Real Estate Tech brokerage Compass earns its $6.4 billion valuation from smart arbitrage; plus 14 short takes on top developments

Hi Fintech futurists --

In the long take this week, I examine how $6.4 billion real estate brokerage Compass stacks up against the digital wealth and lending companies with a similar go-to-market strategy, and provide some ideas as to why it is successful. Compelling questions also emerge when looking on how technologies like AR/VR are commoditizing the property brokerage experience -- what is the equivalent in Fintech?

The latest short takes on the Fintech bundles, Crypto and Blockchain, Artificial Intelligence, and Augmented and Virtual Reality are below. Thanks for reading and let me know your thoughts by email or in the comments!


Long Take

Imagine an industry. In this industry, professional sales people with a technical background try to sell some intangible asset to other people. The asset has a lot of regulation and legalese associated with it -- mountains of paper, contracts, and arcane instruments. Everyone wears a suit, and things feel *important*. Transactions don't happen very frequently, but when they do, it is a life event, and a difficult moment for the customer making a purchase.

Now imagine a technology start-up coming along and saying that they will use software to make this process more efficient. Accounts will be opened online or on mobile phones, using automated KYC/AML. Money will be moved seamlessly, reducing the time of the traditional approach from several weeks down to a few minutes. CRM will be deployed across the sales force, to function like a workflow automation tool that integrates into all of the legal and financial features that make this industry complex. Pricing will go down, customer numbers will go up, and the technology will be deployed directly to the consumer, and then to other traditional incumbents who will rent the software.

I could, of course, be talking about any number of financial services industries. When you look at wealth management, this is the Personal Capital or AdvisorEngine story -- taking financial advisors and plugging them into modern technology. A few billion dollars of wealth tech investment per year over the last 5 years have funded a whole set of competitors that know how to make a human/software advisor hybrid -- whether at a startup or at Bank of America Merrill. Goldman Sachs just paid a hefty $750 million for one of these things as well!

Or maybe you want to focus on digital lending, noting how OnDeck and Kabbage did the same thing for business loans. Instead of going to a human underwriter that processes paperwork manually before your firm can get financing, instead fire up a clean web interface supported by human staff (or a chatbot). If you are a global bank, you can free-ride on the $3 billion of annual venture capital in digital lending by renting a private label version of the startup software.

But in this particular case, I am talking about someone else. I am talking about Compass, a residential real estate startup that built out a platform for brokers -- proprietary and external -- and has recently raised $370 million at a $6.4 billion valuation. I found the language and positioning sort of eery, in how similar it was to the story in industries I closely follow. It even bought a CRM earlier this year, not unlike AdvisorEngine buying Junxure, or Salesforce getting into financial verticals. What I did find unusual, was the absolutely massive valuation.

What makes this type of company any more valuable than a similarly positioned company in Wealthtech or Digital Lending or Insurance or Trading? A couple of things come to mind. First, those other industries do have their vertical unicorns, like SoFi or Robinhood. But such B2C players are not really about an augmented advisor helping individuals make large individual purchases -- rather they are about democratizing access to previously unaffordable financial product. This makes Compass a less transformative company by comparison, since it *merely* improves the user experience. That should make it less valuable.

Second, Compass did heavy financial recruiting of brokers from top competitors -- essentially buying revenue or what in financial-advisor-land you would call a "book of business". If I give a large sign-on bonus to a Douglas Elliman broker, I will inevitably bring over some portion of their revenue generation. This is a short term trade, where you are betting that your platform will have superior operating performance based on the technology-enabled model. Traditionally, you would never get a venture capital type multiple on buying real estate commission revenue; you would similarly never pay more than 1-3x revenue for a financial advisory business. But in the case of venture capital, which funds Fintech companies at 20-100x revenue these days (thanks Softbank!), there is a clear M&A arbitrage. Get cheap financing, acquire top producers.

Third, the market timing in the case of Compass was very positive. You can see in the charts above that the core financial verticals have seen Fintech venture inflows over the last decade, until equilibriating and leveling off at GDP percentages between 2014 and 2016. Real estate technology investment has lagged behind -- until the pop to $5 billion per year in each of the last two years. This means that investors were looking to put money into this thesis, with many simply trying to find "the Lemonade" or "the Revolut" of Real Rstate. Enter Compass, and its valuation. Same can be said of course for WeWork -- the best timed $700 million market arbitrage of them all. A less critical venture investor makes for a better entrepreneurial experience. That's not to say these guys don't deserve the success -- it is certainly a great story powered by beautifully designed software. But at the same time, it is important to understand the underlying drivers for differing performance in similar fact patterns.

Another thing, however, that I want to show you is a version of the same use-case (house hunting) solved in China by a WeChat mini-program backed by Tencent, shared in video form by Matt Brennan here. A user can search a map on their device, find a listing, click into a 3D rendering of the apartment, and walk around looking at lighting and detail in a realistic environment. That's more powerful than a broker CRM.

