Purple Rein – Revolutionizing Revenue Models To Thrive Towards Blue Oceans

We are happy to introduce Mike Schavemaker, Innovation Transformation Lead and senior innovation consultant at Royal Philips, and member of the FINDER Advisory Board, on the FINDER blog! Mike guides the fellows with his academic and industry experience. Together with Barbara Voelkl, he shares his opinions, exciting developments and future revolutions in the world of business models in a blog series, so stay tuned.

Disclaimer:
The content of the FINDER blog is not an expression of Royal Philips, nor created on behalf of Royal Philips. The content is created and contributed by private persons.

Last year, on March 28th, Amazon announced to move into health care space. The company, founded in Seattle on the concept of delivering books at the most convenient way possible, now a tech-giant that delivers anything from overstock toys to data lakes through AWS makes it way to an arguably complete new venture space: health care. Why does Amazon think moving into health care space is the next place to be? Amazon is renowned to move into red ocean industries where traditional suppliers and supply chain rein such as publishing (with acquiring a.o. the Washington Post), catalog sales and ubiquitous data center applications and turn them into blue oceans. And leading the pack.

Amazon does this profoundly by understanding a fundamental question in business: who owns the customer. It enters spaces where providers of goods and services conveniently sell in a status-quo market. Where these same incumbent providers do not question any more how to bring additional value through combinations of innovations to capture the attention of the customer and retaining them; at least not in a paranoid sense. Rather they tend to relish themselves the comfort of their existing business models and only incrementally improve the propositions that they bring to market.

Navigate Uncharted Waters – Streamline Your Business Model

We argue that the simplest way to uncover industry leaders – or industry revolutionaries – are to find those companies who push their revenue models whilst fully aligning their value chain, from innovation, operations to sales, in their obsessed sense to stay close to their customers, or even fully align their customers’ interest with their own. The revolution therefore starts by focusing on the bottom right of the business model canvas and understand how to move your ship and your crew in line with this next purpose. For traditional product oriented companies, this means to move from a capital expenditure model to an OPEX-delivery model in the first place.

Essentially this means that as a product company your start to develop capabilities to address the needs of your customer according to their life cycle – and let them pay accordingly across this life cycle. Typically as a service, not as a mere product sell. In ‘product-sell country’, market share is your ultima. This accounts for hardware products, for ‘productized’ software where you buy a license per release. Appreciation by the customer presents itself by a transaction; thereafter product companies typically direct the attention to the next interested party.

In ‘solutions country’, wallet-share is your ultima. Wallet-share resembles how relevant you are as a company in the eyes of the customer. If your customer only brings 3% of their income to you, then you are not likely to be invited to the proverbial birthday party. If you manage to your customer to bring 30% of their income to you, then you are certainly invited to your customer’s birthday party: in fact, the party wouldn’t be complete without your presence. In a business sense, relevancy is connected linearly with the dollar-amount running from your customer to you. It is connected to your ability to address your customer’s preparation, planning, design and implementation of a solution, and being able to sustain the solution operationally for your customer and to enrich the solution optimally to your customer’s needs. The other currency acting as a proxy for relevancy is time: how well you are able to address their imminent need and invest time to persistently and longitudinally in making their lives easier, achieve their goals more effectively and raise the bar from satisfaction to delight. Taking your customer by the hand across these steps in the life cycle means that you can now shift from product based CAPEX-sell, to the game-play of providing a solution.

Get Your Customer On Board – Leverage The Relationship

The first stepping stone of providing a solution is to extend a product or license sell with a performance based revenue model. Particularly business-to-business oriented firms have extended their portfolio of offering to this model in the nineties. Nowadays any self-respecting product company in B2B-space has a service organization to support their ‘productized’ maintenance services, even if they deliver components to a solution. In this context, the firm commits itself to ensure business continuity and resilience for their customer base and leverages their contracts to substantiate the commitment.

The contract itself becomes the embodiment of how thick, or how thin the umbilical cordis between the firm and the customer is. And how simple it is to do business; as simple it is to deepen out the relationship. In performance based revenue models, the needle still hinges towards ‘transaction’ rather than ‘relation’.

