Data analytics was once the sole domain of giant tech companies. Amazon suggests products based on previous purchases. Facebook’s algorithms determine your friend’s posts; you most want to see on your timeline. Google propagates data about you so that when you search for something like hotels in San Francisco, you start seeing ads for restaurants in San Francisco on other sites.
With the proliferation of data across multiple systems, the increase in computing power at a decreasing price, and tools to extract and harness data, the science of data analytics is being relied on to create solutions to business problems. Credit unions increasingly use business intelligence to make better decisions. And it’s not just the most prominent credit unions introducing business intelligence through data analytics to their staff. Credit unions with under $500 million in assets realize that use cases for data analytics drive ROI, better member experiences, and increased product penetration across their member base. Almost ironically, it is the smaller credit unions that need to embrace the use of data analytics – they are the ones that need to remain competitive or merge out of existence.
The Justification for Data Analytics
It’s essential to keep in mind that no company, regardless of what industry, invests in data analytics just for the technology. The cost of the tools, hardware (or cloud storage), investment in staff (business analysts and data scientists), and consulting services can represent a significant up-front investment and ongoing cost that must be justified.
The justification for a proper data management framework comes in the form of use cases. Individual examples of decision-making illustrate how data-driven credit unions reward their members or what products they offer them. Having the right data allows credit unions to make members feel more connected to their organization through targeted, meaningful campaigns.
In fact, for a credit union that’s just embarking on the data analytics journey, the best way to start is with the end in mind. Pick one use case – a single vexing problem to solve, ideally one with a reasonably high payback if solved correctly. Many articles talk about the intangible benefits of business intelligence. But credit unions, especially their CFOs, want to see a return on their investment. The following examples are a couple real use cases that credit unions have shown to prove their investments.
Use Case #1: Creating a VIP Member Program
Identifying and retaining its most valuable members is vital to the long-term success of any financial institution. In developing its popular VIP+ program, Ideal Credit Union, based in Woodbury, MN, partnered with Trellance to integrate data from its core system and other ancillary product databases to build a data warehouse and achieve a member-centric view of its data.
Utilizing the Trellance M360 enterprise data integration platform, Ideal can look at credit card, loan, mortgage, deposit, checking account, and debit card activity to measure profitability. The VIP+ program has been a driving force at Ideal, helping staff increase Share of Wallet (SOW) by focusing on the 4 C’s – Checking, Credit Card, Car (vehicle) and Casa (mortgage loan). Throughout the year, Ideal’s staff works with members to maximize their VIP+ payout. To date, Ideal has paid our VIP+ members over $3.1 million in cash dividends. So far in 2018, Ideal has 4,286 VIP+ members on track for a payout in 2019.
Use Case #2: Growing Credit Card Balances
Sometimes you need to unlearn things you used to believe in when presented with the data, according to Royce Ngiam of Partners FCU. Partners set a goal to grow their credit card total outstandings. Typical, common-wisdom approaches include announcing a promotional rate, all the way down to a teaser rate of 0% for some number of months. Partners looked at data across credit card portfolio balance growth, comparing credit unions that offered promotional rates versus those that did not. The data showed that promotional-rate-driven balances were very temporary; credit unions that did not provide promotional rates had steadier growth. Instead of focusing on introductory rates, Partners focused on driving transaction growth by increasing incentives to cardholders to use their cards more often. As a result, Partners could grow their credit card revolving base by $27 million over 18 months, just by focusing on transaction growth, which is counter-intuitive, but digging through the data proved the correlation.
Read part 2 of this blog post for additional use cases.
