AI

Five UK startups pioneer AI across the Consumer Fintech Spectrum

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AI is no longer a differentiator amongst startups, it has become a default feature that most firms will need to have as one of their core capabilities. UK has never been short of AI success stories, with one of the first being Deepmind, that was acquired by Google in 2014. The Fintech wave was just getting started then, and there have been some good tales in the UK-AI-Consumer Fintech space, across various sub-clusters.

Personal Finance Management: Cleo

Cleo, an AI assistant that helps customers manage personal finance was founded in 2015, and after two years of work was launched commercially this year. The AI assistant taps into consumers’ bank accounts and helps them save money. Since launch, Cleo have close to £400 Million worth of assets under management.

They have integration with Facebook messenger to manage payments, and have an interface that has managed to retain 70% of their users even after 3 months of signing up – thats pretty impressive. VCs have been pouring their money into PFMs in anticipation of PSD2, and Cleo has recently closed a £2 Million round in which Skype’s Niklas Zennstrom participated.

RegTech: Onfido 

London based Onfido, was recently announced by the World Economic Forum as one of the “Technology Pioneers”. They help verify people’s identities digitally. Founded by three entrepreneurs from Oxford University, Onfido uses AI to perform background checks and spot frauds. They validate a user’s identity by comparing biometrics with identity documents. Identities can then be cross-referenced against international credit and watchlist databases

They operate across the globe in about 195 countries with a team of 150 employees, and support close to 1500 businesses. They have recently managed $30 Million in funding from Salesforce ventures and IdInvest Partners.

InsurTech: Tractable

AI within Insurance has seen some really good use cases in the last couple of years. Tractable is a deep learning startup specializing in computer vision to solve specific high impact problems. Their imagery algorithm can be used to quickly perform visual inspection of an accident and provide data digitally to support insurance claims.

In the past where even minor accidents took a few days if not weeks to settle, AI programmes can quickly scan the damage and digitally assess the cost to fix them. The deep learning capability that they have built in collaboration with Cambridge Machine Learning Group, the Visual Geometry Group (Oxford University) and the Neuroscience unit at UCL, can now assess damage to a vehicle more accurately than a human expert. Tractable closed their Series A round of $8 Million last month.

Mortgages: Habito

I wrote about Habito in detail in one of my previous posts. They are an AI capable online Mortgage broker based out of London. Their AI algorithm helps identify the best deal in the market, and also get real time approvals for mortgages. Customers have access to over 60 mortgage lenders through their platform.

Earlier this year, they closed a £5.5 Million funding round which they would be using to build an end to end AI enabled real time mortgage experience.

Credit Scoring: Aire

Aire offers AI enabled alternative credit scoring capability to lenders, where they get insights into borrowers with thin credit files. Aire has an interactive virtual questionnaire that provides insights on top of traditional credit data. Through this new capability, lenders on average have managed to increase credit approvals by upto 14% without increasing risk exposure.

Aire has recently signed partnerships with Zopa and Toyota Financial Services, and closed a funding round of $5 Million last month.

AI for decades has been a fairy tale as it lacked the data volumes and data quality to provide the right insights. However, with Social Media, Open data, and PSD2 providing a firm footing this time, the API era should see some Consumer Fintech AI success stories over the next few years.

Arunkumar Krishnakumar is a Fintech thought leader and an investor. 

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email.

 

Fraud Detection using AI and Mastercard’s acquisition spree

“Progress is made by the improvement of people, not the improvement of machines.”

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As more consumers turn to digital banking for their everyday transactions they will generate huge amounts of data that banks can use to identify trends and highlight suspicious behavior.

As digital transaction volumes increase, and real-time payments become the norm, banking solutions to identify frauds are often inadequate. In most cases these systems will need to determine if a transaction is genuine or not in a fraction of a second. Thanks to the AI wave, as fraudsters get better, machines spotting them get better too.

Cybercrime is estimated to cost the global economy 400 billion dollars. Credit card fraud accounts for a large proportion of this cost. Artificial Intelligence (AI) can provide faster, cheaper and more accurate fraud detection.

Some of the key considerations of a payments infrastructure (using AI) while solving the fraud detection problem are,

  1. Initiate the payments safely
  2. Handle billions of transactions
  3. Identify relationships through graph maps
  4. Social media integration and Sentiment analysis
  5. Behavioural analysis
  6. Adapt quickly as fraudsters evolve their modus operandi

An AI system can use thousands of data points in every transaction and do a fuzzy lookup to billions of other transactions to identify patterns, coincidences and anomalies.

