An AI hedge fund designed a cryptocurrency to open source Wall Street

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WHY THIS MATTERS IN BRIEF

  • The finance marketplace is unique in that, unlike the technology sector, it has little to no “network effect” but one entrepreneur is trying to change that


 

Wall Street is a competition, a Darwinian battle for the almighty dollar. Gordon Gekko said that greed is good, that it captures “the essence of the evolutionary spirit.” A hedge fund hunts for an edge and then maniacally guards it, locking down its trading data and barring its traders from joining the company next door. The big bucks lie in finding market inefficiencies no one else can, succeeding at the expense of others. But Richard Craib, who runs crowdsourced artificial intelligence (AI) fund Numerai wants to change that. He wants to transform Wall Street from a cutthroat competition into a harmonious collaboration.

 

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Last week, the 30 year old South African technologist issuing a new digital currency, kind of. Craib’s idea is so unlike anything else that has preceded it, that naming it becomes an exercise in approximation. Inspired by the same tech that underpins bitcoin, his creation joins a growing wave of what people in the world of crypto-finance call “digital tokens,” internet based assets that enable the crowdsourcing of everything from venture capital to computing power.

Craib hopes his particular token can turn Wall Street into a place where everyone’s on the same team. It’s a strange, complicated, and potentially powerful creation that builds on an already audacious arrangement, a new configuration of technology and money that calls into question the market’s most cherished premise. Greed is still good, but it’s better when people are working together.

Based in San Francisco, Numerai is a hedge fund in which an AI chooses all the trades. But it’s not a system Craib built alone, instead, several thousand anonymous data scientists compete to create the best trading algorithms and win bitcoin for their efforts. Numerai has been making trades in this way for more than a year, and Craib says it’s making money, and it’s also attracted marquee backers like Howard Morgan, a founder of Renaissance Technologies, the wildly successful hedge fund that pioneered an earlier iteration of tech-powered trading.

 

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Numerai’s system is elegant in its way, the platform encrypts its trading data before sharing it with the data scientists to prevent them from mimicking the fund’s trades themselves and therefore creating their own competitive hedge fund. At the same time, the company carefully organizes this encrypted data in a way that allows the data scientists to build models that are potentially able to make better trades. The crowdsourced approach seems to be working, but in Craib’s eyes, the system still suffers from a major drawback – if the best scientist wins, that scientist has little incentive to get other talented colleagues involved. The wisdom of the crowd runs up against Wall Street’s core ethos of self interest; make the most money for yourself.

That’s where Craib’s new token comes in. Craib and company believe Numerai can become even more successful if it can align the incentives of everyone involved. They hope its new kind of currency, Numeraire, will turn its online competition into a collaboration, and turn Wall Street on its head.

In its first incarnation, Numerai was flawed in a notable way. The company doled out bitcoin based on models that performed successfully on the encrypted test data before the fund ever tested them on the live market. That setup encouraged the scientists to game the system, to look out for themselves rather that the fund as a whole.

“It judged based on what happened in the past, not on what will happen in the future,” says Fred Ehrsam, co-founder of marquee bitcoin company Coinbase and a Wall Street veteran.

 

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But Craib feels the system was flawed in another way, the same way all of Wall Street is flawed. The data scientists were still in competition. They were fighting each other rather than fighting for the same goal. It was in their best interest to keep the winnings to themselves. If they spread the word, the added competition could cut into their winnings. Though the scientists were helping to build one master AI, they were still at odds. The fund and its creators were at cross purposes.

Last month, to fix that problem, Numerai distributed one million Numeraire tokens to 12,000 participating data scientists. The higher the scientists sit on the leaderboard, the more Numeraire they receive. But it’s not really a currency they can use to pay for stuff. It’s a way of betting that their machine learning models will do well on the live market. If their trades succeed, they get their Numeraire back as well as a payment in bitcoin, as a kind of dividend. If their trades go bust, the company destroys their Numeraire, and they don’t get paid.

The new system encourages the data scientists to build models that work on live trades, not just test data. The value of Numeraire also grows in proportion to the overall success of the hedge fund, because Numerai will pay out more bitcoin to data scientists betting Numeraire as the fund grows.

“If Numerai were to pay out $1 million per month to people who staked Numeraire, then the value of Numeraire will be very high, because staking Numeraire will be the only way to earn that $1 million,” Craib says.

