Management nicht-finanzieller Risiken: eine Forschungsagenda

Franke, Günter

doi:10.1007/s41471-020-00096-z

Schmalenbachs Z betriebswirtsch Forsch

2020

DOI: 10.1007/s41471-020-00096-z

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Management nicht-finanzieller Risiken: eine Forschungsagenda

Günter Franke

Abstract: Zusammenfassung Das Management nicht-finanzieller Risiken wie ESG-, Nachhaltigkeits- und Compliance-Risiken stellt Unternehmen vor große Herausforderungen. Im Gegensatz zu finanziellen Risiken ist zu nicht-finanziellen Risiken nur wenig Information verfügbar. Dies erschwert ein effektives Management erheblich. Unternehmen haben in den letzten Jahren hohe Verluste durch nicht-finanzielle Risiken erlitten. Die Corporate Governance dieser Risiken wirft zahlreiche, ungelöste Fragen auf. Dieser Beitrag skizziert mö… Show more

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The Impact of Transitory Climate Risk on Firm Valuation and Financial Institutions: A Stress Test Approach

Schult,

Müller,

Friedl

et al. 2023

Schmalenbach J Bus Res

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Addressing recent calls by European regulatory and supervisory authorities, we develop a new bottom-up climate risk assessment method to examine the resilience of the European banking industry regarding transitory climate risks. We illustrate our approach by estimating the impact of a 50–100 EUR carbon tax per $$\textit{tCO}_{2}$$ tCO 2 equivalent on the valuation and default risk of STOXX Europe 600 firms. For about 5% of the sample firms, we find asset devaluation shocks larger than 30% and for about 16% of the firms probabilities of default (PDs) dropping below investment-grade level of 3%. At the sector level, our results yield asset devaluations shocks of 15–36% and new PDs of 5–34% for the six most affected sectors. Running a stress test on credit risk based on these results, we find a decrease in capital ratios between $$-1.2$$ - 1.2 and $$-1.6$$ - 1.6 percentage points for key regulatory capital ratios in the most adverse scenario while only addressing 36% of the bank’s total risk-weighted assets. Our analysis sheds light on the substantial transitory climate risk for asset portfolios of banks and contributes to the pressing question how to integrate climate risk into risk management and regulation of financial institutions.

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The Impact of Transitory Climate Risk on Firm Valuation and Financial Institutions: A Stress Test Approach

Schult,

Müller,

Friedl

et al. 2023

Schmalenbach J Bus Res

View full text Add to dashboard Cite

show abstract

Knowledge Leaks in Data-Driven Business Models? Exploring Different Types of Knowledge Risks and Protection Measures

Fruhwirth,

Pammer-Schindler,

Thalmann

2024

Schmalenbach J Bus Res

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Data-driven business models imply the inter-organisational exchange of data or similar value objects. Data science methods enable organisations to discover patterns and eventually knowledge from data. Further, by training machine learning models, knowledge is materialised in those models. Thus, organisations might risk the exposure of competitive knowledge by sharing data-related value objects, such as data, models or predictions. Although knowledge risks have been studied in traditional business models, little research has been conducted in the direction of data-driven business models. In this explorative qualitative study, we conducted 28 expert interviews in three rounds (two exploratory and one evaluatory) and identified five types of risks along the three basic types of value objects: data, models and predictions. These risks depend on the context, i.e., when competitive knowledge could be discovered from shared value objects. We found that those risks can be mitigated by technology, contractual regulations, trusted relationships, and adjusting the business model design. In this study, we show that the risk of knowledge leakage is a relevant risk factor in data-driven business models. Overall, knowledge risks should be considered already during business model design, and their management requires an interdisciplinary approach via a balanced assessment. The level of knowledge protection from a technology perspective highly depends on computer science innovations and thus is a moving target. As an outlook, we suggest that knowledge risk will become even more relevant with the extensive usage of machine learning and artificial intelligence in data-driven business models.

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Management nicht-finanzieller Risiken: eine Forschungsagenda

Cited by 2 publications

References 37 publications

The Impact of Transitory Climate Risk on Firm Valuation and Financial Institutions: A Stress Test Approach

The Impact of Transitory Climate Risk on Firm Valuation and Financial Institutions: A Stress Test Approach

Knowledge Leaks in Data-Driven Business Models? Exploring Different Types of Knowledge Risks and Protection Measures

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