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| {{a|Technology|{{image|Robolawyer|jpg|John Cryan's legal department yesterday.}} }}''A shame you couldn’t say the same for John Cryan. Originally published in 2017, this article, and the grit in the steampunk wheel who wrote it — are still grimly hanging on, whereas the then CEO of Deutsche Bank is now the ex-CEO of Deutsche Bank.'' | | {{freeessay|technology|rumours of our demise|{{image|Robolawyer|jpg|John Cryan’s legal department yesterday.}}}} |
| === Rumours of our demise are greatly exaggerated ===
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| In 2017, then-CEO of Deutsche Bank John Cryan thought his employees’ days are numbered. Machines would do for them. Not just back office grunts: ''everyone''. Even, presumably, Cryan himself.<ref>The horror! The horror! The irony! The irony!</ref>
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| “Today,” he warned, “we have people doing work like robots. Tomorrow, we will have ''robots behaving like people''”.
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| You can see. They have displaced us in our routine functions. Soon they will take the good stuff, too.
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| In any case, No bad thing, you might say — who will miss the bankers?
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| You can see where Cryan’s idea comes from: what with high-frequency trading algorithms, AI medical diagnosis, accident-free self-driving cars: the machines are coming for us. Some see technology at a [[tipping point]], at which ''we'' will be tipped out. The machines have taken over our routine tasks; soon they will take the ''hard'' stuff, too.
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| A fashionable view. But a big call, all the same.
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| Technology is not new. As long as there has been the lever, wheel or plough, humans have used machines to do tasks which are [[tedious]], repetitive or require brute strength beyond our frail earthly shells. Because machines follow instructions better than we do, ''by definition'': that’s what means is to be a machine. ''In the stuff they are good at'', they’re quicker, stronger, nimbler, cheaper and less error-prone.
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| But it’s an important caveat: as {{author|George Gilder}} recently put it: “The claim of superhuman performance seems rather overwrought to me. Outperforming unaided human beings is what machines are supposed to do. That's why we build them.”<ref>{{br|Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy}} (2018)</ref>
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| ===The division of labour===
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| Machines can only operate in constrained environments. They make flawless decisions, as long as both question ''and'' answer are pre-configured. But take a machine out of its designed environment and it is useless: Good luck getting a [[Jacquard loom]] to plough a field.
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| We [[sacks of meat]] are better at handling ambiguity, conflict and novel situations. We’re not perfect, but whatever the conundrum is we can at least produce an answer. We don't hang, or freeze waiting for a dialogue box to be clicked: even though syntax errors are par for the course: humans don’t (easily) crash. That’s the boon and the bane of the [[meatware]]: you can’t tell when one makes a syntax error.
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| But put human and machine together and you have a powerful proposition: the machine handles the rule-following; the human figures out what to do when you run out of road. It’s a partnership. A division of resources. Technology is an extended phenotype. But this is nothing new: this is always how we’ve used technology: the human figures out which field to plough and when; the horse ploughs it.
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| Now technology has caused the odd short-term dislocation — the industrial revolution put a bunch of hand-weavers out of work — but the long-term prognosis has been benign: “labour-saving devices” have freed us to do things we previously had no time to do, or hadn’t realised you could do, before the technology came along. As technology has developed, so has the world’s population grown, while poverty and indolence have fallen. ''People have got busier''. Whatever technology is doing, with due regard to the risk of confusing [[correlation]] and [[causation]], it ''isn’t'' putting us out of work.
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| Technology opens up design-space. It expands the intellectual ecosystem, domesticating the ground we know, and opening up [[frontier]]s we don’t. [[Frontier]]s are places where we need smart people to figure out new tools and new ways of operating. Machines can’t do it.
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| But it also creates space and capacity to care about detail. [[Parkinson’s law]] states: it frees us up to care about things we never used to care about. The microcomputer made generate duplicate and distribute documents far, far easier.
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| So, if you want to say this has all changed — that now the machines will put us out of work — you have to explain ''how''. What has changed? Why is this time different? We’ve heard this record before: twenty years ago, the wizards told us the internet had changed start-up valuations forever. Didn’t work out so well.
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| So, are the robots coming for us?