In the West, Matterport is the key company working on this vector -- digitizing physical spaces and mapping them into an AR/VR rendering that can then be inserted into mobile and web applications. Now Matterport is "only" valued at around $325 million, most recently raising $48 million. If I were Compass, I would acquire this company yesterday to lock in real technology innovation into my model. Revenue multiple arbitrage doesn't hold a candle to taking the very asset you are working on transacting, and digitizing it such that the need for human-hand holding trends to zero.

I wonder how the same can be done for non-property financial product. How do you tangibly communicate investing, or banking, or lending using frontier technology? End of the day, those products are nothing more than some abstracted rates of return from one entity to another. Charts can be rendered in more dynamic or simple ways, and stories can be told in more emotional media. But until someone really figures out a way to convey those products as impactfully as these 3D renderings of homes and the associated feeling of presence, such financial services will continue to be intermediated by expensive people.

The closest thing today, I would wager, is the abstraction of financial products into features within other types of commerce. As finance moves to point of sale, its detail becomes less relevant (and likely more commoditized by API-based banking-as-a-service competition). We make decisions not on the best loan or the best ETF, but on the product we are actually buying. Thus Greensky wins by financing home improvements in the process of home improvement contractors physically evaluating your home. Or, Affirm wins by being tied to your eCommerce shopping experience at checkout. Doubtless, there is still great distance to cover.


Short Takes

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Losing our Sacred Data - how to make sense of Capital One, Equifax, and Facebook; plus 13 short takes on top developments

Hi Fintech futurists --

In the long take this week, I explore Capital One's massive data breach, and the penalties they are likely to face. We can compare the potential outcome to those faced by Equifax ($600+ million) and Facebook ($5 billion). A compelling framework emerges out of this analytical journey about which data we hold sacred, and how our behavioral biases may betray us.

The latest short takes on the Fintech bundles, Crypto and Blockchain, Artificial Intelligence, and Augmented and Virtual Reality are below. Thanks for reading and let me know your thoughts by email or in the comments!


Long Take

Here is our factbase for this week. Capital One recently suffered a data breach resulting from poor security practices that exposed 100 million credit card applications and accounts. They expect the breach to cost the company $150 million. Two years back, Equifax lost 140 million identities, again from poor security practices. At the time, I said that according to GDPR this should cost them $150 million. They have since settled for about $600 million -- though some of that seems to be in-kind services coverage like free credit monitoring (lol!). Separately, Facebook has settled for a $5 billion fine associated with the Cambridge Analytica privacy "breach".

As a percentage of revenue, $5 billion out of $60 billion (~10% for Facebook) or $600 billion out of $3.5 billion (~20% for Equifax) seems to be of a similar magnitude. Capital One's estimate for $150 million on $28 billion seems off, to say the least. But let's get some macro data out there, before thinking more deeply about the issue. Identity and data, and in particular financial identity and data, are valuable. On average, a stolen digital human is about $200 on the black market, and the per-capita cost of a data breach to the company is roughly the same. Cyber insurance, which is in the aggregate supposed to counteract these damages for companies, is at least a couple of billion in annual premia -- amounting to probably a few dozen billion in coverage.

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So here's the issue I have. There is a lazy thing to say, and I said it in 2017 about Equifax. It goes like this. Look at all those hypocrites in the large financial companies! They point to Fintechs and Crypto, the innovative parts of our economy, and accuse it of poor practices. They insist on inequitable, overly heavy-handed regulation and security expectations that stifle out young companies. And yet, only 2% of all Bitcoin transactions have anything to do with illicit activity -- no different that in the traditional economy, which sees 2-5% of GDP pass through money laundering. And yet, they keep losing our most important data by the millions, never having to face repercussions for their sins.

That's a fun, accurate, finger-wagging argument to make. But it doesn't do any work. It is useless. Instead, let's take a more systemic approach. We can acknowledge that crime, theft, and mutual destruction is a human attribute, not some externality of a technology. Yes, we would like to minimize the crime. But it is endemic to all human systems, it is a part of us. Therefore, we have to accept that some percentage of our data, money, privacy, and other valuables will be stolen, misappropriated, or destroyed. We will fight that -- but some amount, let's say 2%, will slip through. This issue is about the actors in the system itself, and today the problem is merely becoming more transparent.

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The second step is to think about our rationality versus our feelings (if you want to read 1,000 pages on this topic as prep, I recommed Yudkowsky). From an economic perspective, the following two scenarios are identical. In scenario A, you lose 2% of your data with 100% certainty. Imagine this as losing a non-core credit card once per year, and then having to cancel it with the bank. Inconvenient, but nothing to worry about. In scenario B, you lose 100% of your data with 2% certainty. The expected (dis)utility of this outcome is exactly the same, but I would guess that most of us would pay way more to avoid such a problem, because we are risk-averse animals. Any chance that you will lose everything you have is terrifying -- and much harder to remedy.

