KEMBA Financial Knocks Down Silos With Shared Data Ownership

When it comes to data, the Ohio credit union tasks different departments of the institution to take joint ownership.

Who owns data analytics at KEMBA Financial Credit Union ($1.1B, Gahanna, OH)?

We have a number of parties who own data here, and some of this is joint ownership, says Phil Hunt, the suburban Columbus credit union’s senior financial officer.

That includes lending, which crunches numbers to focus on loan quality; marketing, which uses data to make decisions on resource allocation and campaign choices; and, of course, finance.

We use data to ensure we’re pricing correctly and to see how productive we’re being, Hunt says.


Data as of 03.31.16

  • ASSETS: $1.1B
  • MEMBERS: 85,345
  • BRANCHES: 11
  • 12-MO SHARE GROWTH: 10.09%
  • 12-MO LOAN GROWTH: 11.17%
  • ROA: 1.28%

That joint ownership is a key concept at KEMBA, where managers are working to break down silos as they extend the credit union’s shift from rewarding members for balances to rewarding their levels of engagement.

Hunt likes to harken back to the idea of real silos, the kind that hold corn and wheat, when he talks about using relationship pricing in his shop.

The grain elevator cooperative is one of the older forms of cooperatives in our country, and they’re based on members receiving benefits based on how much they use it, the KEMBA executive says. We’re trying to do the same with our products and services.

Phil Hunt, Senior Financial Officer, KEMBA Financial Credit Union

That approach requires using one another’s specialties to determine what might work and how well it actually does. At KEMBA, it also has come to mean using some of the same software that produces that data.

The marketing team, for example, started using the same Baker Hill Analytics software as the finance folks after realizing it does a better job than the credit union’s previous MCIF system. According to Hunt, marketing uses the software to calculate the next profitable product a new member is likely to sign up for during the crucial first 90 days of membership.

KEMBA Financial Credit Union uses Baker Hill Analytics to help craft member engagement strategies. Find your next solution in the Callahan Associates online Buye’s Guide.

The credit union also uses the data tools to parse transaction and balance activity off the general ledger and determine eligibility for the credit union’s flagship relationship product, its Advantage account. That share draft account comes with direct deposit and transaction requirements, which KEMBA rewards with free and unlimited check writing, no minimum balances, and other perks.

Approximately 38,500 of the credit union’s 85,000 members have qualified for the Advantage account.

Using data like this, we can stratify where we’re losing money and where we’re making money.

Whether you have a lot of money or not much at all, a member can qualify as an Advantage member and enjoy those benefits based on their activity, Hunt says.

He concedes that some members are never going to want more than a $5 minimum balance and a CD, regardless of the rewards they’re offered for adding loans and credit cards to their activity. But KEMBA managers are learning more about that as they deepen their experience with using and sharing their analytics tools.

See It In Action

Make sense of deposit data for individual branches, institutions, and entire markets. With BranchAnalyzer, the ability to make smart tweaks to your branching strategy is just a click away.

That’s happening now with a specialty product: health savings accounts. KEMBA has increased balances significantly but is finding HSAs don’t necessarily equate to deeper relationships.

We can see that in the data, Hunt says. We think it’s because of the way members open those accounts. These accounts are typically automatically done by their employer and we never get a chance to talk to the member about their other financial needs.

That’s quantitative data and qualitative insight working hand in hand.

For all U.S. credit unions | Data as of 03.31.16
Callahan Associates |


Source: Peer-to-Peer Analytics by Callahan Associates

That kind of synergy already has led to the decision to eliminate a specialty auto product KEMBA had offered for years. Hunt says it used a static pool profitability analysis to determine an auto loan with insurance wrapper for higher-risk members yielded only 40 basis points in profit because of the cost of the insurance.

It’s easy for things to get out of whack, the KEMBA executive says. Using data like this, we can stratify where we’re losing money and where we’re making money.

Credit unions, after all, have to be profitable to continue serving members. And they have to serve members well to build deeper relationships.

Ideally, everyone contributes equally, Hunt says. But in a typical institution, including ours, about 20% of the members produce all the profits.

Sharing ownership of the data, then, and acting on it, helps branch managers, lenders, finance staff, and all the other stakeholders meet the credit union’s five annual goals, which this year are improving loan growth, deposit growth, checking penetration, Net Promoter Score, and ROA.

It brings some common purpose, especially at the senior management level, in terms of what we need to accomplish to consider ourselves a successful credit union, says Hunt, who is retiring later this year after 20 years at KEMBA.

You Might Also Enjoy

  • What Does Business Intelligence Mean for Credit Unions?
  • How A Governance Committee Helps Langley FCU Tackle Business Intelligence
  • A Way To Predict Member Behavior
  • How Analytics Can Drive Efficiency And Innovation
June 20, 2016

Keep Reading

View all posts in:
More on:
Scroll to Top
Verified by MonsterInsights