Everything about blockchain
Claims such as “robo advisors will replace bankers” or “banks will have disappeared” could be read frequently over the last decade in connection with accelerated digitization. However, we don’t notice much of this in Europe. Is the fintech movement really a revolution or rather an evolution?
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Despite many known advantages, it is still difficult, especially for practitioners, to identify concrete application areas for blockchain-based applications. This article takes this as its starting point and presents a sector-independent typology of application fields, which not only serves to analyze existing blockchain applications, but also provides users with an orientation as to which general possible uses there are for the blockchain and how complex an initial implementation of the respective applications can turn out to be.
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For small and medium-sized enterprises (SMEs), AI offers enormous potential for scaling and increasing efficiency, but for these companies in particular there is no alternative to using GAFA services because they themselves lack, for example, machine learning knowledge or the necessary data to train algorithms. An analytics marketplace could solve these challenges.
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Two weeks ago, we introduced the BlockWiki here on the blog, a website where we compile and explain the most important blockchain and DLT terms. The blockchain map, a graphical summary of blockchain terms, can also be purchased there. The overview differentiates between the technical and the business view of the Blockchain. After the left side with the technical view was described in detail in the blog post “The Technical Side of the Blockchain Map”, in this article we focus on the business view of the blockchain universe and explain the terms depicted there within their context.
Continue reading » In our last blog post, “The BlockWiki – The Blockchain Explained,” we introduced the BlockWiki, a compilation of blockchain terms and research on blockchain and distributed ledger technology. One component of the BlockWiki is the Blockchain Map, which graphically depicts the technical background, various uses and functions of the technology. It is divided into two sections: technical view and business view. In this blog post, the focus will be on explaining the elements of the technical side.
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The blockchain is gaining more and more attention and importance worldwide and across industries. Although there is a broad field of application behind this technology on both the technical and economic side, the terms surrounding blockchain in research are not entirely consistent and often unclear. The BlockWiki is a website where relevant terms regarding the blockchain are explained and related to each other and can therefore be used as a reference tool by anyone interested in the blockchain.
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On the occasion of the 20th anniversary of the Agile Manifesto, I would like to take another look at the central concepts of the document. Because even after this long time, the values and principles contained represent the basic tenets of the agile working method and can be found in many different agile methods, such as Scrum, Kanban or SAFe.
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In my lecture, “The Tokenization of Everything,” I explore the topic of tokenization starting from the concept all the way to the status quo of the token economy. The lecture was created as part of the Frankfurt School Blockchain Center’s Industry Insights series.
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Breaking up the value chain in the financial industry has been explicitly promoted and demanded in all states of the European Union since January 13, 2018 by the Payment Services Directive II, or PSD2 for short. PSD2 gives AIS and PIS open access to customer account data and payment behavior via application programming interfaces (APIs). This creates potential for the use of AI technologies.
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In my last post, I explained what characteristics distinguish the robo-advisory process from that of traditional client advice provided by a human advisor. Today, I explain how exactly these characteristics affect the traditional client advisory process and change it to create the robo-advisory process that I presented in the third post of this series. Finally, I answer the question of which of the two advisory processes is the better one.
Continue reading » In my last post, I detailed the customer advisory processes for a human advisor and a robo-advisor. Today I explain what causes these differences. This step is important to be able to understand and explain the differences between the two advisory processes and then, in a next step, to be able to derive the impact of robo-advisory services and to evaluate the advantages and disadvantages of robo-advisors compared to the traditional customer advisory process.
Continue reading » My last post before the Christmas break was about which business models and strategies a robo-advisor can align its offering with. Today, I will present the customer advisory processes of traditional, human banking advisory services and robo-advisors. In the rest of the series, I will then discuss the impact caused by robo-advisors which form of advisory is better and whether robo-advisors will be able to replace bank advisors in the near future.
Continue reading » Last week’s post was about how robo advisory services are defined and how they came into being, whether they are serious competition for banks, and what stage of development robo-advisors are at now. Today I present the prevailing business models and strategies of robo-advisors.
Continue reading » In the course of the change from a personalized customer experience at a bank to the desire for standardized and digitized processes, “robo-advisors” are becoming increasingly important. Today’s article looks at how robo advisory services are defined and how they came into being, whether they are serious competition for banks, and what stage of development robo-advisors are at now.
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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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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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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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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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