Firms who push the needle further away from transaction, will typically start to develop usage-based revenue models. Moving towards this model will yet require, or actually demand the firm to understand how their product is consumed in the hands of the customers. Ensuring to provide richer functionality and solutions to answer for the customer’s ever evolving needs. Data becomes the inevitable carrier to understand how/when/who/what/where/how the customer’s needs continuously evolve. Addressing a richer set of offerings requires on the one hand a clear contract, on the other hand data mapping translated in integrated lifetime-serving offerings, being enabled by a digital platform that accommodates an ecosystem of solution and channel partners. The prior unlocks a leading position, the latter unlocks to sustain that leadership position. Not the other way around. Leadership, defined in its nature not by means of market share in a total addressable market; the traditional line of thinking. Contrary, leadership, defined by remaining relevant in terms of the wallet-share you manage to address at your customer, complemented by your natural role to orchestrate the connections and probabilities in your ecosystems.

Just look at players as Salesforce.com and Microsoft. By first building a comprehensive portfolio of products that captures (and captivates) the value of the customer, they then stretch their portfolio to additional adjacent applications – which on their term are offered in a partnership program. The composite of this approach allows these industry leaders to create a fine network of application partners, whilst retaining the central orchestrating role around addressing the life cycle their customers. Cisco referred to this as Customer Advocacy, Microsoft perfected the approach by introducing the practice of Customer Success Management, a concept that takes relationship to a next level.

Orchestrate Your Customer’s Reality – Build Up Joint Relations

In history, the strongest relationships are based on trust and a sense of co-investment. An investment in time, an investment in money – or both. This brings us to the ultimate revenue model, being the outcome-based class. Providing services that allow a win, or a loss to your customer – and yourself – if you fail to address the need correctly, if you do not reach the opted result. This type of risk sharing requires your company’s capabilities to fully plug-in in your customer’s reality. This is not for the faint-hearted, especially for those companies that have full focus on establishing shareholder value. Company risk is often associated with volatility. Volatility requires a premium. Another reason why this revenue model is not often seen in any industry, is simply that economic or even political context is not ready yet. For instance, in the case of healthcare space, solution providers who try to offer these solutions to hospitals often face that the economic reimbursement model does not entice the hospital to opt-in: the investment costs would arguable be lower, however this defeats the purpose of the hospital trying to sustain their allocated annual budget to run their facilities. However, in the United States, the health care reimbursement is much more liberal.

What if you could, simply spoken, put your organization’s capabilities to use that you have garnered whilst developing yourself towards an outcome based service provider. Can you turn red oceans to blue, or even to purple on a global basis? This is arguable exactly what happens with Amazon Health. Amazon takes its organizational capabilities to use to provide improved health care services to its employees. What stops them to make the full hospital equipment floor completely digital, reading out vital signs first on assets to weave in the hospitals as outcome based partners, then elevate their partnership with these same hospitals to create meaningful outcome based treatment based on clinical vital signs. Who owns the customer? Making hospital operations fully digital and fully life cycle immersed is just one step to turn the red ocean a little bit more purple. Just apply this simple thought experiment: offering incumbent field service staff an extra raise and tools to be more effective in handling operations would create a massive shift in the existing U.S. healthcare service landscape. Healthcare provided as a financial service by a new entry tech leader: to any actor in the value chain.

The same procedure as all the time? The potential of digital financial business models to change our decisions for better

Whereas FinTechs and digital financial applications are labeled “disruptive forces” and “game changers” shaking up the existing world of finance and beyond within industry and even politics, academics tend to hold the view that by a bare change of the platform or transaction setting of our financial decisions, existing theoretical frameworks are not challenged too intensively.

