Contactless payment cards are almost everywhere these days. Cryptocurrency coins and tokens are now being issued by many companies, especially via ICOs. Many parties are planning blockchain-based settlement solutions. At the same time plug-and-play type FinTech components can be easily integrated to any system to support new payment services.
As more companies look to adopt digital payment solutions, the trick is to match the right solution with the right service or scenario. Examples like London Underground tickets, paying digital music royalties, or a blockchain system to handle settlement between big companies might look very different from each other. But they actually face the same basic question in finding an optimal solution: Do we build our payment system with open public solutions, or do we implement a closed private solution?
To answer that question, we can highlight some important preliminary questions to inform that decision:
Let’s take some examples.
In a public transportation system, we’re talking about millions of users and hundreds of millions of transactions annually. Consequently, the cost per user/transaction and operating costs become more important than the set-up costs. Typically, for example, debit and credit cards have transaction fees that are based on the value of a transaction with some minimum fee to a card processing company (e.g. Visa or MasterCard). But processing in a proprietary system also has its costs.
In this kind of system, the user experience is also very important. If a customer can use any card or mobile payment system, it is much easier for them to use the service than if they first have to get a proprietary card, pay a deposit for it, and then load money on it. A better user experience also increases usage and revenue.
A good example is Transport for London (TfL), which started with the Oyster contactless card payments almost 15 years ago, but nowadays it allows people to use their own existing contactless debit and credit cards, as well as mobile payments from Android Pay and Apple Pay. Why would expensive proprietary solutions make sense in this scenario?
For cryptocurrency coin solutions, one area where this is taking hold is music royalties. Traditional solutions to track and handle payments of music royalties have been complex, inaccurate and slow. Digital music is easier to track thanks to DRM but the payment mechanism is still complex. A blockchain-based token payment system would be able to track whenever a song is downloaded from iTunes, streamed on Spotify or licensed for an ad, and ensure that the proper fee is paid by the user and received by the rights holder.
This kind of system must be very easy to use and understand, it must support millions or billions of users, and the end-to-end flow of transactions needs to be efficient, which means significant transaction and operating costs.
Compare that to a system for logistics or finance companies to settle and pay each other based on how they use each other’s services globally. This kind of system might have only dozens of users, but individual payment amounts (and commission fees) can be significant. Here, a proprietary solution could be suitable, since ease of use for consumers is not a key factor.
One important point regarding cryptocurrency token systems is exchange rate risks. For example, if a token is linked to Ether, the value of Ether creates a risk for token owners, and there might also be restrictions to converting them back to ordinary (fiat) money. In principle, we could also say that a proprietary transportation card has similar risks – e.g. the transportation system stops accepting it or there is very high inflation. But typically, these risks are small, especially when we talk about small sums of money on the cards.
As we can see, selecting an optimal payment system requires a lot of complex evaluation that also must include also forecasts of future use and costs.
At the risk of oversimplifying, we could say that for systems supporting large groups of ordinary users, open systems are probably more cost-effective and offer a better user experience, but they should be based on systems that don’t come with significant exchange or future-proofing risks. A settlements solution supporting a smaller number of parties could be a closed system with access restrictions and no transaction fees for external parties.
FinTech also enables the ability to include plug-and-play type finance and payment components for many services. Things like external payments, tokenized or lending solution can be integrated to any service. It is possible to use cloud-based back offices, services over open APIs, and open source components. We have come to an era where it is possible to innovate finance services inside any service and easily implement it via standard components.
In any case, it’s important to evaluate which models make sense before deciding what payment system to adopt.
The article first appeared on Disruptive.Asia.
The only methodology that yields proven and measurable results is trial and error. No matter the MBAs in the room and the PowerPoint charts and simulations, nothing will compare to trial and error. If we accept this fact, and we should, then the thing to aim for is to maximize the amount of experiments in order to observe and measure what in fact works and yields the result we desire. Move fast and break things, so to speak.
The only methodology that yields proven and measurable results is trial and error. No matter the MBAs in the room and the PowerPoint charts and simulations, nothing will compare to trial and error. If we accept this fact, and we should, then the thing to aim for is to maximize the amount of experiments in order to observe and measure what in fact works and yields the result we desire. Move fast and break things, so to speak.
How exactly do you do that, when you’re sitting inside a risk averse, global bank that manages trillions of dollars of transactions and funds? And can you ‘break things’ without ending up in an orange jumpsuit? In this post I’ll explore not only why that is possible in a complexly regulated, highly conservative and risk-averse organization, but rather why it’s critical for the survival and competitiveness of such an organization.
Tom Chi has this now famous talk he does from the early days of Google Glass. After hours of debate about the color of the heads up display (HUD), where the room full of smart, innovative people could not find common ground, a simple prototype was built in an hour yielding a simple result. Smart people argue about the color and with all the smarts, the prototype put an end to the discussion and formed an argument everyone agreed with. The thing with smart people is, they can make a self-serving, factually incorrect argument sound smart by their own vary nature.
Separating what you know and what you think you know.