Most payment giants are increasingly turning to AI and Mastercard is no exception. They have been acquiring firms focusing on fraud detection as AI deal activity hit all time highs in Q1 2017. In March 2017 Mastercard announced the acquisition of NuData Security to deliver online and mobile anti-fraud solutions using session and biometric indicators.

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“Our unprecedented use of artificial intelligence on our network is already proving successful. With the acquisition of Brighterion, we will further extend our capabilities to support the consumer experience.”

– Ajay Bhalla, President of Enterprise risk and security for Mastercard

 

Earlier this month, Mastercard announced the acquisition of Brighterion. Brighterion’s portfolio of AI and machine learning technologies provide real-time intelligence from all data sources regardless of type, complexity and volume. Its smart agent technology will be added to Mastercard’s suite of security products already using AI.

“Progress is made by the improvement of people through the improvement of machines.”

Arunkumar Krishnakumar is a Fintech thought leader and an investor. 

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email.

 

Venture Wanted: AI Based Regtech firm to spot Mis-selling

As per Boston Consulting Group, since 2008, Financial services firms have spent about $321 Billion in conduct/mis-selling related issues.  Regtech firms have focused on improving efficiencies of compliance processes within banks. However, mis-selling products and services is a behavioural problem, and a harder nut to crack for Regtech firms. In this post, I have attempted to define some of these behaviours, the outcomes, and how a Regtech app using Artificial intelligence could catch these behaviours by plugging into the right sources of data.

 

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Regtech firms focusing on mis-selling need to define a methodology and the data sources to develop AI and machine learning to proactively address mis-selling. Some of the key data elements needed to identify mis-selling in my opinion are,

  • Product Life cycle
  • Marketing and Sales
  • Customer/Social Media Sentiment
  • Employee compensation
  • Operations and Technology Spend

Product Life Cycle data is critical to understand the process to develop and approve a product. It shows the involvement of senior management in the process, and the governance involved in getting the product out to the market. Data around complexity scores of a product will be useful for compliance teams to understand if there is enough support for both employees and customers to understand the product.

Marketing and Sales data is critical to ensure that right amount of money is spent in marketing the product and the sales commissions are aligned to the firms strategy. Sales data is also critical to analyse a sudden spike in sales of a product. Data can show if it was because of the new sales manager, a tweak to the product or just plain old mis-selling triggered by some year end target.

Customer complaints and social media sentiments are required to understand if a product or a service sold is keeping the customer happy. Also, in the open data world, product usage information could give firms a good view of, if a customer is using them.

Employee compensation often is directly related to aggressive sales done by sales people at banks. Combine this data, with sales of products, usage of products by customers and even complaints from customers, you get the view of how a particular bonus structure drove an employee to sell a product to a consumer when he or she didn’t need it.

An AI algorithm that can have this data can spot regularly occurring trends such as the above, and even alert senior management when they approve a particular product, or agree to a compensation structure. Of course, many firms already use social media sentiment to spot product issues, but that is just one side of the story.

The root of the problem is within Financial services firms where their strategy often doesn’t align with their culture. AI can spot if their product strategy and employee compensation are genuinely aligned with their “Values”. AI could spot mis-selling based on social media sentiments, identify them even before it gets to social media, but a even better state could be to identify patterns that instigate mis-selling behaviour even before they occur.

In proactively managing mis-selling, banks can not only save fines they have paid to regulators but also cut down on the £5 Billion claims market. I believe, a well analysed framework that identifies mis-selling issues and reports on them to the regulators would help all parties involved. It will most definitely save billions for banks. Regtech firms, are you listening?

Arunkumar Krishnakumar is a Fintech thought-leader and an investor. 

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email.

 

No matter who wins UK election today, homeowners get a small break thanks to Neos Insurtech with AI + IOT

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UK Insurtech Neos was in the news last week for raising a £5M Series A round, led by Aviva Ventures with strategic partner Munich Re.

In this post we dig below the news headlines to understand the trends illustrated by what they are doing.

More than a random buzzword generator

At one level, one could view Neos as combining all the hottest buzzwords to unlock VC funding:

  • Insurtech
  • IOT and connected home.
  • AI via Chatbot.

