Big data has the potential to revolutionise banks’ understanding of their customer base, allowing them to target individual business needs. But are banks ready for this new internet age? 

Everyone is talking about big data these days. Big data means taking the massive volumes of data we receive and analysing it in depth to create sales opportunities with individual customers. So why do banks find this such a challenge?

The term big data has been around for a while now, but where did it come from? The term actually derives from around World War Two, when the phrase big science was used to describe the rapid cycle of changes in scientific disciplines during and after the war.

A good example of this rapid cycle of change was the invention of computing. John W Mauchly, a physicist working at the Moore School of Electrical Engineering at Pennsylvania when the war began, believed that an electronic computing device could be created to predict the weather. The idea was floated in August 1942 and, by June 1943, funds were allocated to the project. The system that was developed was called Eniac, the electronic numerical integrator and computer, otherwise known as the world’s first computer.

In the beginning...

The term big data was first used in the late 1990s, although no one can put their finger on how it came about. It appears to be through a combination of academic papers and the work of IT research and advisory firm META Group. That firm, now known as Gartner, defines big data as: “high-volume, high-velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimisation”.

It would be simpler to say that big data is a phenomenon where every person on the planet is creating so much digital output that we are drowning in data.

This is well illustrated by Google’s CEO, Eric Schmidt, who noted that “there were five exabytes of information created by the entire world between the dawn of civilisation and 2003. Now that same amount is created every two days.”

An exabyte is a 1 with 18 zeroes after it – or 1,000,000,000,000,000,000 bytes – an incomprehensibly large number that is generated every two days by mobile phones, Facebook, Twitter and so on. It is important to get to grips with the issue, as those firms who make sense of big data will be the winners.

This means war

Data is the new source of competitive warfare and data mining will be the weapon of mass destruction of the competition. The firms that really get this are the ones that have been spawned for the internet age: Amazon, Apple, Google and Facebook. Banks fear these players, because they know how to sift the data and make sense of it.

As one bank chief executive recently said: “Our peers I can handle. We’re in the same boat. But if Google opens a bank with all its data, then we’re in big trouble.”

Eran Feigenbaum, Google’s director of security for their apps, regularly refers to Google as “a bank for your data”. Surely, this should be cause for concern for banks, especially considering how they operate.

For example, if Amazon was a bank, the book division would not talk to the music division. The music division would not talk with the electronics division. The retail business would not talk with the wholesale business. The wholesale business would not talk with the cloud business. Oh, and the Kindle division would not even talk with the book division! None of these units would share customer information with each other and, as a result, no one would know what customers bought from Amazon as a group, when they bought it or with which payment type. In other words, Amazon would be organised in silos of business that competed with each other at a granular level. Amazon’s success is because it is organised differently and uses data effectively.

That is how many of the banks I deal with are structured and the silo divisions of banks mean they ignore their greatest competitive weapon: data. Something has to change, or banks will cede their greatest asset to the new banks of data, such as Google.

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