However, not only does digitalization allow for more collaboration – between humans, distributed humans as well as between humans and technological entities – but also for different ways of collaboration. Imagine you consider buying Apple stocks in four different situations:

i) Analyzing your finances, you consider you are liquid enough now to invest and Apple seems a solid start for that. You open your online depot and fulfil the transaction.

ii) When opening your interactive depot, you just saw your boss sold his 120 Apple stocks just a minute ago. You still continue your transaction?

iii) When opening your online depot which you share with your baseball mates, you need to get the majority of them on board before the buying trade is possible. Do you consider researching a bit more? Are your mates going to agree to this transaction?

iv) While surfing on your phone, a push-up from your online trader pops up – their chatbot informs you it is a good time to buy Apple stocks now. Do you follow this advice on the go?

Considering these, a mere selection of possible scenarios of a trading situation, it becomes obvious that human financial decisions are shaped through contact, if online or offline, direct or indirect, if in the form of advice, communication or the pure existence of a social group within which an individual makes a decision. Keeping in mind the vast financial and strategic decision-making literature on nudges with the numerous examples of how framing a decision context changes our decisions, FinTech applications with their diverse setups, designs and defaults are definitely worth having a second glance from an academic perspective. FinTech applications give a new angle to financial decision-making transforming the way of collaboration. Does online and task-related communication such as in a collaborative investment app free individuals from halo effects? Does advice from AI remove or strengthen critical thinking? It remains the joint task of practitioners and academics to understand and design these applications as frames for inclusive, unbiased decisions so that research can serve its purpose – society.

by Barbara Voelkl, FINDER ESR

Emotion recognition technology in the financial sector – Curse or blessing?

Emotion detection and recognition is a hot topic in the tech industry. It could enable companies to react to emotional states of their customers by e.g. hindering or fostering impulse purchases, changing the tone of voice in customer services or identifying product functions that are extremely frustrating to use. For instance, virtual assistants like Siri could assess when people are screaming furiously and react more kindly – if that is not fanning the flames. In general, the emotion detection and recognition market is a huge and rapidly growing one: in 2012 it was estimated to be worth $12 billion and some people expect it to rise to $90 billion by 2024

How does emotion recognition technology work?

Based on the analysis of voice and facial expressions in videos, audio or images machine-learning algorithms try to predict the current emotional state of humans. These days, this is often done through supervised deep learning algorithms (mostly convolutional neural networks) which are previously trained on large sets of manually labeled data. The labeling is done by human raters who assess which emotion they perceive as most prevalent in a given image or piece of audio. The analysis is often limited to the so-called “basic emotions” ( happiness, sadness, fear, anger, surprise, and disgust) which are believed to be universal and identifiable by all humans independent of their culture.

How is emotion recognition technology used in the financial sector? 

Personal finances are an emotional topic for many persons. Studies have shown that the emotional state has a significant influence on the ability to make wise financial decisions.  This is an interesting point for banks and financial institutions that want to build services around their customers’ needs and feelings. One of the first movers in this domain was the United Bank of Scotland who partnered with an emotion recognition software company in 2016 to assess customers’ preferences concerning wealth management in a pilot study. However, the software was never adopted, despite the enthusiastic statement of UBS’ chief investment officer who dreamt about identifying his customers’ “subliminal desires”. Rosbank, a Russian bank whose majority shareholder is Societe Generale, decided to use emotion recognition software in call centers to calculate a “customer satisfaction index” in real-time. This is supposed to help operators identify the most critical issues but can also be used as a KPI for call center employees. Moreover, WeSee AI adopted emotion detection and recognition software to detect insurance fraud. The company promises to be able to assess the validity of claims “more significantly and accurately than ever before” through automatically evaluating people’s emotions. Overall, it seems that companies in the financial sector like the idea of using emotion recognition technology. But how reliable is the technology currently? In the following, we will assess the technology’s maturity level from research perspective.

How far developed is emotion recognition technology?

The scientific background for emotion recognition technology is weak. The latest report by the AI NOW Institute of the New York University argues that the technology should, therefore, be banned from the application in decisions that affect people’s life. We are going to discuss two major reasons the authors state in their report.