Our belief is that the hype cycle and the reality cycle are disconnected. Yes, all the above are hot, hot, hot. Yes, all will fall into the slough of despond, because that is what happens to all overhyped trends. Yet all three have huge value – if applied properly to solve a real pain point. That is what we now turn our attention to.

A win/win/win proposition

Neos is creating a win/win/win proposition for:

  • Homeowners. Brits love the expression “a stitch in time saves nine” meaning that paying attention to something small now – like a plumbing leak – will prevent an expensive disaster later.

 

  • Service contractors. They will benefit from a flow of work to fix those things – like the plumber coming in to fix a leak.

 

  • Insurance companies. They save on preventable expensive disaster claims and re-establish themselves as being central to their customer’s lives (not just a premium bill to be paid each month).

 

Look at this chatbot conversation to see something that will resonate with almost every homewner:

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That makes IOT and connected home useful in a way that the oft-hyped milk buying fridge does not do. It also shows the use of AI Chatbots to deliver something useful; we believe that AI Chatbots will become as ubiquitous as websites and mobile apps, no longer a source of advantage, simply a must have item.

Now if only somebody could apply that same thinking to something even more precious than a home – the human body. Prevention is the back to the future of healthcare and health insurance and IOT sensors and AI Chatbot will be the key to this market as well.

UK innovation is alive and well

My home country has been down in the dumps since Brexit and goes to the polls today to decide who will lead the future of the country.  Whatever direction the country goes in, innovation will be the key to jobs and prosperity. Neos shows that UK innovation is alive and well.

Join the debate;

On this election day, do you think UK can reclaim tbe fintech capital of the world title?

Bernard Lunn is a Fintech thought-leader and deal-maker. 

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email.

Millennial Mortgages – Can AI deliver a human touch to home lending?

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Every year $25 Trillion in new mortgages are issued. Mortgage is perhaps the biggest investment decision consumers make in their lifetime. However, the mortgage process is inefficient, highly intermediated with many pain points and remained has so without too many disruptions for decades.  Low interest rates and squeezed margins define the current state of the incumbent mortgage lenders, who can hardly think of a better way of doing business. Two startups Habito in the UK and Better in the US are using AI to add efficiencies to different parts of the Mortgage processes.

Habito is a UK based startup that is the first to use Chatbots to address the Mortgage advisory/broker space. Habito’s Digital Mortgage Advisor (DMA) looks up details of a customer’s financial life (e.g. employment, salary and personal life plans) with real-time market mortgage rates to calculate an indicative monthly payment. The DMA explains the impact the customer’s decision will have on the mortgage numbers as a traditional mortgage broker would, but in a fraction of the time (average 10 minutes). Habito is founded by Daniel Hegarty, who was Wonga’s head of Product, and is backed by angels including Transferwise CEO Taavet Hinrikus, Funding Circle’s founder Samir Desai and Yuri Milner.

Better, a startup based out of New York led by Vishal Garg, have managed to address the broader mortgage process, right from advising them on the right mortgage option, using AI ofcourse, to funding the mortgage. They have hired the CTO of Spotify to help them with AI capabilities that would personalise the mortgages to the customer’s financial profile. Since their launch in 2014 they have managed to fund over $500 Million in Loans. Earlier this year Better raised $15 Million from Kleiner Penkins and Goldman Sachs that valued them at $220 Million.

"I'm sorry if some of the 'affordability' questions we're require to ask may seem inappropriate."

A JD Power survey earlier this year, found that 62 per cent of people under 35 who bought a home this year said they would use a mobile app for a mortgage application, if their lender provided it. The home buying process, which is meant to be a happy phase in life, often turns out to be traumatic, filled with uncertainties. We have seen some startup activity in the real estate/proptech space (Purple bricks in the UK), real estate transaction management (on Blockchain), and real estate valuations using IoT data monitoring. However, the major pain points in the mortgage process have been broadly overlooked.

Mortgage Pain

Better and Habito have managed to look at the Mortgage lending process and improved it through clever technology, processes and business model changes. Let’s look at a few example pain points within the traditional mortgage process.

Inefficiency #1: Customers looking to buy a property typically need to factor in a few weeks to get a letter of verification (called Agreement in Principle in the UK). This letter states how much the customer can borrow, at what rates and what the monthly payments would be. So if by chance a customer found a property that he would like to move quick on, he would generally be disadvantaged. Cash only customers always have an advantage in real estate transactions.

