By the end of this module you will have acquired all of the knowledge and skills needed to succeed in the industry, whether as an entrepreneur creating a startup, or as a member of a FinTech team in an existing company.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

  • 1. examine case study approaches to how FinTech businesses work;
  • 2. critically review and discuss a range of academic and non-academic papers reflecting on FinTech.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

  • 3. analyse the techniques employed in FinTech.

ILO: Personal and key skills

On successfully completing the module you will be able to...

  • 4. demonstrate analytical and critical thinking skills;
  • 5. demonstrate digital literacy and basic programming skills.

Syllabus plan

  • New Developments in FinTech
  • The Bitcoin whitepaper & protocol
  • Big Data, AI & Machine Learning
  • Intermediate Programming

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad
161340

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching Activity1111 x 1 hour lectures
Scheduled Learning and Teaching Activity55 x 1 hour tutorials
Guided Independent study134Reading, question practice, and tutorial preparation

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Participation in Group WorkSeminars and 20 minute report back1-5In-Class Verbal Feedback

Summative assessment (% of credit)

CourseworkWritten examsPractical exams
80200

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Mid Term Exam2050 minutes5Verbal feedback & Indicative Answers
Assignment802500 words1-4Written feedback
0
0
0
0

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Mid Term Exam (20%)Exam (50 minutes, 20%)5Referral/Deferral Period
Assignment (80%)Assignment (2,500 words, 80%)1-4Referral/Deferral Period

Indicative learning resources - Basic reading

Gupta, P & Tham, T.M. (2018). FinTech: The New DNA of Financial Services. Walter de Gruyter Inc, Boston/Berlin.

Indicative learning resources - Web based and electronic resources

ELE – College to provide hyperlink to appropriate pages

Key words search

FinTech, Bitcoin, Blockchain, Big Data, Machine Learning, AI

Credit value15
Module ECTS

7.5

Module pre-requisites

None

Module co-requisites

BEEM061

NQF level (module)

7

Available as distance learning?

No

Origin date

20/08/2020

Last revision date

20/08/2020