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| Firstly, remember Cryan is talking his own book. Banking is a hard business to make money in these days. Opportunities to develop new businesses (read: ''opening new frontiers'') are diminished; managing to margin is ''de rigeur''. Mr. Cryan needs to fire as many people as he can. What he doesn’t automate, his competitors will, and they’ll take his lunch. “We’re ditching the meat sacks”: that is what DB’s investors want to hear.
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| And banking requires less novel judgment than it used to. The West has been — well, won: ploughed over and converted into shopping malls. Much of it can be boiled down to formulating rules and following them by rote.<ref>There remain emergent risks, [[black swan]]s and regulatory complexity, of course, but a lot of stuff could be automated which hasn’t been.</ref> Only the edge cases — where pioneers stand on the frontier gazing into the horizon — require judgment. That is no place for an algorithm. These are the situations of real risk: the “unknown unknowns”.
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| As a strategy for coping with “known knowns” automation is good business. Humans are bad at following rules. They are expensive. They occupy real estate. They require human resources departments. They misunderstand. They screw up. They leave. They don't write things down. Machines are much better on all of these measures.
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| But, still ''the race to automate “known knowns” is a race to the bottom''. The value in a product is the resources and skill required in producing it. Banking products need no fields, raw materials or warehouses: only ''skills''.
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| Two types of skills, categorically: ''computational, analytical'' skills and ''interpersonal, imaginative'' skills.
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| Computational skills — those suited the symbolic manipulation — can and should be automatic algorithms, high-frequency trading strategies, data analytics, neural networks and machine learning. But the value of computational “skills”, once automated, tends to zero. ''Even those requiring artificial intelligence''. The margins they generate will tend to zero, too: everyone with a decent PC will be at it.
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| If Mr. Cryan thinks ''that'' is the future of his business, he needs his head read.
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| Your future, sir, is in your people: those ones who stand at the frontier, staring resolutely into the horizon. They may have robots at their disposal, but only your human pioneers can set them to work.
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| ===Perez’ Folly===
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| Not long before departing the ship erstwhile head of UBS Evidence Labs Juan Luis Perez — not by background a banker — remarked that the incipient competition for banks was not “challenger” banks, but Apple, Amazon, or Google.
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| His argument was this: banking comes mostly down to three components: technology, reputation, and regulation.
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| Two of these — technology and reputation — are hard, substantial problems, while the other — regulation — is comparatively formalistic, especially if you have a decent technology stack. How do the banks stack up against the FANGS?
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| {| class="wikitable"
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| |+Banks v FAANGs: showdown.
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| !
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| !Technology
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| !Reputation
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| !Regulation
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| {{aligntop}}
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| |'''Banks'''
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| |Generally legacy, dated, patched together, under-powered, under-funded, conflicting, liable to fall over, susceptible to hacking.
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| |Everyone hates the Financial Services industry.
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| |All over it. Capitalised, have access to reserve banks, connected, exchange memberships, etc.
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| {{aligntop}}
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| |'''FAANGS'''
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| |Awesome: state of the art, natively functional, at cutting edge, well-funded, well-understood, robust, resilient. Ok could be hacked
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| |Who doesn’t love Amazon? Who wouldn’t love to have an account at the iBank? Imagine if banking worked like Google Maps!
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| |OK there is a bit of investment required here — and regulatory capital is a thing — but nothing is insurmountable with the Amazon Flywheel no?
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| {{aligntop}}
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| |'''Winner'''
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| |Cmon: are you kidding me? '''FAANGS''' all the way!
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| |'''FAANGS'''. Are banks even on the paddock?
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| |'''Banks''' have the edge right now. But look out white-shoe types: The techbros are coming for you.
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| |}
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| Apple, Amazon, and Google ''wipe the floor with any bank on technology'' — I can go with that — and have materially better standing with the public. Who doesn’t love Amazon? Who ''does'' love the Wells Fargo bank? The only place where banking presently has an edge is in regulation. It’s wildly complex, fiendishly detailed, the rules differ between jurisdictions, and the perimeter between one jurisdiction and the next is not always obvious. To paraphrase {{author|Douglas Adams}}: “You might think GDPR is complicated, but that’s just peanuts compared to MiFID.”