Unless you are building on real data, you do not know anything. Real data has to be representative and it has to be valid, yet the very concept of rapid prototyping does not require it to be perfect from the start. It simply requires it to be experienced by someone who does not know, what the experiment is or have an interest in behaving in a predisposed way. Realizing that you are wrong is powerful. The way to be less wrong is to launch something and improve. You can only improve when you know how and where you are wrong. That’s important and arguably, that’s the quickest and shortest way to get to being incrementally less wrong over time.
A Word On Culture
Financial services and especially the largest institutions are risk averse and let’s face it, you want them to be risk averse. Yet all the reasons (excuses) why you couldn’t adopt a prototyping culture in lets say a bank, will fall away when examined closely.
Everything comes down to design. You don’t want to launch things publicly due to brand risk? OK – launch it internally to another division. Then launch it internally to a second, to a third. Then launch it to an early adopter group, e.g. a partner company. Build up your confidence in your process, design it so it can succeed. What about regulation and risk management? Build that into your process and even more so, into your products. Regulators and risk managers love nothing more than you giving them more granular data, more security and more sophistication. Today’s technology can do that efficiently. Give them a (self-serving) reason to support you.
Culture is important and it’s important to take seriously. Yet it’s crucial to ask questions. Don’t fall into the trap of assuming the way its been done before is correct, just because no one asked questions and even if they have asked questions, don’t assume today is no different than last year. Ask questions and question models, that’s the only way they really improve.
With Open Banking and PSD2 we are seeing a large scale cultural shift, toward technology-centricity. It is not always comfortable and large institutions are building their talent pools with cross-disciplinary technology competence. This shift is just beginning and the most successful early adopters we have seen so far in financial services, are those that have embraced it head on and made a clear commitment. Pulling Goldman Sachs into retail after 147 years of no retail operations and launching the no fee personal lender platform Marcus shows commitment and an organizational bravery tackling new challenges. Surely it was a calculated and tested modeling that led to the launch, after several pilots and prototypes internally, but in the market it looked quite smooth.
That’s the thing. Move fast and break things, but manage what you break and who’s looking. Financial services are moving toward an API ecosystem at a fast pace with catalysts like PSD2. Embracing the change requires a different thought process and models, but the rewards may be enormous.
The article first appeared on the Difitek Blog.
Future Technologies Poised to Transform Our Lives for the Better are the focus of this podcast. Almost here means these technologies are Now Here, or Just Around the Corner: from Bitcoin to Artificial Intelligence, 3D Printing, Blockchain, Virtual Reality and More.
In October 2016, Richard Jacobs started a podcast called “Future Tech Podcast” – the goal was and is to learn about ‘round-the-corner’ new technologies, such as Artificial Intelligence, 3D printing, stem cells, regenerative medicine, Bitcoin and blockchain (of course), and more. From the Complex world of Quantum computing to the booming crypto market, the podcast has a lot in store. So we invite all of you to listen to the Podcast & share it with your friends and family.
Grow VC Group Chairman and Co-founder Jouko Ahvenainen was the guest of the podcast in this week. The discussion focused especially on the FinTech and blockchain and their impact on the finance industry. They also discuss the history of the Grow VC Group from the first crowdfunding services to the current group of companies for FinTech. An important part of the discussion is practical examples of services and lessons learned from experiences.
In the end of the podcast there are also some forecasts about FinTech, and maybe the important services are not that are the most visible now. You can listen to the podcast below, or here.
Grow VC Group and its companies participated in Mobile World Congress in Barcelona in the last week. Here is a report of the highlights of the event, written by Jouko Ahvenainen. These reports were originally published on Telecom Asia.
Distributed models for AI and finance
Clouds have come to dominate computing and data services. At the same time there are more and more devices connected to the internet, devices have more data, make more real time actions based on data and users want to have more control. This all means that one totally centralized cloud model is not enough. We have to adopt more distributed - technically speaking Edge computing - models.
I have written earlier about personal AI and distributed data models. Both are demonstrations that there is a need to distribute data and its processing. Those services could still be cloud based, but if we really make real time, data heavy applications, then it is important to optimize local and centralized computing and data transfer. This is the case with many IoT based services.
Wikipedia defines Edge computing as “a method of optimizing cloud computing systems by performing data processing at the edge of the network, near the source of the data. This reduces the communications bandwidth needed between sensors and the central datacenter by performing analytics and knowledge generation at or near the source of the data.”
Professor Mahadev Satyanarayanan from Carnegie Mellon University made a strong case at an AI panel at MWC2018 for Edge computing and how its time is now. He basically gave examples that more personal AI (e.g. glasses to give personal assistant or connected cars) cannot transfer all data to a data center and wait for instructions from there. A part of the processing must be local. The training and learning of AI will probably be a hybrid model where there is centralized learning and ‘instructions’ that can be adapted locally in devices to be e.g. more personal or more relevant to the local context.
Professor Satyanarayanan gave four main reasons for why Edge computing is crucial for the future AI and ML applications:
We can see this is also linked to security. How, for example, local devices can protect themselves against attacks and be able to operate in all situations. These devices will need more firewall and other protected solutions in the future and maybe also use AI to protect themselves, in kinds of self-defense solutions.
