The Big Data Gold Rush
Let’s say it does turn out to be valuable. What does the financial industry look like then?
Everyone is competing against everyone else. If one firm succeeds in making the market more efficient through quantitative techniques, then there’s less money left over for other people to make exceptional investment returns. There will be one or two firms that are good at innovation and recognizing things that other people haven’t recognized. But everyone else will be fighting over scraps.
One of the fallacies that people have is the assumption that because the people who are working at certain firms are smart, they must be successful. But the fact that they understand artificial intelligence or machine learning or big data is somewhat useless as a competitive advantage if everyone else understands it as well.
So as those techniques get diffused across the industry as a whole, they start to be less of a differentiator. How does this impact employment? How do you see these technologies affecting either how many people the financial industry employs, or the level of skill required in different roles?
Back before the financial crisis, there was a theoretical basis for the rise of the mortgage-backed security industry. If you can diversify the risk to the investor by bundling a bunch of mortgages together, then the investor should be willing to accept a lower return, which in turn should reduce the cost to homebuyers of taking out a mortgage. That’s the theory: when financial markets work well, the benefits should percolate throughout the economy. Obviously, in 2008, that theory broke down.
In the field of quantitative investing, the same theory plays out. Let’s say people are saving money for retirement by investing in a mix of stocks and bonds. Those assets are a little cheaper for them to buy because there are all kinds of participants in the market who are fighting over making the market a little more efficient because there’s a financial incentive for them to do so.
The flip side is that the entire financial industry also has an incentive to encourage people who don’t know as much as them to give them money to do all the things that ordinary investors don’t know about. “Give me money to use a machine learning technique to manage your money, even if the machine learning technique doesn’t work, because it’s very profitable for me to take 2 percent of your fund every year.” So the incentive to make the market more efficient is balanced against the excessive proliferation of financial services that don’t add value.
What is the mechanism that’s going to eliminate that? Well, it’s the recognition that the industry as a whole may be getting paid far in excess of the value it’s providing.
How does that recognition actually begin to remake the industry, and what role will new technologies play in that process?
The short answer is that tons of jobs are on the verge of getting wiped out because technology can do those jobs. And there are benefits to scale, so you may not need many firms to replace those that don’t survive.
Take the mutual fund industry. It has more than a hundred thousand employees in the US. And every one of those jobs is at risk from the realization that the economic value of those funds is replicable with the right computer systems. For the moment, those jobs are sustained by inertia, or they are sustained by a story about why a certain manager is going to make you more money than an index fund. But that’s changing. That change will play out over the next couple of years.
Take the big money managers in Boston like Fidelity and Putnam. Those are old, large institutions. Effectively all of those jobs are at risk unless they evolve fast. And even if they do, automation will cut deep. Hedge funds, same thing. Some of them will be able to eke out value from the development of new techniques, but everyone else will be replaced by computers.
You’re already seeing big changes at investment banks. Even though investment banks continue to be very large in terms of their physical footprint, number of employees, and impact on the economy, the actual participants inside banks have changed a fair bit. It’s far more automated. Many of the actual operations inside an investment bank are done by computers. It’s not humans deciding to buy Apple stock; it’s computers deciding to buy Apple stock. So that job shift is already happening.
Financial firms are increasingly becoming tech firms. JP Morgan Chase employs 50,000 technologists, two-thirds of which are software engineers. That’s more engineers than many big tech firms: Facebook, for example, employs about 30,000 people total.
Q: You’ve been in the financial industry for a little while so you’ve seen this transformation firsthand. How has the influx of technologists changed the industry?
A: The very clubby nature of traditional financial firms like investment banks has been diluted. You’ve got a lot more geeks and nerds. You don’t see certain jokes being made. Football conversations have been replaced by conversations about restaurants or other staples of yuppie culture.
The culture has mellowed quite a bit. It’s less driven by adrenaline. It’s less loud. The value is provided not by the person yelling into the phone but by the person who’s sitting at their computer, writing the right algorithm, who needs a little bit of thoughtfulness to does that work. The old model was about driving transactional flow through sheer energy. The new model is about driving transactional flow through computers.
Q: So less Wolf of Wall Street and more The Social Network?.
A: Totally. But that tension is still playing out. For instance, there’s still a big disconnect between the way that HR divisions recruit, especially at large firms, and the kind of candidates that are actually needed. So you’re seeing the development of completely alternative hiring tracks within large firms. The traditional hiring track just doesn’t give you enough good quantitative candidates.
Q: Returning to the question of employment: you said you expected that one of the biggest consequences of these technologies will be a reduction in the number of people the financial industry employs. Does that also affect the overall size of the industry? On the one hand, it seems like many jobs could be eliminated or deskilled. On the other hand, it also seems possible that the very large size of the financial sector relative to the rest of the economy could be reinforced and even intensified by these technologies. ?
A: I think you’re right.
There’s a contradiction built into managing money using quantitative techniques. Let’s say you’re a hedge fund and you get paid a lot for an advanced technique. In order to demonstrate to your customer that your technique really does make money and does so in a replicable and sustainable fashion, you need to be a bit open-kimono in talking about why the technique works. You probably have to talk about the actual algorithm itself. But of course once you’ve described the algorithm, well, why does the investor need to pay a manager to do it? It’s just lines of code. Once you’ve developed it, you can run it for the marginal cost of next to zero.
Some of the managers who have been successful at raising money for their quantitative funds may have done the work of educating investors on why people shouldn’t be paying that much money to invest using these techniques. The result is that fees are dropping fast.
Currently, the largest growth in investment industry funds is happening in entities like BlackRock or Vanguard. These firms are launching a number of funds that use algorithms to invest but charge very low fees. So they are competing with hedge funds, who are having to lower their own fees in response. But BlackRock and Vanguard are also competing with themselves, because they are educating the market on why their own previous products were too highly priced.
If you measure their scale by the number of assets under management, these entities have grown at an explosive rate. Black Rock manages trillions of dollars at this point. But the actual revenue it ekes out from its assets isn’t growing nearly as fast. So you see both forces at play: the expansion of funds being managed along quantitative lines, but also the difficulty in sustaining profitability on those assets as more customers become aware of the actual cost and value of managing those assets using quantitative techniques. Even though the footprint might expand, the profitability will probably start to retreat towards levels that reflect the underlying value created.