Use analytics to highlight the credit union difference.
When credit union leaders think about using data to improve their services, they often focus on what they can do with analytics or worry about how to do it. But the real question they need to focus on is why.
Why do credit unions want to use analytics and what goal are they trying to reach?
“I find it really helps people to ask them ‘What do you want to do and why do you want to do it?” rather than ‘How?’” says Andrea Brown, SVP/growth at Lodestar Technologies Inc., a Toronto-based provider of data services and analytics for financial institutions that in early March was acquired by Evergreen Services Group.
Brown observes that people and businesses new to using data analytics often get hung up on the process. “They say, ‘We have this big idea, but we don’t know how to do it,’ and that’s OK because we do know how, or we can help you figure out how.”
So Brown says she asks credit unions: “What do you want to do and why? The why is important.”
For example, if a credit union CEO is thinking of using data to implement a rewards program, it’s common to get sidetracked worrying about “how to track this and this and this, and they’re going to paint themselves into a very small box because they don’t know, and that’s not their job.
“People really put up a lot of barriers that don’t exist when they approach it from ‘How do we do this?’” Instead, she says, executives and boards need to think about what they want to do for their members and their organization and why that initiative matters.
Brown notes that every credit union is on a data journey; even small ones that don’t think about it are no doubt using data for basic reporting or operational tasks. In fact, that’s sometimes where she starts her questioning process—by asking what operations are currently being carried out by sharing Excel spreadsheets that need to be filled in by several people.
“It’s easier to start with something simple like this than it is just to pick something out of the clear blue sky,” she says. “A lot of times people don’t realize how much data they have. They might not think about certain systems in terms of what data they can pull from it.”
She points to loan origination systems and the wealth of information they hold, even on loans that have been rejected or not completed.
“The loans that aren’t booked are a huge set of data that you could be mining for people who’ve been approved and haven’t closed the loan, or you could do a ton of analysis on applications that are not approved and see if you need to make program changes,” Brown suggests.
Stuck in Silos
Data silos and data that is stuck in proprietary systems continue to be problems for many credit unions.
“Siloed data is a challenge, and I think because it’s so siloed and separated, people have a hard time thinking about how they would use it and the value of bringing it all together,” Brown says.
Lodestar focuses on helping credit unions create data warehouses that bring together all their data so it can be accessed and analyzed. This approach integrates all the data into one usable source.
The problem of data silos is not just caused by legacy systems, she explains. Even some newer platforms “aren’t putting a huge focus on data.” That usually means the credit unions using the software aren’t understanding the full value of the data being generated or collected. “If [credit unions] don’t have the vision for how they’re going to use it, they’re not going to put a lot of time or effort into figuring that out.”
Dan Demers is CEO and co-founder of Cinchy, a Toronto-based company that says it “liberates data,” allowing for collaboration, not integration.
“The traditional approach to data management and data architecture allows organizations to start off with something that seems simple, but as they add more capabilities, it ends up adding more complexity,” Demers says.
Cinchy’s approach relies on bidirectional links between data sources so that data can be shared without being relocated. “What you can then do from there is start to build this network and create connections between the data without having to do integrations between the systems,” he says.
Demers explains the difference by comparing the way a group can work on a shared Google Doc, making changes in real time, together. Compare that to individuals making changes and emailing their versions to group members.
“It’s like jailbreaking the data. The link is really freeing the data from being limited by the application. We’ve separated the data from being constrained by the application that created it, hence the term ‘liberation.’”
The collaborative approach gives credit unions control over their data without needing to provide access to Cinchy.
Ty Robbins, chief data officer at $1.4 billion First Service Credit Union based in Houston, Texas, said he turned to Cinchy for its data platform technology because he knew from experience how difficult it is to curate data and turn it into useful information. Several years ago in his previous position at Oregon Community Credit Union, his team spent many months manually building and automating processes to move data and doing custom programming to build a data lake from scratch.
After all that work, “I was skeptical, but we signed the deal with Cinchy in December, got everything installed in January and February, and after they applied their liberator, within two weeks we were writing reports,” Robbins says. “Once you liberate the data, its use cases are really up to your imagination.”
First Service CU is now moving towards real-time visibility of its operations focused on leading, not lagging, indicators.
An example of a lagging indicator is your bathroom scale. When you get on it, it gives you an accurate number at that moment, but it does nothing to change the behavior that got you there. Similarly, members’ account balances are lagging indicators that can imply problems but do not give a clear picture of causes. These are the results or outcomes of activities and events, whereas leading indicators look toward future events.
Robbins says cash flow can be a similar lagging indicator for credit unions—and it’s only so useful on its own.
“A lot of credit unions look at their end-of-month cash flow report and see ‘We had this many deposits and we made this many loans,’ but does the data go deeper and [show us] if the money is staying in the institution or moving elsewhere? Did somebody just convert from cash in a savings account and put it into a well-yielding CD?”
Demers says some credit unions get too excited about the technology and begin to dream of new uses when they should focus on starting simply. “Start with what you’re actually trying to get done. If you need reporting, start with reporting. If you need simple integration, start with a simple integration. Honestly, the less mature you are, the bigger the opportunity is for you.”
