It’s the aim of this blog post to put the theory of disruptive innovation in its proper context and to use it to explore the extent to which blockchain is a disruptive innovation that threatens the continued existence of financial services firms.
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“Financial Industry Meets BigTech”: On the 25th of August 2022, the third Open Banking Summit opened its doors in the Google event rooms in Zurich. The OpenBankingProject.ch organized this event for the third time and once again provided a stimulating get-together on the topic of open banking. The event featured national and international success stories, and the subsequent panel discussion reflected on and discussed selected topics and questions posed by the audience. Once again this year, around 120 decision-makers from the Swiss financial sector gathered to learn about current developments and to network over the subsequent aperitif.
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Various trends, such as an increased focus on customer interaction and embedded banking, will shape the bank of the future. To provide services along the entire “customer journey”, banks are increasingly dependent on networking with other industries. The expansion of partnerships in the ecosystem goes hand in hand with the promotion of integration capabilities via APIs and steady investment in the banking architecture. The latest Core Banking Radar article examines the system architecture of the bank of the future and, in this context, compares the four neo-core banking systems examined in earlier publications of this series.
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In recent years, the call for data-driven decisions and processes has grown rapidly in companies across every industry. Data-driven companies such as Apple, Alphabet, and Microsoft are now among the most valuable companies in the world. But in order to make data-driven decisions, different challenges concerning a company and its data (management) need to be solved. These include the challenge of keeping an overview of their own data stocks. An overview of one’s own data is playing an increasingly important role in the financial industry, too. Banks must be able to disclose their data to the regulator at any time, and regular reporting is becoming the norm. In this context, the principle of “data lineage” has become established. Based on the approach of metadata management, this concept enables the structuring and visualization of one’s data inventories and sources. The following article explains the most important basics of the topic “data lineage” and shows possible areas of application in the financial industry.
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Since DeFi Summer 2020, DeFi applications have become a significant trend in the blockchain industry. However, vulnerabilities of DeFi applications have also been identified over the past 24 months. The third and final part of our series “Decentralized Finance – a Hype, a Threat or an Opportunity for Regulated Financial Institutions?” takes a closer look at recent developments in the DeFi sector (DeFi 2.0) and how they address well-known challenges in the context of DeFi, such as the potential for errors when setting up smart contracts, the lack of incentive structures for investors, or the requirements for investors’ technical and professional knowledge, without compromising the strengths of DeFi applications.
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Software is eating the world. The production of high-quality software solutions is increasingly becoming a decisive competitive factor for companies that operate in the environment of digital technologies. Particularly in a highly regulated market, such as the financial market, very special challenges apply to the companies involved in software development. One financial services provider that has been successfully using this approach for three years now is Commerzbank, and as part of a project, we had the opportunity to explore the topic of CI/CD with them in general and their experiences and learnings in particular. The result is the “CI/CD White Paper”.
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The success of agile teams or even entire agile companies is not exclusively due to the application of agile techniques, practices and methods, but above all to a certain attitude, way of thinking and behavior of both the individual and the entire team – the so-called “agile mindset”. And the agile mindset is an essential success factor in an agile transformation. In this post, I’d like to explain in more detail why this is so.
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The abbreviation OKR, which stands for objectives and key results, is a method that pursues the goal of promoting transparency, clarity and communication of goals and justifying the prioritization of activities. In February, Fabian Lehner already wrote about the basics and the potential of OKRs in the blog post “OKR – The Key to a Successful Company”. After all, many fast-growing companies such as Google, Spotify, LinkedIn or Amazon use this method. Building on this blog post, today we would like to explore the question of how OKRs support agile management and how agile leadership with OKRs actually works.
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Everyone is familiar with the following situation from everyday life: financial service providers or service providers (e.g., mobile network operators) offer services only for registered and verified users. The consequence: In order to be able to prove one’s own identity online, a new account must first be created using an e-mail address and a selected password. The process of creating and verifying different accounts results in a single user having many online identities and involves almost as many identity providers. Above all, the protection of one’s own data falls by the wayside in many cases. The advancement of blockchain/distributed ledger technology in recent years has given rise to a new approach to online identity processing and verification, Decentralized Identity. This post explores the concept as well as the underlying technology and highlights advantages over the traditional use of identity providers and user accounts.
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In the media, Meta (formerly Facebook) is positioning itself very strongly as the future metaverse, and it seems as if Meta is building the “one” metaverse. This impression is deceptive. In this article, we will talk about what a metaverse is, which competitors are currently building metaverses, and what opportunities they open up for banks.
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The term “business ecosystems” is not only a term used by the Competence Center Ecosystems of the Business Engineering Institute St. Gallen (CC Ecosystems), but it also attracts a large number of publications in the broader business and academic community. But what does it describe in concrete terms and what basic definition do we refer to when we talk about the development of business models within business ecosystems and the accumulation of “value” among individual actors (value capture)? In what follows, I first provide an overview of various aspects of ecosystem research. Subsequently, the focus will be on the definition of ecosystems as a specific structure of the organization of interaction in a network. Finally, implications for the work in the Competence Center Ecosystems are described.