Another dimension I want you to think about is "sacredness". Something is sacred, in the sense I am using the word, when the cultural significance attached to it precludes an economic discussion. For example, human lives are sacred. No amount of insurance will make up for an outcome where a person is killed! And yet, governments make these calculations all the time when evaluating policies on topics like speeding, smoking, and water safety. Further, some things are sacred to some people, but not to others. What is a political cartoon to one person, is a declaration of religious war to another. To bring us back down to Fintech and cyber security, my main point is that *privacy* and *personal data* could be sacred in one context (e.g., an American high income person that studient constitional law at Yale), and not as sacred in another (e.g. a farmer in China who gets loans from the government).

Sacredness is a multiplier on how important something is to the person within their context. For many of us, we are fine losing social media photos, Twitter puns, or even our passwords. But financial information can be much more personal and embarassing -- take for example the fact that we still do not have Donald Trump's tax returns. I would bet that he finds those to be a sacred screed. Similarly, Google has a lot of sacred data. Imagine exposing to the world all of your search history, or having that search history be the basis for eligibility to get a bank account. Ok. So with these tools, let's put together a framework.

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What does this tell us? First, the Capital One and Equifax bits are negatively surprising, but in the way that losing a gambling bet is negatively surprising. We have always known that there is some low chance of loss, and we have known that the data at stake is our financial data. We took the gamble of a 2% loss on a 100% cost, and when that loss actualized, we felt badly. The outrage we see today is a response to experiencing the cost. Perhaps we thought the chance of loss was lower, or we are apalled at the technical incompetence of the humans involved in those cases. But there's nothing deeper there, in my view.

The correct outcome is to improve the quality control of the system. This can be done perhaps by forcing cloud providers like Amazon to have more safety limitations out of the box, or to move more of our information onto blockchain-based systems where individuals control their own data. At least in that case, the losses will be internalized to each individual at the time of their personal failure (lost my keys!), rather than correlated and externalized to the entire group whose data a centralized party (e.g., Capital One) is managing. But we cannot fix human society structurally just by asking people to download wallets. We cannot change our lazy, careless nature.

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The second thing the framework tells us is about the scenario of 100% loss with 2% cost. We used to believe that Facebook and Google had our information, but that it wasn't particularly valuable, personal, or sacred. This is of course entirely wrong. We have learned the hard way that the Tech giants have everything; and that the more sacred it is, the more they want it. Second, we used to believe that what they have is relative secure and inaccessible to others. This too is incorrect. By opening up the honeypot to Cambridge Analytica, Facebook made it a core business practice to bleed out what we want to protect.

I would say what we have lost is the right and the ability to think our own thoughts. To make up our own opinion, crushed as we are in the maw of algorithmic advertising and propaganda.

This second thing is far worse than a hack, and should be punished far more punitively. Systemic design that takes the probability of loss and turn it into a business model is a flawed system -- and one we should abhor deeply. I don't have to persuade people to be outraged at Facebook; they already are for far less clearly articulated reasons. But this thought process has helped me identify why invisible microthefts are a problem, and how to fix them. We see Facebook adressing the issue by both (1) lowering the chance of loss by saying that the open developer program that powered up Cambridge Analytica is now closed (or better monitored), and (2) lowering the value of the loss by re-focusing on privacy and submitting itself to increasing regulation. And yet here they are, trying to start a new global currency!

The good news is that people are finally waking up to the fact that they have made a bad bargain. We recognize that the faces of our children are used to power machine vision artificial intelligence algorithms, that our location and shopping data can be used to discriminate access to financial services product, and that our searches and conversations are neither private nor fully protected. With this recognition comes a sense of cost -- how much are we willing to give up, now that we see that things are not free. Listen, all technology and human processes are fallible, and so we should not aim for perfection. We should aim at the intersection of marginal cost and marginal benefit around security, privacy, liberty, and convenience. We should assume the risk and sail into the Great Beyond.

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Featured

  • Check out my interview on the CIOs & Bowties podcast. Here are Part 1 and Part 2. We talk about wealth management, artificial intelligence, YouTube influencers, Asian Fintech, and all sorts of good stuff.

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Short Takes

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Big Fintech: LSE's $27B for Refinitiv, Softbank's second $108B vision, Ping An's $160B Revenue; plus 12 short takes on top developments

Hi Fintech futurists --

In the long take this week, I start with the $27 billion contemplated acquisition of Refinitiv by the London Stock Exchange, track the $20 billion of projected Fintech venture capital investment in 2019, highlight the second $108 billion SoftBank fund, and land on the Fintech story in China. Did you know that Ping An was running at over $150 billion in revenue?

The latest short takes on the Fintech bundles, Crypto and Blockchain, Artificial Intelligence, and Augmented and Virtual Reality are below. Thanks for reading and let me know your thoughts by email or in the comments!


Long Take

Fintech is expensive. Fintech is everywhere. If you are a thinking about starting a financial services company, and it does not have technology at its core -- don't. You will lose to someone similarly positioned building a more augmented business. Fintech is the global competition for regulation, talent, and macroeconomic supremacy. Fintech is the trade war between the US and China. Fintech is Facebook and Amazon. Fintech is the next bubble to burst. Fintech has burst already.

