IBF562 Special Topics in Finance
Syllabus | International University of Sarajevo - Last Update on Feb 02, 2026
Syllabus Quick Jump
Search and navigate to any syllabus instantly
International Business and Finance
Admir Mešković
Course Lecturer
Course Objectives
The main objective is to face students with current and challenging issues in finance and to make them reflect on the research opportunities that those challenges provide.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Imerman, M., & Fabozzi, F. J. (2025). The Economics of Fintech: Understanding Digital Transformation in Financial Services. MIT Press.
Additional Literature
James da Costa (2024) Fintech Wars: Tech Titans, Complex Crypto and the Future of Money. Kogan Page Ronit Ghose (2024) Future Money: Fintech, AI and Web3 1st Edition Gupta, P., & Tham, T. M. (2018). Fintech: the new DNA of financial services. Walter de Gruyter GmbH & Co KG.Teaching Methods
The methods include lectures (which may involve PowerPoint presentations
Videos
And audio aids)
Student presentations
Projects
And class discussions.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction to Fintech | Syllabus, Chapter 1 |
| 2 | The Economics of the FinTech Revolution | Chapter 2 |
| 3 | Data Science and Its Role in FinTech | Chapter 3 |
| 4 | Financial Intermediation | Chapter 4 |
| 5 | Risk and Risk Management for FinTech | Chapter 5 |
| 6 | Sources of Financing for FinTech Companies | Chapter 6 |
| 7 | Financing Vehicles and Equity Options | Chapter 7 |
| 8 | Midterm exam | |
| 9 | Payments Technology | Chapter 9 |
| 10 | Digital Banking | Chapter 10 |
| 11 | FinTech Lending | Chapter 11 |
| 12 | Digital Wealth Management | Chapter 12 |
| 13 | InsurTech | Chapter 13 |
| 14 | Decentralized Finance and Blockchain Technology | Chapter 15 |
| 15 | AI applications in Finance | Special reading material |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| IBF562.1 | Course | Monday 17:00 - 19:50 | B F1.35 FBA Conference Room | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Monday | 15:00 - 17:00 | B F1.12 | |
| Tuesday | 12:00 - 15:00 | B F1.12 |
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes : 4 5
Midterm exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Participation
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Case study
AI: AllowedAlignment with Learning Outcomes : 1 2 3 4 5
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lecture Hours
45 hours ⏳ (15 week × 3 h)
Home study
15 hours ⏳ (15 week × 1 h)
Case study
40 hours ⏳ (1 week × 40 h)
Midterm exam study
25 hours ⏳ (1 week × 25 h)
Final exam study
25 hours ⏳ (1 week × 25 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [IBF562] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Feb 02, 2026 | International University of Sarajevo
Print Syllabus
Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| IBF562 | Special Topics in Finance | 3 | 0 | 6 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Admir Mešković | Office Hours / Room / Phone | Monday: 15:00-17:00 Tuesday: 12:00-15:00 |
|||||||
| ameskovic@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | The main objective is to face students with current and challenging issues in finance and to make them reflect on the research opportunities that those challenges provide. |
|||||||||
| Textbook | Imerman, M., & Fabozzi, F. J. (2025). The Economics of Fintech: Understanding Digital Transformation in Financial Services. MIT Press. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | The methods include lectures (which may involve PowerPoint presentations, videos, and audio aids), student presentations, projects, and class discussions. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction to Fintech | Syllabus, Chapter 1 | ||||||||
| Week 2 | The Economics of the FinTech Revolution | Chapter 2 | ||||||||
| Week 3 | Data Science and Its Role in FinTech | Chapter 3 | ||||||||
| Week 4 | Financial Intermediation | Chapter 4 | ||||||||
| Week 5 | Risk and Risk Management for FinTech | Chapter 5 | ||||||||
| Week 6 | Sources of Financing for FinTech Companies | Chapter 6 | ||||||||
| Week 7 | Financing Vehicles and Equity Options | Chapter 7 | ||||||||
| Week 8 | Midterm exam | |||||||||
| Week 9 | Payments Technology | Chapter 9 | ||||||||
| Week 10 | Digital Banking | Chapter 10 | ||||||||
| Week 11 | FinTech Lending | Chapter 11 | ||||||||
| Week 12 | Digital Wealth Management | Chapter 12 | ||||||||
| Week 13 | InsurTech | Chapter 13 | ||||||||
| Week 14 | Decentralized Finance and Blockchain Technology | Chapter 15 | ||||||||
| Week 15 | AI applications in Finance | Special reading material | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 35 | 4, 5 | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm exam | 1 | 35 | 1,2,3 | Not Allowed | |
| Participation | 1 | 10 | 1,2,3,4,5 | Not Allowed | |
| Case study | 1 | 20 | 1,2,3,4,5 | Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture Hours | 3 | 15 | 45 | Home study | 1 | 15 | 15 | |||
| Case study | 40 | 1 | 40 | |||||||
| Midterm exam study | 25 | 1 | 25 | Final exam study | 25 | 1 | 25 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 22/02/2026 | |||||||||