This Week in Fintech

During the week when heatwaves boiled the world, our Experts posted cool fresh insights each & every day. Daily Fintech offers unique insights about the future of Fintech written by and for senior executives, entrepreneurs and investors. Monday Ilias Hatzis @iliashatzis our Greece-based crypto entrepreneur, wrote “Bitcoin to the Moon”  TLDR: Bitcoin, Ethereum, Litecoin and […]

The post This Week in Fintech appeared first on Daily Fintech.

Blockchain for branding, as banks see little benefits – WEF reports

Image Source Is it a Golden bullet? or just a jewel? When I used to be a developer in banks, I used to get this question all the time – “do we have a golden bullet (tech) that can solve all our problems?”. The question used to be from very senior people in the bank […]

The post Blockchain for branding, as banks see little benefits – WEF reports appeared first on Daily Fintech.

InsurTech is still looking for traction with customers and companies’ staff

image   TLDR   Are the InsurTech advocates/enthusiasts ‘preaching to the choir’ and considering that to be conversion of the masses?   Within the orb of InsurTech press, social media, and conferences one would think innovation and migration to adoption of the most clever of tech and innovative practices is de rigueur within insurance- if one […]

The post InsurTech is still looking for traction with customers and companies’ staff appeared first on Daily Fintech.

Friendly fintech MoneyLion lands $160 million in fresh funding

Who doesn’t love being part of a club? Most of us are suckers for anything that looks and feels a touch exclusive. Frequent Flyer points are probably the most obvious example of this in practice, alongside the coveted airline lounges, and their tiers of exclusivity and privileges. What if banking was a club, rather than […]

The post Friendly fintech MoneyLion lands $160 million in fresh funding appeared first on Daily Fintech.

Environmental Sustainability and Finance: Poker or Chess?

In early July, Onalytica published an article on Sustainability with a focus in the financial services sector. Comparing the WEF`s Global Risks Reports over the past 10 years[1], they highlight a stunning shift. We are confronted with the reality that Sustainability risks are Business, economy, and Societal risks. All industries are realizing this and the […]

The post Environmental Sustainability and Finance: Poker or Chess? appeared first on Daily Fintech.

Bitcoin to the Moon


TLDR. Bitcoin, Ethereum, Litecoin and many other cryptocurrencies continue to experience massive growth in price, market capitalization, and mainstream adoption. Cryptocurrencies change and improve the way we do things. It is no longer a question of whether cryptocurrencies are disrupting the global economy. The only question is how much and how fast.

On July 20, 1969 we made history. Two days ago, we had the fiftieth anniversary of the Moon Landing, when man walked on the Moon for the first time.

The Apollo Guidance Computer  was the primary computer for the Apollo mission. It was one of the first computers to use integrated circuits, so instead of filling an entire room, it squeezed everything into a box just a couple of feet in size. Today, the A11 chip in an iPhone X can perform six hundred billion floating point operations per second. That’s a million times faster than the computer that put man on the Moon.

In 1969, a 50 year old man was old and was expected to live another 17 years. But today, being 50 isn’t old. I am expected to be around at least another 30 years or so. I’ve seen my fair share of technology revolutions over the last fifty years:

1969 — Arpanet:  Before the entire world was networked, there was the Arpanet, four computers linked together in 1969. It introduced the concept of “packet switching,” delivering messages as short units and reassembling them at their destination.

1977 — Personal Computer: The Apple II, Commodore Pet and Radio Shack’s TRS-80 are introduced in 1977, four years before IBM, soon to become synonymous with the term “PC,” unveils its personal computer.

1978 — GPS: The first satellite in the modern Navstar Global Positioning System (GPS) was launched. It is not until the year 2000, though, that President Clinton grants nonmilitary users access to an unscrambled GPS signal.

1979 — Sony Walkman: “This is the product that will satisfy those young people who want to listen to music all day,” Akio Morita, Sony Chairman, February 1979.

1983 — Microsoft Word: Multi-Tool Word, the precursor to the Microsoft Word text-editing program, makes its debut as free copies are bundled with the November issue of PC World.

1989 — World Wide Web: Sir Tim Berners-Lee creates “hypertext markup language” (HTML) to make Web pages and the “Uniform Resource Locator” (URL) to identify where information is stored. These breakthroughs form the foundation of the World Wide Web.

1998 — Google: It began as early as January 1996 as a research project, by Larry Page and Sergey Brin, PhD students at Stanford University. Conventional search engines ranked results by counting how many times the search terms appeared on the page. Google developed PageRank,  that determined a website’s relevance by the number of pages, and the importance of those pages that linked back to the original site.