The Millenial Way: Better have approached this as a two stage process. The first stage where they get information from the customer, and tell them what products are available for them. This is done by proprietory AI algorithms similar to Spotify’s algorithms to provide personalized music. At the end of this process customers would have a verified pre-approval letter reviewed by an underwriter. Better claim this letter would be available in 24 hours from the time the customer has made the request. The second stage kicks in after the customer has found a property, where the mortgage economics revolves around the property.

Inefficiency #2: The process of choosing the lender involves a lot of variables, however, customers generally go with the lowest overall cost of the mortgage (including various fees, upfront monies and Monthly EMIs) for the best period. They often lack visibility and guidance on what would be better for them, a larger upfront deposit or a larger monthly EMI.

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The Millenial way: Better provide complete transparency in terms of what is good for a particular customer – a higher upfront payment, or higher monthly EMI. This would depend on how long the customer intends to live in the property chosen, which in turn would decide if the break even would occur within that period.

Habito takes an unbiased and a personalised approach to choosing mortgages depending on the customers profile. The AI behind it ensures that customers are at the heart of the mortgage recommendations.

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Inefficiency #3: Mortgages often come with various costs attached to them, which is primarily because there is a person behind the scene trying to sell and close the deal for the lender, and this person needs to get paid. Also, mortgage brokers often sell products that get them better commissions

The Millenial Way: Better mortgage has no hidden costs, and it is completely free of admin charges. Better employs staff who will unblock the mortgage process, and help people through it, rather than sales staff to close deals. Their loan officers never get paid commissions. That’s a much needed change.

Habito charges equivalent fees across all mortgages as AI algorithms don’t have vested interest (yet). This ensures the customer gets the best product suited for his needs, everytime.

Inefficiency #4: Mortgage lenders offer a rate, but very often during or just before the process of the application increase the rates. I know a few friends and colleagues affected by this completely unacceptable approach by Mortgage lenders.

The Millenial Way: Better mortgages offer full transparency throughout the mortgage process. The use of technology to hold all mortgage information centrally, and loan officers who are not incentivised to mis-sell products helps too.

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As a Better customer, you can stay on the mortgage process 24 X 7, all 365 days. If a customer wanted to progress quickly on a property over a weekend (day or night), unlike high street banks, they would be able to get the required approval letters. That truly feels like a Millenial way to Mortgages!!

AI is no human

These are some interesting stories of efficiencies being added to the Mortgage process and business model, through intelligent AI algorithms. However, I firmly believe AI cannot completely replace a human on a Mortgage or an Insurance conversation. If I were going through a home buying process, or an insurance claim for a car accident, I prefer to talk to a human who understands the emotions of the process and treats it with empathy. However, I believe AI can add efficiencies, make the process unbiased, and provide personalised insights through thousands of data points that the human brain can’t cope with. The human in this process will just need to be – humane.

The US mortgage industry is $8.4 Trillion in size, and the top four fintech firms offering mortgages do just about $1 Billion in funding. There is still a long way for these firms to go, but a ground up approach to mortgages, cool technologies, and of course a human touch throughout the process can definitely proivde a happier home buying experience for customers.

Arunkumar Krishnakumar is a Fintech thought-leader and an investor. 

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email.

Fintech solutions to problems of #GAFA people

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Happy New year to all. We are all #GAFA (Google Amazon Facebook Apple) people with different passports and IDs.

Our predictions “2017 Tech, Strategic, and Investment trends in WealthTech” are already out there for testing. In this first post of the year, I want to focus on a complicated topic that concerns all #GAFA people (and please stand out, if you are from another planet).

Personal data monetization is the GAFA business backbone and I foresee that in 2017 we will be hearing more about the ethics of monetizing our data in Fintech too.

I also have a wish list that includes seeing more Fintechs focused on “gating” our data, empowering us with a choice, and sharing subsequently revenues with us.

Three picks for a 2017 watch list

I picked three companies that are worth watching because they recongize our problems as #GAFA people and intend to help us.

A Telco

In September 2016, Spain’s Telefonica announced that in 2017 they will roll out a platform to enable their users to manage the use of their personal data from Google and Facebook and WhatsApp. Users will be able to block or require compensation through the OTT platform.

