ARTIFICIAL INTELLIGENCE: Evolution of Creative AI and WeChat's Payment Score

One ongoing, false refrain is that machine learning does not generate creative outcomes. Increasingly, this is proven wrong by the technologists and artists playing with the technology. What started several years ago as "neural style transfer" (i.e., transferring Picasso's visual DNA to any photo) has moved on to BigGAN, which is a machine learning algorithm to manufacture images that appear realistic but are made from machine hallucination. Notably, artists are playing not just with the realistic versions of these hallucinations, which you can see below, but with the "latent space" in between. This mathematical term for interpolation is filled with abstract, surprising, and surreal outcomes. Our takeaway from these results is both (1) that machines will be far more precise in understanding and approximating humans than we assume, and (2) that machines will be far better at creativity that we assume.

Fitting a financial product to a ranked "perception" of a human being matters -- especially when it is done at a scale of a billion people. Tencent's WeChat is running a new initiative called "WeChat Pay Score", which is analogous to the Alipay's "Sesame Credit", both of which (we expect) flow to the Chinese government to make up the national social credit score. Sesame Credit looks at 5 dimensions: safety, wealth, social, compliance, and consumption from over 3,000 specific data points collected by the app. The WeChat version is collecting data on how users chat on the messenger, what they read and buy, where they travel, and how they run their life in general. These combined attributes grant access to perks, like waiving bank account minimums.

Listen, in a massive nation where a large swath of the population doesn't have traditional financial data or bank accounts, machine-learning based estimates of credit-worthiness are a life saver. Not every economy comes with a FICO score and legacy credit agencies (though the Equifax breach wasn't particularly kind to incumbents).  But they key question comes back to the two picture sets below. Do the machines see us like those perfectly generated, accurate pictures of people? Or like the surreal goo in abstraction? The former means distributed access to well-suited financial products, while the other is a Black Mirror nightmare.


Source: Medium (GANs), Joel Simon (GANreeder), TechCrunch (WeChat)

ARTIFICIAL INTELLIGENCE: Morgan Stanley, Yext and Chinese AI-first Apps.

A point is not enough. It takes two points to make a trend-line, at least in a two dimensional space. One of the muscles we try to flex often is to connect points in different sectors and themes to see the limits of the possible. Let's contrast the following: (1) Morgan Stanley partnering with Yext for financial advisor business pages, and (2) Andreessen Horowitz' commentary on Chinese consumer artificial intelligence applications on a path to capture the hearts of teenagers everywhere. Disparate, funky, and painfully obvious.

About ten years ago, "hyper-local" became a venture catchphrase. News would go from being general to local, video would go from main-stream to niche, and so on, contextualized by the GPS in our pockets. Yext is a company that won one of the battles for hyper-local content by building the retail knowledge graph that gets printed on Google Maps. Simply, if you see a business listing for a laundromat on your Maps app, likely the app provider is licensing local data from Yext. This data then scales up into pre-made business websites, analytics, and customer funnel conversion. Morgan Stanley inked a partnership with this scale content manager to give their 15,000 financial advisors a digital presence. Controlling and printing out that content at scale, with embedded compliance and into every Google/Apple phone, is hard and smart. And perhaps physical presence is the main value of a human advisor.

Now for Chinese AI. Unlike Americans, with their hand-wringing about privacy, choice, and human agency, Chinese apps don't care. The next generation version of Instagram and Snapchat is called TikTok, and the storied venture firm Andreessen celebrates them for taking away any human choice in what content a user would see. The algorithm is not a search support tool, it is the only and ultimate arbiter of where your attention goes. And it tends to make kids happy (unlike Youtube, which generally makes them into Twitter trolls). 

So let's mesh these things together. A financial services version of TikTok with a Yext overlay would be an app that is tied to the physical world, perhaps through Augmented Reality or just simple Maps, that would decide for you which financial provider to find. It would know that you still want to talk to a person for that emotional connection, and would find one that's closest geographically and a best-fit emotionally -- a two factor optimization problem for an AI. Yext financial advisor reviews, combined with a Morgan Stanley risk/behavioral client questionnaire could do this. Thus the TikTok aspect kicks in, with the human in the loop simply being a form of physical content marketing, gaming the algorithm with a meatspace presence. 


Source: Finextra (Yext), Andreessen Horowitz (AI apps), FactorDaily (App downloads), 

ARTIFICIAL INTELLIGENCE: Apple trying to catch up in conversational interfaces through privacy

Apple acquired Silk Labs, an AI startup with significant tech pedigree, whose tagline is to "embed instant cognition into your next product". We have to respect the science fiction marketing, of course. But we also respect that the machine learning solutions from this company allow machine vision, sound recognition and natural language processing to be done locally on a particular device. That means that a specific device that you use for conversational interface interaction will be locally better at understanding you -- rather than some giant squid-like monster AI hosted on Amazon Web Services. And of all the tech companies, Apple is the most credible in its claim to protect your privacy on the iPhone, with such an acquisition potentially powering other edge-computing / Internet of Things products.