Displaying and feeling are not the same

Current psychological research concludes that displayed emotions do not necessarily reveal the actual inner emotional state of a person. Hence, it is misleading to rely on software that is only analyzing a fraction of all signals that have to be considered to assess a person’s mood (including asking how she or he feels). A recent paper by the Association for Psychological Science revealed that e.g. facial expressions alone are a very weak indicator to determine someone’s real feelings. If financial products and services are built upon these assumptions they at best add noise to their analysis and at worst disadvantage people or at least offer negligent consulting. Furthermore, facial expressions and tone of voice are for the most part under voluntary control. That could lead to absurd behavior when people interact with emotion-sensitive software: people could scream at call-center software just to be forwarded to a real person. This seems far-fetched but technology has always had behavior-changing effects on society: an ongoing study with currently 66.000 participants found that people are on average checking their phones 35 times to see (among other things) whether somebody texted them. Just imagine people running to their mailbox 35 times a day, seven days a week.   

Illegally scraped and biased data

Finally, the data sets that are needed to train the emotion recognition algorithms are often created by scraping websites without the informed consent of the people pictured in the harvested images or videos. This practice seems to be applied by both companies and research institutions. Not only does this depict a violation of privacy rights but it can also imbalance the composition of training data sets leading to wrong conclusions: a study found systematic racial biases in two well-known and widely used emotion-recognition software (Face++ and Microsoft’s Face API). Software that detects negative emotions based on racial biases could propose very conservative financial products that significantly lower the interest rate of their clients and therefore, further increases systematic racism.

Final thoughts

Facial recognition is often a necessary antecedent for emotion recognition software. Therefore, it is encouraging to see that the tech-savvy city of San Francisco recently stopped using facial recognition software and that a bipartisan bill to regulate commercial use of facial data is currently discussed in the US congress. To conclude, emotion recognition software is still far from being applicable in most business settings. Especially in finance, as an industry that has a strong direct influence on the well-being of people, companies should be careful not to draw wrong conclusions or overestimate the technology’s potential. Researchers have to stay ahead of the industry to ensure transparency and be able to act as technological and ethical evaluators.  

Sister Project Receives NWO Funding

The Netherlands Organisation for Scientific Research (NWO) has awarded a €15,000 grant to Drs. Rick Aalbers (principal investigator, FINDER project) and Armand Smits (assistant professor Radboud University). The researchers, both employed by the Nijmegen School of Management at Radboud University, will investigate business models in creative industries for complexity and improvement potentialities.

Dr. Rick Aalbers

This project will employ qualitative comparative analysis, an innovative research technique that systematically assesses combinations of cases in order to find complex interactions and relationships. In doing so, the grant enables the researchers to build an inclusive knowledge-generating collaboration, using contemporary techniques, between the research and business sectors through dynamic exploration.

Finally, this project will contribute to CLICKNL‘s Knowledge and Innovation Agenda 2018-2021.

– S. James Ellis

The first FINDER PhD collective meeting has been successfully completed!

The FINDER PhD collective meeting on Wednesday, October 2nd 2019 at Radboud University has been a major success as we welcomed our supervisory teams to Nijmegen.

We, the PhD students, presented our recent research activities and developments to our supervisory promoters: Dr. Rick Aalbers, Dr. Miriam Wilhelm, Dr. Koen van den Oever, Dr. Saeed Khanagha and Dr. Philipp Tuertscher, Dr. Professor Koen Heimeriks who all joined this collective meeting. The supervisory teams have created a very open environment and encouraged us to express our research ideas and  also gave immediate feedback during the meeting. In addition, they have provided sound advice on each of our current research work.

In this meeting, Jonas Röttger first presented his research project regarding the influence of a company’s communication. After which, Barbara Völkl discussed her research on the digital business models from the behavioural aspects. S. James Ellis introduced his current study on the strategic management of different partnerships, followed by Ami Xiaolei Wang who proposed from her work from the network view to study the firms under the digital transformation, and lastly Tze Yeen Liew discussed her research on the impact of the competitive tensions from an academic perspective.

All in all, presenting and discussing our current academic work, showcasing the diversity of topics, approaches and interests at the frontiers of sustainable strategies to achieve to value of financial technology and reflecting its insights from academic research.