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| But, but, but — there are any number of artificially intelligent startups that can manage that regulatory risk, right? The [[legaltech roll of honour]] refers.
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| But really. Let’s park a few uncomfortable facts and give Me Perez the benefit of the doubt:
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| Firstly — if it is such a cinch, where the hell are they? It is 2023, for crying out loud. None of Apple, Amazon, or Google as so much as cast a wanton glance in the direction of the financial services industry, despite the revenue opportunities. ''Something'' is keeping them away. Maybe the regulatory piece is a lot harder than it looks.
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| But that’s not it: if it were then you would expect tech firms to be awesome at ''unregulated'' financial services. But — secondly — ''they’re not''. We’ve been treated to a ten-year, live-fire experiment with [[Cryptobabble|unregulated financial services]], from which the traditional financial institutions have mainly stayed away, ''and it hasn’t gone well''. The [[cryptobro|cryptobros]] have rediscovered, and promptly fallen down, pretty much every manhole known to the world of money management — they’ve even found some new ones of their own to fall down that money management didn’t know about. Helpfully, [https://web3isgoinggreat.com/ Molly White] is keeping a running score. Crypto, despite its awesome tech and fabulous branding, has been a disaster.
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| Secondly a company that makes cool gadgets has as much change of keeping its branding following a pivot to banking as does it is a toy factory could that moves into dentistry.
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| Thirdly it is naive in the extreme to prime that regulatory compliance is formalistic, let alone “the easy bit of banking”.
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| Park all that. For what Mr Perez overlooked as a core competence in a successful bank is the same thing Mr Cryan did: its ''people'". They are the irreducible, ineffable, magic difference. The ''informal'' networks by which it works, magically crossing the terrain like some hovering, morphing jellyfish. Sundar Pichai can’t code that. That human expertise is required to hold the creaking systems together, to work around absurdities and take a pragmatic view — this is not a big in the system, but a feature.
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| Not how modernist a disposition this is. It is to critique an organism by its formal, legible operation. It is the view from the disembodied luminaries who occupy that Cartesian theatre called the executive suite. They see only formal vulnerability, because formal structures are all they can see. Individuals are measurable by floorspace occupied, salary, benefits, pension contributions, revenue generated. Most employees don't generate legible revenue. They show up on the map ''only as a liability''.
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| From the executive suite, the calculus is obvious: why hire a dude to do that, when a machine could do it cheaper, quicker, and more reliably?
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| Therefore the model, articulated by Cryan and implied by Perez: ''prepare for the coming of the machines''. Automate ''every'' process. Reduce the cost line. Remove people, because when they come for us, Amazon won’t be burdened by people
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| Now, to be clear, the tech stacks of most banks are dismal. Perez is right about that. Amazon’s tech ''would'' wipe the floor with any banks tech: most are sedimented, interdependent concatenations of old mainframes, Unix servers, Windows terminal servers, and somewhere in the middle of the thicket will be a wang box from 1976 with a CUI interface that can't be switched off without crashing the entire network. These patchwork systems are a legacy of dozens of mergers and acquisitions and millions of lazy, short-term decisions to fix broken systems with sellotape and glue rather than maintaining and overhauling them properly. And banks are tech companies: you can't stop a bank and put it up on the blocks for 6 months while you rebuild it. (though covid: opportunity missed.) it is hard to rebuild the engine of a car while it is barreling down the motorway at 70mph. Banks didn't start thinking of themselves as tech companies until the last twenty years.
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| Per John Gall: temporary patches have a habit of becoming permanent.
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| We presume Google and Amazon, who always have, are better and more disciplined about their tech infrastructure than that.<ref>See the [[Bezos memo]].</ref>
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| The tech stack can give them wings, but they have to decide where to fly. They narratise.the bond, form networks, make connections, ''persuade''. These things a machine cannot do.
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| So, note the category error bank leaders make in seeing technology as the competitive threat it is not. It is just the ticket to play.
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| This is bit to say banks employees an unusually are gifted, intelligent bunch. You are invited to read other pages of this site for our views on that.
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| Imagine a bank strategy that said the in
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| {{draft}}
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| {{ref}}
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