Do credit unions have the expertise needed to tackle data analytics?

Do CUs have what it takes?

No one doubts that the very largest credit unions have the expertise – or, at the bare minimum, the financial resources – to effectively tackle data analytics, but those institutions aren't representative of the vast majority of the credit union landscape. During the Analytics and Financial Innovation conference in Minneapolis recently, CU Journal asked experts and analysts if CUs at large have the expertise they need in data analytics – and, if they don't, what will it take to get it?

John Best, CEO of Best Innovation Group

We’re like two years behind, most of us, and I worry about that, because it creates a threat level that bothers me… The good news is we have a better shot at organizing and curating our data than most big banks. If you think about the scale of most really large organizations, the challenge we run into with them is that they’ve got data all over the place. They’ve got separate systems for every single thing; in some cases they have more than one system of record across an entire banking institution. Generally credit unions have a single system of record and so finding that data and getting it together [should be easier]. It’s like a race track: there’s a big straightaway for them, but they’ve got to get engaged.

Anne Legg, CEO of Thrive Strategic Services

It really goes back to what is it that the credit union is trying to achieve? As I see it, there’s a lot of beautiful collaboration happening up and down the asset-size scale. But I wouldn’t want anyone who’s super large or super small thinking they’re out of the game, because they’re not. That’s the beauty of where we are right now, especially with the scalability and the affordability of tech….You’re seeing a lot of different opportunities happening for smaller credit unions. I think CUSOs are going to be seeing a lot of other different players coming in, too.

Andrew Bertrand, data analyst at Our Community CU, Shelton, Wash.

At my credit union, I was in marketing before; I just happened to do the marketing analytics and they recognized that and pushed me forward. It all depends on your staff. … It’s a matter of training. You have to leverage a lot of training, but the main thing is going to be putting the money into training for this person. But you’re going to have to pay a premium for this person, too. That’s going to be the main pain point: can you afford to pay them and keep them happy?

Julie Carpenter, CFO at Ohio HealthCare FCU, Dublin, Ohio

We offer benefits to compensate for the pay. What’s important to a lot of up-and-coming staff members right now is work-life balance. That’s a buzzword and we offer that. We’re a small credit union [$82 million] so we have a lot of empowerment to offer to our employees, but also giving them the flexibility to work from home, to work the hours they want to and trust they’re putting in the work and not the 8-to-5 sitting in the office. And that can compensate for the pay that you might not be able to offer these individuals.

Ben Morales, chief technology officer at Washington State Employees CU, Olympia, Wash.

We need to figure out how we put fintech in a box and be able to stand up a quick fintech solution so that credit unions can use that platform to innovate around data, to get quick to market to “try and fail” on things, without trying to do all this on premise. How do we build a cloud solution that we can turn on and mange for credit unions? That’s the barrier – because the credit union can do the ideation, can get people, can do the journey mapping, but then they need someone to do something with it. There are tons of resources and capabilities in cloud and business partners that if you just had them aligned, credit unions of all sizes could begin to innovate around data and digital, but the issue is how do we lower the complexity?

What I’m hopeful for is that there’s a lot of big credit unions doing good work that we can figure out a model where the smaller-end credit unions can contribute their data so they can get the value and benefit out of it, and then the aggregation actually creates value for the pool of people participating. The more data we have, the more accurate we can be; and as a participant putting your data in, you get access to all of the modeling capabilities and the things you want to look at. I think it’ll be a CUSO model that’s going to do that.

Clay Yearsley, SVP of data analytics at Texas Trust CU, Dallas, Texas

We’ve talked a lot over the last couple days [at the AXFI conference] about data scientists. A data scientist costs $200,000. We don’t have the wherewithal to hire a couple of data scientists, so what we can do is fall back on what CUs do well and have done well historically, which is collaborate with each other. That’s why I really like the CUSO model, because on a macro-economic level we’re taking resources we can’t individually afford and spreading the costs of those over multiple organizations. That’s how we can do some of these things is to pool together. Whether we actually have an agreement with all of these other credit unions to do that or it takes an organic form and a couple of CUs get together and start offering this service … then we can go to that resource and we’re pooling our resources in order to have access to those skills and tools we need to move forward. It’s a more democratic way of going about doing these things rather than having each of us going in our own direction and having to accumulate the resources it takes to do that. It really is an opportunity for smaller credit unions to be able to do some of the same stuff that the very biggest ones are doing. But we have to use some of these resources that are pooled.

Brewster Knowlton, owner and principal consultant at the Knowlton Group

Most of them think that getting somebody that knows SQL or knows how to do the report development is a really tough skill and is really hard to find, but it’s actually really easy to take somebody from IT [or elsewhere] and train them on some of that stuff. So if you have somebody that knows how to do SQL and you have somebody who knows how to do that reporting, even at a very basic level, then what you can actually start to do is have them point those queries and reports at systems you already have. So even if you don’t have a full data warehouse, you can actually start to do some business inteligence. That’s the path that I think a lot of sub-$250 million or sub-$500 million credit unions should be doing, because they can take advantage of the data they already have. Even if it’s just one person – maybe it’s that marketing person or that financial analyst who’s really good with Excel – they can teach them how to do that with just some classes and you can start learning form that and start to develop things very simply and easily.