Edge computing is the concept that there are lots of unique distributed smart devices scattered throughout our physical world, each needing to communicate with other humans and devices. Two layers of this are very familiar to us: (1) the phone and (2) the home. Apple has become a laggard in artificial intelligence -- behind Google on the phone, and behind Amazon and Google at home -- over the last several years. Further, when looking at core machine learning research, Facebook and Google lead the way. Google's assistant is the smartest and most adaptable, leveraging the company's expertise in search intent to divine meaning. Amazon's Alexa has a lead in physical presence, and thus customer development, as well as its attachment to voice commerce. Facebook is expert in vision and speech, owning the content channels for both (e.g., Instagram, Messenger). We also see (3) the car as developing warzone for tech company gadgets.

Looking back at financial services, it's hard to find a large financial technology provider -- save for maybe IBM -- that can compete for human attention or precision of conversation with the big tech firms (not to mention the Chinese techs). We do see many interesting symptoms, previously covered in our Augmented Finance analysis, like AllianceBernstein building an AI-based virtual assistant for bond traders, but barely any compete for a relationship with a human being in their regular life. The US is fertile ground for this stuff, because a regulated moat protects financial data from the tech companies. Is there room for a physical hardware financial assistant in your home? How much of your financial life would you delegate to some*thing* that decides how you should live it?


Source: Silk Labs, Bloomberg (Bond Bot), TechCrunch (Google to be nicer if you say please), Autonomous NEXT (Augmented Finance), USA Today (car AI), Voicebot (Install Base)

ARTIFICIAL INTELLIGENCE: From BMO's Chatbot to a full virtual avatar

Let's paint the progression., a chatbot company that integrates banking services into Facebook Messenger and other chat channels, launches Bolt for the Bank of Montreal. The project took 10 months to private label and deploy to BMO's 12 million customers, covering 250 questions at launch. As the app gathers more information about what customers ask, its usefulness grows and it becomes an increasingly relevant channel for customers to ask their financial institution informational questions.


By the end of 2017, 40 million smart speakers were installed worldwide, with 2018 projected to land at a 100 million install base. People are getting more than one instantiated smart assistant -- littering their home with several Echo dots. And, reportedly, Alexa lives in 3,000 others types of smart-home devices -- giving this bot army 45,000 skills, from Spotify to financial conversations. Google and Apple are working to catch up to these numbers, releasing eerily realistic robo-conversationalists like Google Duplex that can answer telemarketing calls and book hair salon appointments. And maybe cancel your financial subscriptions. What's perhaps most important is that an answer to a voice query is 40-80% fulfilled by the "featured snippet" at the top of a search engine's list, according to Martech. That means no more long tail of any kind, full stop.


Eventually, it is no longer enough for our avatars to be disembodied functions powered by a retail product recommendation engine. From virtual worlds and into augmented reality, agents will take on hyper-realistic rendered physical bodies. A recent Intel whitepaper describes how machine learning is now being combined with a modeling of animal and human bodies under a physics simulator to quickly and realistically build CGI for games and movies. Instead of an artist using intuition to draw the perfect frame, machines build skeletons with physical properties, connect bones with digital ligaments, fire up virtual muscles, and package the final version in the species of choice. Machine learning algorithms add realistic, generalized movement to the equation. They can also add speech, appearance and function. And maybe even help the UBS chief economist look a little bit more lifelike!


Source: BMO case study, Fast Company (Amazon AI), The Atlantic (Smart Speakers), Martech Today (40% answers from featured snippet), Intel (Rendering CGI), Financial Review (UBS CIO)

SOCIAL MEDIA: 15,000 Scammer Twitter Botnet Exposed


What's a botnet's favorite activity, when not trying to take down Minecraft servers using thousands of remotely controlled baby monitors? Some good crypto currency scamming on Twitter, of course! We loved a recent paper from Duo Labs that exposed the structure of the botnet running the "ETH Giveaway" scam which tricks people into sending a small amount of currency to an address for "verification" and never sends any money back (not unlike the famous Nigerian price).

The researchers sat on the Twitter API and pulled out data on 88 million public profiles and 576 million tweets. To classify accounts, they used 22 heuristics like posting frequency, content, unique sources, hashtags, account age and others. They trained a machine learning Random Forest model on the data set, using "verified" accounts as controls, and found a 15,000-entity botnet with a three-tiered hierarchical structure. Within this structure, there were (1) individual bots that would post spreading the scam messages, (2) hub accounts that many of the bots followed, and (3) amplification accounts which would like and otherwise engage with these messages. It's a beauty of growth hacking and attention economy manipulation.

Such creatures are inevitable in a digital-first world, no matter how much Twitter tries to fight "dehumanization". Over time, they will only get more sophisticated and invisible, as initiatives like Microsoft's TextWorld teach bots to carry a conversation with humans. Which is why we also have to use machine learning ruthlessly to weed these things out. Such is the responsibility of the attention platforms, like Google, Facebook and Twitter. At the same time, we must not cross the fine line between machine moderation and machine control (looking at you, China). Whoever gets to decide how closely to turn the dials on the algorithm controls the volume of millions of voices across the web.


