The ever-increasing digitalization confronts companies with dynamically changing environmental conditions requiring them to regularly adapt their product and service portfolios and business models to changing circumstances. In order to meet this requirement, an agile organizational culture is indispensable.
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Digitalization is necessary, but its costs are often not offset by corresponding additional revenues. Ecosystems can provide a solution.
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With a share of 10% of all FinTech companies in Europe, Switzerland is one of the leading innovation centers. The focus on distributed ledger technology is striking in Switzerland, especially in Crypto Valley Zug. In the meantime, 250 crypto companies have already settled there or are planning a location. However, Switzerland cannot rest on its laurels: to remain a leading innovation center, it constantly needs new FinTechs with innovative ideas. In order to identify gaps in the existing range of Swiss blockchain FinTechs and thus the innovation potential for further services, I analyze in this article the current service offering of the Swiss blockchain FinTech scene.
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The discussion on the use of artificial intelligence (AI) often revolves around the optimization of processes or the recognition of patterns in huge amounts of […]
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Multinational companies have extensive and complex supply chains to operate as efficiently as possible. Within these production networks there is little room for error and preventive stress tests are rarely carried out. The COVID-19 pandemic has shown how fragile such structures can be and what consequences can arise if too little attention is paid to risk exposure (Sneader & Lund, 2020).
But how could companies have better prepared for an unexpected event like the COVID-19 pandemic? And how relevant is organizational agility and resilience in this context?
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The current corona virus situation has shown us that we are capable of taking big steps in digitalization in a very short time in the education sector. Digital methods have already found their way into schools and universities, but this sometimes hesitant development was reinforced to an unprecedented degree by the homeschooling required during the peak of the pandemic. Collaborative platforms have grown enormously, and new teaching and learning formats have been introduced in the form of explanatory videos and virtual lessons or group work. One technology, or rather a concept that has been largely ignored so far, but which offers great potential for improving both digital and face-to-face teaching, is augmented reality (AR), the enrichment of reality with virtual content.
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According to a survey, 90% of bankers are convinced that open banking can increase the organic growth of banks by 10%[1]. A global banking survey also found that 86% of banks plan to use open APIs in the next 12 months to enable open banking capabilities[2]. To address this development and better understand the opportunities and implications of the trend towards opening up a banks’ own IT infrastructure, the Business Engineering Institute and Commerzbank have jointly authored an open banking white paper on the future of corporate banking collaboration. In this white paper, we explored the overarching questions of what the open banking concept is all about and how it will change value creation, particularly in corporate banking.
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Recently, the Swiss Bankers Association published an overview that outlines the status of open banking in Switzerland and formulates requirements for its further development of open banking. These requirements include the clear strategic positioning of Swiss banks and the joint development of standardized APIs for data exchange between financial institutions and third-party providers. The aim of this overview is to “support the dialogue in the financial center”, as Richard Hess writes in the initial contribution to the blog parade of the Swiss Bankers Association. The Open Banking Summit of the standardization initiative OpenBankingProject.ch pursued the same goal on September 10th, with various presentations focusing on these two requirements.
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The examples of Alibaba, Amazon and Airbnb impressively demonstrate the value creation potential of ecosystems compared to traditional, linear value creation structures. But how do you plan and develop an ecosystem? As I explained in the first part of this blog post, traditional strategy concepts cannot be easily transferred to ecosystems. So what constitutes an ecosystem strategy? In the following, I will present three further prerequisites for the successful design of an ecosystem, which must be part of every discussion about building or participating in any ecosystem.
Continue reading » The term ecosystem strategy is very present in science and practice and numerous strategic recommendations for action, for example for taking on certain roles, can already be identified. However, a uniform understanding of the term or an overarching approach to building up or positioning oneself in ecosystems does not yet exist. In this blog post I try to approach the topic by identifying four prerequisites for the success of an ecosystem and by investigating the extent to which an ecosystem strategy differs from a classical corporate strategy.
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Since the beginning of 2020, the coronavirus pandemic has caused an enormous slump in the global economy due to lockdowns all over the world. The IMF expects global GDP to decline by 5%, and for the euro zone it is likely to be as much as 10.2% [1] – and these are the figures before a possible second wave. It remains to be seen how the economy will recover. What can already be well assessed, on the other hand, are the qualitative effects of the pandemic on the macro trends relevant to the financial industry.
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In the first two contributions to this three-part series, we have shown that the simultaneous use of distributed ledger technology and artificial intelligence can improve today’s lending process in many ways. However, the lending process is only one of many processes that can potentially benefit from the merging of DLT and AI. In the following we have compiled the process characteristics that indicate that a process leads to the convergence of the two technologies and can therefore be optimized by them.
Continue reading » Technological convergence means that two or more technologies merge into a single system that is more powerful than each of the technologies individually. Since AI and DLT are technologies that have some opposing characteristics (e.g., centrality vs. decentralization; transparency vs. black box), the two technologies complement each other and can compensate for crucial weaknesses of the other. Since the lending process is one of the main processes in the banking business and involves both communication and data analysis (AI) and the transmission of sensitive data (DLT), it is ideally suited for a practical examination of both the prerequisites and the effects of technological convergence.
