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| Semester | Frühjahrsemester 2024 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende | Kumar Rishabh (kumar.rishabh@unibas.ch, BeurteilerIn) |
| Inhalt | In this course, we explore the dynamic world of modern banking, focusing on its essential roles and the emerging challenges it faces. Our journey includes understanding how banks support today's economy through crucial financial services like maturity transformation, risk management, and mitigating information asymmetries and contract complexities. We'll also dive into the significant impact of fintech innovations, driven by big data, artificial intelligence, machine learning, and digital ledger technology, and their role in reshaping the financial landscape. We will critically analyze the effects of fintechs and bigtechs, observing how they challenge traditional banking functions and potentially transform the financial industry. We'll use real-world events such as the US banking crisis of 2023 and the fall of Credit Suisse as case studies to understand the vulnerabilities and resilience of financial institutions. This course uniquely combines theoretical knowledge with practical skills. We cover banking theories rooted in contract theory, and offer a (jargon-free) introduction to machine learning techniques, with hands on experience on applying these techniques to banking and fintech data. You'll recive access to various banking and fintech datasets to work for your essays that will help you sharpen your analytical abilities in practical financial scenarios. Our curriculum bridges theoretical concepts with their real-world applications, equipping you to skillfully navigate the complexities of today's finance. No previous background in these topics is necessary, but a keen interest and proactive engagement will enhance your learning experience. |
| Lernziele | Upon completion of this course, students can expect to have gained: • Comprehensive understanding of the banking sector's evolution and its contemporary challenges. • Deep insights into the disruptive impact of fintech and bigtech in financial services. • Theoretical and practical skills in economic modeling, particularly in asymmetric information and contract theory. • Proficiency in applying machine learning to real-world financial and banking data. |
| Literatur | 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. |
| Bemerkungen | This course is also open to MIME students from the University of Bern and actively encourages collaboration between students from both the University of Bern and the University of Basel. |
| Weblink | Weblink: Course Syllabus |
| Teilnahmebedingungen | This course has no formal prerequisites, as advanced topics will be developed from the ground up, making it accessible to all interested students. While prior knowledge in microeconomics and econometrics may be beneficial, it is not a requirement. We particularly encourage motivated students, even those without prior background in these areas, to join. Engaging actively in discussions, asking questions, and utilizing opportunities to meet with instructors can greatly enhance the learning experience for all students, regardless of their initial level of familiarity with the subject matter. |
| Anmeldung zur Lehrveranstaltung | 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! |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| wöchentlich | Dienstag | 12.30-15.45 | Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32 |
| Module |
Modul: Ausgewählte Themen aus Ökonomie und Rechtswissenschaft (Masterstudium: Actuarial Science) Modul: Field Electives in Finance and Money (Masterstudium: Finance and Money) Modul: Specific Electives in Economics (Masterstudium: Wirtschaftswissenschaften) Modul: Specific Electives in Finance, Controlling, Banking (Masterstudium: Wirtschaftswissenschaften) Modul: Specific Electives in Monetary Economics and Financial Markets (Masterstudium: Wirtschaftswissenschaften) Spezialisierungsmodul: Areas of Specialization in International and/or Monetary Economics (Masterstudium: International and Monetary Economics) |
| Leistungsüberprüfung | Leistungsnachweis |
| Hinweise zur Leistungsüberprüfung | 1. Group Presentations (40% of the final grade): Groups, consisting of 2-3 students each, will present short 20-minute discussions on a selected published paper or case study. Over the semester, a student may make up to three presentations, but only the best two will count towards their final grade. The group discussions are designed to encourage a congenial and collaborative atmosphere, where presentations are opportunities for mutual learning and growth. Additionally, students receive individual written feedback from the instructor after each presentation, further supporting their development. 2. Essay (50% of the final grade): Students are required to write an essay on one of the provided topics or propose their own, subject to the lecturer's approval. Group essays (group of 2 students) are preferred, but individual essays are also accepted. 3. Class Participation (10% of the final grade): Your active engagement in class discussions is welcomed and positively impacts your final grade. |
| An-/Abmeldung zur Leistungsüberprüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,1 |
| Wiederholtes Belegen | beliebig wiederholbar |
| Zuständige Fakultät | Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch |
| Anbietende Organisationseinheit | Wirtschaftswissenschaftliche Fakultät / WWZ |