This development to more distributed models will have business impacts too. It gives opportunities to new companies to develop optimal services for these new needs, when the cloud services start to be quite consolidated to the biggest players. Professor Satyanarayanan actually saw that most likely the leading cloud companies, like Google and Amazon, might have problems adapting to this model. He saw that Microsoft might have a better capability to do it, thanks to its history with PCs.
At the same time, this is a way that startups can really get to the AI market too, when for them it is really hard to compete with Google, Amazon and Facebook and their huge resources in AI.
Finance and FinTech services is one area where these new distributed models are already happening. We can say distributed ledger and blockchain are linked to the same development. It is to distribute the data, processing of transactions and offer more user control. As we can see in FinTech services, it is important to find an optimal model to manage global centralized ecosystems with local services and data. Open APIs are also a part of this model, when they enable to develop local services and applications that work with centralized services and back offices.
We will see different layers of computing and data centers:
At MWC2018 we can see AI models, needs and applications from many angles including computer science, venture capital investments and user applications (e.g. connected cars). The message from the AI expert is that this development is happening now, i.e. companies should invest in these things now, not first wait for proven business cases. The experts also wanted to emphasize that it is now the time to develop real user applications, not only conduct research, i.e. there are already enough theoretical models and research results to implement a lot of useful applications.
Distributed models have really started to emerge at the same time, when the big cloud services are still winning business from proprietary legacy IT solutions. This is an area where we will see a lot of new models and services in a few years, probably also a lot of startups and investments. The big players are also ready to make acquisitions. The development of connected digital services seem to be an endless rollercoaster between more centralized and more localized intelligence.
Data privacy, user control and AI ethics
Data has been an important topic at Mobile World Congress for many years. This is the case at MWC2018 too, but with some new angles and perspectives. Data privacy, user control of his or her own data, and ethics have become important topics in discussions. This is also linked to the development of AI, when machines are becoming more autonomous to use data and make decisions. This doesn’t happen only at MWC, but we can say the data business and discussion are stepping to a new era.
There are still many companies that are mainly talk, making promises about how they can collect more data than others and monetize it better. It can be mobile user data, advertising and content data or financial data, but these companies just want to offer better weapons to get to know customers and sell more to them. This was maybe a cool story 5 years ago. Today, not so much.
GDPR is on the way in the EU and other countries are working with similar initiatives. Users are more interested in how their data is used. Many international organizations, including European Council (e.g. Convention 108), UN (e.g. Resolution 68/167; The right to privacy in the digital age) and IEEE (e.g. P7002, work group for data privacy processes) are working with guidelines and standards to give more control to people regarding their own data.
It is no longer only about data and privacy. AI is changing the game, and it is also about AI ethics. With AI you have input and output data from the system, but also the algorithms that then process the data. Both data and algorithms can have a bias or ‘unethical’ components, and both of them are relevant when we talk about the rights of people and liabilities of companies.
Paula Boddington has conducted AI ethics research at the University of Oxford. She held a speech at MWC2018 and raised some interesting cases. She told about Microsoft’s chatbot (Tay) which became racist on Twitter and Microsoft had to close it down. Ms Boddington raised a question that it is not easy to answer - if we can blame AI on this, or was the underlying reason Twitter itself, i.e. tweets from people or peoples' behavior on Twitter. We can say social media seems to make many people behave like angry racists. Maybe AI just illustrated the real nature of social media behavior.
She also talked about the famous Milgram Experiment, where people at Yale University were asked to give electric shocks to people in another people, who’s audio they could hear, to help them to learn about ethical behavior. The voltages were increased all the time, and when instructed by their researcher, many people continued to give shocks at levels that were a threat to the life of the subject. Ms Boddington pointed out, that this illustrates, how people can get to unethical behavior step by step, without really realizing it. This might be the case with the use of data and AI too, and that’s why it is really important to discuss these topics all the time.
Of course, the work of academics and international organizations is not alone enough in this area. The reality is that lawmakers must create guidelines and companies must realize a business case to protect privacy and ethical use of data and machines. We can see now evidence that many companies are starting to see this. For example, in finance services MasterCard introduced a token model (MDES) to better protect the card user’s data. Blockchain and distributed models offer solutions to consumers to manage their own finance data (e.g. Prifina). Qualcomm, AT&T, IBM, Nokia, Palo Alto Networks, Symantec and Trustonic have formed a IoT cybersecurity alliance. And there are many other examples. Many companies also develop better digital identities, but they are still more complex to evaluate from a privacy point of view, when they can help and challenge privacy.
AI and data are gaining key roles in all industries. We must remember that intelligence is not only about the use data and making decisions; ethics is an important part of intelligence too. Now it is positive to see that more and more parties realize this and MWC2018 also illustrates this new era of data and AI business. Consumers need solutions to manage their own data and get AI to work for them. It is not only about individual people, but how data and AI can serve a common good and justice.
MWC still looking for a big picture of FinTech
FinTech is not the focus of MWC, but nowadays FinTech is somehow linked to many services, and definitely finance is entering mobile. In that way it is somehow surprising that FinTech hasn’t a more prominent role at MWC. There are components that help with FinTech on show, but a larger understanding and ecosystem point of view are missing.
