Credit unions are in a strong financial position. They've done well managing assets, and many are on growth paths. They're increasingly competing with banks in attracting and retaining new members. They’re feeling strong and competitive.
And I’d wager many credit union executives feel public perception is in credit unions’ favor. More than 80% of that much-coveted millennial consumer demographic
But the data doesn’t back that up. A
Another 87% are satisfied with their credit card issuer; 81% believe their credit card issuer has given them good information about the rates, fees and risks associated with their card. And 83% are satisfied with their mortgage lender.
Which means credit unions may not be as infallible as assumed. And there are some major areas of catch-up for a number of credit unions — even the big ones — if they want to compete. To me, one of the most critical,
Calling it low-hanging fruit makes it sound inexpensive. Let’s be blunt here — it’s not. But it’s obvious and it’s essential.
Financial services companies have long-established data warehousing, business intelligence, advanced analytics and data governance programs credit unions can learn a lot from. In other words, credit unions can learn from banks’ decades of failures, innovations and billions of dollars of investment to target the best strategies with minimal trial and error.
Credit unions are often an amalgamation of silos, both operationally and in data management. It’s the result of an underinvestment in IT, perhaps because of a focus on controlling costs with the intent of benefiting and serving members. But it’s done the opposite.
And now it means credit unions often don't have enterprise-level programs for data management. Why does that matter? It limits credit unions’ ability to make decisions based on data.
When data is highly siloed, with management reporting being provided by each of the different vendor-provided operational systems, credit unions aren’t able to see a complete picture of their members. Their peers in insurance and banking are able to analyze their data — often to a scary degree — across all their systems via enterprise business intelligence tools which are fed data from integrated data warehouses (governed by mature, business-led data governance programs).
Too many credit union managers and executives are limited to looking at their business on a system-by-system basis, lining up reports side-by-side to make their own comparisons instead of having integrated dashboards and reports that allow leadership to spend time understanding and analyzing instead of cobbling.
Sound familiar? It can be intimidating to know where to begin, but it doesn’t have to be all-or-nothing.
First, make sure you have a clear business strategy. Data and technology strategies can only be as strong as the business strategies they support. Then assess the opportunities for value that exist in the data and relate them back to strategic business goals. What positive business outcomes could come from improving your data assets? This provides the high-level understanding of what is needed.
Then the real design and implementation work begins. Executive sponsorship and involvement is critical to the success of any budding data management program. The payoffs with better business intelligence and analytics are high, but the costs and risks are too. There must be resource commitments such as subject-matter experts, internal IT staff, licensing of tools and consulting.
To justify the investment, there has to be value. And there is.
Data management allows for analysis that leads to efficiencies. With data management investment comes the opportunity to automate things that were manual, the ultimate efficiency.
Credit unions also have the chance to tie together data from multiple vendors and build solutions that let them ask better questions of their data and better compete.
Good member experience analysis provides access to generational understanding and how changes in member demographics drive the different ways people interact, allowing credit unions to focus on giving members what they want, on their terms. You don’t get that from individual operational reports across systems. You have to look at how people interact with the whole credit union and ask the right questions to draw meaning from the data.
And then there’s compliance. Every financial institution deals with growing and changing regulations and reporting requirements. The government expects organizations to have an integrated picture of their member data, among other things.
To have a clear picture, you must have a consistent definition of what a member is across all your systems. That often requires an independent integrated data source. A place where we bring together all the information and define, “This is what a member means.” Then you can report that. Compliance will always be with the entire financial services industry, and data management will always be the make-or-break factor in efficient and effective reporting.
Credit unions are already doing well. Imagine what they could do if they had better analytics and better data management capabilities. You don't have to be as big as Bank of America to make better decisions through data, but you can compete with them.
Credit union executives can drive this transition — and secure their credit unions’ future success — by finally harnessing the power of their data assets and tackling the hard work and risk that comes with growth.