Source: Futurism (Twitter Bots), Duo Labs (Paper), Slate (Dehumanization on Twitter), Microsoft TextWorld

ARTIFICIAL INTELLIGENCE: UBS Chief Investment Officer now a Video Game AI

File this one under -- "They'll never automate my job, oh wait". We've got three delicious data points for you. The first is Google's voice generation platform called Google Duplex. We're sure you've seen the demos by now (if not see the source below), so we'll merely place this into context. Google's virtual assistant has an experimental new feature that can be your agent by calling restaurants and other small business and booking appointments. Google has the map of all SME data, their hours and phone numbers, can generate and route call, and now makes a robot that sounds eerily human as well. The virtual agent comes with "ehmms", "umms" and lip smacking in its voice generation algorithm, to the point where the clerk really has no idea they are speaking with a machine that's doing busy work. Neural networks are getting really really realistic with speech.

Second, remember Alibaba, the Chinese version of Amazon plus eBay plus all of Facebook and JP Morgan in one, give or take. One of the requirements of the platform is to enable merchants to advertise and sell goods to consumers. But the scale of the selling is beyond human management -- with some days seeing $25 billion in revenue. So the firm has launched an AI written copy generator which can manufacture description of products based on the millions of data points the firm already has on prior commerce. Yep, just casually writing 20,000 lines of proposed description, in styles ranging from "promotional, functional, fun, poetic or heartwarming.” The company claims this tool is now used on average 1,000,000 times a day. 

Last data point, which picks up nicely from several observations we made prior about HSBC using Pepper robots in branches and other physical/digital interactions. UBS is launching something fresh in Switzerland. The first is a cute virtual assistant animated object that will be able to help people do basic account actions in physical branches. It looks to us like a Siri or Cortana attempt, but for finance troubleshooting. The second is an animated 3D rendering of the firm's Chief Investment Officer, to be displayed on a screen while visiting a private banker. This AI CIO will be able to answer more complex questions in real time about markets and investing, and has been developed by IBM and FaceMe. We'll let you connect the dots.


Source: Finextra (UBS), Alizila (Alibaba AI writer), Ars Technica (Google), Autonomous NEXT (Alibaba $25BHSBC)

ARTIFICIAL INTELLIGENCE: HSBC's branch robot and BBVA's facial recognition payments

We are always searching for what's exciting about Fintech, what's at the edge of the wave. It's encouraging to see, for example, JP Morgan launching its digital bank Finn out of St. Louis into the world, Goldman's Marcus lending to lots of subprime risks, and Venmo (i.e., PayPal) putting out a debit card to fight over the neobank consumer. But it's also sort of obvious. This is the innovation of 5 years ago, deployed at scale. Of course large finance firms have no choice but to innovate and copy startups, of course startups will diversify products from payments and banking to investments and insurance. We know the direction of travel, there is only one way to go.

The edge in consumer banking, apart from crypto, is figuring out the role of the human in the context of artificial intelligence. About four years ago, we started seeing chatbot companies like and Kasisto building out natural language interfaces into financial data, and virtual agent companies like Digit and Trim perform account actions like savings and planning. Now, robots are spilling out into the physical world to do the emotional labor of human employees. Take a look at HSBC, parking Softbank's Pepper robots into its physical branches. And while yes, this is a gimmick like Saudi Arabia giving citizenship to the Sophia robot, it is another step towards embodied digital agents.


The robot is currently used only for generic queries, like a chat window on a website but in a physical location. Its cartoonish form moves it out of the uncanny valley, to which both Sophia and something like Soul Machines still succumb. It is not integrated into a user's account or actual financial situation, but we can see a future where such automated interfaces are a bridge to bring in new customers -- both those that are not tech savvy and require the emotional labor, and those that want to geek out over a new user interface. And if you want to understand how something like this could become a window to your financial soul, just check out BBVA's new payment system. A camera placed at the checkout counter reads your face, identifies it using machine learning, and charges your account. All it takes is one camera, and one robot.


Source: Reuters (JP Morgan's Finn), Business Insider (Goldman subprime MarcusSoftbank Pepper), Techcrunch (Venmo debit), Independent (Sophia citizenship), FSTech (BBVA facial recognition payments)

ARTIFICIAL INTELLIGENCE: $1 Trillion in Exposure from Artificial Intelligence on Finance.


We looked at the applications of AI across the front, middle and back offices of banks, investment managers and insurance companies, highlighting a rich ecosystem of sophisticated software. The outcome is Augmented Finance --  an investor’s guide to how AI is pulling apart and breaking down the financial services industry. We estimate the economic impact of AI on financial firms globally, finding nearly 20% of costs potentially reduced through implementations, equivalent to $1 trillion by 2030.

AI is not a panacea nor a single thing. It's math, data and software, searching for the right use case. In this dive, we looked at conversational interfaces, biometrics, workflow and compliance automation, and product manufacturing in lending, investments and insurance. In the front office, the most promising applications focus on integrating financial data and account actions with software agents that can hold conversations with clients, as well as support staff. In the middle office, as regulations become more complex and processes trend towards real-time, artificially intelligent oversight, risk-management and KYC systems can become very valuable. And in product manufacturing, we see AI used to determine credit risk using new types of data (e.g., social media, free text fields), take insurance underwriting risk and assess claims damage using machine vision (e.g., broken windshield), and select investments based on alternative data combined with human judgment.

In the US alone, 2.5 million financial services employees are exposed to AI technologies. There is potential cost savings of $490 billion in front office, $350 billion in middle office, $200 billion in back office, totaling $1 trillion across banking, investment management and insurance. Not surprisingly, many firms talk about AI, but very few actually hold intellectual property in the space. And the best performer -- Bank of America -- is still leagues behind the GAFA. Talk about Black Swan risk!


