Digital Innovation covers the fundamentals of digital innovation and the development and implementation of novel and original solutions in which the innovation process, its outcomes, or the ensuing organisational and social transformation is embodied in or enabled by digital technologies. Digital Innovation is one of the core topics of the degree programme, so the course also provides a basis on which students can choose their electives. The course covers six primary topics:

• Fundamental properties of digital technologies and digital innovation
• Organising for digital innovation
• Digital platforms and ecosystems
• Digital innovation and capital creation
• Digital business models
• Digital entrepreneurship

• The module involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.
• Case studies are used to discuss the course contents. Contemporary scientific publications from Information Systems and Management are discussed in class.

After successful completion of the course, students will

Professional competence
• understand the basics of the fundamentals of digital innovation and the development and implementation
of novel and original solutions that are relevant to the field of information systems
• understand the main concepts, theories, and methods related to digital innovation

Methodological competence
• be able to apply the understanding and the methods into their projects or illustrative cases
• be able to analyse the role of digital technologies in existing business models
• be able to develop business models that consider options created through digital technologies

Social competence
• be able to collaborate and work in teams
• support each other during the learning process

Personal competence
• critically reflect on technological outcomes

• Students are provided with the lecture slides and supplementary material (e.g., selected journal articles)

Written exam (90min)

Digital Humanities stands at the intersection between digital technology and social action – between computing and humanities. Besides enabling digital innovation, digital technology has fundamentally changed the way we see the world, work, and socialise. We are increasingly challenged to make sense of data and information, and turn them into things we can use for different goals. On the other hand, we also need to adjust ourselves in order to collaborate with each other through digital technology – and sometimes even with digital technology itself. How far should we go? How do we find a balance? This course is primarily concerned with understanding different and sometimes contradicting views on the relationship between digital technology and social action. The course covers five primary topics:

• Introduction to digital humanities
• The computational turn
• Favourable views on digitisation and digitalisation
• Critical views on digitisation and digitalisation
• Examples of digital humanities projects

• The module involves interactive lectures with exercises to integrate theoretical knowledge with critical analysis skills.
• Case studies are used to discuss the course contents.
• Recent scientific publications from Information Systems and Digital Humanities are discussed in class.

After successful completion of the course, students will

Professional competence
• understand the basic concepts and underlying theories related to digital humanities
• understand different and sometimes contradicting views on the relationship between digital technology
and social actions

Methodological competence
• be able to analyse everyday examples based on these initial understandings

Social competence
• be able to collaborate in teams and support each other during the learning process

Personal competence
• be able to reflect on their own relationship with digital technology

• Students are provided with the lecture slides and supplementary material (e.g., selected journal articles).

Written exam (60min)

In Digital Business, students collaborate with small and medium-sized companies to develop new business models, open new markets, and innovate with existing products and services, so students learn to recognise, understand, develop, and exploit digital innovations. The course topics change from semester to semester, but the course usually addresses seven grand themes:

• Designing digital business strategy
• Digital entrepreneurship and intrapreneurship
• Opportunity recognition
• Business model innovation
• Value creation and cocreation
• Digital transformation
• Project management

• The course involves interactive seminars with workshops and regular presentations.
• The faculty and a jury of representatives from regional companies evaluate the students’ solutions in terms of innovativeness and usefulness and provide them with feedback and advice.

After successful completion of the course, students will

Professional competence
• understand the complex nature of digitalisation in small and medium-sized enterprises as well as start-up
ventures
• understand the entrepreneurial aspects in digital business: from opportunity recognition to designing digital strategy and business model and convincing potential stakeholders

Methodological competence
• be able to develop feasible solutions to their identified issues and evaluate them using appropriate methods

Social competence
• be able to collaborate in teams and with external partners
• be able to outline a project plan to implement their ideas and complete the project under time pressure

Personal competence
• demonstrate readiness to innovate and to view an idea, a problem, or a solution from several different
angles
• be able to articulate their ideas clearly in an elevator pitch, in order to persuade potential collaborators
and sponsors of the values of their ideas

Technological competence
• be able to identify the appropriate technologies to support digital business solutions

• Gupta, S. (2018). Driving digital strategy: A guide to reimagining your business. Boston, MA: Harvard Business Review Press.
• Rauser, A. (2016). Digital strategy: A guide to digital business transformation. North Charleston, SC: CreateSpace.
• Saldanha, T. (2019). Why digital transformations fail. Oakland, CA: Berrett-Koehler Publishers.