Rhetorical flourish aside, I think we can paint a good picture of the macro environment in the industry, and see where both investments and returns are flowing. The stellar FT Partners quarterly research report is out, and you can see continued health in the sector. In terms of North America, we can expect over $20 billion in venture financing this year again -- much of it flowing to data aggregators, banking-as-a-service entrants, and insurtech (e.g., Plaid, Lemonade). In Europe, over $10 billion could be invested this year, doubling that of 2018 and driven by the sector's leadership in integrated digital banking (e.g., Revolut, N26). In Asia, however, the numbers are slowing down. That's partly due to the Ant Financial outlier last year, partly due to the collapse of the P2P digital lending industry, and partly (I think) due to the rise of crypto assets (e.g., excluding $1 billion for Tether).

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Let's cut more specifically on the difference in how value is accrued and realized. Perhaps I am relying too much on anecdotal evidence, so let me know if you see data that suggests otherwise. But, we can still plod along with this thought experiment. One of the big news items last week was that the London Stock Exchange, valued at $20 billion, is in talks to acquire Refinitiv, valued at $27 billion. You may remember the massive payments and core banking consolidations earlier in the year, and this is a version of that type of consolidation in the capital markets. For a while now, the story has been that the most valuable thing about exchanges isn't the trading venue, but the data generated from the trading venue. Such an acquisition is a massive directional bet towards data and market infrastructure.

For fun, some history. Refinitiv was partially spun out of Thomson Reuters (which now owns a minority stake) at a $20 billion valuation into the hands of Blackstone in 2018. In a bit over a year, it has added $7 billion of value. The entity is essentially 130 fintech companies assembled together into a 40,000 client powerhouse, generating $6 billion of revenue. That extra $7 billion of value that LSE is willing to pay won't be fully covered by $350 million of cost-savings over 5 years, but you know, Fintech is hot. I wouldn't mind being a private-equity backed CEO in a case like this. That said, it's not a fresh tech stack. If anything, it is the opposite of a fresh tech stack -- rather, it is the financial optimization of a massive financial industry data infrastructure founded in 1850.

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And that managerial optimization of legacy finance is something that the United States is really good at doing. Gigantic, global, US-headquartered businesses are consolidating into immobile utilities that define what is possible for entrepreneurs. How can you not be excited about Crypto, when your only alternative is to buy a Bloomberg (or Refinitiv) terminal? Why would you want to buy $7 billion of accounting goodwill on solidifying this infrastructure, when $7 billion of venture activity can get you a super highway to the future? Most of the banks are getting it now -- whether you are Deutsche Bank or JP Morgan or BBVA, the story is how you will spend $10 billion on digital transformation and fire all your employees.

Venture investors invest in ventures, and traditional investors invest in tradition. This gets me to other side of the barbell -- SoftBank and China. SoftBank is launching a $108 billionfollow up to its first Vision Fund, which unwitting public investors could get to own any day now. While it is easy to snipe at SoftBank for sky-high price-insensitive valuations, it is wrong to dismiss the strategy without appreciating the results. SoftBank famously played the key role behind Alibaba (cashing out $11 billion), which launched Ant Financial, arguably the most important fintech company in the world. Without Ant, we wouldn't have Facebook building Libra, or the Chinese payments revolution. Without SoftBank, we also wouldn't have many of today's American and European fintech unicorns, from SoFi, to Robinhood, to Revolut. When you are price insensitive, a $100 million option bet on a owning an entire market of future consumers is a fair gamble.

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What is SoftBank? It is, at its core, an Internet company. It wants to spends its winnings to do to Finance -- companies like Refinitiv -- what it did to Media. Who is investing in their second Vision fund? Microsoft, Apple, and Foxconn. Facebook, Google, and Amazon are building Fintech solutions directly, so no need for side-car bets with idle cash. How much of that cash is there? Between the top US tech companies, there is at least $500 billion of a balance sheet. You still think Deutsche's Bank $10 billion digital transformation makes any long term difference to anything but the CEO's golden parachute?

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The last puzzle piece in our journey this week is China, with Alibaba's success largely subsidizing SoftBank's swashbuckling. I want to point you to a couple of high quality pieces. Fortune's China’s Biggest Private Sector Company Is Betting Its Future on Datawalks through how Ping An generates about $160 billion of revenue (haha, $6 billion Refinitiv) and uses AI to settle 7 million auto accident claims per year. The company collects data on hundreds of millions of customers, and re-uses that data across healthcare, insurance, and wealth management. Its products are distributed by over 1 million indepedent sales agents.

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Or check out this a great write-up on Tencent's WeBank (by Norbert Gehrke), which is another top Chinese fintech that delivers products across lending, investing, banking, and wealth management. While we in the West are just starting to think about our Fintech bundles, these apps started with attention and spun out one finance feature after the other. What really stuck with me, however, is that WeBank has a valuation of about $30 billion after receiving its license in 2014. Deutsche Bank, that giant of suits and accountants, boasts a market capitalization of less than $15 billion. The screenshot below is twice as valuable.