In mapping out the future of AI in financial services, we saw several routes. One potential path is that AI tech companies like Amazon and Google continue to add skills to their smart home assistants, with Amazon Alexa sporting over 20,000 skills already, outcompeting finance companies and stealing their clients. Another potential path is the example of China, where tech and finance merge (e.g., Tencent, Ant Financial) to build full psychographic profiles of customers across social, commercial, personal and financial data. And last, but increasingly tangible, is the path is towards decentralized autonomous organizations that are built by the crypto community to shift power back to the individual, with skills made from open source component parts. 

ARTIFICIAL INTELLIGENCE: Inequality, Unethical Robots and Unemployment

Source: KKR

Source: KKR

Something's going on when MITKKR and Bain & Company all publish on inequality, automation and ethics breaches resulting from technology. The KKR report highlights that GDP growth is likely to slow in the West resulting from an aging population and a displaced worker force due to declining manufacturing employment. Productivity may go up on average as augmented humans become more efficient the work place, but the long tail of regular people who do not have gainful (i.e., cyborg) employment will increase. Re-skilling has not kept up, and the down-case is that 30% of all activities across 800 occupations can be replaced by software. We have argued before that digitization results in 50% revenue declines in industries that are fully transformed. 

The Bain study reiterates the main points -- automation of the US service sector has the potential to be a catastrophic event in terms of human employment (20%+ down), a conclusion previously reached by McKinsey. The corollary is that this will happen much faster than the transitions out of farming and manufacturing. Therefore, volatility in capital markets will increase, driven by the the middle-class being hollowed via the power laws of software and capital rents, thereby negatively impacting many industries targeting them as consumers. And the headline takeaway is a $5.4 trillion GDP shortfall by 2020. Yikes.

And the robots we make aren't even nice to us! In a study of image recognition artificial intelligence systems, top three commercial software packages had an error rate of 0.8% when determining the gender of a light-skinned man, and a 20-24% error rate when analyzing pictures of dark-skinned women. This bias comes from the underlying data, which does not have enough diversity to correctly teach the software, and the bias in the data comes from bias in the development team and organizational culture. Now imagine that such systems are used by police to identify criminal suspects, the way China is doing today. Would discrimination go up or down, if all people of a certain type are imprecisely profiled by software? Or imagine connecting these data sets to access to financial services? 

So what solutions can we imagine to this dystopian television series? Well, one idea is Universal Basic Income, which is being explored in Finland, Scotland, and the UK. Or maybe Amazon and JP Morgan will save us.

Source: Bain

Source: Bain

Source: Bain

Source: Bain

ARTIFICIAL INTELLIGENCE: Chatbot Zombies in a Consumer Wasteland

Source:  Digit

Source: Digit

Conversational interfaces are one of our most watched platform shifts. With (1) Amazon's sales of Echo devices exceeding expectations and 30,000 Alexa skills built by a growing developer community, (2) messaging app Telegram launching a $1 billion ICO, and (3) Apple about to enter the smart device market, it seems that voice and chat are strong theses about the future. But could we be wrong?

In an eye-opening interview with, Digit founder Ethan Bloch talks about his conclusion that chatbots are overrated. As a reminder, Digit is a mobile-first app that focuses on automated savings using a chat interface, one of the top apps in mobile finance. This company bet heavy on chat as the native interface for Millennials, similar to Lemonade doing the same for insurance. His argument that designing for chat-first actually created more work for the user, and that the messaging experience is like a frustrating DOS command prompt. Bots are just not smart enough to hold a conversation. In response, Digit will adjust its design closer to an app with simple menus, rather than a chatbot that doesn't understand you.

And yet. TD Ameritrade is launching trading functionality through a chat interface on Twitter, using direct messaging. Or see SoftBank building conversational capabilities into its physical robot, Pepper. Bank branches full of Pepper bots are already in the wild (i.e., in Canada). So how should we make sense of the growing number of smart devices that can remember faces, understand emotions, speak with users, and support branching decision trees of financial account actions -- and the conflicting first hand experience of the entrepreneur who tried it and says it doesn't work.

The answer is always with the customer. Just like you can't sprinkle Augmented Reality on a complicated user experience and hope for magic, you can't add chat to a well-designed experience and make it less well-designed. The reason Digit works isn't because it can talk back to you, but because it does the homework of automated savings. Bots should do the financial homework, not just talk about it.

FINTECH: What Will 2018 Fintech & Crypto Look Like?

We are thinking about 2018, and here you will find our best educated guess about the year to come. 

Crypto Eighteen  

If you thought 2017 was loud about crypto, just wait till 2018. Up or down, that doesn't matter -- what will certainly be in play is massive volatility as the crypto economy beats on against traditional finance, regulators and sovereign power. The largest mountains to climb are the development of institutional crypto custody and a vanilla ETF product to absorb the splurging demand, and we think this will happen. In terms of creative destruction, we expect one of the top ten 2017 currencies to collapse 80%, one of the enterprise blockchain consortia to fall apart, and new technical solutions like the Tangle or Hashgraph to challenge our assumption that Bitcoin is the endgame.

