On November 13, the members of the OpenBankingProject.ch met for the eleventh time to discuss current developments in the field of open banking in Switzerland and to take a look into the future together. The event offered exciting insights into the latest advances and chal-lenges in the sector. In this blog post, the most important highlights and insights of the day are described.
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In collaboration with Swisscom, a series of articles has been created to answer typical cloud myths in a banking context. We will try to explain these together with three articles and give you simple and common cloud wordings to help you understand the cloud.
In today’s article, we will address the last three myths. If you missed the last article about myths 1 and 2, check here.
Myth 1: The cloud always saves money
Myth 2: The cloud makes it easy for cybercriminals
Myth 3: Once you’ve chosen a cloud provider, there’s no going back
Myth 4: Software in the cloud makes you more innovative
Myth 5: Cloud migration is too complex
In collaboration with Swisscom, a series of articles has been created to answer the typical cloud myths in a banking context. We will try to explain these together with three articles and give you simple and common cloud wordings to help you understand the cloud.
In today’s article, we will clarify Myth 1 and Myth 2:
Myth 1: The cloud always saves money
Myth 2: The cloud makes it easy for cybercriminals
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In collaboration with Swisscom, we have created a series of articles to address the typical cloud myths in the banking context. We try to explain these together with three articles and give you simple and common cloud wordings to help you understand the cloud.
In today’s article, we clarify the current market trend and the different cloud models that are available.
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The special feature of LLMs: they can be asked questions using natural language and also respond using natural language. The knowledge required for this was stored in the parameters of the LLM during extensive training with huge amounts of data (“parametric memory”). The sometimes inadequate quality of the answers, especially in specific domains, can be improved on the basis of “in context learning” approaches using prompt engineering methods or the more complex fine-tuning of the LLM. This is one of two dimensions of improvement options: changing the capabilities of the LLM and/or the quality of the context provided.
The last article in this series on generative artificial intelligence highlighted the characteristics and weaknesses of LLMs as well as approaches for possible improvements. So far, another dimension of LLM improvement has not been discussed in more detail: contextual enhancement by means of a Retrieval Augmented Generation (RAG) process, which enables the LLM to use external knowledge to provide up-to-date and subject-specific answers. In this blog post, Wilhelm Niehoff presents the RAG method and current development approaches.
Fan tokens have established themselves as an innovative digital asset class that forms an interface between cryptocurrencies, blockchain technology and the sports sector. They enable a new form of fan participation and offer exclusive benefits such as co-determination rights in club decisions and access to special rewards and games. These blockchain-based assets, which have already been issued by 81 sports organizations – including prestigious clubs such as FC Barcelona and Manchester City – have found their way into various sports such as combat sports, motorsports, tennis and rugby and offer far more than just speculative value . This blog post describes the concept of fan tokens and how they impact fan engagement.
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At the Open banking Summit 2024 with over 150 participants and top-class speakers, the OpenBankingProject.ch once again demonstrated its importance as a vital business network […]
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Note: This blog post contains excerpts from the article “ Data Value Creation Matrix — Options for Organizations to Create Value from Data”. Available at: […]
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The transfer of the AI paradigm “Foundation Models” in the language domain leads to Large Language Models (LLMs), which can be used to communicate in natural language and can be used in a variety of ways for different tasks due to their “broad training”. However, this requires adaptations of the models for the specific application domains. In this second part of his blog series, Wilhelm Niehoff presents the three method areas of In Context Learning (ICL), prompt engineering and fine-tuning that are used for this purpose. By addressing and using the LLMs, however, design-related weaknesses such as hallucinations, lack of topicality and expertise in detailed topics occur. In addition to the three method areas, there are “up-to-date” approaches such as DSPy and TextGrad, which aim to relieve the user of the task of constructing prompts. Accordingly, the weaknesses are eliminated by adding further components that are coordinated by LLMs.
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In recent months, the BEI has analyzed the future business models of asset management companies in Germany and Switzerland and has published a study. In the process, interviews were conducted with asset managers and, as a result, recommendations for action and business models of the future were defined. The aim of this study was to understand and explain the current state of the art and potential developments.
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A Bitcoin-based financial system will necessarily be built in layers. This is because today’s financial system is also multi-layered and recognizes an inherent hierarchy of money-like assets. To properly assess the potential of Bitcoin as a productive asset, it is essential to understand the trade-offs that come with it. In the first part of this two-part blog post, Bitcoin was introduced as a novel monetary asset and the necessity for productive yield generation was discussed so that Bitcoin can take the next step in its evolutionary phase. In the second part, three perspectives on Bitcoin yield products will be evaluated concerning their trustworthiness and the associated risks and trade-offs. Based on these insights, the gold standard of a Bitcoin yield product will be defined and what can be concluded from this for banks and their customers will be explained.
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OpenBankingProject.ch is currently organising a series of workshops on the topic of “digital customer proximity”. Around 40 participants from 30 companies from the financial sector and beyond are examining various target images and use cases on how banks can use concepts such as open banking or embedded finance to position themselves closer to their customers. The aim is to support end customers with digital service access outside of banking and to assist them with banking data, products or services. In this blog post, Stefan Knaus presents the workshop series, the results of the first events to date and the content planned for the future.
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From 2019 to 2024, the global volume of digital data generated or replicated annually almost quadrupled – a trend expected to persist (Tenzer, 2024). Technology companies are demonstrating how data is being used to generate revenue that often dwarfs physical assets. Neglecting data can put companies at a significant disad-vantage in the future, leaving them behind data-driven competitors. However, many companies do not utilize the majority of their data and face issues such as data breaches and data silos (DalleMule & Davenport, 2017). The key is to develop and implement data strategies. This blog post presents a categorization for data strategies and their relevance for digital companies and banks in particular.
