Human Intelligence & Small Data
The interest in “big data and artificial intelligence” is overwhelming – but will machine learning and data from the past save the financial services industry from disruption?
The financial services Industry is surrounding itself with an exponentially growing sea of data measured in zettabytes, that’s terrabytes with additional 9 zeros. This doesn’t in itself help banks under pressure but if you add new financial technologies such as “big data” and “artificial intelligence” experts believe that financial institutions will be able to get a better understanding of what goes on, make smarter decisions and design new tailored services for their customers. IBM talks about the future cognitive bank, where the ability to decode the data stream into information will transform the industry and Accenture talks about the big data revolution that will bring new profitable growth to the sector. Few if any disagree with these predictions and all the big banks and technology companies subsequently pour tons of money into fintech startups working with new solutions based on “big data” and “AI”.
Several successful hedge funds are now entirely based on artificial intelligence and the founder of the Hong Kong based hedge fund Aidyia, Ben Goertzel, said optimistically last year: “If we all die, Aidyia will keep trading”. Capital markets are different from consumer banking but it’s generally the same everywhere. It’s an algorithm that decides whether I get my loan or not, it’s an algorithm from Marks and Spencer that has chased me through the Internet since my x-mas shopping and it will be algorithms supported by Big Data and AI that control future banking services, it seems.
To be honest – I think artificial intelligence and big data are overrated. It’s about time modern banking started to make human intelligence and small data a priority.
I’m supported in this line of thinking by the branding expert Martin Lindstrom. In his new book “Small Data: The Tiny Clues That Uncover Huge Trends” he writes that corporate decision makers are far too focused on finding the answers to their problems in big data from the past. Instead, he suggests they look at the way people behave in every day life. All the little things people do gives you a far better understanding of their behavior. Lindstrom mentions, that the founder of IKEA, Ingvar Kamrad, makes most of his decisions based on what he learns from watching and talking to customers in the checkout queues. This is what Lindstrom means by small data.
When so many banks are exposed to disruption it’s more likely because they neglect the small data that big data. Let me give you a couple of examples: The onlinepayment service Dwolla was founded in 2009 by Ben Milne, because he had a company selling speakers and was annoyed about paying 4 per cent in fees to credits card companies. The Revolut app, that saves its users from currency exchange fees was started by Nikolay Storonsky for more or less the same reason. Simple in America, was founded by Josh Reich because he felt that traditional banks were so complicated and the other day I talked to Samuel O’Connor, one of the two founders of Monizo, who plan to launch the first online bank for freelancers: “We have talked to a lot of freelancers, we know what goes on in their minds and what it takes for a bank to help them”
Despite their fine equipment, I’m sure meteorologists sometimes look out of the window to see what the weather is like, and we forgot to do just that up to Brexit and the presidential election in America: Leave and Trump came as surprises to most of us despite all our data and algorithms. I think it’s time banks too started to look for small data and care more about what happens on street level.
Of course, I know that we will see more to big data and artificial intelligence in the future. But while the capital market is trading by itself supported by my robo-adviser, and the autonomous cars are driving around London with robots on their way to work and Marks & Spencer takes care of my Christmas shopping far better than I’ll ever be able to do myself – I’ll sneak out of the second world with my hard-earned cash and put it into a bank where management has human intelligence and can interpret all the small data I reveal when I talk about my trivial problems.
Consulting futurist and founder of
This article first appeared here