2001 — Wikipedia: A multilingual online encyclopedia, based on open collaboration through a wiki-based content editing system. It is the largest and most popular general reference work on the World Wide Web. It features exclusively free content and no commercial ads, which is incredible.

2004 — Facebook: Harvard dropout Mark Zuckerberg launched “,” a social network site originally restricted to his fellow classmates, in February 2004. Today Facebook is used by 2.3 billion people around the world.

2007 — iPhone Steve Jobs introduces Apple’s first smartphone with a prank-call order of 4,000 lattes from a nearby Starbucks. The iPhone was also the first U.S. smartphone without a physical keypad, and goes on to become the best-selling gadget ever, with more than 2 billion sold to date.

2009 — Bitcoin: The pseudonymous Satoshi Nakamoto launches the first popular cryptocurrency, an anonymized peer-to-peer encrypted form of cash. Bitcoin uses blockchain, a decentralize ledger to verify payments, that is nearly tamper proof.

“Bitcoin to the Moon” is a term introduced by crypto enthusiasts denoting an extreme spike in BTC rate. It became part of the crypto lexicon in late 2017, when Bitcoin hit $20,000

What will it take for Bitcoin to revisit the moon again?

When you look at the fundamental developments in the space you will realize that what happened back in 2017, when we had Bitcoin’s crazy rally, will happen again. There are potential catalysts that can lead this market to another 10x, potentially 20x over the next few years.

It’s not going to be altcoins, with 100x returns. It’s not going be institutional money or Bitcoin ETF, either. While they will play a huge role and increase the liquidity of the market, it will have to be something much more fundamental for the industry to the reach the next level.

One potential catalyst is DeFi. Decentralized Finance or DeFi is basically a shared effort to build open source decentralized censorship resistant technology, that opens up financial opportunities to everyone. It tries to cut out the middlemen and provide the best peer-to-peer experience for finance. We are seeing offerings like hedging, shorting, derivatives, and more, without intermediaries, clearinghouses or the need for trusted third parties. Imagine exchanging assets and tokens, opening up markets, for example crypto loans and stable coins, that allow anyone to have the purchasing power and stability of the US dollar. One example is Maker, both a stable coin and a collateralized lending platform. The collateral for the loans, is what stabilizes the Maker stablecoin.

Another important catalyst is programmable applications for Bitcoin. We will have to see Bitcoin adopt smart contracts, that have been so important and successful for Ethereum. Frameworks like RSK are important, because they allow us to lock up Bitcoin in smart contracts and to generate stablecoins like DAI.

Obviously there is more room for adoption. When we look at the most basic metric, ownership, we still have a long way to go. In the last 2-3 months, while BTC has jumped from $3,000 to $12,000, owning some type of cryptocurrency is still so low at 1% global adoption. Even if we just had a moderate jump in adoption, reaching 2-3%, we would see an exponential flow of institutional capital and possible a Bitcoin ETF, that will allow people to access the market in different ways,

Things like this could play an important role for the crypto space overall, but most importantly for Bitcoin’s valuation. These developments would allow Bitcoin to act as collateral, a store of value, and become the backbone for a new wave of stable coins.

The impact of the moon landing is all around us, forever a reminder of spectacular possibilities. Bitcoin is a moonshot. It’s the idea that anyone can be their own bank. It eliminates the middleman, no longer required for authorizing and authenticating any kind of transaction. This is a highly polarized topic, with strong sentiments on both sides of the centralized and decentralized debate. Time will tell how far this revolution will go.

Image Source

Ilias Louis Hatzis is the Founder & CEO at Mercato Blockchain Corporation AG. He writes the Blockchain Weekly Front Page each Monday and has no positions or commercial relationships with the companies or people mentioned and is not receiving compensation for this post.

Subscribe by email to join the other Fintech leaders who read our research daily to stay ahead of the curve. Check out our advisory services (how we pay for this free original research)

The post Bitcoin to the Moon appeared first on Daily Fintech.

Last week in Fintech & Crypto

During the week when American politics became even more toxic, Daily Fintech Experts posted fresh insights each & every day.

Monday from @iliashatzis, our Greece -based crypto entrepreneur, described the strange news of President Trump publicly voicing his negative views on Bitcoin. Read here

Tuesday from @efipm, our Swiss-based Fintech Adviser, analysed why incumbents are beating startups in the robo advisory market which she has been tracking since 2015. Read here

Wednesday from @jessicaellerm, our Australia-based Fintech entrepreneur,  described how a major digital challenger bank, Nubank in Brazil, is moving into the small business market. Read here

Thursday @insuranceeleph1, Patrick Kelahan, our US based Insurtech expert, interviews the author of a study of 194 insurtech ventures with the aim of having a solution box to look in when you have identified what problem you want to solve. Read here

Friday from @karunk, a London based Fintech investor, looked at how AI based credit decisions, while smarter than ye olde FICO scores need to make their algos transparent both to consumers and regulators. Read here

Saturday @lunnbernard, CEO of Daily Fintech,  described the technology from satellites to mesh networks that will power Bitcoin even if the Internet is shut down. Read here

The post Last week in Fintech & Crypto appeared first on Daily Fintech.