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The best macro mental model I found for why Fintech activity in the East is both more innovative and more valuable is from Gapminder. The vertical axis in the chart below is life expectancy, and the horisontal one is a logarithmic plot of income. Each bubble is a country, color coded for its continent and sized for its population. That big green one on the right is the United States, surrounded by smaller ones like Singapore and Sweden. The two big Red bubbles are China and India, with China having higher GDP per capita.

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I am showing you two time periods about 70 years apart, but seeing the animation in real time is quite persuasive. The simple answer is that all countries are floating up and to the right, improving both their life expectancy and GDP per capita. The two are deeply interlinked. While the US has a bit more room to squeeze out, it is pretty much on top of the world. Nobody is standing still. What is more impressive: going from $16k to $60k per capita (3.5x US), or from $1k to $16k (16x China) in the same time period? And if you look forward 70 years, what possible outcomes do you see? Covering the ground of bringing a billion people towards AI-enabled financial services is a much bigger opportunity than optimizing how institutional traders download their PDFs.

That said, there is a high amount of irrational exuberance around this thesis, and it is easy to lose your shirt. I recently had an invaluable lunch with a reader of this newsletter, who is a venture investor in China, and she suggested that many private Fintechs are hitting the wall. It is difficult in the mainland to go public or achieve a free-market exit, other than flipping the company to Baidu, Alibaba or Tencent. This limits the upside structurally. Separately, opportunism and scams have been rampant in both P2P lending and crypto businesses, resulting in increasing central government control and legal action. Thousands of companies have been shuttered, users have lost access to their invested capital, and unscrupulous entrepreneurs are being tracked on public offender maps.

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Chinese tech company valuations are more expensive than ever. User attentions are over-saturated with commerce, lending, and other financial products across dozens of competing apps. As a result, venture investment into the sector is slowing, with bike companies dying left and right. If you go back to the very first Fintech venture chart in this write-up, you'll see that the Asian numbers are the only ones down year-over-year.

In this context, it is interesting to think about the opening up of Chinese financial markets just initiated by the central bank. One of the main barriers -- a restriction on foreign investors owning more than 25% of a company's shares -- has been removed. Similarly, foreign rating agencies can now rate bond instruments in the inter-bank markets, as well as make their own investments, and set up money management enterprises (from wealth to pension funds). Will Facebook and Google now be able to acquire a Chinese high-growth lending Fintech? Will Ant Financial stake and distribute Libra through its mobile app? Fintech is the next big bubble! Fintech has already burst!

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Short Takes

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  • Apple contractors 'regularly hear confidential details' on Siri recordings. Whistle blowers at the tech company are saying that Siri records private conversations routinely -- from doctor visits, to crimes in progress, to sexual encounters. It then sends those recordings to human staffers to "improve speech recognition".

  • The FTC’s Remarkable $5 Billion Fine for Facebook. Facebook makes about $60 billion in revenue annualized, with a $20 billion profit, so this is a 10%-ish haircut for a single year. The cost of undermining democracy and blowing up privacy on the Internet is like paying a nasty parking ticket. Alternately, you could tell a story about how allowing Cambridge Analytica access to user data wasn't intentional, and the fine is an oversized and arbitrary regulatory response. But you know, actions louder than words.

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What Finance can learn from the Evolution of Beautiful Artificial Intelligence Art; plus 14 short takes on top developments

Hi Fintech futurists --

In the long take this week, I take a journey from Michelangelo's Sistine Chapel, to the impact of Photography on Portraiture, to Artificial Intelligences building generative art on blockchain networks. We take stops along the way to see analogies to financial services, and to notice how expert craft turns to code.

The latest short takes on the Fintech bundles, Crypto and Blockchain, Artificial Intelligence, and Augmented and Virtual Reality are below.

Thanks for reading and let me know your thoughts by email or in the comments!


Long Take

Enough Finance, let's talk Art. I promise it will swing back to Finance anyhow. One of the key takeaways that keeps spilling out of the conversation around Artificial Intelligence is whether humans will be augmented or replaced by software. Most of the time, these transhumanist discussions are science fiction hand-waving. But let me walk you through some tangible examples, so you can see and feel the distance traveled.

Let's say it is the 1500s, and you'd love a portrait of your family, or an image from your favorite allegory to behold once in a while. Since it is the Middle Ages, not everyone can just fire up Blade Runner (my favorite allegory) or take DSLR photos of their cats. If you are a locally powerful sovereign in the local feudal community, you might be able to hire a craftsman like Michelangelo to paint the ceiling once every twenty years. For your trouble, you will get the following masterpiece!

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Of course, you are not really hiring Michelangelo alone to do all this work. He comes with a guild of apprentices and professionals that scale up the capabilities of his practice, deploying Michelangelo's style and leveraging his reputation to do illustrations all over Europe. You are welcome to analogize this to a successful investment banker doing deals all over Silicon Valley -- a craftsman with years of experience and a strong reputation using teams of underpaid interns to immortalize people in power.

