More than a few folks in recent months have pushed back a bit on one of our 6 Big Ideas for 2016, Disruptive Collaboration. The gist of the critique is that the CUSO model works just fine as it is. And it does, to a point. It’s one of the great wonders of the credit union movement, one of our greatest assets, and the source of immense potential competitive advantage.
Potential. That’s the crux of it. Are we making the most of the model, of our ability to collaborate, and of our ability to work together to beat the competition?
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My sense is no, we’re not, but we are making progress. Over the past few months, I’ve seen that progress most clearly in the area of advanced data analytics (Big Data for the buzzwordy among you).
In January, I used advanced data analytics as a poster child for the potential of greater, deeper, broader collaboration to be a game-changer for credit unions.
Most credit unions barely scrape the surface of their vast array of data, let alone integrate other useful information, apply powerful learning algorithms, and derive actionable business intelligence. But data analytics is central to everything we do marketing, management, and risk mitigation obviously, but also the development of core member relationships and the ability to support improved and sustained member financial health.
I learned a lot of about this at the second annual Credit Union Big Data/Analytics Conference, organized last year by Paul Ablack and his data warehouse and analytics company, OnApproach. A number of things surprised me there, but the biggest one was a sponsor that wasn’t selling anything, just advocating for clean, accessible data and the kinds of open systems that foster a network effect.
Creating such data is their business, but their plea wasn’t for credit unions to use their services, just for credit unions to do the work and to demand that philosophy from whomever they choose to have help them. Not what I expected, even from a CUSO, but the catalyst for a terrific meeting full of energized, committed practitioners.
Everyone who spoke at the conference was in the data analytics business. Some represented old-fashioned approaches (small data?); others were close to the cutting edge. Some were clients of OnApproach, some were their partners; others worked with OnApproach competitors.
What tied them together was a belief in high-quality, reliable, complete data and the clout it can deliver for all credit unions if the movement will make a universal commitment to it. They shared a belief that clean, easily accessible data and transparent, open data governance standards will enable credit unions not just to survive but to thrive.
Everyone understood that just giving a damn isn’t enough anymore. Credit union competitiveness and the member-owner model depends on the empowerment of knowledge, the insight that can only come from exceptional data analytics.
If there is an underlying message from this conference, it comes in two parts. One is that credit unions can either complain about this set of facts or respond to it, but it isn’t going away. Big banks have already spent hundreds of millions of dollars on advanced data analytics. We don’t have to play in that league to survive, but we do have to play. The second is that our chances are much better if we find ways of working together.
This was also the theme of First Tech’s recent Data Analytics Summit in Silicon Valley. It was a different kind of affair, with minimal vendor presence and a couple hundred credit union IT and business intelligence professionals talking about the challenges they all have in common: how to win executive buy-in, capture and best employ an adequate budget, create standards, learn from one another, and achieve scale.
In a world where data analytics is already a difference-maker, and where credit unions uniquely have the freedom and experience to work together effectively, these should be straightforward, achievable objectives, non-trivial but attainable. They are not. That’s why it’s time for a new model of collaboration bigger in scale, broader in scope, and less parochial in scheme.
Scale matters in data analytics. The more data you have, the more effective advanced data analytics is at teasing out the kinds of insights and intelligence that move the needle. The entire American credit union movement combined is smaller than any one of the four largest banks in the country. The only way for us to compete effectively is to be smarter, more willing to think outside the box, and more willing to work together.
From the Callahan perspective, that means every credit union needs its own data to be clean, interoperable, and freely accessible, but that’s just the starting point. It also means transparent data standards to facilitate data aggregation on a massive scale across the industry, standards that are universally embraced and forced upon even the most parochial and self-interested of vendors. It means open platforms to foster the network effect among data scientists and entrepreneurs whose skill and knowledge will be central to the whole endeavor.
Of course expenses matter as well, but this isn’t about saving money. Credit union analytics budgets are going up whether there is collaboration or not. It’s not a matter of how much we spend, but of what we get for it, and there, too, scale and collaboration promise tremendous dividends.
Since holding their Summit in February, First Tech’s analytics team hasn’t slowed down their efforts to drive collaboration. They’ve held webinars and fostered ongoing network development with any credit union data professional who is ready to engage. Their plans are ambitious, if still evolving, and I expect more to come in the near future.
In the meantime, there is already more coming from the folks in Minneapolis. Their third annual conclave, renamed the Analytics and Financial Innovation (AXFI) Conference, is happening the last week of June. I’ll be there. Whether you are or not, you should pay attention to what comes out of it it’s going to matter.
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