“The more you disrupt banking, or trading, or asset management, the cheaper and easier it becomes for anyone to set themselves as a bank or trading shop. That makes it much more profitable for a far greater number of individual firms to enter the rent extraction business. The size of the rent extraction footprint doesn’t shrink, it just gets distributed more widely.”
A potent discussion of the California Ideology extolling the so-called disruptors.
Excerpted from Dizzynomics:
“There are always going to be negative unintended consequences associated with bringing down industrial barriers or making certain services easier or cheaper to set up, especially if and when those services are low value businesses like finance.
The more you disrupt banking, or trading, or asset management, the cheaper and easier it becomes for anyone to set themselves as a bank or trading shop. That makes it much more profitable for a far greater number of individual firms to enter the rent extraction business. The size of the rent extraction footprint doesn’t shrink, it just gets distributed more widely.
So whereas you used to require four diligent expensive minds (complete with lavish lifestyles) to work the numbers/dynamics so as to wisely allocate customer money (let’s give the techies the benefit of the doubt on their ability to do that in and of itself, even though there aren’t really all that many transferable skills between the two sectors) you now need only one much lower maintenance techy to do the same job.
Yes, you possibly eliminate some of the fat by replacing expensive CFA/MBA bearing traders and bankers with techies, but…. you also make it much easier for anyone to become a techy rentier, since their qualifications/skills are arguably much easier to acquire and more poorly regulated. There is as a result an almost immediate diminishing return. I’d also bet, it’s unlikely that their low-cost lifestyles will stay low cost for very long.
Ultimately, if it costs you less to run or start a hedge fund, it will also be more enticing to start a hedge fund — irrespective of whether there’s more capital flowing to the sector or not.
[Did you know”technological solutions” have brought us something in the region of 76 corporate bond trading platforms purporting to be THE venue for corporate bond liquidity?]
Also, for as long as investors/management lack the expertise to tell the good programmers apart from the bad ones (at least not until it is too late) it will actually be pretty hard to tell if the fat’s really been cut out of the system at all, or if techies like bankers are tending to front-load rewards and bonuses before the consequences of their actions are properly understood.
My only other point is: errr hello tech support?
As far as I know, algos (even the supposedly intelligent ones) need continuous tech support and human-level supervision if they’re to intelligently adapt for nuanced “gut feeling” stuff like the emergence of overly herded trades and market behaviours, or any other instinctive stuff that comes naturally to humans.
Let’s also not ignore that tech firms don’t tend to stay lean for long. The more they disrupt incumbents with low-cost algos, the more they realise that to keep hold of their newly acquired market share they need large-scale investment in human resources — whether that’s for tech support reasons (hello Apple geniuses) or qualitative stuff like making judgments about whether or not overly standardised tech approaches are making bad calls for non-standard customers or simply failing to account for unique circumstances more generally.
Google, one of the most techy and algo-ridden firms, isn’t a faceless algorithmic black box with a staff of less than 10 people. To the contrary, it’s a sprawling tax efficient mega corp which employs over 50k people. Go figure. Apple meanwhile employees 115k employees, Microsoft in excess of 100k; Amazon’s got over 150k and eBay* has over 30k people.
Even AirBnb, which prides itself on being an asset light operation, already employs as many as 2000 people and is recruiting new employees like mad (that’s without accounting for the literally hundreds of thousands of property rentiers it empowers as a whole).
To compare, Goldman Sachs employs about 34k people.
In the US, the financial services and insurance sectors as a whole employed up to 6 million people in 2014. The information tech industry, which in and of itself is mostly a wealth redistribution business, employed 6.4 million.
Fair to ask really: if algos really can replace humans in the workforce, how come there’s so many people managing algos?”