LAS VEGAS–It’s a good news/bad news scenario for credit unions when it comes to data analytics, according to one analyst. But even the bad news has the potential to turn to good.
And that good news includes a surprise source, according to one person: the new financial accounting methodology—CECL—that credit unions have largely been wary of.
“I think this industry is extremely well positioned for the future, especially in member analytics,” said Paul Ablack, CEO of the Minnesota-based CUSO OnApproach.
Paul Ablack speaking to NACUSO meeting in Las Vegas.
But Ablack also made clear that when he says “industry” he means all credit unions are going to need to act together collaboratively, as there are few that are going to be able to go it alone.
“The challenge for credit unions is how do we reinvent ourselves in a retail business where the stakes have gone up dramatically, he said.
The opportunity to reinvent amidst the much discussed retail “disruption” is “knocking,” said Ablack, adding credit unions have the ability to respond to that knock, thanks to the amount of data they have on member behavior.
When it comes to building a data warehouse and leveraging all that member behavior data, Ablack told the NACUSO annual conference here, “This is too big for any one credit union. And vendors have not stepped up. This has to come from across the industry and it has to be vendor agnostic. Collaboration is going to be very important.”
That’s because data and connectivity have intersected to create “the perfect storm,” said Ablack.
The Real Story
Ablack, who sub-themed his presentation “How to Prevent Getting Ubered,” noted that the real story isn’t that in just two years in New York City ride-sharing service Uber took 30% of the market away from taxis. The real story is it isn’t just any business that Uber has taken: it has been the best business. “They took the best customers and the most profitable rides. One question for you to ask is what percentage of your members generate your profits and dividends. The rule is 20%, but I’ve seen cases where it’s smaller than that. When those members start being skimmed off, that’s where the trouble starts.”
For credit unions, learning from online retailers is critical, said Ablack, citing Amazon and others that are taking advantage of “people creating information for free for retailers through reviews. And that is one dynamic that has really changed, which is to create information about your products and to create value around that.
“What Amazon has really figured out is association analysis,” continued Ablack. “It’s why Best Buy has power strips in all sorts of locations. For credit unions it’s the same thing--when you sell an auto loan, you want to make sure to get insurance products, and want to offer other products as part of the bundle. We have all the data we need to do a really great job. None of Amazon’s data sits in silos; it’s related and integrated. When you look at retailers they don’t have the kind of information credit unions do.”
For Trends To Watch
Ablack said there are four trends CUSOs and credit unions should be watching:
- Mobile Usage. Measure mobile/online vs. physical branch activity.
- Payments. “How can you monetize that payments data? Every other industry is doing so. Some merchants are paying a credit un ion or group of credit unions because they want direct access to those members.”
- Peer-to-peer lenders, such as Lending Club. “My concern is what is that going to look like in five years? They are doing a lot of origination of loans on some sketchy data.”
- CECL (Current Expected Credit Losses). “This is about the probability a loan is going to fail. Regardless of how this ends, the real opportunity here is around pricing opportunities, better managing risk, and better managing attrition. CECL has driven us toward developing better predictive analytics around member behavior on loan.”
Given the size of the task, and the limited resources of most CUs, Ablack said he has watched as many credit unions have turned to outsourcing. But that creates another issue, he said.
“A lot of data you see today is being shipped out for someone else to do the work. But whoever is doing this is becoming enriched by the data being sent to them, rather than that data staying with the credit union.”
The New Gold
Similarly, Ablack called data the “new gold,” but good analytics also come with a gold-like cost.
“The question is how does a credit union solve this problem of having the data but needing to bring it all together,” said Ablack. “I will tell you that the resources needed to build a data warehouse are outside the reach of most credit unions. If you want to build it, you have to budget at least $2 million over three years for a base solution. I think the largest 50 CUs can afford to do that and support it, but even for a $1.5-billion CU it’s a stretch; that money is coming right off the bottom line.”
Smaller credit unions need a hosted solution, said Ablack, and all credit unions need to be working together.
“A solution for the industry requires thinking about the whole spectrum of 6,200 credit unions,” he said. “That’s why this has to be a CUSO solution. Our job as a CUSO was to build this really good X-Box and then to partner with credit unions to build out the games. Some of those games require a lot of data. If you’re going to do predictive analytics and you’re a $1.5 billion CU, you don’t have enough data to predict a loan loss. So you bring it all together in a pool and then you can begin to make predictions.
Among the CUs with which OnApproach has worked and which is effectively using analytics is Topline FCU in Minnesota, said Ablack. It uses association analysis to identify the “next best product” for the member. “They are able to use specific marketing based on the specific behaviors of the member, such as how they use their checking account. We are redefining the MCIF analysis and looking at transaction level rather than the product level. FICO is not a good predictor of risk or pricing. Good margin models come from good forecast models, especially in pricing per segment.”