The Spanish carrier Telefonica is involved in many ways in the 4th industrial revolution. Telefonica owns a startup incubator based in the UK, Wayra, focused on digital business ventures since 2012 and offering the potential to access the 300million Telefónica customers globally.

Telefonica Germany (a subsidiary of the Spanish Telco) is launching O2 Bank, a digital bank, in partnership with Fidor Bank. This will allow German clients in a few minutes to open an O2 bank account (Fidor has the banking license which is valid all over Europe). The identity check will be done via a video on the customer’s smartphone. To transfer money, customers have to enter the mobile phone number of the recipient in the address book and select it for a transaction. The O2 Banking MasterCard can be activated or deactivated directly at any time via the app, and the card details can be presented for online shopping, without having the physical card in hand. A financial planning tool provides an overview of their spending and on request they can be notified in real-time of transactions and events by app push messages sent to their smartphone. Smaller consumer loans will be available directly via the app. O2 banking phone contract holders will “also benefit from a variety of perks and add-ons” when using O2 Banking, such as increased 3G or 4G data allowances (Source).  

In 2017 we all need to watch how the OTT platform that empowers users with the monetization of their personal data, will be combined with the O2 Banking services.

A true digital bank

September 2016 was also when SeccoAura started accepting registrations on their alternative way of monetizing personal data. SeccoAura launched in the fashion industry, allowing customers, to earn Tokens if other users “Like” what they are wearing. If “Likes” on SeccoAura lead to a “Buy”, then the SeccoAura customer who wore the “Liked” item, will earn a referral bonus. The concept could be applied to any retail purchase and wealth can be created through these tokens.

We covered the concepts behind this breakthrough business model in Secco Bank and the Future World of MyDigitalAssets.

A chatbot Fintech

Novastone Media is a UK-based tech firm in the space of information security (similar in a way to the space that Symphony, the Wall Street darling, operates in). Novastone Media’s financial services offerings are targeting private banks, financials advisors, robo-advisors, retail banking and corporate banking.

Solutions include secure messaging platforms that empower conversations, increase engagement, offer security and compliance accountability. Novastone Media prospect clients can choose to use their messaging, chatbot, WhatsApp-like solutions, in a more conventional way. That would result in simply offering finserv end-customers protection from #GAFA using personal data.

In 2017, we will be watching whether any Novastone Media finserv client will choose to monetize their customer data securely collected through these solutions and share revenue with the end users.

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Daily Fintech Advisers provides strategic consulting to organizations with business and investment interests in Fintech & operates the Fintech Genome P2P Knowledge Network. Efi Pylarinou is a Digital Wealth Management thought leader.

2017 Tech, Strategic, and Investment trends in WealthTech

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Watson helped me write this post. I fed him all Daily Fintech posts from last year and all the conversations on the Fintech Genome and gave him access to all my Tweets, Quote Tweets and Replies (he said he couldn’t access my Linkedin interactions; are they gated?).

Paolo Sironi and Susan Visser, would welcome such a use-case of Watson’s capabilities; but for now it is only in my dreams that this happened which I dare to share with you today since it is “Charles Dickens season”. I don’t qualify as poor in the conventional social understanding but I am poor in cognitive tech resources for my Fintech thought leadership.

Last year in December we issued a Warning (just before the traditional year-end predictions)

The truncated message from the myth of Icarus, is that it is dangerous to fly high; but the forgotten message is more important for Wealth management: “It is equally dangerous to fly low”.

It is Not Safe anymore to continue “business as usual”. This is a Warning.

The warning is still very valid and the only clarification I’d like to add is that when we talk about “Wealth Management” don’t just think we are referring to services offered to mid to higher end clientele. This category extends to any level of “wealth creation” that can be derived from small amounts of conventional currency savings, or a low digital credit score. It also encompasses the Capital Markets infrastructure and the regulatory environment which sets the rules of the game of wealth creation at a wholesale level.

End-users continue to push the transformation boundaries. Fintech startups, incumbent institutions in financial services, Financial software vendors, Telcos, and Cloud service providers, are responding to this unstoppable trend. The old adage “If it aint broke, don’t fix it” isn’t anymore valid. The Icarus warning “It is equally dangerous to fly low” encapsulates the reality of our era that is breathing down our neck “Danger to become obsolete”.