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The term decentralized finance (DeFi) refers to a decentralized, blockchain-based architecture for processing financial transactions without intermediaries. we will show in this article why offering access to digital assets and DeFi business models is worthwhile for financial institutions and what challenges they have to overcome in order to provide such an offering to their customers. Based on practical examples, positioning possibilities for regulated institutions will be presented as well as concrete opportunities and challenges.
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The development of a business ecosystem promises the opportunity to provide existing customers with integrated services through cooperation, in some cases across industries, and to gain access to new customer groups. However, building a business ecosystem by yourself is a challenging task, as there are many parties to orchestrate around a value proposition that is attractive to all participants. To increase the chances of success for such a project, it is worth taking a structured approach that not only helps with the design of a promising solution, but also with discovering potential stumbling blocks as early as possible and, at best, avoiding them. One such approach, which is already used by several banks in German-speaking countries, is presented in this article.
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The amount of data about real products, processes, and services has increased dramatically in recent years. This opens up new possibilities for planning, simulation and analysis. For this purpose, more and more companies use the concept of a digital twin. But what are digital twins and what potentials do they offer at the enterprise level, especially in the financial industry?
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In the financial industry, customers expect high standards with regard to data protection and the integrity of their own data. Nevertheless, from the perspective of value creation, it is essential for banks to evaluate customer data using statistical methods and algorithms. Banks are thus caught in a conflict between maintaining data privacy and enforcing their own business model. To address this problem, the concept of “federated learning” has become established on the market in recent years, in which the data used for model training is always stored decentrally and the models are trained decentrally.
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The traditional approach to AI focuses on the process of training the model. The underlying data is often a secondary concern. This approach works particularly well for Internet corporations, as they have vast amounts of data and the capabilities to analyze it. In contrast, there is little potential for using AI in small businesses with this approach due to a lack of data. Therefore, it is worth taking a look at the data – moving away from model-centric to data-centric AI.
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Decentralized Finance (DeFi) has been one of the dominant trends in digital assets at least since the DeFi summer 2020. Since the summer of 2020, the digital assets community’s gaze has turned towards the possibilities of a decentralized financial ecosystem, DeFi applications have become highly popular and the prices of corresponding tokens have multiplied. Why is DeFi seen as having such great potential and what does this mean for regulated financial institutions? In the next three blogposts, I will outline these and other questions, show different perspectives and provide an outlook on the opportunities for regulated financial institutions in the context of DeFi. To get started, this blog post will outline the functionalities of DeFi applications, present selected use cases, and highlight opportunities and risks in this context.
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Today, markets are characterized by constant change. To cope with this, many companies are applying agile methods. This article investigates how agile methods potentially affect the achievement of corporate goals in general and those in the financial industry in particular, taking the most widely used agile method, Scrum, as an example.
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The agile organizational model of the Swedish music and video streaming service Spotify has been the talk of the town for some time now. Many banks, including Commerzbank and ING, are basing their organizational structure on the Spotify model. But what actually distinguishes the model? And what is the truth behind the statement that Spotify itself has not used the model at all?
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In cooperation with the Business Engineering Institute St. Gallen (BEI), the Core Banking Radar of Swisscom has been monitoring the system support of banks since 2017, and analyses the most relevant systems for the Swiss market using a comprehensive assessment model. The latest publication of the Core Banking Radar looks at Vault Core from the U.K.-based company Thought Machine, which aims to adopt best practices in software development from technology companies with a cloud-native platform and give banks the flexibility to develop any product with smart contracts.
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For a good four years now, open banking has been a topic considered relevant by the Swiss financial industry. This was triggered in particular by the EU regulation PSD2, which became valid for all member states in 2018 and was subsequently implemented. Various players have been working on this topic since then, but implementation is progressing slowly.For this reason, the State Secretariat for International Financial Matters (SIF) feels compelled to make a clear announcement. Regulation seems to be getting closer.
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Ideally, a bank’s data strategy should be derived from its corporate strategy. Possible goals of the data strategy can be process optimization with associated cost reduction, better customer understanding (which can also lead to cost reduction or revenue optimization), or the development of new business models. The following blog post provides an overview of which data strategies for banks there are generally and which use cases can be observed in practice.
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A platform, sure, that’s something you can build other things on. I’m sure we all remember the “Lego plates”, which provided the basis for giving free rein to one’s imagination and indulging in architectural test projects. In economics and science, it is unfortunately not as easy to define the platform concept as in the example described above. With this article, we will now try to shed some light on platform definitions. In addition, we will shed light on the core value driver – network effects – and establish the concept’s connection to business ecosystems.
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The world is becoming increasingly unpredictable and chaotic. This makes it all the more important for a company to be able to respond appropriately to new circumstances. OKR, short for “Objectives and Key Results,” is a dynamic steering tool that helps to ensure that all activities contribute to achieving the same, most important goals within the organization.
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More extensive business cases such as opening a bank account or an account with a FinTech require several minutes of time each for a low-value-added customer experience – wouldn’t it be great if you could skip all the tedious steps relating to data collection during onboarding and start right away with the advisory service or the effective satisfaction of your core needs? These and other questions have been considered for a little more than half a year as part of a workshop series of the OpenBankingProject.ch (OBP) and discussed together with more than 30 companies from the Swiss financial industry. This article is intended to provide an overview of the background, initial delivery results as well as the current state of knowledge of the efforts within the OpenBankingProject.ch workshop series.
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