Module Description

The students get a high-level overview of managing a bank. On the one hand, they get familiar with the core aspects of traditional instances of a universal bank such as the credit department, the treasury, and the risk function. On the other hand, they learn the implications of recent disruptive elements of the banking industry such as digitisation, new types of trading venues, distributed ledger technology (DLT), FinTech, open banking, and machine learning (ML). The module is designed as a useful preparation for internationally recognised certificates such as the «Chartered Financial Analyst (CFA)», the «Certificate in Quantitative Finance (CQF)», or the «Financial Risk Manager (FRM)».

Knowledge of elementary probability theory, interest in financial markets

Closed-book exam; it is recommended that the examinees bring along a pocket calculator without communication abilities that features at least the four basic operations (±,×,÷) as well as the exponential function e^x together with its inverse ln(x).

Professional Competencies

Participants can

• evaluate the impact of innovative concepts (digitisation, DLT, ML, open finance) on traditional banking models, identifying opportunities and challenges, understanding their implications for competition, innovation, and customer experience in the banking sector, and how they may impact different business models.
• explain the origination, relevance, and countermeasures of financial risk, applying risk management principles to support various aspects of banking operations.
• design and implement robust asset-liability-management (ALM) strategies, structuring the balance sheet to manage interest rate risk and liquidity risk effectively, while accounting for constraints and profitability and considering the specific needs of diverse banking business models.

Methodological Competences

Participants can

• use comparative analysis techniques to assess the business models of neobanks, understanding their differentiation from traditional banks and their impact on the broader banking industry.
• apply innovation analysis tools to assess the role of FinTech in reshaping the financial services industry, identifying key innovations and potential synergies with traditional business models.
• employ assessment methodologies to identify and manage risks holistically, tailoring measures to the specific needs of different business models.
• quantify risks.
• implement model risk management frameworks in accordance with market standards (e.g., SR 11-7), ensuring the accuracy and reliability of financial models in various banking business contexts.

Self-Competences

Participants can

• independently research and stay informed about historical developments in banking, demonstrating a commitment to continuous learning and staying abreast of industry evolution.
• manage their personal and professional development to navigate the evolving landscape of risk management, adapting to changes in regulatory frameworks and industry best practices for various banking business models.
• reflect on their decision-making processes, recognizing the ethical implications and societal impact of banking practices, aligning personal values with the principles of different business models.

Social Competences

Participants can

• communicate complex risk management concepts and strategies clearly and persuasively to diverse stakeholders, including those without a financial background, facilitating understanding and cooperation within various business models.
• collaborate effectively with experts from diverse fields, recognizing the interdisciplinary nature of managing a bank and the need for cooperation to address challenges and opportunities in various business models.
• engage in constructive dialogue on the societal impact of banking, considering issues such as financial inclusion, privacy, and accessibility in the context of different business models.

Bank Management

• Introduction and banking history
• Learning from financial crises
• Key mechanisms of banks
• Type of banks
• Banking environment in Switzerland and around the world
• Basics in regulatory, legal, and accounting requirements
• The future of banking (digitisation, FinTech, BigTechs in finance, neobanks, open finance)
• DLT and crypto assets
• Negotiation techniques in banking

Financial Risk Management

• Introduction to financial risk management (origination, relevance, countermeasures, elements of best practise)
• Credit risk management (loss distribution, risk quantification, credit models, rating models, multiple yield curves, marketable products and derivatives, Basel accords)
• Market risk management (market overview, financial products, hedging)
• Other risks
• Asset-liability-management (ALM)
• Model risk management (SR 11-7)
• Introduction to machine learning (ML) in finance and its implications on risk management

Lectures, exercises, case studies, discussions, excursions

• The lecture is based on a comprehensive slide deck.
• Guided self-study (mainly exercises) is key for the understanding of the content.
• Further literature for in-depth studies will be announced during the lectures.