Seminar paper, presentations, project results; attendance is mandatory (80%)

Master students have the opportunity to take part in educational journeys to the world’s most important financial centres. Taking place annually, the educational journey adds a practical perspective to the academic content of the programme.

Destinations of previous journeys include: New York (2005), Shanghai (2007), Hong Kong (2009), Singapore & Kuala Lumpur (2011), New York and Chicago (2013) , Beijing and Shanghai (2015) and Singapore (2017).

Excursion

After successfull completion of this module, students

• know the role of international enterprises and organizations including banks, asset or hedge fund management services, portfolio managers, insurance companies, chambers of foreign trade, chambers of commerce, supranational organisations, ambassadors, politicians or universities in structuring the competitiveness of a financial market;
• know the specifities of the visited financial market;
• established an international and intercultural network.

Depending on the topic of the assignment and the geographical target of the educational journey.

See lecture within the module.

Ob Crowdfunding und Crowdlending, Online-Zahlungsdienste, Robo Advice, der Einsatz künstlicher Intelligenz, RegTech oder auch Outsourcing in die Cloud – all diese Themen bringen eine Vielzahl regulatorischer und aufsichtsrechtlicher Fragestellungen mit sich. Anhand der aktuellen Rechtsentwicklung mit besonderem Fokus auf das EWR-Recht, werden die damit verbundenen An- und Herausforderungen analysiert und darauf aufbauend mittels praxisbezogener Fallbeispiele Best Practices und Methoden zur Bewältigung dieser vielfältigen Aufgaben vermittelt.

-Wissen und Verstehen:
Die Teilnehmende verfugen uber vertieftes Wissen im Bereich der digitalen Innovationen. Sie kennen die Unterschiede, Vorteile und Herausforderungen der jeweiligen technologischen Modelle, wie diese einzusetzen sind, welche Schnittstellen es gibt, und verstehen komplexe Aufgabenstellungen.
-Anwendung von Wissen und Verstehen:
Die Teilnehmende sind in der Lage, regulatorische und aufsichtsrechtliche Fragen auf hohem Komplexitatsniveau zu verstehen und Losungen zu erarbeiten. Sie erkennen Herausforderungen, verstehen die sich daraus ergebenden Rechtsfolgen und konnen selbstandig Losungsstrategien entwickeln.
-Urteilen:
Nach Abschluss dieses Moduls sind die Teilnehmenden fahig, relevante Sachverhalten zu analysieren und zu beurteilen. Sie erkennen neue Moglichkeiten und damit verbundene Herausforderungen und konnen diese nach regulatorischen und aufsichtsrechtlichen Aspekten beurteilen.
-Kommunikative Fertigkeiten:
Die Teilnehmenden sind fahig, unterschiedliche Ansatze zielgruppengerecht zu kommunizieren, auf andere Argumente einzugehen und diese zu begrunden und zu verhandeln. Sie identifizieren die mit digitalen Innovationen verbundenen An- und Herausforderungen und konnen notwendige Massnahmen klar und eindeutig kommunizieren.
-Selbstlernfahigkeit:
Die Teilnehmenden finden sich in der Welt der digitalen Innovationen zurecht und konnen sich selbstandig mit der damit verbundenen rechtlichen und aufsichtsrechtlichen Aufgabenstellung in der Praxis auseinandersetzen. Sie erkennen Losungsmoglichkeiten und wissen diese in Unternehmen umzusetzen.

Smolinski/Gerdes/Siejka/Bodek, Innovationen und Innovationsmanagement in der Finanzbranche (2017); Alt/Puschmann, Digitalisierung der Finanzindustrie (2016); Klebeck/Dobrauz, Rechtshandbuch Digitale Finanzdienstleistungen (2018), Brühl/Dorschel, Praxishandbuch Digital Banking (2018)

Gruppenarbeit: Fallstudie inkl. Präsentation

Data Science covers statistical and exploratory techniques that are used to make sense of the vast and complex data sets that have emerged in business. Data Science is one of the core topics of the degree programme, so the course also provides a basis on which students can choose their electives. Students learn to detect patterns in large data sets in quantitative and qualitative formats to translate them into actionable insights. The course covers seven primary topics:

• Data visualisation and exploration
• Supervised learning techniques for regression (e.g. logistic regression)
• Supervised learning techniques for classification (e.g. classification trees)
• Unsupervised learning techniques (e.g. clustering, dimensionality reduction)
• Fundamentals of deep learning
• Text mining (e.g. topic modelling)
• Hands-on labs with Python

• The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.