For our smartphone readers, I am confining myself to an outline of themes in Wealth Management and Capital Markets for 2017:

The 2017 technology-led trends

  • AI and ML will be the technology that will be “a must have” shifting from “nice to have” and “transactional only”. AL and ML will be leading the movement towards Invisible and Contextual wealth management services. For those that have been investing in AI for many years and have yet to be compensated for being early; 2017 will provide them with great signs of relief. This era will be the AI& ML Walk and Talk starting 2017.
  • The macro environment will continue to be challenging and will result in a genuine shift in wealth creation. For years, it has been Buffet vs. Soros (fundamental vs. macro) and passive vs. active. 2017 will be the year that we will increasingly entrust wealth creation to AI & ML guided processes (mostly actively managing passive financial products (like ETFs) and customization towards goal-base investing).
  • 2017 will be the year that it becomes clear that an API offering will leapfrog a White Label offering. For those that have both and are agile, it will be work out very well.
  • 2017 will be the year that the ISDA agreements in the Swap market give way to Smart contracts.
  • There will be more digital wallets opened in 2017, than any other adaptation of a Fintech service (payment service, digital bank account, robo-advisor etc). Looking at new financial assets for 2017, there are two possibilities to consider. The P2P loans as part of our fixed income allocation and cryptocurrencies as part of either our FX exposure or to include in the commodities allocation or the inflation protection risk buckets. Both have significant regulatory hurdles to face, however, the rate of adaptation of these new assets (not yet recognized as such) will favor significantly cryptocurrencies. P2P loans as an new asset class will not gain significant traction in 2017.

The 2017 strategic trends

  • We will be seeing more of the “Sell-side empowers the Buy-side” shifts mainly out of the US.
  • We will be seeing more cross-selling innovations in wealth creation launched by the incumbents and partnerships of Fitnechs; the US and China will lead.
  • The Transparency movement in wealth management will pick up speed. 2017 will be about Transparency rather than Disintermediation, which became “out of vogue” already in 2016 with more collaboration between startups and incumbents than genuine disruptive moves.
  • 2017 will be the year that IBM, Microsoft, Amazon etc, the Big cloud computing providers will no longer be the Gorillas on the Fintech stage that go unnoticed.
  • 2017 will be the year that Asset managers wake-up and shift from asset-gathering mode and the traditional way of managing the entire investment cycle process. From all parts of the ecosystem they have been by far the laggards. Brokers have been the leaders on the transformation highway.
  • 2017 will also be the year that private bankers and independent Financial advisors are brought further up to speed. The incumbents for which private bankers work for and the affiliated incumbents that the IFAs collaborate with (for custody or execution etc) will empower them.
  • European regulators will continue to lead. PSD2 will influence all other continent regulatory thinking. The FCA will focus more on international collaborations. The Global Innovate Finance summit will become more of a genuine global summit.

The 2017 investment trends

In this part, I share my predictions and also pose a few questions (I don’t have the answers on their timing) because they are important considerations to keep in mind.

  • Alternative wealth creation in 2017 will only refer to what Secco bank is aiming at (i.e. create wealth from digital assets like reputation and monetizing our own data) and cryptocurrency investing.
  • In 2017 I will be writing more about emerging cryptocurrencies investment managers rather than Vanguard, Betterment, and Fidelity and their investment performance. In 2016, we only watched cryptocurrency exchanges and brokers.
  • The cash piles that are sitting around the world wont be reduced significantly in 2017, simply because those chasing them (from Fintechs to incumbents) are in their second phase of innovation and users (like myself) still have to consider three dozen apps to cover all financial needs from Fintechs.
  • The ICO unstoppable trend will continue but will remain predominantly for blockchain related ventures. In 2016, the first steps in shedding light in the very opaque private markets were taken (Title III in the US, ICOs, Stock exchange innovations for private companies to prepare their IPO). This trend will be slow in penetration but will continue with the East joining.
  • Will 2017 be the year for the huge market opportunity of Chinese robo-advisors to create and offer an investment portfolio that can truly match the risk profile and goals of the Asian end-users; rather than being constrained from the very limited local investment pallet?
  • Will 2017 be the year that we all start considering investments in the Goldmans’ or the Alibabas’ because of their strides in Fintech innovation? This I foresee, is two years down the road.

Have a great holiday, for all our readers taking a digital break starting this week.

Daily Fintech Advisers provides strategic consulting to organizations with business and investment interests in Fintech & operates the Fintech Genome P2P Knowledge Network. Efi Pylarinou is a Digital Wealth Management thought leader.