Source: Pexels CC0

Source: Pexels CC0


Augmented Commerce 

Let's go out on a limb, with that limb being a 3D rendered object in virtual reality. We think there's a storm brewing in digital goods spilling out into our real world (think Crypo Kitties), and physical goods becoming virtual (think Ikea). Machine vision combined with Whole Foods, Amazon's augmented reality app, and the iPhone X signals to us that a new type of commerce is emerging. Symptoms like the dominance of eSports and the popularity of sponsored SnapChat filters will only increase, and lead to a new purchasing and payments experiences. Financial companies will miss this completely.

Source: Minecraft

Source: Minecraft


Social Selling Meets Propaganda Bots 

How can financial advisors, insurance agents, bank tellers and other human front office staff compete with bots? How can they compete with Kim Kardashian and kitten GIFs for attention? They can't -- at least not without some automated help. We think that 2018 will see a much fuller implementation of Social Selling, i.e., using social networks like LinkedIn to prospect for business, and that this channel will become plugged into roboadvisors, neobanks and insurtech startups. Further, social selling is all about content marketing, by using writing, podcasts and video. To distribute these at scale, we expect the technology behind propaganda bots to find a way into the mainstream economy and become a more acceptable strategy. Call it demand generation.

Source: Pexels CC0  

Source: Pexels CC0 

Here is the long form update on all the themes we are tracking for next year.

#Blockchain for Enterprise

  • A major incumbent custodian will offer an institutional platform for crypto assets and will see inflows of $5 billion in response
  •  Traditional securities, like equities and fixed income, will be traded on a production blockchain platform that also supports crypto instrument trading (not just futures, but the actual thing)
  •  An industry consortia will fall apart and give up its proprietary blockchain format for a public alternative instead; and a non-blockchain technology, like the IOTA tangle or the Hashgraph, will create a new rush of excitement for incumbents 
  •  1,000 back-office financial services staff will be laid off resulting from settlement / reconciliation automation

#Bitcoin & Initial Coin Offerings

  • The SAFT will face a well respected challenger for how to legally paper crypto currency investing
  •  Five exchange traded funds will be in the American market by year end, two of which will purely track single instruments (Bitcoin, Ethereum) and three of which will be indexes of the top coins. Decentralized exchanges fail to be widely adopted due to a lack of global liquidity.
  •  There will be 500 crypto funds managing 20 billion in assets, using strategies from AI to distressed investing, and two of them will be managing over a billion each.
  •  Protocol-level token interest is replaced and outgrown by use-case/app level token interest (e.g., machine economy, fintech startups) in terms of ICO funding and human capital. ICO funding eclipses all Fintech venture capital funding.
  •  One of the top 10 crypto currencies today will collapse over 80% in market cap


  • Things get worse before they get better. Deep Fakes (i.e., videos with superimposed faces of other people and their voices) spread by propaganda bots hit the Internet and cause a media stir, with a particularly painful media scandal affecting a political party
  •  The Asian artificial intelligence giants (Alibaba, Baidu, Tencent) outcompete anything Google or Facebook can do by (1) creating a more powerful neural network cluster, say by a factor of 2x, (2) investing twice as much capital into R&D, and (3) having unprecedented access to government data
  •  Decentralized Autonomous Organizations with certain functions defined by machine judgment start to battle with the traditional economy


  • An ETF with a price point of 0 bps will be created
  •  Mid-sized stand-alone roboadvisors begin to die in droves, as venture investment into the space moves onto greener pastures. Seed stage wealth tech investment is lower than 2015 numbers. 
  • A micro-investing service reaches 10 million users, introduces crypto currencies and becomes solvent based on the crypto-fees
  •  One of the incumbent roboadvisors (Schwab, BlackRock, et al) turns on industrial-strength content farming and social selling, clogging up LinkedIn and Twitter with bot armies of asset allocation advertising

#Neobanks & Digital Lending

  • Neobanks will become cryptobanks, and cryptobanks will become neobanks. Personal Financial Management and budgeting will recede into the background as currency conversion becomes the most important part of a mobile bank app. The category will raise $2 billion in funding.
  •  The two largest digital lenders by underwriting volume will be Amazon and Goldman Sachs, or similar high tech and high finance players. Standalone digital lenders will continue to struggle with scale and capital.
  •  A neobank will get hacked, and will thereafter die

Financial #APIs and Banks-as-a-Service

  • Open banking and PSD2 will hit Europe like a tsunami and force the opening of data ... but nothing drastic will actually happen. Bank-as-a-service infrastructure startups, like ClearBank, may see a few dozed $ million shift onto their platforms, but incumbents will not see major consumer behavior change.
  •  The data availability will contribute to the progress in virtual financial assistants, who can move money between accounts, spot the top interest rate, and tell you about it on chat and voice channels
  •  An enterprise tech player, like Oracle or IBM, will package all the bank APIs together into a single service offering and capture all the usage

#Chatbots & Voice

  • 3D rendered avatars begin to represent traditional brands in virtual worlds and retail locations, and are able to sell financial products
  •  One of the voice assistant, like Alexa, Google Home or HomePod, will have 100,000 skills, but none of them will be good at financial advice just yet
  • A startup focused on being the virtual assistant for financial services will reach 5 million users