Blockchain is a newcomer also at MWC. There seems to be a wild variety of scenarios where blockhain is planned to be utilized. Some companies have started to offer blockchain-as-a-service, some focus on managing ID or wallets with blockchain, and then there are models outside core finance services for smart contracts and data sharing. But as it is also with banks, not too many corporation executives know, what they mean, when they say they want to be active in blockchain.
Identification, KYC, mobile payments and wallets and money transfers are maybe the most typical FinTech services at MWC2018. All these components are relevant and they are needed in digital finance services. The surprising fact is that not so many of these providers have really thought, how their components are linked to other services and support a larger ecosystem to work smoothly. For example, mobile identification and payment services offer mainly their solutions for telcos and banks, but it sounds like they haven’t e.g. thought, how components of identification, KYC, AML, payment processing and wallets are linked to each other, data should be exchanged between them and you need all of them to offer secure regulated services.
Cashless has been the topic of several discussions. The conversation is not yet really about crypto currencies, but how to pay without cash. The market is quite divided, when the emerging markets are coming to cashless mobile payments, because they have no existing banking infrastructure, and the most developed countries (e.g. in Sweden and Canada over 70% of transactions are cashless) go to cashless thanks to their advanced infrastructure.
There were some interesting examples of how the cashless reality is built especially based on good usability and attractive services. Fenix International is a new kind of electricity company. It offers solutions such as the ability to manually or solar charge mobile phones and improve lighting in Africa. Mobile money and payments become important for them for offering use-based payment model for their products and services. They have expanded their offering to provide finance for paying school fees. In that way they develop financial inclusion and when they also collect data from customers, it helps them to evaluate credit ratings and offer more loans.
Transport for London, TfL, was another case talking about cashless payments at MWC2018. Their case is very different from Fenix, in a very advanced finance market. They started with their Oyster touch card payments almost 15 years ago, and nowadays they support payments with many debit and credit cards (that have a touch payment chip) and also with mobile payments, like Apple Pay. Many cities have proprietary payment solutions and cards for public transportation, but London’s case is important, how people can use their existing cards and payments solutions also with public transportation. Why would expensive proprietary solutions anymore make sense?
Regulation and compliance are always important parts of finance services, including payments. For example, you need to have KYC, if you really want to build a sustainable service, although one speaker made a good point “if you are really worried about KYC and AML, maybe then it would be better to focus first on Swiss banks than micro-payments in Africa.” It is important the regulators don’t make new important services too complex to implement.
One important aspect in a cashless panel was user experience, especially how to decrease fear and increase confidence in the use of new payment services. Many people are still worried, if new payment solutions are accepted, if they are secure and how they should really use them. This is linked to UX design of the services, but it is also important for service providers to provide more information to users.
Some experts made predictions that there could be a war between banks and telcos in the finance market. Telcos have a role to play in some finance services especially in developing countries. Typically, this is limited to payments and money transfers, and often these services are also implemented by a third party service provider. I have seen these predictions also earlier, and I still have a hard time believing them. As a whole banks offer a lot of services, and there will be many companies that challenge them with different services. The core banking services also require significant capital. Telcos have never been good to offer anything other than connectivity services to customers. Online and mobile services will change finance, but probably telco carriers’ role will be small in that disruption.
We can still say, as I have said earlier years too, that FinTech is component, not ecosystem, oriented at MWC. It is somehow surprising, when the finance system and new finance services are a huge new business and opportunity in mobile and all networks. There are lot of companies that offer advertising solutions at MWC, but actually finance services are often easier to make money with, because money is always a part of services in finance. Maybe in the next year we see FinTech has one focus area of MWC with a bigger picture emphasis on services and ecosystem.
Funnier side of MWC
Many people come to MWC to work hard, have business meetings and also participate in networking events. But as we know, each business, industry and event also has its more ironic parts. Especially if you have been to the event many times, you cannot take all things, announcements and comments too seriously. I was again curious about some things at the event.
Barcelona is a great place to eat with very nice restaurants, tasty food and reasonable prices for great food. But inside the MWC event, it is a totally different story. The catering has been outsourced to a company and its services and food puts me wondering about the deal every year. The main food offering is English style sandwiches (i.e. tasteless white bread and cheese) for €5.20. You get excellent sandwiches with actual taste in Barcelona downtown for €3 euros. The service at those event cafeterias is extremely slow, even the process to order a coffee is like from the Soviet Union to get a ticket and then walk to the next person, who shouts the order to the next person, and then after 5 minutes you get a latte, if you have ordered an Americano. This year’s extra was that their mobile payment terminals didn’t work, and the staff were walking around with them for a few minutes to get a connection to make the payment transaction. But howis it possible that the mobile payment terminals not work in the world's leading mobile event?
Sustainable Development Goals, SDG, were one of the main themes of the event in this year. Blockchain as a service was also a quite visible topic. There are several models to make blockchain services, but especially bitcoin type proof-of-work takes a lot of computing resources and electricity. For example, Kazakhtelecom said that their new business offering is blockchain as a service, because they have a lot of cheap energy available. According to the latest statistics, about 72% of electricity is generated from coal and about 5% from oil in Kazakhstan. I was just wondering, how sustainable a business is that, from an ecological or financial point of view?
