#BigData is not a phenomenon unique to fintech: basically every consumer-focused service with the money to do so has been utilizing it since the term was first coined in the late 90s; or
even before that point, really, as using data to make decisions is the literal definition of deductive reasoning. So why are people, especially fintech people, so excited about it?

The hashtag #bigdata is currently reaching around 2.2 million users on Twitter, with about 380 re-tweets this week, according to data collected today. Interest in big data has increased pretty much parallel with the world’s Internet usage, though again, use of data hasn’t really changed. But the sheer quantity of it has, which dramatically multiples the possibilities for its applications, and that makes all the difference.

As such, big data has become incredibly important for most industries and especially in industries like fintech, since the company who has the best understanding of the consumer –especially we tricky millennials–is the one that’s going to succeed.

Companies have more data on consumers at this point than in any other time in human history, so the focus on big data is no longer on its collection but on its application. That means wading through trillions of bytes of data, most of which has been created in the past two years, though only around 1% is ever actually analyzed.

To avoid getting overwhelmed by the massive amounts of data collected on a daily basis, banks today have to  have a sharp line of focus when analyzing it which is why machine learning was invented. Feed a computer a stream of consistent data about the area you want to improve, such as your mobile banking app or improving payment solutions, for example, and you have fast, efficient, and clear results.

However, simply crunching the numbers isn’t enough; as yet, AI technology has not evolved to the point where it can recognize if the numbers generated are actually useful. (Which in fintech, as in most businesses, means profitable.)

Currently, companies still have to rely on the human intellect to come up with a clever use of that 1% of data. Today, this is what drives the success of both digital or brick-and-mortar banks —  the majority of which offer online banking anyway. According to a paper published this year by MIT, which can be viewed here, use of “smart big data” from an investor, as well as a banking perspective, is “the cornerstone of the digital banking edifice.”

“It is imperative to be able to evaluate collected customer transactions in real time and connect them for prediction of future customer behavior using deep learning and other probabilistic algorithms,” the report reads.

The importance of big data to better understand what consumers today want, need, and are currently spending money on is not lost on traditional banks either, and is used by members of the Old Guard, like Goldman Sachs, to make sound investment choices, as well as predict customer choices and banking trends.

You can check out Goldman Sachs’ podcast on the subject here, where Chief Investment Officer of Goldman’s Asset Management’s Quantitative Investment Strategies team Armen Avanessians predicts that, to use a sports metaphor, the banking world is in the “third inning” of big data, where both fintech and traditional banking services alike are just fulling realizing what can be done with its use.

Avanessians was also quick to point out, however, that data should be used as exactly what it is—a tool, one that can only be fully understood and acted upon when combined with a human’s intuition.

To learn more about big data, join us at Bank Innovation Israel in November. Register here.