Blockstream satellites, Locha mesh networking and the Bitcoin domesday scenario


TLDR. Analog Bitcoin fans (aka Gold Bugs) like to talk about domesday scenarios where there is no Internet and so Bitcoin will be worthless. In the real world (as opposed to the talking heads circuit) it is not Bitcoin or Gold it is Bitcoin AND Gold. However nobody wants worthless Bitcoin. This update to The Blockchain Economy digital book describes Blockstream satellites and Locha mesh networking . These ventures and technologies ensure that you can still use cryptocurrencies even in the domesday scenario.

This update to The Blockchain Economy digital book covers:

  • Domesday Scenarios without Internet
  • Blockstream satellites
  • Locha Mesh networks
  • Context & References

Domesday scenario without Internet

The Chapter entitled Why BTC = USD1 million may be possible, but not desirable even for those with Bitcoin describes 4 scenarios that investors plan for, the 4th being what we refer to as the domesday scenario:

  • Scenario 4. Legacy Finance assets suffer a catastrophic decline and Bitcoin goes to zero. In that awful scenario, shelter, food & physical safety become critical and financial assets become only a distant memory and it is the gold part of your tail risk insurance that you rely upon.

Bitcoin can go to zero because a) it was always just a mirage or ponzi scheme or b) it becomes impossible to use because it requires Internet access and there is no Internet.

There are three ways we can be deprived of Internet access:

  • There is a catastrophic disaster from climate change or nuclear war or economic/societal collapse.
  • Your Government orders ISP’s to cut off Internet access for everybody (possibly to prevent a stateless challenge to their Fiat currency).
  • Your Government orders ISP’s to cut off Internet access for you (because you are viewed as an enemy of the state).

We look at the two technological solutions to this domesday scenario – one from above (satellites) and one from your neighbours on the ground (Locha Mesh networks).

Blockstream satellites

The Blockstream Satellite network broadcasts the Bitcoin blockchain around the world 24/7 for free, protecting against network interruptions and providing anyone in the world with the opportunity to use Bitcoin.

Blockstream is a private venture funded business with a lot at stake in Bitcoin. The theory is that even if the Internet is not available, you can still use Bitcoin via satellites. The problem is that as a centralised venture funded business, they are susceptible to pressure from Government.

Locha Mesh networks

This is a more ground up initiative coming out of Venezuela. The best introduction in the English language is this podcast interview. There is a lot about the political situation in this interview; if you want to skip to the tech, go to around minute 15.

101 on mesh networking: Traditional networks rely on a small number of wired access points or wireless hotspots to connect users. In a wireless mesh network, the network connection is spread out among dozens or even hundreds of wireless mesh nodes that “talk” to each other to share the network connection across a large area. Mesh networks use publicly available radio frequencies.

In short, wireless mesh networking is a decentralized, open permissionless network like Bitcoin ie nobody can shut it down.

This is an example of why this chapter describes The Path To Mainstream Adoption Of Bitcoin Is Not Through Legacy Finance Institutions, It Is Through The Excluded

Context & References

Why #GetOffZero Gets Sensible Investors To Look Seriously At Improbable Bitcoin Based Solutions.

Why BTC = USD1 million may be possible, but not desirable even for those with Bitcoin.

The Path To Mainstream Adoption Of Bitcoin Is Not Through Legacy Finance Institutions, It Is Through The Excluded

Bernard Lunn is a Fintech deal-maker, investor, entrepreneur and advisor. He is CEO of Daily Fintech and author of The Blockchain Economy.

I have no positions or commercial relationships with the companies or people mentioned. I am not receiving compensation for this post.

Subscribe by email to join other Fintech leaders who read our research daily to stay ahead of the curve. Check out our advisory services (how we pay for this free original research).

The post Blockstream satellites, Locha mesh networking and the Bitcoin domesday scenario appeared first on Daily Fintech.

FinServ in the age of AI – Can the FCA keep the machines under check?


Image Source

I landed in the UK about 14 years ago. I remember my initial months in the UK, when I struggled to get a credit card. This was because, the previous tenant in my address had unpaid loans. As a result, credit agencies had somehow linked my address to credit defaults.