#Regtech, #Crowdfunding

  • Centralized government technology becomes a major investment theme, as sovereigns battle decentralized crypto chaos, North Korea hackers, Russian propaganda bots, and Asian AI giants. A marquee check of over $5 billion is spent on a GovTech venture.
  • Identity solutions -- face ID, blockchain KYC/AML -- create the impression that we are safer. But another massive 100 million person hack happens and catalyzes a major innovation in identity theft recovery (rather than prevention).
  • Billionaire crypto whales becomes patrons of a new wave of art and entertainment, especially in VR and eSports


  • Augmented reality payments are seen in the wild, using for example machine vision on fruits and vegetables at Whole Foods to create an experience without checkout
  • International B2B payments begin to see margin collapse as Ripple, or potentially consortia technology, begins to meaningfully eat into SWIFT's network and technology
  • Standalone messenger apps like Kik will fail to replicate the success of WeChat in combining payments with messaging, but one of the GAFA will see an unexpected surge in payments volume within its broader platform and will offer a savings product


  • Claims assessment using machine vision goes mainstream at a top 5 insurance company, and results in 500 layoffs for claims adjusters
  • A B2C insurtech startup like Lemonade reaches 500,000 customers, with a better loss ratio than its legacy competitors
  • Another unprecedented hurricane season catalyzes large insurers to campaign against climate change and for green energy

#AttentionEconomy & Millennials

  • Millennials are supposed to inherit $30 trillion in a wealth transfer over the next 20 years, but crypto will have accelerated that transfer by 5 years
  • The number of hours humans spend on media will have peaked at 12 hours, and will stay flat in 2018
  • Media companies will begin to optimize not for attention but for emotion, and advertisers will expect to be able to buy an emotion associated with their brand and web traffic
  • The quantification of human attention units, being built by projects like Brave or GazeCoin, will be integrated as a core functionality by one of the GAFA

#VirtualReality & #AugmentedReality

  • Virtual Goods (e.g., 3D rendered objects in video games and virtual worlds) continue to grow in value relative to the overall economy, and a massive commerce company for AR/VR objects is born
  • Augmented Reality social networks and games will be the new normal. A new viral phenomenon, bigger than Pokemon Go, will take the world by storm.
  • The number of VR headsets sold, however, will be a disappointment as dedicated VR content struggles


  • There will be 3 times more smart IoT devices in the world than human beings. A new botnet more powerful than anything we've seen yet will be run off several hundred thousand of these devices to attack Internet services.
  • On-demand risk insurance -- either via telematics inside of smart cars or biometrics / chip implants inside of humans -- will become a major source of innovation, similar to on-demand cloud storage or processing power 
  • The machine economy, powered by AI aggregators like Amazon or Hut34 and cryptocurrencies like IOTA, will begin to take shape, with a marquee $100 million venture investment in the space as a signal

SOCIAL MEDIA: Should our AI Overlords be for Sale?

Source: Twitter

Source: Twitter

Source: Facebook

Source: Facebook

Facebook, Twitter and Google testified this past week in from of the American Congress about the activity of propaganda agents on their platforms during the 2016 election cycle. Putting aside anything relating to politics, we want to focus and highlight the incredible takeaways about the reach, power and ethics of what is currently for sale to the highest bidder. Let's just say the tech giants did not have the strongest hand in the conversation and are likely to face regulations on their attention economy monopolies.

Here are the data points. Around 126 million people on Facebookwere exposed to advertising campaigns associated with a propaganda organization, and another 20 million people were exposed on Instagram. On top of that, Facebook may have 270 million fake accounts (i.e., non-human agents) that may help spread misnformation. On Twitter, there were 37,000 accounts generating 1.4 million automated, election-related questionable propaganda Tweets, leading to 288 million impressions. That's a small number in the context of all tweets in the period -- only 1% was election related, and only 0.74% of that was automated propaganda. But given that American elections are nearly always 50-50, and flip based on the marginal voter in a marginal state, those numbers have real impact. 

One major point, highlighted by the always insightful Stratechery, is that the tech giants really have no practical way to scan and make ethical judgments about each and every ad and post.  The reason for this is sheer scale -- Facebook runs 276 million unique ads per quarter, most delivered via automated self-service interfaces. Nor do we want our tech companies to become filters of free speech, akin to the great firewall of China. And yet, sovereigns, corporations and online communities have developed the language and weapons of "memetic warfare". See for example this article on how disinformation spread into the mainstream using swarm networks, botnets, and massive social media distribution. We don't need to freak out, but do need to understand the modern distribution of information and start making informed ethical guidelines and building appropriate defenses. These same information highways are being used in the crypto economy, and will make their way to the financial markets.

ONLINE BANK: Virtual Assistants - Chase, Finn or Facebook?

Source: Chase, Tearsheet

Source: Chase, Tearsheet

Financial virtual assistants. They will know everything about us, give us sage financial advice, and implement everything through financial products available via open APIs. Roboadvisors and microinvesting companies have pointed the way, but these FVAs will be far more powerful and embedded into the core of our daily life. So who will be the winner? First contender is non other than JP Morgan, leader in our Bankosaurus innovation analysis and heavy investor into Fintech. The banking giant launched a neobank app called Finn, which is targeted at Millennials. While the design may be new, the idea has been pretty well established before by companies like Simple (not to mention Mint in 2007) -- a Personal Financial Management tool. The idea could get incumbent traction by default, like Zelle, but doesn't seem particularly thought leading.

