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What is Big Data?
Thursday, January 21, 2016 6:30 AM

Jay Kassing

Every year or two, the banking lingo morphs and new buzzwords are added to our lexicon. Today, the phrase that pays has landed on “big data.”

A 2010 quote from former Google CEO Eric Schmidt likely started the big-data ball rolling for everyone not named Google. “There were 5 exabytes of information created between the dawn of civilization through the year 2003. But that much information is now created every two days, and the pace is increasing.”

Generally speaking, big data involves having a very large database to collect “structured data” (like loans, deposits, transactions, etc.) from your core and ancillary systems, combined with “unstructured data” (blog posts, Facebook rants, Twitter thoughts, etc.; random data which does not conform to a standard length or content) in the hopes of better understanding your clients, prospects, and trends.

The terminology “very large quantities of data” is most often used when speaking about petabytes and exabytes of data. This is the kind of data required to map the human genome or go to Mars. Unless you're among the very largest financial institutions in the land, you couldn’t scrounge for enough data to get to big-data status.

So, credit unions don’t have big data, but they do have lots of data about their members. Jim Collins, in his book Good to Great states, “The kind of data available to average institutions and great institutions are about the same. The difference is that great financial institutions turn the data they have into information they cannot ignore.” Information of this kind illuminates strategic opportunities.

What would you learn if you made sense of the data you already have?

  • Who are your most profitable members that deliver all of your profit?
  • Who are the 50 percent of your members that have only a single product with you?
  • Who are your members that have loans elsewhere (typically 3-4) and what kind of loans are they?

And, if you knew who they were, what would you do?

A joint research project by the Aite Group and the Financial Brand found that high-growth financial institutions spent twice as much on data analytics than their lower-growth peers. Analytics drives measurable growth. You need member and market analytics.

You use data to measure, plan, and budget your expenses. Why would you not leverage the data you have to understand what your members have and want—and then talk to them about it? Marketing strategy and execution are best built from data analytics.

Example 1: Fee Income Growth

Would you like members who have a credit/debit card with your credit union to use their card more? And with the expectation that more transactions = more fee income? What about members who have a credit/debit card from your institution but haven’t used it at all?

This data is very available. If you can get the who, what, and when for each of these scenarios, you simply need a marketing tactic to go along with each, which will help you achieve your objective: greater fee income. You don’t need big data to do this. You do need data analytics and action.

Example 2: Bill Pay Loan Recapture

Many of your existing members have bill pay. Every month, they are making loan payments from your bill-pay solution to some other financial institution. Why aren’t you looking at this activity and making offers to your members to recapture these loans from your competitors?

Again, this isn’t a big data problem, but it is a data/information opportunity that begs for action.

Example 3: Capturing “Active” Loan Activity

Need loans? Right now, every day, your members are applying for loans with an institution that isn't yours. The data and technology exists to identify and communicate with these members, and to deliver a compelling offer from you almost immediately.

Unless you're a retailer like Walmart, Amazon, Google, or Bank of America, you don’t have big data. But the data you do have can be leveraged to help you achieve your goals. John Naisbitt says, “We are drowning in information but starved for knowledge." Data analytics is the key to unlocking the knowledge buried within your credit union’s member data.

Jay Kassing has been writing for and about the financial services industry for more than 25 years. As president of MARQUIS, he is uniquely qualified to understand and address the concerns of credit unions. Since 1987, MARQUIS has been a leading provider of marketing and compliance software and services, with hundreds of clients across the U.S. Kassing can be reached at 214-778-3015 or