It took me sometime to understand why my requests for a post paid mobile, a decent bank account and a credit card were all rejected. It took me longer to turn around my credit score and build a decent credit file.

I wrote a letter to Barclays every month, explaining the situation until one fine day they rang my desk phone at work to tell me that my credit card had been approved. It was ironical because, I was a Barclays employee at that time. I started on the lowest rungs of the credit ladder for no fault of mine. Times (should) have changed.

Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks and a whole suite of methodologies to make clever use of customer data have been on the rise. Many of these techniques have been around for several decades. However, only in recent times have they become more mainstream.

The social media boom has created data at an unforeseen scale and pace that the algorithms have been able to identify patterns and get better at prediction. Without the vast amount of data we create on a daily basis, machines lack the intelligence to serve us. However, machines rely on high quality data to produce accurate results. As they say, Garbage in Garbage out.

Several Fintechs these days are exploring ways to use AI to provide more contextual, relevant and quick services to consumers. Gone are the days when AI was considered emerging/deep tech. A strong data intelligence capability is nowadays a default feature of every company that pitches to VCs.

As AI investments in Fintech hit record highs, it’s time the regulators started thinking about the on-the-ground challenges of using AI for financial services. The UK’s FCA have partnered with Alan Turing Institute to study explainability and transparency while using AI.

Three key scenarios come up, when I think about what could go wrong in the marriage of Humans and Machines in financial services.

  • First, when a customer wants a service from a Bank (say a loan), and a complex AI algorithm comes back with a “NO”, what happens?
    • Will the bank need to explain to the customer why their loan application was not approved?
    • Will the customer services person understand the algorithm enough to explain the rationale for the decision to the customer?
    • What should banks do to train their staff to work with machines?
    • If a machine’s decision in a critical scenario needs to be challenged, what is the exception process that the staff needs to use?
    • How will such exception process be reported to the regulators to avoid malpractice from banks’ staff?
  • Second, as AI depends massively on data, what happens if the data that is used to train the machines is bad. By bad, I mean biased. Data used to train machines should not only be accurate, but also representative of real data. If a machine that is trained by bad data makes wrong decisions, who will be held accountable?
  • Third, Checks and controls need to be in place to ensure that regulators understand a complex algorithm used by banks. This understanding is absolutely essential to ensure technology doesn’t create systemic risks.

From a consumer’s perspective, the explainability of an algorithm deciding their credit worthiness is critical. For example, some banks are looking at simplifying the AI models used to make lending decisions. This would certainly help bank staff understand and help consumers appreciate decisions made by machines.

There are banks who are also looking at reverse engineering the explainability when the AI algorithm is complex.  The FCA and the Bank of England have tried this approach too. A complex model using several decision trees to identify high risk mortgages had to be explained. The solution was to create an explainability algorithm to present the decisions of the black box machine.

The pace at which startups are creating new solutions makes it harder for service providers. In recent times I have come across two firms who help banks with credit decisions. The first firm collected 1000s of data points about the consumer requesting for a loan.

One of the points was the fonts installed on the borrowers laptop. If the fonts were used in gambling websites, the credit worthiness of the borrower took a hit. As the font installed indicated gambling habits, the user demonstrated habits that could lead to poor money management.

The second firm had a chatbot that had a conversation with the borrower and using psychometric analysis came up with a score. The score would indicate the “intention to repay” of the customer. This could be a big opportunity for banks to use in emerging markets.

Despite the opportunities at hand, algorithms of both these firms are black boxes. May be it’s time regulators ruled that technology making critical financial decisions need to follow some rules of simplicity or transparency. From the business of creating complex financial products, banks could now be creating complex machines that make unexplainable decisions. Can we keep the machines under check?

Arunkumar Krishnakumar is a Venture Capital investor at Green Shores Capital focusing on Inclusion and a podcast host.

I have no positions or commercial relationships with the companies or people mentioned. I am not receiving compensation for this post.

Subscribe by email to join Fintech leaders who read our research daily to stay ahead of the curve. Check out our advisory services (how we pay for this free original research).




The post FinServ in the age of AI – Can the FCA keep the machines under check? appeared first on Daily Fintech.

Have the horse before the cart- problem first, then innovation solution


TLDR Insurance is not complicated, say compared to sending a man to land on the moon, but it’s big, and its current challenges are like finding the proverbial needle in the haystack.  Innovation, digitization, virtual sales and service, and so on.  Not unlike the elephant in the fable, insurance is perceived differently by each beholder- is it tail, ear, leg, trunk, sales, or underwriting, claims, accounting, actuarial, or customers?  What is to be innovated?