For some credit unions, the challenge is finding a way to manage and use the data they have on hand without overwhelming staff.
Wade Decker, CFO at $1.2 billion Financial Plus Credit Union, Flint, Michigan, said his credit union knew it had a wealth of information, but it didn’t have a system to display and use its data nor the skills internally to build such a system. This led the CU to partner with White Clay, a data analytics firm based in Louisville, Kentucky.
“We’re extremely fortunate,” Decker says. “We’re blessed with literally years and years of loan and deposit information. We have it; we just didn’t have a good way to get to it and organize it and put it into a format that’s easily digestible.”
Financial Plus CU had created a data warehouse and spent a lot of time cleansing the data and building processes to ensure it updated accurately. But the database could only be used by its IT staff and a few financial analysts, and there was no way to present information simply and usefully to front-line staff.
The credit union engaged White Clay in October 2022 and by January had a test site in place with an improved interface. White Clay was just expanding into the credit union sector, so Financial Plus CU had the opportunity to work with the firm to edit and massage the system. This came in handy in March when the collapse of Silicon Valley Bank led depositors everywhere to wonder how safe their money was.
“We had a quick way to generate the top 50 depositors for each branch,” Decker says. “We could easily use the system to filter that out and provide a way for our branches to touch base and reassure anybody that was concerned about deposit insurance.”
Work Smarter, Not Harder
Decker says Financial Plus CU is already seeing other benefits. Using the White Clay interface, it has been able to segment its channels and get a better handle on which ones are being used to open new accounts and acquire new products and services. That visibility will help the credit union determine staff levels and better deploy resources.
In contrast to a bank that has to focus on its shareholders, “our main focus for any initiative is how is it going to impact either employees or members,” notes Decker. “Hopefully, we can do something that positively affects both. The new system gives us visibility into our members’ lives to make sure that they’re in the right product.”
If a member requests a rate match on a loan or a fee waiver, for instance, instead of relying on a gut feel, the service representative will know exactly what products and services the member uses and can quickly determine whether the request should be granted.
“There is no secret sauce or silver bullet,” Decker says. “The goal is to find a middle ground of providing enough information to be actionable without it being completely overwhelming.”
Scott Earwood, director of community solutions for White Clay, explains that data must be made usable to support the credit union mission. “We focus on converting a credit union’s data … so that it can be acted upon and they can see a benefit from the data instead of just having the data.”
One challenge for credit unions is that they need to understand their data and data quality initiatives are not a one-time project, Earwood says. “It actually needs to be an ongoing, living thing, because the moment you stop paying attention to the data quality and putting it together and maintaining it, it starts to get dirty.”
Earwood notes that while banks will look at their client data and seek ways to make more money, credit unions can use the same information “to spot a hole in the relationship where we can take better care of that member and perhaps tell them something they don’t know.
“If we can give the customer rep better information, they can have a better conversation with you. You get taken better care of and maybe even get offered something else. Maybe it’s a product; maybe it’s a service that makes your financial life better, that makes you have better peace of mind.”
Earwood says data analytics can help credit unions focus their attention where it can be most useful. For example, using the recent deposit scare as a lesson, by identifying the 10% of members who hold 70% or more of your deposits, you can ensure you reach out to the right people.
“We can help [front-line staff] work smarter instead of harder by analyzing their data and giving them a list of 500 people to contact instead of worrying about 5,000 people,” he says.
Using data to get a full picture of a member’s relationship with your credit union can also help you understand the risks you face when a competitor raises rates or cuts costs, Earwood says. In some cases, a credit union might make bad decisions because it fears losing a member who really is unlikely to shift their business.
“We want to help credit unions focus on the full membership and the relationship instead of just trying to win a pricing war,” Earwood adds.
Get a Better Picture
Robbins says many members who have already made the decision to come to a credit union for the social and cooperative aspects are far less rate-sensitive than bank customers—and your data can help identify those people.
“Look into the demographics and look into the cash flow habits of the individuals. Those can be leading indicators when it comes to the fundamental decision-making for a credit union,” he says. “If a credit union is truly engaged with its membership, you have the opportunity, instead of merely placing a product, to actually have a compelling conversation about the health and well-being of your member.”
Of course, having in-depth insight from the data allows you to make better decisions on products as well. “It allows you to make better decisions on how you would place and discuss products because you know what your members need,” Robbins says.
“The future of data and credit unions is using that data to reinforce—or in some cases, build—personal relationships with the members,” Robbins adds. “That’s our goal.”
He hopes to be able to use the credit union’s data to show members how their deposits were turned into local loans and investments that make their community stronger.
“I think what credit unions have to their advantage compared to the big banks is the focus on the ‘why,’” Robbins notes. “It’s not about more money or the bottom line, it’s about improving members’ lives. With that philosophy, we can build the next-best-product model centered on what makes sense for individual members and their financial health.
“We have the technology, the skills and the education to build out complex models, just like the big banks do, but when the credit union philosophy is added, it enriches our ability to serve members completely.” cues icon
Art Chamberlain is a writer who focuses on the credit union sector.