The “next generation” SMS, i.e. Rich Communication Services (RCS), seems to be still one of those things operators want to create a big business with. They tell stories of how it is much better than native apps or chatbots for brands to communicate with consumers. Of course, they like it - when they can control them and make more money there than from apps. One more instance of carriers trying to get out from their bit pipe business. There was a panel about RCS and its opportunities. A marketing lady from British TV channel ITV told the crowd how excited she is about it, and Orange and Vodafone guys looked so happy. She compared moving from SMS to RCS to moving black-and-white TV to color TV. She was so excited that I was mainly wondering, what does she smoke, and does she know the color TV came 50 years ago, and now we have a thing called the internet, and even the mobile internet. Someone commented after the panel that RCS is an option for communications immediately after fax machine, pigeon and donkey.
IBM is very proud of their Watson AI. They tell how it helps manage big events, facility management and even predict problems with technical devices. So, I decided to go to IBM’s AI and predictive analytics sessions and indicated my intention also at MWC app. I went there, but I couldn’t get in, because they said it was overbooked and they cannot take more people in. I have learned also earlier about analytics, it is not really just to analyze data, but it is really about how you are able to execute and act based on your data and analysis. I think this experience told me a lot about IBM’s solutions to manage big events.
AI was an important topic at the show. There are always discussions about how much AI can really do and can it replace human beings. I always wonder about the passive crews many companies have at their booths at MWC. It is a big investment to be there. So, how can it make sense to have so many people there mainly tapping their phones or using their laptops, and even if you ask something, it is hard to get good answers. I was thinking that one place AI could really replace human beings is the staff at the booths in MWC.
Mobile and online advertising targeting is one exciting category at MWC. I mean, the exciting part is to understand, how it makes sense to have 1001 small companies there that tell, how they are better to target ads based on algorithm XYZ, and how they improve conversion by 7x. Especially this is exciting when the prices of online and mobile ads are now so low that it is hard for anyone to make significant business from it. Google and Facebook can do it with more than 1 billion users, but even with millions of users it is hard.
One of the best 5G comment came from F1 driver Fernando Alonso who was speaking in a panel. He said he has been doing it for 17 years, and his neck is used to it.
MWC has also mobile phones and some journalists that don’t understand other stuff there write stories about them. I also found myself one day at a huge stand that was full of mobile phones, but I have never heard about that brand. I asked the crew, what is this brand. They said the same company has also another brand, maybe I have heard about that one. No, I haven’t. Then she told me it is from China. I said it is unnecessary to say, when I know all big mobile brands I don’t know are from China. Then I walked to another big mobile phone stand, and found out, those phones were actually from Algeria.
The guys from mobile phone history - Nokia and Blackberry, had also devices with their brands at the show. Blackberry continues with its old style, i.e. black, thick, and slow phones with physical keyboard. Nokia was even more retro and brought back the banana phone. All those people who say the mobile phone is only for talking and texting like them. Except, such a phone is useless nowadays, and not even those real retro people really want to use them.
MWC is a good industry event, many interesting new things, if you want to find them, and Barcelona is a great city. There is always something to improve, and some companies should also do their homework better that they don’t look so out of place. In that way we can create the next generation MWC. But really, please, don’t call it ‘next generation’, because there are already hundreds of companies at MWC that offer next generation products.
New applications that sit at a legal gray area for financing innovative companies. Excited investors pouring in millions and millions of capital. Regulators and policy makers trying to understand the new models and introduce investor safeguards as well as industry guidelines. Financial institutions watching by the sidelines, evaluating what their next move will be and how to respond. The year is 2010 and everyone is excited about the prospect of crowdfunding.
This is the first true fintech ‘revolution’ I was truly part of, so to me everything that is going on with Initial Coin Offerings or Initial Token Offerings bears a striking resemblance. Yet if we break it down, the actual development of the market while profound was a lot different than what we had expected.
1) Moonshot Initiatives Lead To Long Term Adoption
The very start of the equity crowdfunding market saw innovators like Seedrs, Angelist, the Grow VC Group create online marketplaces for startup financing, and other related pioneers such as Kiva grew their global loan marketplace.
There were hundreds if not thousands of other companies we saw over the years, yet ultimately approaches diverged, become more specialized or found niches to truly lead the way in. There was also a clear separation of regulated securities platforms and non-securities platforms that paved their own ways, ultimately serving a different client demand and use case.
These specific applications started the discussion, forced incumbents, challengers, service providers (payments companies, fraud prevention, ID verification services) and policy makers to examine their approaches and decide upon what position, if any, they would play in the new market. This lead to an ecosystem that started flourishing and supporting end to end value chains, in order to serve an ultimate client value.
In examining positions, many financial institutions also adopted peer-to-peer and crowd syndication technologies to their existing processes, such as raising equity capital for mid market companies from a group of investors online or providing additional loans through automated applications to fill a void left by falling bank financing in small business loans. The ecosystem of services available expanded.