Speaking of Finns, the second alternative to win the FVA market is a software like, which is a chat-based AI-powered private label software that banks can deploy to interact with their customers. Not just interact, but check balances, move money, and pay bills. The company  raised $3mm and launched a partnership with ATB financial. One day it may live inside all other chat and voice bots, like Facebook and Alexa, or connected in a decentralized manner through something like Hut 34.

Speaking of Facebook, the tech giant is in a prime position to own the virtual assistant market more generally, and also control the feature set of financial products that access their customers. McKinsey just pointed out that big tech is a bigger danger than Fintech, something we highlighted in the Future Vision analysis. Two examples of Facebook following an Amazon strategy are (1) integrating Visa's tokenized payments services into the platform for digital payments and (2) lending made available to small businesses on the Facebook platform for up to $500,000 in growth capital via digital lender Clearbanc. Finance is a platform enabler in this equation, not a standalone product pushed at strangers. The cash advances are often spent back on Facebook advertising, which provides insights into how well businesses connect with customers, which could further inform underwriting risk. We still need the manufacturer, but they are far less powerful.

CRYPTO: Tokenizing the AI Messenger

Source:  Activate Media

Let's connect two data points and make a trend. First, Canada-based chat platform Kik is working on a $125 million token sale, which will embed a cryptocurrency into the messaging network itself. No need for Paypal, ApplePay or other shenanigans. The network itself becomes the payments mechanism by giving literal value back to its participants. Can this happen to WhatsApp, Facebook Messenger, Telegram and create a Western version of WeChat? What is payments but a derivative of communication?

Second data point. Tech giants are partnering -- in retail, it's Amazon vs Google and Walmart. And in voice interfaces and AI, Amazon Alexa is now working with Microsoft Cortana to take on Google and Apple. In a spectacular Quora post, Brian Roemelle walks through how the audience resulting from this partnership is immediately 200 million (if not bigger). So what we have is a multi-purpose artificially intelligent agent that mass-personalizes products and software across ecosystems. This thing that will live in our smart speakers, autonomous cars, VR headsets and neural implants (thanks, Elon!).

So let's connect the data points. A messenger with 300 million users is creating financial liquidity for its community through tokens. The attention economy is evolving its own economic power, outside of financial services. But remember, messaging and conversation will be not only between (1) humans, but between (2) humans and machines, and (3) machines and machines. There are only a few billion people, and far more software and hardware agents, which thanks to Amazon/Google can now talk to us directly. Voice-first is not just a front-end upgrade, it's an economic vector. It is human intent with machine money attached. 

ARTIFICIAL INTELLIGENCE: Amazon Lex for Wealth Management & Banking

Source: Amazon Lex

Source: Amazon Lex

We believe that bank-as-a-platform is inevitable for any meaningful financial institutions, and that it is more likely to be a narrow, utility-like platform than the dominant iPhone app store. A strong enterprise tech platform like Amazon is the main vector that would compress financial institutions from large manufacturers and distributors to regulator-facing APIs.

In wealth management, roboadvisor Betterment uses 20 different applications on AWS. In this excellent article, Financial Planning discusses how Amazon's conversational interfaces can become prevalent across the industry. What starts as a conversation about payments can turn into a conversation about financial products, planning, investing, trading and retirement. And talking, or even chatting, is far more natural than thumbing through buttons on the glass screen of your phone. But perhaps advisors can use the technology to their advantage, or build skills and applications to live in the Amazon ecosystem.

In banking, take a look at ING, and its vision of voice-activated digital assistants. The combination of open banking mandated by European regulation PSD2 (i.e., all banks have open APIs) and natural language processing means that data is free. Building the first voice-based financial data aggregator can create a lead generation engine for deposits and lending. Or it can commoditize all financial product manufacturing.

ARTIFICIAL INTELLIGENCE: Alexa's 15,000 Useless Skills

Source: Techcrunch, eMarketer

Source: Techcrunch, eMarketer

So while we wait for the Apple HomePod to enter the market in December 2017 at a premium price, Amazon and its Echo line of devices have been slowly amassing voice-activated skills. In fact, Alexa now boasts over 15,000 such skills built by developers across a variety of functionalities. Do they work well? No, not really. People are still mostly treating the device as a timer or fancy radio player. But unlike the Apple approach of proprietary Siri software, Amazon is becoming a platform, running not just one music app, but everything from Spotify, to Pandora, to Amazon Prime. And we already know what happens when Amazon builds open platforms (Amazon wins).

This matters for personal finance. We've already seen Amazon come out of the blue in lending within the SME category, launching a fundamentally better mousetrap than anything the banks can do for that market segment. Similarly, the conversational interface platform, driven by an AI virtual assistant with API connections into thousands of other micro-skills supporting niche functionality is likely to have massive network effects. Now is an opportunity to build meaningful services on a nascent platform.

We are working on mapping the chatbot landscape for financial services across different industry verticals. As we do this, two things become clear. First, chatbots have already been deployed across the finance industry, but they are currently trapped inside text interfaces like Facebook Messenger and Slack. Can you imagine wearing your VR headset and texting? Us neither. Second, chatbots should not be just a command-line interface or a navigation menu for a website. People can see through that approach. Therefore emotional / empathetic design is the killer feature. Think about emojis, animations, movie clips, animations, and human language. In the end, all people want is stories.