After successful completion of the course, students will

Professional competence
• understand the basic concepts and methods of data mining and predictive analytics
• be able to assess the assumptions and quality of statistical models

Methodological competence
• know and be able to select and apply the right statistical models for a given task or data set
• be able to derive actionable insights from statistical results
• know basic visualisation and storytelling techniques

Social competence
• communicate effectively using visualisations
• understand different stakeholder perspectives in a data mining project

Personal competence
• critically reflect on analytical outcomes
• improve and mitigate self-inflicted errors

Technological competence
• be able to use Python including their libraries such as scikit-learn and matplotlib to apply machine learning
and to create visualisations

• James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning: With Applications in R. New York, NY: Springer.
• Witten, H., Eibe, F., & Hall, M. (2016). Data Mining: Practical Machine Learning Tools and Techniques. San Francisco, CA: Morgan Kaufmann Publishers.
• Provost, F., & Fawcett, T. (2013). Data Science for Business. Sebastopol, CA: O’Reilly Media.

Written exam (90min)

BPM and Organisational Practice explores Business Process Management (BPM) through an organisational-studies lens, so it is a BPM elective. Emphasizing the duality of stability and change in organisational work, the course covers the factors, mechanisms, and interventions that affect how processes behave over time. The course covers six primary topics:

• Organisation theory
• Process- and practice-based research
• Organisational routines
• Intra-organisational dynamics and endogenous change
• Organisational learning, unlearning, and forgetting
• The role of agency and intention in the execution of organisational work

The course involves interactive lectures with exercises to integrate theoretical knowledge with practical design and analysis skills.

After successful completion of the course, students will

Professional competence
• understand the key assumptions and management implications of BPM
• understand key assumptions about process work from organisation theory
• understand the main concepts of (strong) process theory
• understand the main competence of routine dynamics theory

Methodological competence
• be able to synthesize the main tenets of two different scientific fields (BPM and routine dynamics)
• be able to analyse organisational phenomena through the lens of (strong) process theory
• be able to attend to (subtle) social dynamics evolving throughout organising processes

Social competence
• Be able to change roles when addressing managerial questions (role as BPM expert versus role as organisation theorist)
• Be able to work together with colleagues on case assignments

Personal competence
• Be able to find unconventional approaches to BPM-related question
• Be able to reflect on strengths and weaknesses from specific scientific fields

Technological competence
• Know about ways to observe and measure process dynamics

• Students are provided with the lecture slides and supplementary material (e.g., selected journal articles).
• Langley, A., & Tsoukas, H. (2017). The SAGE Handbook of Process Organization Studies. London, UK: SAGE Publications.

Written exam (60min)

• Current and past developments in sustainable finance
• ESG data, data providers and materiality
• Environmental and social impact
• Channels of action: primary and secondary market, direct investments, real estate, politics
• Tools of action: positive and negative screening, ESG integration, proxy voting and engagement, green bonds and loans, political influence
• Regulatory frameworks and initiatives

Lecture

• Student will describe, understand and discuss past and current developments in sustainable finance
• Students acquire a basic understanding of Sustainable EU-Regulation
• Students understand the structure, challenges and alternative providers of ESG data
• Students can distinguish between different types of sustainable finance products and investment strategies
• Students understand and can apply the concept of materiality

• Schoenmaker, D. and Schramade, W. (2019). Principles of Sustainable Finance. Oxford University Press, Oxford.
• Kaiser, L. and Oehry, O. (2020). Überblick zur Klimawirkung durch Massnahmen von Finanzmarktakteuren. Im Auftrag des Bundesamt für Umwelt BAFU.
• CFA Institute & Swiss Sustainable Finance. (2017). Handbook on Sustainable Investments. CFA Institute Research Foundation.
• Swiss Sustainable Finance. (2016). Handbuch nachhaltige Anlagen - Hintergrundinformationen und Praxisbeispiele für institutionelle Investoren in der Schweiz

• Identifying, Measuring, and Management of Financial Risks
• Risk Categories and Associated Models: Market, Credit, Operational and Liquidity Risks
• Rating Agencies and Credit Ratings

Lecture

• understand both the importance and the potential of financial risk management,
• relate financial risk management to other areas of finance and within financial institutions,
• know about the risks associated with financial derivatives as well as their potential for applications in risk management and financial engineering,
• apply appropriate methods to identify, measure and manage financial risks,

Hull, J.C. (2018). Options, Futures, and Other Derivatives. Pearson
Jorion, P. (2009) Financial Risk Manager Handbook. Wiley

see lecture(s) within the module