The discussions following up on the presentations focused on the importance of the management strategy as a source for the disruption and innovation of financial technology; and the need for a good academic perspective that ensures technology sustainability. The valuable feedback received during the meeting will enable us all to improve our research endeavours in the time to come.

We proudly present: Voleo, FINDER FinTech Partner

The Canada-based FinTech Voleo is a key project partner within the FINDER project. The investment platform enables groups of friends, families, colleagues and anyone who joins to collaboratively invest and manage a stock portfolio together. Unlike solo investing, investments through Voleo are conducted within investment clubs of three to hundred people and trading decisions are made as a team. With each individual contributing cash and proposing buying or selling actions, the team together takes the final trading decision – “Investing is better. Together”, as Voleo states it.

Voleo App (C) Voleo Inc.

A major mission for Voleo is to grant access to trading to people intimidated by the seemingly complex world of investments and thereby increase financial literacy on a fun and easy-to-use app or web platform. By following the investment decisions of top-performing clubs or individuals while having a clear and dynamic overview of the club’s own portfolio and performance, barriers to investing fade. The currently starting annual Voleo Student Competition in cooperation with the NASDAQ emphasizes the vision to encourage investing among ages and demographics.

(C) Voleo Inc.

Currently operating in the United States, Voleo recently surpassed eight thousand registered users partnering with Google’s Digital Strategy program. More information about the Voleo platform and exciting developments can be found on their website or LinkedIn. Stay tuned as the research collaboration progresses!

Fintech: Defining a Constantly Evolving Term

This short series of editorials is a compilation of a few of the FINDERs’ observations on the definition of the term “fintech.” One that has not yet been standardized in any practical way, the definition seems to differ depending on the context and actors at play. That said, the following entries reflect the FINDERs’ initial considerations of the term and shall be revisited nearer to the end of the four-year research project.


What is a FinTech?

A FinTech is an organization using 21st-century technology and software to provide, ease and automate financial and insurance services of any kind as captured in the NAICS Codes 52. The definition is not restricted to start-ups. These serve however as clear examples of FinTechs as – in contrast to incumbent banks – they mostly focus on one concrete aspect of the financial service world. A FinTech always contains a technological component, a mere business model change does not suffice. An interesting point: currently there are no specific SIC/NAICS Codes for FinTechs, which highlights their bridging position between technological and financial organizations.


A Fintech Definition

Here is a definition from a 2016 article that did extensive research on the Fintech term. My self-made definition is:

The term Fintech is often used as short-term for financial technology or financial services and technology. The term defines a company or a solution that uses technology to provide financial services. Depending on the context, a company’s size (rather a start-up or scale-up than an established company), a company’s portfolio (rather entirely focused on technology for financial services) and the innovative and industry-disrupting potential (rather high) are often consulted to define Fintechs in a narrower sense.  


Defining Fintech: Have Patience

It’s a fairly predictable pattern: [concept] arrives in a place of scrutiny, nobody knows what its boundaries are, [person/group/discipline 1] makes a solid attempt, [person/group/discipline 2] makes a convincing counterargument, the cycle continues ad nauseam and/or until everybody seems to just adopt the definition that works best for them in the current context. It happened with the idea of a European continent (which you might think is separate from Asia), it happens chronically with art (caution: that is a playful Buzzfeed link; a more serious line of discourse can be begun here), and as a matter of fact, it’s even happening to you. Yes, you

In a way, it’s a very useful process that tests our societies’ epistemological health. There is very probably a name for this process – a name currently owned by [person/group/discipline 3] (until [person/group/discipline 4] convinces us of a better one). The process, in any case, should not be leapfrogged with the belief that a bunch of useless quibbling will be bypassed. Indeed, good things come from these discussions, though it is quite a nuisance for those who want to have immediate plug-and-play conversations about the topic where everybody knows without question what they mean. That being said, I argue that, despite the instinctive tendency to rush for a universal definition, this is not the most efficient use of brain-power when it comes to new, shiny concepts – concepts such as “fintechs.”