 

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It’s a tricky but ingenious logic. Everyone betting Numeraire has an incentive to get everyone else to build the best models possible, because the more the fund grows, the bigger the dividends for all. Everyone involved has the incentive to recruit yet more talent, a structure that rewards collaboration.

What’s more though Numeraire has no stated value in itself, it will surely trade on secondary markets. The most likely buyers will be successful data scientists seeking to increase their caches so they can place bigger bets in search of more bitcoin rewards. But even those who don’t bet will see the value of their Numeraire grow if the fund succeeds and secondary demand increases. As it trades, Numeraire becomes something kind of like a stock and kind of like its own currency.

For Craib, a trained mathematician, the hope is that Numeraire will encourage Wall Street to operate more like an open source software project. In software, when everyone shares with everyone else, all benefit from the collaboration and the software gets better. Google open sourced its artificial intelligence engine, for instance, because improvements made by others outside the company will make the system more valuable for Google, too.

“Why is tech positive sum and finance zero sum?” Craib asks, “the tech companies benefit from network effects where people behave differently because they are trying to build a network, rather than trying to compete.”

 

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Craib and company built their new token atop Ethereum, a vast online ledger, a blockchain, where anyone can build a bitcoin like token driven by a self operating software program, or “smart contract.” If it catches on the way bitcoin has, everyone involved has the incentive to loudly promote this new project and manically push it forward in new ways.

But getting things right isn’t easy.

“The risk is that the crypto economic model is wrong,” says Ersham, “tokens let you set up incentive structures and program them directly. But just like monetary policy at, say, the Federal Reserve, it’s not always easy to get those incentive structures right.”

In other words, Craib’s game theory might not work. People and economies may not behave like he assumes they will. Also, blockchains aren’t hack-proof. A bug brought down the DAO, a huge effort to crowdsource venture capital on a blockchain. Hackers found a hole in the system and made off with $50 million.

Craib may also be overthinking the situation, looking for complex technological solutions to solve a problem that doesn’t require anything as elaborate as Numeraire.

“Their model seems overly complicated. It’s not clear why they need it,” says Michael Wellman, a University of Michigan professor who specialises in game theory and new financial services, “it’s not like digital currency has magical properties.”

 

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Numerai could try a much more time honoured approach to recruiting the most talented data scientists, Wellman says: “Pay them, but I suspect that that’s something Craib is trying to avoid, for obvious reasons.”

After today, Craib and the rest of Wall Street will start to see whether something like Numeraire can truly imbue the most ruthless of markets with a cooperative spirit. Those thousands of data scientists didn’t know Numeraire was coming, but if the network effects play out like Craib hopes they will, many of those scientists have just gotten very, very rich. Still, that isn’t his main purpose. Craib’s goals are bigger than just building a hedge fund with crowdsourced AI. He wants to change the very nature of Wall Street – and maybe even capitalism. Competition has made a lot of people wealthy. Maybe collaboration could make them even richer.

About author

Matthew Griffin

Matthew Griffin, Futurist and Founder of the 311 Institute is described as “The Adviser behind the Advisers.” Among other things Matthew keeps busy helping the world’s largest smartphone manufacturers ideate the next five generations of smartphones, and what comes beyond, the world’s largest chip makers envision the next twenty years of intelligent machines, and is helping Europe’s largest energy companies re-invent energy generation, transmission and retail.

Recognised in 2013, 2015 and 2016 as one of Europe’s foremost futurists, innovation and strategy experts Matthew is an award winning author, entrepreneur and international speaker who has been featured on the BBC, Discovery and other outlets. Working hand in hand with accelerators, investors, governments, multi-nationals and regulators around the world Matthew helps them envision the future and helps them transform their industries, products and go to market strategies, and shows them how the combination of new, democratised, powerful emerging technologies are helping accelerate cultural, industrial and societal change.

Matthew’s clients include Accenture, Bain & Co, Bank of America, Blackrock, Booz Allen Hamilton, Boston Consulting Group, Dell EMC, Dentons, Deutsche Bank, Deloitte, Deutsche Bank, Du Pont, E&Y, Fidelity, Goldman Sachs, HPE, Huawei, JP Morgan Chase, KPMG, Lloyds Banking Group, McKinsey & Co, PWC, Qualcomm, Rolls Royce, SAP, Samsung, Schroeder’s, Sequoia Capital, Sopra Steria, UBS, the UK’s HM Treasury, the USAF and many others.

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