Industry observers are predicting that this is the year in which financial services institutions will finally put their massive volumes of data to use.
Let’s be candid: At this point, just about any discussion regarding the optimal use of Big Data in the banking industry evokes a strong sense of “here we go again,” and with good reason. It’s a topic that’s been endlessly debated since we essentially became aware of data as a powerful business asset. Sure, it’s the ultimate competitive differentiator, and the more of it we have, the more powerful it can be.
But at the same time, there’s almost a maddening level of frustration. First, it can seem like there’s so much data that it’s more a burden than a blessing. More to the point, what exactly should companies be doing with all this data? How can we tell what’s legal, what’s ethical, and what’s even feasible?
It’s not as if data analytics to guide business initiatives is a new idea—in fact, it’s been gaining momentum for at least the past decade. However, the thinking among some analysts is that as pressures from regulatory costs gradually decrease, many institutions will devote greater resources these software programs and services
However, it’s a little more complicated than just having the money and manpower. One major obstacle to faster and greater progress may be that data doesn’t work in a vacuum. It isn’t a weapon per se, but handled right it can power a full arsenal. That means using data—and the analytics that go with it—to fuel outreach initiatives through social media, geo-location, omni-channel and a whole lot more. And therein lies the way forward.
In a widely used scenario, imagine a typical consumer in the market for a new car. He’s searched online, clicked on ads, posted on Facebook, Tweeted to ask friends for recommendations and finally driven down to the auto dealer to check out the newest models. For the bank, this is the ideal opportunity—and it involves a range of disciplines.
The bank’s own data surely features details on the consumer’s spending habits and credit rating, but now there’s so much more. Those Internet searches serve up invaluable information, the social media platforms offer potential avenues for instant (and highly relevant) communication, and geo-location tools with the banking app tell us exactly when the consumer reaches the dealership. Meanwhile, the algorithms build on all nuggets to run non-stop calculations that provide a quantifiable risk static. So now text and/or favorite social channel can be used to reach the consumer directly with a loan offer (and perhaps even credible advice on which car to get, with what deal.
To be clear, many other industries—healthcare, travel and retail, to name a few—are aggressively pursuing similar strategies. There’s also a whiff of discomfort: When does tracking consumers’ activities become stalking? There’s no single answer to all of these questions; in some areas, we’ll learn as we go.
This is why it’s unlikely there will be a single year in which we cross some kind of Rubicon. Instead, with each passing year, we’ll do more than we did before.
So in that vein, let’s look ahead and make our very own, very confidential predictions about what might actually happen. Inside your own organization, however big or small, by the end of 2016:
- Will there be greater resources dedicated specifically to the use of data for ongoing business activities?
- Will the organization regularly acquire data from third-party providers?
- Will the optimal use of data lead to quantifiably greater social media interaction with existing and new customer prospects?
- Will scenarios like the one cited above—combining a range of disparate disciplines, with data at the core—become common, or more common?
- Will omni-channel initiatives become standard operating procedure?
Let’s check back this time next year.