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Since the launch of Bitcoin spot ETFs in the US in January 2024, Bitcoin has become accessible as an asset to a broad institutional investor base. This marked a significant milestone on its journey as a monetary asset. The next major step in Bitcoin’s development as an investable asset is to unlock yield generation opportunities (similar to dividends on stocks or coupons on bonds). The first part of this two-part blog post introduces Bitcoin as a new type of monetary asset and the need for productive use of Bitcoin and analyses how initial approaches in this area led to the 2022 crypto credit crisis.
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If you look at today’s bank customers, they are always digitally active in their respective living environments. McMakler provides an example of positioning in customers’ living environments. If people search for design ideas for self-built furniture on Pinterest, for example, McMakler displays real estate offers that match their known living preferences. This happens in the context of a cooperation between McMakler and over 400 banks. Under certain conditions, banks can therefore offer their services in the respective living environments of their customers. However, this option is only one alternative as to how banks or individual banking divisions can position themselves strategically. In Stefan Knaus’ blog post from October 24, 2023, we presented four different strategic role profiles in the context of open banking. Now we would like to take a look at current market developments and which use cases have driven banks forward. We will also classify the terms “embedded finance” and “contextual banking”, which are frequently used in this context.
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Large language models (LLMs) have made a quantum leap in the field of natural language processing (NLP) over the last five years, both in terms of understanding (natural language understanding, NLU) and generation (natural language generation, NLG) in the development of communication with computers. With ChatGPT, the general public has also become aware of this. The possible uses in companies are beginning to become more and more relevant. A small series of articles will describe the emergence, integration possibilities in processes and effects of LLMs. In this article, the history of the development of LLMs up to their current status will be outlined, with the aim of presenting strengths, weaknesses and manifestations in the next article on this basis.
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For a long time, everyone was talking about data. “The world’s most valuable resource is no longer oil, but data” (The Economist, 2017) was the ubiquitous mantra. However, advances in the field of artificial intelligence (AI) are currently dominating the media, driven in particular by generative AI such as ChatGPT, DALL-E and the like, which can create new content such as text, images or speech. These generated data instances are in turn created with the help of technology on the basis of enormous data sets (Touati, 2024). Accordingly, it is becoming increasingly relevant for companies today and in the future to deal with the topic of “data” as the basis for value-adding activities. The Competence Center (CC) Ecosystems of the Business Engineering Institute St.Gallen develops solutions for relevant practical problems and addresses, among other things, the use of data as a key role for business success in dynamic environments. This blog post provides an introduction to the research in the field of data value creation for companies at the CC ecosystems.
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As part of his research at the Competence Center Ecosystems, Dennis Vetterling is developing artefacts for the conceptualization of value capture for organizations in business ecosystems. The objective is to provide managers with the basis for in-formed decisions in the context of value capture in business ecosystems. In this blog post, he introduces the service blueprint as a modeling framework for handling the topic of business ecosystems in his research and provides further thought fragments for their analysis.
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More and more companies are entering into partnerships to achieve benefits such as cost reduction, standardization, flexibility and increased quality. Such relationships are essential in order to remain competitive in a complex world. Nevertheless, numerous examples show that failures with far-reaching consequences can also occur. This blog post shows the factors that make partnerships successful and the norms that need to be met.
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The digital revolution has reached the business world, and procurement management is no exception. The latest study by the Business Engineering Institute St. Gallen, “Digitalization in Procurement Management”, sheds light on how profoundly digitalization is changing this area. This blog post summarizes the key findings of the study to shed light on the opportunities and challenges that digital transformation brings for companies.
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At the beginning of January 2024, the Security and Exchange Commission (SEC) in New York approved the first Bitcoin spot ETFs for trading and distribution in the USA. The approval of ETFs in the US further contributes to the availability of digital assets on the broader investor market. Financial institutions can therefore increasingly assume that the demand for digital assets will change. How have banks in Switzerland positioned themselves in the context of digital assets and what are the advantages and disadvantages of each positioning? Based on observations and interactions in the Swiss market, these are categorized in this blog post.
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The first part of this blog series described different ways in which AI can affect individual professions. To analyze the impact of AI on the Swiss economic sector, a comprehensive qualitative and quantitative study on the exposure of individual professions to AI was conducted using a task-based view. The second part of this article series summarizes the results of this study and presents implications for policy and management.
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As a result of recent developments in the field of AI, the impact of automation on the labor market has begun to be reassessed. Non-routine cognitive or manual jobs, long considered unaffected by previous technologies, are increasingly under threat from self-learning algorithms, leading many economists to argue that this time the impact on the labor market is fundamentally different from other technologies. This blog post describes different ways in which AI can influence the tasks of a profession.
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As part of his research in the field of business ecosystems, Dennis Vetterling repeat-edly comes into contact with organizations that use the concept of ecosystems for their own purposes. In his work, two perspectives on ecosystems have emerged: a “company-centric” and a “customer-centric” perspective. In this article, Dennis Vetter-ling gives an insight into these two perspectives and an indication of how organiza-tions can use a combination of both in the context of a strategic analysis.
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Digital transformation presents organizations with the challenge of developing an adaptive culture and harmonizing traditional business practices with digital offerings, whereby a comprehensive willingness to change and learn as well as a holistic approach to corporate management are crucial for an efficient transformation.
The following blog post presents a possible approach to analyzing a holistic transformation. The Capability Compass.
