Credit reference agency Experian hold around 3.6 petabytes of data from people all over the world. This makes them an authority for banks and other financial institutions who want to know whether we represent a good investment, when we come to them asking for money.
Like all financial services, they are being rapidly changed by waves of technological innovation sweeping through industry – none more so than artificial intelligence and machine learning.
Machine learning is essentially teaching computers to teach themselves – much the same way as humans can – by giving them access to huge amounts of data, rather than having to teach them to do everything ourselves.
I spoke to Experian CIO Barry Libenson about how the business – a pioneer in Big Data-driven analytics – is adapting to meet the challenges and reap the rewards offered by the new generation of cognitive, self-teaching technology, and the ever-growing data streams which power them.
Libenson outlined three driving forces behind Experian’s move to be at the vanguard of the “fourth industrial revolution”. The first is new and emerging technology.
“There’s a movement towards open source technology which is less costly to operate and scales very effectively, so essentially you have a lot more horsepower at your disposal and can operate on much larger datasets.
“Just a few years ago when we did analytics on a dataset it was based on a smaller, representative set of information. Today we don’t really reduce the size of the dataset, we do analytics across a terabyte, or petabyte, and that’s something we couldn’t do before.”
Larger datasets obviously give a more accurate picture of whatever they represent, leaving less margin for error. This leads to analytics, simulations and insights which more closely reflect real-world outcomes – such as whether someone will repay a loan.