A portmanteau of “financial technologies,” it might at first glance seem like a very simple concept to grasp. “Technologies that let me pay for things,” you might posit. Yes, but rarely does a technology alone handle your payments cradle-to-grave. This process is often broken up into different pieces. Therefore, is the company that produces the RFID reader in a contactless terminal a fintech? Maybe; maybe not. This example is one drop in an ocean, but it makes immediately apparent how murky these waters can get. However, the term is ripe for discussion in many circles and some sort of shape must take form in defining what, exactly, a fintech is. 

Bounded rationality dictates that we draw the line in a place that makes sense for the current discussion. And yet, powerful players in different domains have rushed to establish what seems like universality in their suggestions. In no unclear terms, the dedicated FinTech Weekly says that companies which engage with finance-related software qualify as fintechs – apparently the hardware side is not part of the club; Merriam-Webster obfuscates this delineation but distinctly points the moniker at products and companies – conspicuously excluding services (such as peer-to-peer financial transacting); Bloomberg opens its gates to “financial-services companies using the Internet, mobile phones, and the cloud”, diving deeper into Merriam-Webster’s pigeonhole and summarily ignoring that the analog history of fintechs that predates the digital age by far (what, after all, was a ledger if not a financial technology?); PwC attempts to take the holistic, conceptual approach, to no apparent pragmatic utility. 

While these agents and many, many more very boldly stick their flags in whatever patch of definition-assigning land they can, we’ve been luckily spared from any one of them sayingmy definition is the most valid” – yet. It’s very likely that each organization that stakes a claim in defining this term has its reasons for doing so exactly where it chooses – I would argue that it’s what makes the most sense for the conversation at hand. Many will likely try – hard – to muscle their definition ahead of others, and let them waste their energy but pay it no serious mind. “Fintech” as a term will constantly shift in meaning. Why? Because it has the convenient quality of being steeped in the realm of digital technology, and the beautiful thing about digital technology, and specifically the way it innovates, is that just when you think you’ve found its limits and how to handle it, you haven’t

First Teaching Experience for FINDER Fellows

S. James Ellis and Jonas Röttger, FINDER research fellows, delivered an interactive lecture to Master’s students in Dr. Rick Aalbers’ Corporate Strategy class at Radboud University. The lecture revolved around a case study authored by the FINDER team that examines the various corporate strategies employed by Atos as well as its strategic partnerships with technology hubs. Students were given roles from various actors highlighted in the case study and played them adjacent to their peers, simulating the behaviors of different corporations in an inter-organizational setting and advancing their understanding of what factors contribute to the creation and destruction of partnerships.

S. James Ellis (left) and Jonas Röttger providing input for the debate in class

The session enabled students to immerse themselves in a real-world business situation learning about the diverging interests of parties involved in hubs and their need to manage both competitive and collaborative relations with various stakeholders. Leading the discussion, the FINDER research fellows stimulated the engaged group with input from the academic perspective and insights from the market of digitized financial services. The underlying case study will be further developed alongside the FINDER project trajectory, allowing students to be exposed to current business challenges and the corresponding academic perspectives.

All Fellows Onboard – First FINDER Symposium at Radboud University

A summary by Barbara Voelkl, PhD candidate FINDER program

On September 10th, the FINDER project team held its first symposium at Radboud University in Nijmegen. With all FINDER PhD fellows on board since beginning of the month, the meeting together with the partners from Atos as well as Radboud offered a valuable venue to get to know the whole team and detect possibilities for synergies.

The core project team at Radboud University

Remco Neuteboom, Atos Group Chief Digital Officer for Financial Services, started the symposium with an introductory lecture on Atos and its far-reaching history of M&As in the setting of the Corporate Strategy course at Radboud University. Understanding the challenges and opportunities in collaborations, among those mergers and acquisitions, builds a significant academic component within the FINDER program. Learning more about strategic deliberations from the practitioner’s side thus adds essential value for the FINDERs to develop practically relevant research proposals.

