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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'' is presented ''[[res ipsa loquitur]]'' — we can go with that without any first hand evidence, just based on how lousy bank tech its — and, sure, the FAANGs have better standing with the public. Who doesn’t love Amazon? Who ''does'' love Wells Fargo?<ref>Though we think Mr. Perez rather confuses the product for its manufacturer. We might feel different about Amazon if, rather than making neat space-aged knick-knacks it made a business of coldly foreclosing mortgages, and charging usurious rates on credit card balances. You sin’tctg7nk it would? Have you seen the cut it takes from the play store?</ref>
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| Therefore, Mr. Perez’ argument goes, the only place where banking presently has an edge is in regulatory licences and approvals, capital, and regulatory compliance. 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 — any number of artificially intelligent startups can manage that regulatory risk, right?<ref> The JC’s [[legaltech roll of honour]] refers.</ref>
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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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| ====So where are they?====
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| Firstly — if bankd ''is'' such a sitting duck for predator FAANGS, ''where the hell are they''? It is 2023, for crying out loud. Wells Fargo is still with us. None of Apple, Amazon, or Google as so much as cast a wanton glance in its direction of let alone the [[Vampire Squid]]’s. ''Something'' is keeping them away.
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| ====Techbros aren’t naturals at banking====
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| And it’s not just fear of regulation, capital and compliance: if it were, you would expect tech firms to be awesome at ''unregulated'' financial services.
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| But — secondly — ''they’re not''.
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| We’ve been treated to a ten-year, live-fire experiment with how good tech firms will be in [[Cryptobabble|unregulated financial services]], during which the banks — “[[trad fi]]” — and, notably, the FAANGS have mainly stayed away, ''and it hasn’t gone well''.
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| [[Chauncey Gardiner|Credulous cryptobros]] have found, and promptly fallen down, pretty much every open manhole known to money management — and discovered some whole new ones of their own to fall down too. Helpfully, [https://web3isgoinggreat.com/ Molly White] has keeping a running score. Crypto, despite its awesome tech and fabulous branding, has been a disaster.
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| ====Tech brand-love-ins won’t survive first contact with banking====
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| Thirdly a cool gadget maker that pivots to banking ''and does it well'' has as much chance of maintaining millennial brand loyalty as does a toy factory that moves into dentistry.
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| Those Occupy Wall Street gang? Apple fanboys. ''At the moment ''.
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| The business of banking will trash the brand.
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| ====Bank regulation ''is'' hard====
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| Fourthly regulatory compliance is hardly formalistic, let alone “the easy bit of banking”. If you could solve it with tech, the banks would have long since some it. They gave certainly tried. Regulations change, contradict, don't make sense, overlap, are fiddly, illogical, often counterproductive and they are subject to to interpretation by regulators, who are themselves fiddly, illogical and not known for their constructive approach to rule enforcement.
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| Getting regulations wrong can have ''bad'' consequences. Even apparently formalistic things like [[KYC]] and [[CASS 6|client asset protection]]. Banks ''already'' throw armies of bodies and [[legaltech]]<ref>Our [[legaltech roll of honour]] refers.</ref> at this and still they are routinely breaching minimum standards and being fined millions of dollars.
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| ===The gorillas in the room===
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| {{Quote|A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects.
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| :—Robert Heinlein}}
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| But in any case park all the above, for it is beside the point. For Mr. Perez overlooked the same core banking competence that Mr. Cryan did: quality ''people'', and quality ''leadership''.
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| We have fallen into some kind of modernist swoon, in which we hold up ourselves up against machines, as if ''techne'' is a platonic ideal to which we should aspire.
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| So we set our children modernist criteria, too from the moment they set foot in the classroom. The [[education]] system selects for individuals by reference to how well they obey rules, how reliably, and quickly, they can identify, analyse and resolve ''known'', pre-categorised, “problems”. But these are historical problems with known answers. This is a [[finite game]]. ''This is exactly what machines are best at''.
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| If we tell ourselves that “machine-like qualities” are the highest human aspiration, we will naturally find ourselves ''wanting''. We make it easy for the robots to take our jobs. We set ourselves up to fail.
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| But human qualities are different — humans can improvise, imagine, narratise, analogise — they can conceptualise Platonic ideals — in a way that algorithms cannot.
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| And there is the impish inconstancy, unreliability and unpredictability of the human condition — these make humans ''different'', not ''inferior'', to algorithms. They make us difficult to control and manage by algorithm.
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| And that is the point. ''We are not meant to be making it easy for machines to manage and control us.'' By suppressing our human qualities, we make ourselves more legible, machine readable, triageable, categorisable by algorithm. The economies of scale and process efficiencies this yields accrue to the machines and their owners, not us.
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| Why surrender before kick-off like that?
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| ===A real challenger bank===
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| Programmatisation has its place.
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| They are the irreducible, ineffable, magic difference between excellent banks and hopeless ones: the transparent ''informal'' networks by which it mysteriously navigates all kinds of terrain like some hovering, morphing jellyfish. Sundar Pichai can’t code that. The same human expertise the banks need to hold their creaking systems together, to work around their bureaucratic absurdities and still sniff out new business opportunities and take a pragmatic and prudent view of the risk — this is not a bug in the system, but a feature.
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| Note how [[modernist]] this disposition is. The critique addresses only the formal, legible operational fame work. The chains of command. The [[silo]]es. The [[reporting line]]s. The [[dotted reporting line]]s.
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| This is the view of the disembodied luminaries occupying 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 what a machine could do 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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| ===Yes, bank staff are mediocre===
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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]]: [[The temporary tends to become permanent|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. They 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 not 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. Commercial banks act as boggling flywheels ''despite'' disastrous tech and a surfeit of mediocre, bureaucratically-conditioned staff.
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| Imagine setting them free: automating the truly quotidian stuff, re-emphasising away from bureaucracy as the greatest good,and towards relationships management and expertise?
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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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