The drum beat of innovation is in some part fashion, but a large part reality- insurers need to evolve with their customers.  But there’s the rub- what evolution is meaningful, useful, profitable, doable, and able to be integrated into a carrier’s strategy, tactics, and admin superstructure?

This week’s discussion- who is useful to consult when you want to do it, or how to tackle it, innovation idea-wise.

I had a very useful conversation this week with an insurance veteran, Joël Bassani, founder and consultant at jinnbee who is now looking to share his knowledge gained over years with the insurance industry.  Our discussion reminded me that there are many aspects to insurance, many lines, covers, regulations, regions, etc. that one must deal with in the globally interconnected insurance world.  And how does one determine what path to take from that which one is on to one that leverages innovation or change?

What Joël told me as a foundational message resonates well- it’s not necessarily knowing the tech to apply, but it’s knowing what problem you have and working from that to what innovation has to help you.  In his opus of an InsurTech study, Joël notes early on, “An InsurTech is a solution, you need to focus on your Problem!”

And how do you know your problem?  Simple- you ask your customers, both external and internal and you strive to #innovatefromthecustomerbackwards .

What jinnbee has compiled for the industry is a compendium of InsurTech purposes:

You have an insurance problem, jinnbee’s analysis can help find an InsurTech solution from organizations that exist, are experts in their fields, and are available.  So you don’t have to create the wheel, you simply need to know the makeup of the wheel and jinnbee will help find a fit.  Do you make the innovation in house, or connect with an InsurTech?  Jinnbee will help lead your decision matrix.

And as comprehensive a study as jinnbee has produced, there are other organizations who have blazed a trail in terms of aggregating InsurTech organizational data, firms’ purposes, an ability to play ‘matchmaker’, and in providing accessible data. The two most prominent examples are Coverager, and Insurance Thought Leadership .


I asked Coverage founder Shefi Ben-Hutta what synopsizes Coverager’s business model, what is the ‘elevator pitch’ that would best describe her firm’s approach:

  • Focus on tech, strategy, and alternative insurance distribution
  • Create and curate coverage (news, not lines of insurance)
  • Address the needs of insurance professionals, those who need access to information regarding how to address their unique problems (sound familiar?)

If the reader has yet to access the Coverage website (or better yet, subscribe to Coverager’s daily email), rest assured you will not be disappointed by a simple blast of information.  Coverager approaches information sharing with a wry tongue in cheek, occasional snark, but always best in class, topical information.  The firm’s web splash page gives an indication of the depth of coverage and information:

Everything from an encyclopedic source of insurance company information, a searchable database of InsurTechs, hosting of industry events, and to the latest marketing scheme or the scoop on a company that has gone off path.  As Shefi recounted, their purpose is:

  • Learn from the past
  • Understand the present
  • Better bet on the future.

Insurance Though Leadership

Take Coverager’s avant-garde approach to InsurTech assistance and look to a somewhat organizational opposite, and one finds Insurance Thought Leadership (ITL).  ITL approaches InsurTech advisory services with more of a formal suit, but with no less breadth of information as Coverager.  ITL has developed through the efforts of its founder, Dave Dias  into a premier source of innovation source/need connections, and a premier host of innovation education.  And the firm is the home of the man with a knowledgeable grasp on the innovation world, Guy Fraker, AKA the man with a thousand sneakers (runners, athletic shoes).  Insurance company C-Suites are encouraged to subscribe to the matchmaking service, and the organization’s excellent editorial staff keeps the industry appraised of the latest concepts.  A look at the Innovator’s Edge page of ITL website provides the searcher an idea of what the firm can offer:

Three very good sources to search and consider, and there are other InsurTech informational resources, e.g., GR Capital’s recent summary article, Why Next Year Can Be a Turning Point for Global Insurance Innovation, and industry influencers who can make connections from personal experience, including those in this list, or this one, or even this one (companies).


But it still requires the asker to know what innovation problem needs to be solved, what the customers are expecting (maybe it’s no change?), and how efforts are to be focused.  Innovation is not fashion, it’s strategic application of resources and there are good resources at hand.  And in most cases it’s not part of the elephant, but consideration of the whole beast.


Patrick Kelahan is a CX, engineering & insurance professional, working with Insurers, Attorneys & Owners. He also serves the insurance and Fintech world as the ‘Insurance Elephant’.

I have no positions or commercial relationships with the companies or people mentioned. I am not receiving compensation for this post.

Subscribe by email to join the other Fintech leaders who read our research daily to stay ahead of the curve. Check out our advisory services (how we pay for this free original research).



The post Have the horse before the cart- problem first, then innovation solution appeared first on Daily Fintech.