2) Novel Applications Introduce Technology for Ancillary Use Cases
What ICOs and cryptocurrencies have already demonstrated, is a thirst for knowledge as it relates to distributed ledger technologies (DLTs) such as blockchain and the possibility of immutability that it can afford. Yet it’s not only blockchain, but also different methods for verifying the authenticity of transactions and their order, such as models like the proof of work, proof of stake and hashgraph concepts. This is far beyond the simple use of payment currency with Bitcoin or Ether, yet those were fundamental in the process itself.
While it seems there was a surprisingly negative reaction to Stripe’s recent announcement to stop accepting bitcoin as a form of payment, for anyone who actually read the announcement from the company, they cited a shifted use case of cryptocurrencies from a simple means of payment to an actual and usable asset class. This would be consistent with how the market has developed and indeep Stripe’s track record of investing into new crypto strategies and companies leveraging DLTs speaks for itself.
Distributed technologies have shown promise, not only in existing applications but in applications that could not be possible without a true decentralization and mathematical validation, that is the lack of a central authority. Tokens, combined with DLTs, have also become a fascinating talking point with planned applications ranging from loyalty programs, to settlement mechanisms and liquidity for illiquid assets.
3) Regulations and Policy Frameworks Lead to Institutional Buy In
One clear innovative approach to come from the peer-to-peer investing and crowdfunding applications was the regulatory sandboxes introduced and pioneered by organizations such as the Financial Conduct Authority in the UK, and ultimately leading to broad adoption through several financial regulators around the world. Started off as a pragmatic initiative to gain visibility and accountability with new services absent a fitting regulation, fostered an industry cooperation and knowledge sharing on both sides of practitioners and policy makers.
This type of knowledge transfer that yields industry best practices is critical in a functioning ecosystem and it ultimately ends up benefiting the end users, giving way to a more efficient and secure ecosystem of services. It is also paramount to gaining institutional adoption, which for example is clear in peer-to-peer lending and the institutional backing of wholesale loans, which has surpassed all other capital sources.
It may be that the crowdfunding wave that started in 2008-2009 has lots of parallels to the ICO and blockchain boom that started in 2016-2017, yet any new market has its own considerations.
We’ve seen all sorts of experts come out trying to capitalize on both innovation cycles, yet its good to keep in mind that in transformative changes, past experience does not necessarily equal knowledge. New models and tricky because they are indeed new and the most valuable models would not have been possible with past tools.
Hype curves and megatrends are good to identify and definitely to be part of, yet one has to keep eyes open and be aware of where the value lies, both short term and long term. With all the billions of dollars invested in token offerings of 2017, we are optimistic we will see a lot of tangible long term value. That does not of course mean, we will not experience one or two hiccups in the short term. Yet these hiccups, similar to those in the crowdfunding and peer-to-peer investing markets, are not what remains for the history books. That’s made up in the difference between short term and long term.
The article first appeared on Difitek's Blog.
Mobile World Congress, Barcelona, February 26, 2018 - Startup Commons (a Grow VC Group company) announces global ecosystem applications marketplace with open call for app developers around the world building applications, SaaS services or platforms focused on startups business creation, managing support services for startups or managing & coordinating ecosystem development, and looking to expand to more ecosystems.
“As part of our work with various startup ecosystems around the world, we came across growing interest in applications used in other regions, to learn from these applications and developers for own local ecosystem needs.” - says Oscar Ramirez, CEO, Startup Commons Global.
“We know there are number of great applications and online services being developed and operated in these ecosystems. There are also many exceptional and dedicated developers working on their digital solutions, having great understanding and perspective of ecosystem developers challenges, understanding business creators or support providers needs at various startup development phases.
As a global ecosystem facilitators with a member base of over 30 000 ecosystem actors around the world, we want to help good applications scale to new markets with new user & customers, and help ecosystems key actors to find best connected applications to accelerate their progress and ecosystem development.”
Applications Marketplace is a natural extension of Startup Commons EcosystemOS - a serverless cloud architecture for developers, including ecosystem level user accounts and ecosystem API's, with global standards and documentation for user data portability, API connections, data models, data sharing principles.
Open a call for first batch of ten best digital solutions:
Apply to join Startup Commons Marketplace
Oscar Ramirez, CEO
Phone: +34 656 180 880
About Startup Commons
Startup Commons is dedicated to digitizing and connecting startup ecosystems globally to scale entrepreneurship, innovation and business creation around the world, by providing digital connectivity and solutions to enable data-driven economic development and policy making for local ecosystems.
Changes take time, until they just happen. Financial services are at the cusp of a remarkable change that few bankers realize. The decentralization of technology, new regulation increasing competitiveness and ecosystem strategies - all these trends will mark the rise of a new era of financial services. This era will be fundamental to end user value and those who provide it will thrive.
Grow VC Group has prepared a report to cover the main changes and drivers in the finance services. This means especially FinTech services, but they have impact on the whole finance industry and also on the Internet services and business models.
This report covers much more than only the most predominant trends in financial services, in it we discuss analogies of data to the oil business, how new models have to truly spawn the rise of new ecosystems. We discuss the rise of financial institutions as safeguards of your money, as opposed to hiding money under your mattress as well as their failings when instead of a mattress, you have an offline wallet in a decentralized ledger system.
