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  6. FI3513: FinTech and Business Analytics

FI3513: FINTECH AND BUSINESS ANALYTICS (2025-2026)

Last modified: 20 Jun 2025 15:10


Course Overview

This course aims to equip students with a solid understanding of the latest financial technologies, including blockchain, cryptocurrencies, payment and lending, and robo-advisors, as well as the analytical skills necessary to interpret and leverage financial data through Python programming. It combines theoretical knowledge with hands-on practical skills, preparing students for a variety of roles in the fintech industry.

Course Details

Study Type Undergraduate Level 3
Term Second Term Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Weihao Han

What courses & programmes must have been taken before this course?

  • One of PO2508 Understanding Statistics (Passed) or Master Of Arts In Business Management-Finance (SCNU) or Master Of Arts In Finance (SCNU)
  • Any Undergraduate Programme (Studied)
  • One of FI2501 Financial Markets and Regulation (Passed) or Master Of Arts In Business Management-Finance (SCNU) or Master Of Arts In Finance (SCNU)
  • One of Programme Level 3 or Programme Level 4 or Master Of Arts In Business Management-Finance (SCNU) or Master Of Arts In Finance (SCNU)

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

To accommodate the development of technology in the financial service industry, this course endeavours to cover the development, challenges, and future trends of financial technology along with practical data analytics skills in Python programming. Specifically, this course will emphasise topical issues such as blockchain and cryptocurrencies, digital payment and lending, and robo-advisors in order to deliver an in-depth understanding to our students. On the other hand, students will also learn data analytical techniques incorporating data wrangling, data visualisation, exploratory data analysis, among others, via the gold-standard programming language – Python programming. 


The course may include, but may not be limited to:

  1. Fintech Innovations and Financial Markets: An Overview
    Objective: To introduce the concept of financial technology (Fintech) and its impact on the financial markets, providing a broad overview of current innovations and trends.
  2. Introduction to Python for Data Analytics
    Objective: To familiarise students with the Python programming language, focusing on its application in data analytics for financial technology.
  3. Blockchain and Cryptocurrencies
    Objective: To explore the principles of blockchain technology and the functioning of cryptocurrencies, examining their role and significance in the Fintech ecosystem.
  4. Data Wrangling in Python
    Objective: To teach students the process of cleaning and unifying messy and complex data sets for easy access and analysis in Python.
  5. Fintech and Banking
    Objective: To discuss the integration of Fintech in traditional banking systems, including the transformation and emerging challenges in the sector.
  6. Advanced Data Wrangling in Python
    Objective: To advance students' data manipulation skills in Python, preparing them to handle more complex data operations required in financial technology applications.
  7. Fintech in Payments and lending
    Objective: To examine the advancements in digital payment systems and lending processes facilitated by Fintech, evaluating their impact on the financial industry.
  8. Data Visualisation in Python
    Objective: To develop students’ proficiency in creating meaningful visual representations of financial data using Python 's graphical capabilities.
  9. Fintech in Other Financial Services and Its Regulatory Issues
    Objective: To analyse the application of Fintech in various financial services sectors and to understand the regulatory landscape surrounding these technologies.
  10. Statistical Modelling
    Objective: To teach students statistical modelling techniques within Python, allowing them to perform complex analyses of financial data and make informed decisions.

 


Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 31 August 2025 for 1st Term courses and 19 December 2025 for 2nd Term courses.

Summative Assessments

Report: Individual

Assessment Type Summative Weighting 75
Assessment Weeks 39 Feedback Weeks 42

Look up Week Numbers

Feedback

2,000-word Individual report.

Written feedback will be provided to each student.
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualEvaluateStudents are expected to evaluate the potential opportunities, risks, and outlook of the disruptive Fintech revolution in the finance industry.
FactualApplyStudents are expected to implement data wrangling, visualisation, and statistical modelling to solve real-world problems using Python programming.
FactualUnderstandStudents are expected to understand the current development in Fintech and its influence in the financial service.

Report: Group

Assessment Type Summative Weighting 25
Assessment Weeks 39 Feedback Weeks 42

Look up Week Numbers

Feedback

1,500-word Group report.

Written feedback will be provided to each group.
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualEvaluateStudents are expected to evaluate the potential opportunities, risks, and outlook of the disruptive Fintech revolution in the finance industry.
FactualApplyStudents are expected to implement data wrangling, visualisation, and statistical modelling to solve real-world problems using Python programming.
FactualUnderstandStudents are expected to understand the current development in Fintech and its influence in the financial service.

Formative Assessment

There are no assessments for this course.

Resit Assessments

Report: Individual

Assessment Type Summative Weighting 100
Assessment Weeks 50,51 Feedback Weeks

Look up Week Numbers

Feedback

2,000-word Individual report.

Written feedback will be provided to each student.
Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
FactualUnderstandStudents are expected to understand the current development in Fintech and its influence in the financial service.
ConceptualEvaluateStudents are expected to evaluate the potential opportunities, risks, and outlook of the disruptive Fintech revolution in the finance industry.
FactualApplyStudents are expected to implement data wrangling, visualisation, and statistical modelling to solve real-world problems using Python programming.
 

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