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2025/2026  BA-BHAAI1115U  AI, Fintech & Deep Tech in Finance and Business

English Title
AI, Fintech & Deep Tech in Finance and Business

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration Summer
Start time of the course Summer
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 30
Max. participants 100
Study board
Study Board for General Management
Programme Bachelor of Science in Economics and Business Administration
Course coordinator
  • Rama Seth - Department of Finance (FI)
For academic questions related to the course, please contact course responsible Rama Seth (rs.fi@cbs.dk).
Instructor: Prabhu Venkatesh
Main academic disciplines
  • Innovation
  • Project and change management
  • Accounting
Teaching methods
  • Face-to-face teaching
Last updated on 20/11/2025

Relevant links
Learning objectives
Literacy in fintech
Applications of AI, machine learning, algorithms, and quantum computing in corporate and entrepreneurship
  • Identify, explain, discuss methods in AI, deep learning, and other deep technologies as they relate to finance and business.
  • Analyze, interpret, and evaluate how AI, machine learning, and emerging technologies are used in financial and corporate decision-making, including for risk management, marketing, and operations.
  • Evaluate, present, and discuss the strategic, ethical, and regulatory challenges that arise from the implementation of these technologies.
  • Synthesize knowledge from various sources to develop a practical implementation plan for an AI solution and deep tech within a business context.
Course prerequisites
High school mathematics, general interest in finance, technology and management.
Examination
AI, Fintech & Deep Tech in Finance and Business:
Exam ECTS 7.5
Examination form Written sit-in exam on CBS' computers
Individual or group exam Individual exam
Assignment type Written assignment
Duration 4 hours
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Summer
Aids Open book: all written and electronic aids, including internet access
Read more here about which exam aids the students are allowed to bring and will be given access to : Exam aids and IT application package
Make-up exam/re-exam
Same examination form as the ordinary exam
The number of registered candidates for the make-up examination/re-take examination may warrant that it most appropriately be held as an oral examination. The programme office will inform the students if the make-up examination/re-take examination instead is held as an oral examination including a second examiner or external examiner.
n/a
Course content, structure and pedagogical approach
  • Week 1: AI Fundamentals & Financial Applications
    • Defining AI, machine learning, and deep learning.
    • Case studies on AI for credit scoring, risk assessment, and algorithmic trading.
    • The role of NLP for market analysis and sentiment analysis.
  • Week 2: Deep Tech & Business Transformation
    • Generative AI for business operations and marketing.
    • AI applications in supply chain optimization.
    • The intersection of blockchain, digital assets, and AI.
  • Week 3: Strategic Implementation & Emerging Tech
    • Developing an AI-first business strategy.
    • Ethical and social implications of AI (bias, privacy, jobs).
Research-based teaching
CBS’ programmes and teaching are research-based. The following types of research-based knowledge and research-like activities are included in this course:
Research-based knowledge
  • Teacher’s own research
  • Methodology
Research-like activities
  • Analysis
  • Discussion, critical reflection, modelling
Description of the teaching methods
The pedagogical approach is to get students to understand the dynamic landscape of technological development in the context of maximizing the efficiency of technology use in the emerging corporate infrastructure. This will include the evolution of how technology is used, to set an agile learning platform to allow students to navigate emerging and future technology.
Feedback during the teaching period
Continuous feedback is provided to students such that they can get a better understanding of the concepts covered in the course and learn how to apply them via polls, quizzes and problem-solving.
This continuous feedback is a key cornerstone of the learning process in the course.
Student workload
Pre-course Activity 20 hours
Classroom attendance 38 hours
Preparation 121 hours
Feedback activity 7 hours
Examination 17 hours
Ungraded quizzes for self test 3 hours
Further Information

 

This is an intensive 3-week course that cannot be combined with any other course.

 

 

Pre-course Activity:  The course coordinator uploads the pre-course activity on Canvas at the end of May. It is expected that students participate as it will be included in the final exam, but the assignment is without independent assessment and grading.

 

We reserve the right to cancel the course if we do not get enough applications. This will be communicated on  https://www.cbs.dk/en/study/international-summer-university/courses-and-exams  in early March.

 

 
Expected literature

We will draw upon the following texts in class:
 

• Artificial Intelligence For Dummies by John Mueller and Luca Massaron.

• Blockchain Basics: A Non-Technical Introduction in 25 Steps by Daniel Drescher.

• The EU AI Act

Other material will include supplementary readings that may be circulated in lectures or included in downloadable lecture notes, available at CBS Canvas (canvas.cbs.dk).
Last updated on 20/11/2025