Those are examples of questions that are considered in this report. No one has explicit answers, but this report gives new insight and angles to find answers. Finance services are a complex combination of finance services, instruments and technology, and it needs a lot of competence to develop new services, but it also requires to challenge the old models and thinking.
The disruption of the finance services is not driven by technology; it is driven by customer needs, and enabled by FinTech. Financial services as they stand today, cannot truly meet customer expectations of today’s and especially tomorrows global Internet and mobile era. Financial services firms are also competing in a breadth of services, where they cannot expect to be key contenders in all in the future. As startups and technology companies start to offer better services and really compete, the whole financial services industry must react.
The three key technology drivers are:
Currently the real influence of these components is in the order above, although if you were to look at the public discussion the order would seem to be the opposite. In reality cloud-based services have already started significantly changing finance services development and costs. Data analytics is already very important, whereas AI is more like a nice key word.
Key transformations to be seen:
The report is prepared by the Grow VC Group, together with two group companies, Difitek and Prifina. It has the foreword from Oracle's Financial Services and the media partner to distribute it is Disruptive.Asia.
The report covers many aspects of the disruption in finance and Internet services. It cannot cover all aspects, but it is one of the most comprehensive summary of FinTech, distributed finance models, and finance data services. The report helps everyone to identify the key drivers and changes that will impact on digital finance services and Internet services during the coming years.
You can read the report here, and download all Grow VC Group reports here.
Startup Commons, a global platform for startup ecosystem development publishes its serverless service architecture - EcosystemOS.
Startup Commons (a Grow VC Group company) launches its serverless platform version for digital startup ecosystem development and marketplace for application developers for sharing and distributing best applications and services between ecosystems around the world.
EcosystemOS offers common user accounts and API's with documentation for user data portability, API connections, data models and data sharing principles to develop applications for startup ecosystems. It also includes a marketplace for connected ecosystem applications and third party API functions. EcosystemOS is especially used by public sector organizations (e.g. regional and municipal development agencies) and private startup services that operate startup and entrepreneurship ecosystems and offer services to startups, investors, and other stakeholders.
“As part of our work with various startup ecosystems around the world we have come across with active interest to use applications from other regions and to learn from other application and SaaS service developers for own local ecosystem needs.” - says Oscar Ramirez, CEO, Startup Commons Global and continues,
“While Startup Commons focuses on developing and providing EcosystemOS as the backbone for ecosystem user accounts, API’s, data models, data portability and sharing, we know there are many great applications and online services developed and validated in real ecosystems around the world. Now we want to offer an easy way to offer these applications globally through EcosystemOS. There are many excellent and dedicated developers that implement applications for startup ecosystems locally and have great understanding of unique aspects, challenges and needs of those ecosystems and startups in different phases. Now they get an opportunity to offer their services globally.”
Learn more at: www.StartupCommons.org/EcosystemOS.html
Oscar Ramirez, CEO
Phone: +34 656 180 880
About Startup Commons
Startup Commons is dedicated on digitizing and connecting startup ecosystems globally to scale entrepreneurship, innovation and business creation around the world, by providing digital connectivity and solutions to enable data-driven economic development and policy making for local ecosystems.
ICOs and cryptocurrencies became a big thing last year. Some people think they have changed the whole world, while others think they are the biggest bubble we’ve seen in a long time. The value of an individual coin or currency is hard to evaluate when the market is new and transparency not always good. It is much easier to say that the concepts, models and technologies behind cryptocurrencies will make a big change for finance and also for the Internet and economies. Distribution, tokenization and tokenomics are the new new economy.
Tokenization is the process of converting the rights of an asset or a service into a digital token typically on a distributed ledger such as blockchain. ‘Tokenomics’ is a model of distributed ledger-based financing for the economy. There are probably other ways to define these new terms, but basically, they refer to how securities and transactions can be based on digital tokens that are issued, sold and traded in blockchain-based markets and services.
Note that these models and concepts are not important only for finance and FinTech. Distributed models are also changing the very fundamentals of Internet services. While Internet architecture is of course distributed, Internet services are highly centralized – big databases and services that gather a lot of users. This has led to the idea that the Internet easily creates natural service monopolies similar to Facebook, Google and Amazon.
Blockchain and other distributed ledger models enable decentralized services in which data, transactions and ownership are distributed around the Internet to different parties. Bitcoin is a well-known example of this. It is not issued by a central bank, big banks do not handle transactions, and they are not stored in bank accounts.
But this is not limited to virtual coins. Distributed models can also mean, for example, that each consumer owns and manages his or her own data. Currently big Internet companies possess and control the data – when you go to use a service, you log in, and the service provider uses the data it has collected about you to provide the service. In the future, you could come to the service provider and bring your own data with you (or an ‘avatar’ based on your data), and sign up for services based on your personal profile.
This means, for example, you could apply for and receive an optimal loan using your own data via an API without relinquishing that data. Or it could mean a social media service doesn’t own or keep user data, but rather each user has his or her own data and updates – the social media service becomes just an API-based service that displays selected data to selected friends.