SOCIAL MEDIA: Tinder FemBots Swing Election

Source: The Times

Source: The Times

 One theme that we have been tracking since the 2016 American election is the use of software agents -- from chatbots to botnets across Facebook and Twitter -- in forming mass audience opinion and influencing real-world political events and forming political power. Put simply, software makes Kings. And in the case of the British elections, it crowned Queens.

130 women volunteers surrendered their Tinder (mobile dating app) profiles to chatbot software built by female developers and journalists. The profiles swiped right in geographic locations where men were most likely to be undecided or demoralized voters, and initiated flirty conversations with the intent to persuade them to vote Labor. At some point, the chatbot transitioned the conversation to a human, doing the busy work of finding targets and giving over the emotional labor back to people. We know the results.

Whether or not the Tinderbots really pushed the election over the edge, this is an incredible development for the Attention Economy. Forget cyber-hacking of your personal data. How about social hacking of the populace en masse? We are particularly worried about this as it relates to the ICO market / bubble. While there are certainly many worthwhile technical projects being developed, much of the activity is happening in an unregulated environment. Incorrect prices can result from massive cryptocurrency supply (Bitcoin whales parking gains) and the technical expertise of the cryptocurrency community. It takes very little to build software that tilts human opinion on social networks. 

SOCIAL MEDIA: Facebook Messenger as Enterprise Chatbot Platform

Source: Facebook, Techcrunch

Source: Facebook, Techcrunch

Facebook's F8 conference hit the news last week, and one of the key developments for Fintech is the massive rise of text agents and their adoption. Some numbers first -- Messenger has 1.2 billion users, and those users send 2 billion messages a month. This is where a large portion of the world's conversation is happening, literally. The remainder is on WhatsApp (also owned by Facebook), WeChat, QQ and others. On Messenger, there are over 100,000 unique bots, built by over 100,000 developers. Things are not looking good for human customer service agents.

This new blue ocean platform is perfect for enterprise software, not just games and media sharing. It is an informal communication medium where smartly designed bots yield better conversation rates, higher customer satisfaction and productivity than other channels. New additions to the platform include a discovery section in the app (think iOS Appstore, owned by Facebook), modular functionality that can be inserted into group chats, and the virtual assistant "M" which may become an overarching voice that incorporates narrow functionalities into a more general artificial intelligence.

The fintech bots are plenty. From incumbents, see Wells Fargo, Mastercard, Western Union, MoneyGram, American Express, not to mention the native payments capability of Facebook. On the startup side, there are personal finance management tools like Trim or . In aggregate, these bots open accounts, answer questions, transfer funds across 200 countries, analyze your spending, and save/invest money. How prepared is the financial industry?

SOCIAL MEDIA: Army of Chatbots Hack Collective Thought

Source: Data for Democracy, Jonathan Morgan

Source: Data for Democracy, Jonathan Morgan

 Regardless of your politics, this is an incredibly important article to read and understand. What today influences the public arena has the potential, and is likely already being used, to influence the financial markets and trading. Here are some numbers leading up to the election: (1) a network of over 1,000 bots posted identical political messages in conservative Twitter communities, (2) a network of 30,000 bots were posting identical messages on Trump's Facebook page. Additionally, "sockpuppet" accounts (where a person adopts a false persona to drive a particular message) were used to create an illusion of consensus around news or messaging. The result is pockets of online communities which form quickly rising information bubbles.

As finance professionals, we don't often have to think about Botnets and automated propaganda. Don't the SEC, FCA and other regulators make sure that financial promotions are clean and there is no market manipulation? Yet, in an age where social influence is all online views and clicks, and tech strategies evolve daily, we must understand how opinions are manufactured. One such area of concern is Initial Coin Offerings, which have been an alternative funding source for blockchain companies that want to side-step regulated crowd-funding or venture capital. Next time you listen to the social chatter about companies, consider carefully the source.

ARTIFICIAL INTELLIGENCE: Uncanny Valley Realistic Chatbots

Source: MIT Tech Review, Soul Machines

Source: MIT Tech Review, Soul Machines

Why should we analyze virtual reality, the attention economy and preferences of the Millennials generations (including their addiction to video games) when thinking about financial services? Here is an example. A startup called Soul Machines has combined the functionality of chatbots, which includes natural language processing and machine vision, with hyper-realistic renderings of human faces. These virtual assistants can model facial expressions and read the facial expressions of their counterparties through machine learning image recognition techniques. We have covered before that speech generation (not using recorded voices but manufacturing human speech sounds) is around the corner as well.

To see the video in action click through the image below or on this link. Does it creep you out to have the bank teller, investment advisor, insurance agent or lawyer replaced by a 3D-rendered head connected to automated knowledge? If yes, welcome to the uncanny valley, a term for near life-like simulations that don't quite hit the mark. But note two things. First, Millennials have spent the last 20 years training how to interact with such characters in video games, such as Mass Effect. And second, virtual reality and augmented reality are scanning physical reality into 3D environments usingphotogrammetry, and we will soon forget the difference.