It is nice when a story about your industry comes across your desk, promising to enliven what may have a been a run-of-the-mill day. Even better when the article in question seems to have missed the most-vital element of the narrative but instead skirts around the edges of the real story. The story we are referring to was reported by the Financial Times in its Big Read section last month called ‘AI in Banking: The Reality Behind the Hype’ (paywall). The report was written by Laura Noonan, the FT’s investment banking correspondent.
The report begins by focusing on three predictions. Firstly, a now-former Deutsche Bank chief executive positing the idea that half of their 98,000 workforce could be replaced by robots; secondly, a former Citigroup chief saying AI could take over 30 per cent of banking jobs within five years; and, third, Mizuho Financial Group saying AI will replace about a third of its employees by 2027.
Other facts, statistics, and predictions abound–UBS using Alexa for customer service, JP Morgan using robots to execute trades, Morgan Stanley’s AI fraud detection team, and HSBC saying it would use AI to detect money laundering, fraud, and terrorist funding. The paper reported that one bank predicted that ultimately 50 to 70 per cent of jobs could be replaced by AI. The numbers illustrate a move towards an increased uptake in AI by banks. The report points to one European bank that said it had between 500 and 800 people working on AI and to another bank which is looking to increase its spending on AI from less than $3m a year to more than $50m.
However, the assumption is that robots are there to replace humans. But that is not true. The truth is that they cannot. But, as we’ve said before, there is another way. And that is because the best way forwards will be for robots not to replace humans but buttress their ability to work on high-quality and in-depth tasks.
This is not so much alluded to within the report as said directly. As Foteini Agrafioti, head of Borealis (Royal Bank of Canada’s AI research arm) is quoted, “There are too many people making these statements [about big cost and job impacts]. The problems we have solved are very narrow. The misconception is that humans and machines can perform at the same level. There’s still a long way to go and many challenges we need to solve before a machine can operate [at a level] even near the human mind.”
A quote attributed to ING goes further. “We would like to use AI to bring smarter solutions to our customers, and be more effective in our decision making processes,” the banking group is reported to have said, “As such, rather than ‘AI replacing workforce’, we believe in the power of ‘AI-empowered workforce’.”
We’ve recently put together something for a major bank in Germany that we feel best illustrates this. One of our teams recently developed a mailbot that automatically sorts IT requests from employees and sends them to the correct department. This is done through a semantic analysis of the text, made possible by Retresco’s technology, that leads to a form being filled out. If the system is unable to put together an answer from the available data in the text, the message is returned to its sender as a follow-up. While we may have eliminated the part of an IT manager’s role to sort through these requests, we have freed up that same manager to do something more creative and human-centred.
That sounds glib and while some employers may use AI to reduce a workforce, a more economical, streamlined organisation may be better placed to serve customers. There will also, if things go to plan for the big banks, the funds to do this. Says the FT article, “Of the seven big banks willing to estimate the long-term cost savings of AI, six said it would cut costs by less than 20 per cent, others were more optimistic.” That’s a fairly-negative statement but cutting costs by anything is generally a good move. And those funds could be used to fund development, a greener organisation, or charitable outgoings.
The future of work is AI-augmented. It’s time to embrace, not fear this. Contact us to find out more about how NLG can help.
Founded in Berlin in 2008, Retresco has become one of the leading companies in the field of natural language processing (NLP) and machine learning. Retresco develops semantic applications in the areas of content classification, recommendation, as well as highly innovative technology for natural language generation (NLG) . Through nearly a decade of deep industry experience, Retresco helps accelerate its digital transformation, increase operational efficiencies, and enhance customer engagement.