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However, mastery is not immune to automation. As a profession, portraiture melted away with the invention of the Camera, which in turn became commoditized and eventually digitized. The value-add from painting had to shift to things the camera did *not* do. As a result, many artists shifted from chasing realism to capturing emotion (e.g., Impressionism), or to the fantastical (e.g., Surrealism), or to non-representative abstraction (e.g., Expressionism) of the 20th century. The use of the replacement technology, the camera, also became artistic -- take for example the emotional range of Fashion or Celebrity photography (e.g., Madonna as the Mona Lisa). The skill of manipulating the camera into making art, rather than mere illustration, became a rare craft as well -- see the great work of Annie Leibovitz.

But nothing is sacred. As we moved into the Machine Age, photography was democratized through the shift to digital cameras and smart phones. This meant that the populace at large could generate endless visual imagery, and perfect their selfi skill-sets. Home photo albums grew from a few dozen mundane, poorly composed pictures, to millions of images immaculately designed and filtered for social media. Today, every single person on Tinder and Instagram is a fashion photographer. They are also their own self-immolating Madonna. It is a heavy burden.

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Let's analogize back to Finance. It used to be that complex financial products, like derivatives, real estate investing, global tactical asset allocations, and foreign exchange arbitrage were built for institutions and wealthy people. Today, it is pretty much trivial to access all of these products in any corner of the world. Roboadvisors in 2019 will give you Goldman's 2006 asset allocation for pretty much free. Neobanks will provide institional-level intererest rates (almost the Fed rate!) to the smallest accounts. Crowdfunding sites have introduced real estate and high yield bond markets to regular people. And if you want to see FX arbitrage or high frequency trading at play levered up 100x, just go to Bitmex. Today, you are empowered to have the misfortune of figuring out your own investment and retirement strategy. For most people, this is as much fun as trying to make it as a YouTube influencer.

So now we come to Data. As web apps filled up with our millions of selfies, cat photos, and selfies with cats, humanity's engineers figured out one more trick. We could run thousands of simultaneous regressions across all these images to create self-managing algorithms that identified the subject matter of the content. And as the math classified what was already in the images, it also learned how to hallucinate the underlying structure of the world. By scanning through the history of human visual arts, the machine learned the styles of different artists -- and how to project them as filters on any image you decided to choose. An artist in your pocket from any moment in history!

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This is roughly where we are with financial services Artificial Intelligence today. Take for example a digital lender that uses AI to maintain an underwriting model for personal loans. European core-banking company Temenos just bought a startup called Logical Glue to build exactly this feature inside its broader platform. By studying past human judgment in lending, literally teaching the machine through supervised learning on existing data sets, the software is replicating the "style" of a prior underwriter. Perhaps the underlying picture will change -- but the overall vibe, and hopefully the associated default rate, will stay a masterpiece. Lending Club charge-offs below illustrate the point by analogy.

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But the story does not end here. New media art has been thriving over the last several decades, as programmers learned to write code that visualized beautiful and complex algorithms, which in turn could be rendered by increasingly more powerful hardware and websites. Artists like Holger Lippmann created generative systems that would yield infinitely variable patterns, fractals, and other gorgeous designs that take your breath away. Still, these are highly engineered, mathematical outcomes. Like the case of Michelangelo earlier, they are shaped by an expert craftsman using modern tools. You can compare Lippmann to the billionaire mathematician financiers behind Two Sigma, or D.E. Shaw, who code the quantiative fractal investment strategies to beat markets.

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Today's innovations of Artificial Intelligence and Blockchain are opening up a new frontier for the machines, and their implications for our creativity. Neural networks -- the math that powers the style transfer I referenced earlier -- can now create their own generative outcomes based on the millions of images of photos and visual artifacts that the Web has fed them. Take for example a project called Ganbreeder, which allows users to traverse mathematically between different types of objects in a visual space (e.g., an image could be half fish, a quarter truck, and a quarter castle). The network can be used to hallucinate forward music covers, landscapes, or human portraits. The below illustrations were not done by a human hand, other than the coding of course.

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These infinite realistic, abstract, or Surrealist images are not all equally valuable. Some are gorgeous and should be saved, while others are redundant and uninteresting. This is where blockchain networks add their magic. Check out this great article on Artnome about the attempts to make scarce and commercial digital art by tokenizing its ownership. If the machine authors a beautiful thing -- or perhaps if you discover it during your travels through its alien landscapes -- how do we record provenance and property rights? How do we value, exchange, gift, create reproductions, or destroy the thing itself?

Here are a few projects working on the issue: SuperRare, KnownOrigin, Portion, RareArtLabs, DigitalObjects, Crypto Punks, Dada.NYC, CurioCards, Pixura, and Freeport. By tieing each piece of digital art to a blockchain collectible, scarcity allows for economic activity between human beings.

