Author: Kevin Moland, KMoland@profitstars.com
A couple of Octobers ago, I asked my seven-year-old son what he wanted to be for Halloween. He replied, “Dad, I want to go as a pickup truck.” I explained to him that we didn’t have the time, materials or tools to create a truck costume. The next morning, however, I saw a large box in the garage and it got me thinking. Two nights later, my son proudly stepped out in his cobbled together cardboard version of a Ford F150, complete with chrome—ok, aluminum foil—bumpers, a poster board grill, and two hastily configured guitar straps that let the entire chassis rest on his little shoulders. It was the best Halloween of his life. His “truck” wasn’t perfect, but it got rave reviews at every house we visited, and I got brownie points that lasted until the next Halloween, when he expectantly declared, “Dad, this year I want to go as an eighteen-wheeler!”
When I hear financial industry pundits talk about how banks and credit unions need to leverage their payments data to better understand their customers’ needs, the look I see on bankers’ faces reminds me of how I felt on that pre-Halloween evening, sitting in my garage with a cardboard box, a few cans of spray paint, two rolls of duct tape and a crazy vision of a costume that I didn’t have the slightest idea how to build. In short, I empathize with those who are asked to do a seemingly impossible job without the appropriate tools.
When it comes to making better use of our data, the pundits are right: The answer to some of our most important questions lies buried in activity logs, audit tables and archived databases. Collectively, this information can tell us what our customers/members are doing, what products they’re using, even where they’re spending their money. Companies like Apple, Microsoft and Google would happily shell out a few of their hard-earned billions for a look at the financial service industry’s treasure trove of data.
Financial institutions spend a lot of time and money providing space for it and protecting it, so why do so few spend time doing meaningful analysis of the data stored in the nooks and crannies of their IT systems?
Simply put, they don’t have the tools to do the job.
Financial services vendors have been busy turning new technologies into popular product channels (e.g. – Internet banking, mobile banking, mobile remote deposit), but there has been little progress in helping banks and credit unions utilize the increasingly complex flow of payment data generated by these new services. Without the means to quickly and intuitively evaluate their data, most financial institutions resort to burdensome manual processes to monitor customer activity. Many just give up.
With recent regulatory changes and a renewed examiner focus on anomaly detection, financial institutions have to do a better job of utilizing the information they store, if only to protect themselves. Instead of using security as an excuse to leave transaction information cloistered behind firewalls and network security defenses, software providers must give financial institutions better methods to view key metrics and drill down to determine the behavior and status of key account holders.
Unfortunately, developing data analysis tools is difficult and expensive. Efforts to give banks and credit unions the ability to instantly and intuitively slice payments data can impact the entire payments platform, even requiring major changes to how the data is stored in the first place.
But there is some good news! The industry and the market are beginning to reward vendors that help clients analyze their data. Earlier this week, NACHA awarded SmartSight®, an interactive dashboard that powers actionable insights from payments data running through ProfitStars’ Enterprise Payment Solution products, the 2013 Kevin O’Brien Award for ACH Quality. And as other tools appear, similar industry accolades are sure to follow.
The primitive days of analyzing information with the equivalent of duct tape and aluminum foil may soon be over. Financial institutions are beginning to look at data in innovative new ways. Once they have the right tools, banks and credit unions will finally be able to see past the numbers to understand what the data means.
What tools have you found most helpful in analyzing your data?
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