Intensive debates from academic and practical perspectives

Following up, Dr. Rick Aalbers and the PhD fellows, with the project team from Atos, dove deeper into more specific topics such as scaling, inorganic growth, technological governance and potential boundaries of FinTech networks. Ivo Luijendijk, Atos Group Industry Director Data Analytics and Emerging Technologies for Global Financial Services, shared contemporaneous insights from the Scientific Community of Atos and expressed the intent of a close cooperation with the PhD fellows. Following up, the team agreed on an update of the FINDER LinkedIn and website towards an active, informative platform intended for academics and practitioners likewise, so stay tuned!

Training and community building at Atos and TechQuartier Frankfurt

April 8th and 9th, 2019

A summary report by S. James Ellis, PhD candidate FINDER program

FRANKFURT, GER. – The growing FINDER team convened at Atos’ Worldwide base in Frankfurt on Monday, April 8th, 2019. The multinational, interdisciplinary group traded introductions and immediately got to work setting the stage on trends in the fintech environment. Intuitive as such a first step might be, the importance of standardizing entry knowledge cannot be understated with an academic topic as novel and turbulent as fintech currently is. That turbulence might make “fintech” difficult to pinpoint and create useful conclusions about, but the continued production of knowledge about the topic and how it interacts with society is the quickest way to mitigate these difficulties and, not coincidentally, core to the FINDER focus.

Atos’ partnership in the FINDER program provides a birds-eye view on the development and operation of fintech organizations, which is often crucial for understanding how they originate, evolve, combine, and fail. Remco Neuteboom, senior vice president and chief digital officer of Atos’ Global Financial Services, and Olaf Badstübner, global director of Atos’ Financial Services, provided their professional insights into how the banking sector, often guided by tradition-oriented practices and approaches, interacts most and least effectively with the fintech sector, which often subverts banking institutions in its customer engagement entirely despite the transaction of financial assets.

This is arguably the essence of hype surrounding fintech. Abstracting from the barebones concept of “fintech” as just a mashup of “finance” and “technology,” fintech can comprise the people, companies, processes, and structurations that operate those technologies. Many of these aspects of fintech challenge the ways in which we normally conceive of a financial transaction. Consider the days in which you or your parents wrote checks to pay for, for example, groceries. You (or your parents) wrote the check and gave it to the grocer, but it was ultimately both parties’ banks that determined the terms of the transaction and the time in which it was completed.

In the modern day, you can walk into a store, scan your own groceries, and bump your smartphone against an NFC terminal and carry on with your day. Meanwhile, a whole cascade of processes that no longer orbit around the banks begins. While the Age of PSD2 does not seem to proffer any clear nucleus such that banks were, a major player in the game now is the fintech: a third party service provider whose value added is how it can operationalize the information that you choose to give it and that banks must give it. Considering how ambiguous this new paradigm is, it’s easy to imagine the broad diversity of fintechs that have sprung up to answer the call of consumer demand and structural necessity. These fintechs must start somewhere, which brings the FINDER team to TechQuartier.

Atos & TechQuartier Frankfurt 8/9 April 2019: Training and community building

TechQuartier is a business incubator that intakes small startups, provides a low-cost cooperative workspace for them, and provides forward guidance for their continued growth. The FINDER team convened at TechQuartier on the second day of the Frankfurt event in order to gain insights from Thomas Funke, managing director of TechQuartier, as well as several fintech founders who have passed through the TechQuartier halls. Familiar sentiments arose: the slow speed of banking institutions’ innovations are, in part, enabling the rapid development of fintechs. As the industry is discovering, this does not necessarily mean that fintechs stand to overtake these institutions as the primary engines of financial transacting – one speaker was Oliver Mahr, from the Deutsche Börse, who discussed the late-stage development of fintechs and how mergers and acquisitions driven by large legacy banks both provide stability and strength for fintechs and an innovative speed boost for the banks.

This is one of the research tracks that the FINDER team is investigating, and continuous working papers will provide operable knowledge for fintechs, banks, entrepreneurs, policymakers, and more on this topic as well as many others. The FINDER team will convene early September to begin its four year research duration, so stay tuned!