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Determining what is valuable can be human work, as in the case of Ganbreeder. Or perhaps it is the work of mathematical algorithms as well! One such example is a social media experiment called Archillect, which scrapes the social web for highly unusual images with strong user engagement. This has earned its Twitter account over 1 million followers, and I recommend you check out the results here. Perhaps in Finance, this would be a highly successful momentum trading bot, targeted at the most discussed companies on social websites. Or perhaps it is the trade-copy Fintechs like Covestor or Gimmer.

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We are getting a bit long in the tooth with this entry, so let me land us in the natural conclusion of these developments. Gene Kogan, one of the pioneers in creative AI, has just started work on a generative neural network that makes digital art, and bundles it with a blockchain-based marketplace. Another similar project is Artonomous from Simon de la Rouviere (using a simpler procedural engine), yet to launch. Participants in the training of the AI artist get economic rewards, the artist's outputs are saved as crypto collectibles, and there is potential to leverage all the decentralized financial services that exist on the Ethereum blockchain.

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You could, for example, try to use generated art objects as collateral to get margin loans from MakerDAO. Or, perhaps, you would exchange the works using decentralized exchanges. When the economic value of such artwork is trivial, the concept is not particularly compelling. But once you realize that traditional paintings (with a record of a sale of about $450 million) will follow a similar route, things become interesting.

In the financial services world, Numerai is the main comparable that comes to mind. That team runs machine learning competitions on a common data set, using the winning algorithms to generate alpha in the stock market, and pays out participants in a proprietary cryptocurrency. But I think such an approach is too greedy -- why should one hedge fund get to monopolize the benefits of all that math? Far more interesting would be a Decentralized Autonomous Organization that has a participatory rewards model, such as 20% of carry, for high quality AI-based trading algorithms that pass a certain threshold of quality. If such an open source projects does appear, it may be possible for it to accrue massive returns to scale. That is, if it isn't stomped into the ground by regulators first.


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Deutsche Bank to fire 18,000 people while Amazon upskills 100,000; plus 14 short takes on top developments

Hi Fintech futurists --

I have been reading Paul Graham's Hackers and Painters, and noodling on the social role of exponential software monopolies. When a single person can be 1,000 times more productive than someone else, what is their responsibility to others? The long take this week pushes this question through the example Deutsche Bank planning to fire 18,000 people and invest €13 billion in Fintech, misunderstanding the massive value creation available from upskilling and frontier technologies. Amazon and Ant Financial get it.

The latest short takes on the Fintech bundles, Crypto and Blockchain, Artificial Intelligence, and Augmented and Virtual Reality are below. Thanks for reading and let me know your thoughts by email or in the comments!


Long Take

What's a human being these days? There's of course the human animal, with its various biological, family, and cultural roots. These roots must yield social fruit: each person thrust into our world is due their basic human rights, of which working dignity and mental health are becoming an increasing requirement. Then there is the technological self, with its software nodes splintering across thousands of websites, robot services, and automated agents. Your data and logins animate to life engineered systems and artificial environments. Each action, click, and command is wealth for the tech company. And then there's the Centaur -- a sci-fi way of saying human/machine hybrid -- the augmented person outpacing and outproducing the unplugged, unnconnected, and unbanked.

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Today's corporations and governments are in the business of defining the balance of these aspects of our participation in society and the economy. Beliefs about the immutability of different attributes about what makes a person (or an employee) and how economies are built (cutting the pie, vs. growing the pie) determine the policy decisions you make, top down. As the core example this week, let's take Deutsche Bank. Facing pricing pressure and headwinds in several of its businesses, Deutsche is responding with a plan to fire 18,000 employees by 2022 and an announced investment of €13 Billion in technology and innovation by 2022. They even spun up a hipster-colored neobank as a proof point. Wall Street ain't buying it.

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I am going to take a digression, so bear with me. Many people in Fintech derisively refer to big bank incumbent activity around the start-up space as "Innovation Theater" -- something that a Chief Innovation Officer is hired to do in order to make the company's story sound more promising for public investors, but that in reality has little connection to budget or operating executives managing a P&L. This is an exaggeration; in reality, accelerators (e.g., Barclays Techstars) and corporate venture funds (e.g., Goldman Sachs investing in Kensho, Circle) can make a big difference. And yet, caricatures also speak truth. What I believe we are seeing now is actually worse than innovation theater. It is a Cargo Cult.

During the Second World War, airplanes dropped supplies to troops stationed on the island of Melanesia. Local inhabitants saw this as a religious event, and tried to summon both the airplanes and the supplies by replicating superficial symptoms. They built wooden airplanes, imaginary landing strips, and bamboo control towers. Surely, by copying the steps to invoke airplanes, the supplies would come! Surely, by copying the symptoms of new finance -- neobanks, roboadvisors, Bitcoin, cool offices, the word "data" -- we can turn this thing around! The chant starts with "Innovation".

