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54856-01 - Colloquium: Banks and the Fintech Revolution (6 CP)
| Semester | spring semester 2026 |
| Course frequency | Every spring sem. |
| Lecturers | Kumar Rishabh (kumar.rishabh@unibas.ch, Assessor) |
| Content | Why do banks exist? Can fintechs and bigtechs replace centuries-old banking institutions, or do banks possess something irreplaceable? How is AI transforming credit decisions, and what happens when algorithms fail? Why did Credit Suisse, a 167-year-old institution, collapse in a matter of days? Why did Silicon Valley Bank and other U.S. banks implode in 2023, triggering the largest banking crisis since 2008? Should UBS now hold more capital, as the Swiss Federal Council proposes? What exactly are stablecoins: a revolutionary payment innovation or the next systemic risk waiting to unfold? This course is designed to help you think through these questions rigorously. We begin by examining how banks' core functions (maturity transformation, risk management, liquidity provision, payment processing, and information screening) are being transformed by financial technology. We explore how innovations in AI, machine learning, and blockchain are reshaping these traditional banking roles. Alongside this, we analyze the vulnerabilities and resilience of financial institutions through detailed case studies, including the 2023 U.S. banking crisis and the collapse of Credit Suisse, focusing on their underlying causes and lessons for financial stability. The course combines theory with practical application. You will study banking theories rooted in contract theory, gain a jargon-free introduction to machine learning techniques, and acquire hands-on experience applying these tools to banking and fintech datasets. Access to curated datasets will enable you to analyze real-world problems and develop practical insights for your essays. AI is integrated into the course both as a subject of analysis and as a practical tool. You will learn to use AI tools strategically: to accelerate research, assist with coding, and sharpen your analysis. But the goal is to augment your thinking, never to substitute it. We will develop approaches that leverage AI while ensuring you remain the critical mind behind every insight. Guest lectures by policymakers and industry experts complement the instructor-led sessions. Previous speakers have included representatives from FINMA, BIS, SNB, Raiffeisen Bank, Basler Kantonal Bank, Aperture, and Hypothekarbank Lenzburg, offering firsthand perspectives on regulation, banking practice, and technological disruption. No prior background is required, only active engagement, curiosity, and willingness to work hard. This course equips you with the skills to critically analyze the forces reshaping modern finance and to apply that knowledge to real-world challenges. |
| Learning objectives | This course will enable students to: • Understand the evolution and current challenges in the banking sector • Analyze how fintech and big tech companies are transforming financial services • Master key concepts from information economics and contract theory for banking applications • Gain hands-on experience using econometric and machine learning tools with real banking and fintech data • Critically assess the causes of recent bank failures and draw lessons for financial stability • Develop strategies for using AI tools that support learning without substituting critical thinking |
| Bibliography | The course is based on original papers. All the papers will be available on ADAM. Take a look at the course syllabus on ADAM for the list of papers covered in each lecture session. |
| Comments | This course is open to MIME students from the University of Bern and encourages active collaboration between students from both the University of Bern and the University of Basel. |
| Weblink | Weblink: Course Syllabus |
| Admission requirements | No formal prerequisites are required, but familiarity with school-level algebra and basic regression analysis is expected. Essential concepts will be reviewed during class sessions, and starter code will be available for all data exercises. Active participation and consistent effort are essential to succeed in this course. |
| Course application | Registration: Please enroll in the Online Services (services.unibas.ch); Eucor-Students and mobility students of other Swiss Universities or the FHNW first have to register at the University of Basel BEFORE the start of the course and receive their login data by post (e-mail address of the University of Basel). Processing time up to a week! Detailed information can be found here: https://www.unibas.ch/de/Studium/Mobilitaet.html After successful registration you can enroll for the course in the Online Services (services.unibas.ch). Applies to everyone: Enrolment = Registration for the course and the exam! |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Tuesday | 12.30-16.00 | Wirtschaftswissenschaftliche Fakultät, Auditorium |
Dates
| Modules |
Module: Field Electives in Finance and Money (Master's Studies: Finance and Money) Module: Selected Subjects of Economics and Jurisprudence (Master's Studies: Actuarial Science) Module: Specific Electives in Economics (Master's Studies: Business and Economics) Module: Specific Electives in Finance, Controlling, Banking (Master's Studies: Business and Economics) Specialization Module: Areas of Specialization in International and/or Monetary Economics (Master's Studies: International and Monetary Economics) |
| Assessment format | record of achievement |
| Assessment details | 1. Group Presentation (20%) Students work in groups of 2–3. The instructor assigns each group a topic in banking and fintech. Using AI tools and the course material, each group prepares a 20-minute session in which they teach the topic to the class. Presentations should (i) explain the main economic mechanisms, and (ii) link the topic to at least one model or paper from the course. The instructor provides written feedback to each group. 2. Essay (50%) Students write a group essay on a topic from the provided list or on a self-chosen topic (subject to approval). Essays are written in groups of 2–3 students. Each essay must analyse a concrete banking or fintech setting and connect it to the models and readings discussed in class. Most topics will involve working with data sets on banks, fintech firms or payment systems that are provided in the course. AI tools may be used as support, but grades will be based on the quality of the economic analysis, the use of data and theory, and the clarity of the argument. 3. In-class Test (30%): Students complete a 60-minute in-class written test that covers the main concepts and models discussed in the course. The test consists of short questions that ask students to explain mechanisms, interpret simple results, and apply course ideas to new situations. No electronic devices are allowed during the test. The test takes place in the second half of the semester; the format and sample questions are discussed in class well in advance. |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,1 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Business and Economics , studiendekanat-wwz@unibas.ch |
| Offered by | Faculty of Business and Economics |