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The distributed ledger technology (DLT) and artificial intelligence (AI) are two promising technologies that are at the top of their hype cycle. Scientists assume that the convergence of the blockchain, the Internet of Things (IoT) and artificial intelligence offers considerable opportunities, such as accelerating the pace of service, process and business model innovations. However, the information available in the current literature and research on how such an integration could be implemented in practice is still sparse. Over the next week, this series of articles will explore how specific elements of DLT and AI can be combined to achieve potential technological convergence, and what significance this convergence has for the lending process.
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The economy and society in general have benefited greatly from increasing digitization and access to ICT. However, this development also has its downsides. In recent years, both scientific studies and practical reports have increasingly pointed out that the use of ICT in both private and organizational contexts can lead to strong stress perceptions among the respective users. This specific form of stress is called technostress. This blog post explains the causes and effects of technostress and suggests measures companies can take to minimize technostress for their employees.
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It is an open secret that turbulent times have begun for banks and financial service providers. The market environment is more volatile than ever before – external conditions change often, quickly and extensively. How can banks nevertheless be successful in this environment? The key is agility, which can only succeed if the leadership style, which has a significant influence on the personal attitude, mindset and behavior of employees, is also appropriately agile. The question that arises in this context is: What characterizes an agile leadership style and how can the transformation to this leadership style be successful?
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Our modern world, increasingly accelerated by innovative technologies, demands constant adaptation from companies. Digital transformation is now omnipresent. Now, every transformation also means business model innovation. This innovation can either be developed internally or integrated into the company through external acquisitions. Which of these options is selected depends, on the one hand, on the expertise available within the company and, on the other hand, on the prevailing management system, i.e. on the type of guidelines by which the board of directors sets targets for top management and against which it evaluates its performance. There are basically two options available to the board of directors: strategic or financial control. In this article, we will look at the advantages and disadvantages of these two management systems and which of them is better suited to sustainable innovation and transformation, the prerequisites for long-term success in business today.
Continue reading » While in the past it was sufficient to improve a well-functioning business model through incremental innovation in an attempt to preserve its competitive advantage over the long term, an ever-changing environment with technological innovations and changing customer needs and expectations requires companies to constantly transform themselves and explore new business areas. For this reason, transformation in the context of digitalization is one of the major research topics at the CC Ecosystems. While we at the Competence Center focus primarily on transformation methods and capabilities, in this two-part series, I would like to focus on transformation governance, in particular the role of the board of directors and executive management in initiating and implementing a transformation. Part 1 focuses on the environmental changes that make a transformation necessary and outlines the measures to be introduced by the board of directors.
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In order to position itself in the FinTech market with an AI-based application, a company needs a deep understanding of the AI FinTech market, i.e. both the existing applications and the business models that have developed around these applications. In the first part of this blog post, we used the AI Application Taxonomy, a tool to describe the properties of an AI application in more detail, to analyze a total of 79 AI applications from 75 FinTechs and to identify four overarching application archetypes. In the second part, we now focus on the business models within which these applications are used and the resulting positioning options for financial institutions.
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Assessing the strategic opportunities that the use of Artificial Intelligence (AI) provides a company with requires a sound understanding of AI-based applications. Such an understanding includes not only knowledge of the possible functionalities of AI-based applications (Dietzmann & Alt, 2020), but also knowledge of the characteristics that describe these functionalities in more detail (e.g. the speech input for the speech recognition functionality can be received as an acoustic signal or be available digitally in the form of a video). Combined, these two aspects enable a detailed analysis of existing AI-based offerings, on the basis of which positioning opportunities vis-à-vis competitors in the target market can be identified. The Competence Center Ecosystems has therefore not only developed the periodic table of artificial intelligence but also the “AI Application Taxonomy”, which contains the currently observable characteristics of AI-based applications. In the current and first part of the blog post we introduce the taxonomy and then analyze a sample of European AI FinTechs.
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Scientists are people who work theoretically, are very correct and often withdrawn – so the widespread impression. Far from it, as I was able to experience at the 53rd Hawaii International Conference on System Sciences (HICSS): From a keynote on “bullshit” in the scientific literature to findings on artificial intelligence (AI) in game development and the future of work, exciting, very diverse and above all very practice-oriented topics were addressed. In the following I give a short summary.
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The Business Engineering Institute St. Gallen and the Frankfurt School Blockchain Center cordially invite you to a virtual panel discussion on May 20th where landmark companies in the blockchain space discuss the outlook for crypto assets as an alternative asset class as well as forthcoming market developments.
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In an interview with “Konfuzius-Institut” – the Magazine, Daniel Fasnacht explains how the importance of money is beginning to change, how digital payment systems work in China and what role China could play in financial services and trade worldwide.
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APIs represent an important component of the digital transformation towards networked business models. This inevitably raises questions: Do I start by providing an API developer portal or an overall strategy? Which infrastructure components should be used and to what extent should I provide central guidelines? How can I prioritize possible activities? The “API House of Digital Business” provides assistance in answering these questions.
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The financial sector is currently facing one of its biggest challenges with the Corona pandemic: A collapse in economic growth, high unemployment, credit defaults and volatile stock markets. Furthermore, the old problems such as pressure on margins, increasingly intense competition, the shift of the customer interface towards innovative fintechs and the ubiquitous digitalization have not yet been solved. These developments challenge traditional business models of local banks, but also offer opportunities for those who are willing to change or reinvent themselves.
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