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I live in a glass house, and am not poking fun at the Melanesians -- they are just like us. I am not laughing at legacy finance -- I worked there, and am partnered with many good firms in the space. But I am pointing out how all of us have a Bug in our brain, a Bug that makes us think that symptoms are causes. Or that a technology stack from the past is the same as a technology stack from the future. Or that there is no structural, competitive advantage in breaking your business model and starting from scratch on new ground. This is the existential lesson that Deutsche Bank needs to learn.

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If you look structurally at the Capital Markets and Asset Management, a few trends from the last decade become clear quickly. The growth in electronic trading is tightening bid-ask spreads and increasing transparency. Associated regulation, like MiFIDII, is forbidding arcane pricing models that allowed investment research to be bundled with trading and thus be massively overpriced. Packaging technology that powers ETFs has catalyzed a massive shift from active stock pickers to passive index vehicles, and the associated pricing collapse as a result. As readers well know, roboadvisors have further pushed the business model such that wealth management costs 25 basis points, not 150 basis points. And European neobanks have done the same for retail banking, now coming for the Americas.

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Trends like this are the reason for why Deutsche Bank is getting rid of its Equities division, focusing upstream on human-led advisory where it still has an advantage, and promising €13 billion of "Innovation" as an answer to the existential challenge. It is likely that JP Morgan is a positive aspirational example for them, which had similarly earmarked $10 billion for Fintech. And they have been executing fairly well! When attacked by Robinhood, JPM launched its own free trading app. Attacked by Wealthfront, it is now responding with a 35 basis point price-point roboadvisor, distributing its own asset management product. Threatened by Bitcoin, the bank launched its own crypto asset. And when targeted by Chime, JPM spun up a neobank. Oh wait -- it shut down that neobank, perhaps understanding that Digital is a transformation, not a Millennial channel.

Another progressive example is Schwab, which was a fast follower into the digital wealth market. Being a manufacturer of both the asset management product and the cash sweep, as well as a brokerage and custodian, it had multiple financial services paths to monetization. But in March, the firm implemented a business model innovation on top of the technology platform. Super simple -- it changed pricing to a subscription model. You get music and movies through subscriptions. You get shopping and deliveries done through subscriptions. You even buy Microsoft Office and Adobe Photoshop through subscriptions. There is nothing special about finance, especially as it increasingly is run by software agents and augmented Centaurs (see, I've brought us back home!). As reward, it has gotten $1 billion in new assets since the price change.

But let's be honest. This stuff is all peanuts, relative to the real value creation that can be unlocked by frontier technologies in short order. Take self-driving technology platform Argo AI was founded in 2016, barely 3 years ago. Last week, Ford and Volkswagon contributed $4.2 billion of value into Argo (investment and in-kind corporate assets), setting the valuation at over $7 billion. That's about $2 billion of enterprise value generated per year. This is how you compete with Google, Uber and Tesla -- on the core technology advantage. Give the house to someone who knows what they are doing.

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Maybe you think the automative example to be contrived. Or, maybe you think that financial institutions are doing this today with mutualized blockchain infrastructure (they are, but £50 million into Fnality is no $4 billion). So let's instead take the real competition for global financial services -- not Facebook or Amazon, but the Chinese super apps. If you haven't yet, check out this 110 page deep dive into the market. I quote pages below liberally so you can get the sense of scale and speed we are up witnessing.

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Perhaps we have grown complacent about what it means to lift the productive power of a country's population into the technology age. Deutsche can optimize itself for financial returns and choose software over human bodies and bank branches. They can Cargo Cult themselves into appearing modern. But AI and automation have two potential outcomes. You can either (1) remove $1 billion of cost by slashing your team, or (2) make your team $1 billion more productive. If you do the former, you are not just shedding unnecessary gears of a clunky financial factory. You are losing nodes in your network; its advocates, ambassadors, and creators.

As technology raises the productive baseline for everbody regardless of their role -- through AI-enabled services and agents loosely alluded to in the beginning of this write-up -- leaders have a responsibility to their people. The question isn't what people can't do, but what is it that they can do in the Centaur world? Amazon is taking the right approach. As the robot / software side of the business becomes increasingly self-sufficient, 100,000 staff become less functionally useful to the eCommerce product factory. In response, the company is planning to spend $700 million to upskill these workers (on top of the $15/hr minimum wage vs. $7.25/hr for the US overall). While $7,000 per person on training is not breaking Amazon's bank account, it is an investment in the option value of human potential. And it may even save them from the Luddite revolution.

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Short Takes

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  • Embracing artificial intelligence for the buy-side. When the capital markets are run by trading bots, a human being has trouble understanding what is happening and why on a fast-enough time horizon. You have to be data-driven with trading rules in place, and quickly present decision makers with strategic options.

  • Need quick medical advice in Britain? Ask Alexa. Simple diagnostics and illness descriptions on the NHS website in the UK can now be spoken out loud by Amazon's smart speaker. While it's not really dealing with an AI doctor, we are starting to create consumer expectations. How much longer for Finance?

  • Amperity raises $50 million to unify disparate customer data. The startup is funded largely by financial customers, and parses raw files and data to find customer identities, and create data lakes with a holistic view for use in other system. I.e., data wrangling.

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