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everal years ago, the CEO of Deutschebank stated in an interview that he thought AI would replace up to half of its staff. The predic on sent shockwaves through the industry and made a lot of employees feel uncomfortable about the longevity of their roles. The bank soon fired him and replaced him with somebody else, so he won’t be responsible for the organiza on’s sweeping changes. But it did reveal just how much hype there is in financial circles about the promise of AI. Other people have joined the fray, calling for the end many rou ne jobs in the banking industry. Ci group execuves believe they will say goodbye to around a third of workers. Japanese financial group Mizuho says that it is looking to replace more than 19,000 by the end of the present decade. But whether the digital transformaon in banking will bear fruit remains to be seen. Currently, there’s a problem right at the core of AI research. The people at the forefront of the movement know that the technology is very good when it has an objec ve func on something to op mize - but it isn’t so good in other situa ons. So, for example, it can maximize the probability that an image shows a cat. S ll, it can’t engage very well in regular conversa on - the sort of thing you need for healthy client rela onships.
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Artificial intelligence is also a long way from becoming what you might call “general intelligence.” The so ware is good at performing cogni ve tasks, but it has no subjec ve experience of them. It doesn’t know what it is doing - it just goes through the mo ons. This fact of the ma er means that some of the more outlandish predic ons probably won’t come true. What we seem to be looking at is something that will allow so ware to perform a subset of cognitive tasks. However, it is doubtful we will see programs with subjective agency any time soon. When you tell them what to do, they’ll do it well. But they won’t be running their own companies just yet. That’s very futuris c. AI, however, is a wishy-washy concept. Unlike the tech revolu ons of the last decade - like the cloud - you can’t easily pin it down. AI doesn’t just do one thing - it is a solu on for a whole bunch of tasks. The banking sector, therefore, is going to have to figure out how to deploy it sensibly. For now, it won’t replace people. Instead, it’ll be more like a tool that makes them more valuable. It is, in a sense, a form of cogni ve assistance, just like machines are assistance for manual labor. Robots can’t do all the work themselves, but they can dramatically increase the
output per worker. The same may now be coming to the banking industry. You’ll s ll need officers to process business banking customers manually, but AI could speed up aspects of the process, like credit checking. The banking sector needs to be careful not to set unrealis c expecta ons of AI. The people at the forefront of the field are more than willing to point out that the science isn’t done yet. They can replicate some aspects of intelligence, but they can’t fabricate it wholesale. Researchers s ll need to make fundamental breakthroughs to usher in that exci ng and giddy new world. To call AI in banking pure hype, though, is taking it too far. There are n umerous examples of AI in banking already, and the technology only connues to improve.
Biometrics For Added Security We first saw biometrics in banking in the film Blade Runner. But advances in technology and AI have made it to make it a reality. And it’s already been done. Bri sh bank Natwest, for instance, now allows customers to open accounts with a selfie. It then stores their data securely, linking their biological profile to their financial informa on. The security benefits of AI could be quite extraordinary. It might sound unsafe, but it is actually a massive improvement over the current system of using government-mandated IDs like passports and driving licenses. Biometric forms of iden fica on are much more challenging to forge and, generally, safer than their paperbacked rivals.
Investment Trading Currently, bankers rely on seasoned traders’ quick wits to make investment decisions in the equity markets on behalf of their clients. Movements, however, are often so fast-paced and unpredictable, that many traders struggle to equal the market, let alone beat it.