Almost anything tradeable can be a token
Tokenization has become relevant now especially for startups and new projects that have create utility tokens to use new services, security tokens for equity, and some hybrid models of security and utility tokens. The problem with many ICOs is that the tokens for these services and assets haven’t enough data to properly define a value for them.
Tokenization can be done for all kinds of assets and services, and can be easier to value than startup equity. The ‘tokens’ could be real estate ownership, the right to live in an apartment, the right to use certain infrastructure, ownership of a private company, a currency issued by a government, or loyalty points from a supermarket or airline. Basically, all money, securities and vouchers can be digital tokens. This will change how we issue, sell and trade them. It will be all digital and it can be stored in blockchains, without a lot of paper work or central parties to handle transactions.
Tokenomics is a new term that tends to be used in different ways in different contexts. Put simply, it means economical and financial models that use distributed finance and tokenization as the basis of the economy. It means digital tokens, blockchain, smart contracts and models without centralized transactions or authorization. As the Internet of the 1990s started to create big services and databases, tokenomics can distribute services, data and transactions.
It is early days, of course, so it is hard to say now what all this means for businesses on the Internet. Right now we are worried that Facebook, Google and Amazon know more about us than we know ourselves, and they’re starting to manage our whole lives. Could it be that distributed models will stop this development and actually turn it in the opposite direction – perhaps to the point of even killing some Internet giants? At the same time, it is a threat for traditional banks, payment processors and even governments who worry at the loss of centralized control.
Bitcoin, cryptocurrencies and ICOs are exciting and quick money for some people, just as some hot companies were during the dotcom boom in the late 90s. But these should not distract from the much larger and more fundamental developments happening behind the scenes that are going to change Internet services, finance services and traditional economic structures. It is not yet visible in mainstream activities and discussions, but many parties are already building those new structures, and the potential for disruption is massive.
Amazon can already recommend you books and movies, and remind you that it is time to order more coffee or toilet paper. Many other services make recommendations for you. In these cases the service or online store has your data and makes recommendations. But we are approaching an era where you can have your own data and your AI that makes purchases your behalf. It will change the customer experience, purchase decision making and the balance of power between stores and consumers.
Now large companies, like retailers, banks and media companies especially own that data. They use this data to advertise, make recommendations and tailor offers to you. It is always in their hands to manage this process and optimize offers so that they can generate maximal value from you.
Most companies use a lot of money to build their brands, image and appeal to the feelings of consumers. It has been important – a consumer's feelings and image of brands definitely have an impact on purchasing decisions. Actually, brand versus data oriented marketing practices have divided marketing people and departments, some marketing professionals believe much more in brand marketing and some others in data oriented targeting and optimization.
In the future this can be very different. When you have your personal data and you can use engines (you can call it AI, personal assistant or data analytics) that actually make purchase decisions and orders for you. A good purchase assistant cannot only compare prices; it should know other qualities that are important to you in order to find the right products. It will definitely change a lot in terms of how retailers and other services offer their products, conduct their marketing, and offer data from their products.
We have two very opposite developments in internet services at the moment - one that is its very early phase, and another that is approaching its peak. Big internet giants, retailers and finance institutions are becoming bigger, with more and more of your data that they can use to win more market share. Some people even see that Amazon is already so powerful in the US that it should be split based on antitrust laws. But this development can soon reach its peak.
The new development in the internet is more distributed solutions. We have seen this especially with blockchain and cryptocurrencies. There is no central party or database to manage the data and transactions. This has started to have an impact on finance and especially fintech services. But it is not only limited there. Distributed models will change many other things on the internet, including retail, data management and ownership, and who and how to utilize data to make decisions.
There are old IoT visions, such as how your fridge in the future will know what food you need to buy and make an order. It is hard to say, if it is a fridge or some other systems that will really start to do it, but this day is approaching rapidly. The fundamental change is when can you have your own data and engine to make decisions and orders, not simply trust the analytics of a store.
We already have services that help e.g. to find flights, hotels, and loans based on your preferences. Especially with travel booking these services are significant. They are still quite manual services, when you need always fill your preferences and the compare different options, and some booking services even try to complicate comparisons by having additional attributes and secret prices that the comparison services cannot handle.
Most probably there will be always some purchase decisions we want to make personally. At the same time, there is a significant part of purchases and orders we would like to delegate to a machine. A lot of data is already available to enable this, it just needs some new solutions that consumers can manage and utilize their own data and some smart machines to start to make decisions and send orders. It will put retailers and services into a totally new position. It is not enough to optimize offers and customer experiences only for human beings, but also for smart machines that have a lot of data.
Maybe we will see an arms race between selling and buying machines and who have better data. Consumers get better AI that optimizes their purchase decisions and value for money, and retailers, finance services and other vendors have machines that target to maximize sales and profit. Regulation, like General Data Production Regulation (GDPR) in EU, has also an impact on this, when it empowers consumers to control his or her own data. It will be one more area where data is prevalent in the business in the future.
The article first appeared on Telecom Asia.
Est. 2009 Grow VC Group is the global leader of fintech innovations, digital and distributed finance services. Our mission is to make the finance services more effective, transparent and democratic. The Group includes leading fintech companies in their own areas.
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