Data Use Cases for Credit Unions is an on-going series showcasing real use cases of success that credit unions have had using data analytics to solve real-world problems.
Data analytics was once the sole domain of giant tech companies. Amazon suggests, “If you bought that, you might like this.” 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 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.
Data Just For Data’s Sake – NOT!
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 a data scientist), consulting services (to help you get started) can represent not just a significant up-front investment but an on-going 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 paragraphs are a few 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. Trellance helped Ideal Credit Union 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 and 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.
Read the full case study here:
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. However, 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.
Chapter 2 of the series will consider the importance of data analytics in a declining economy and highlight additional real use cases of success credit unions have had with data analytics to solve real-world problems.
Suppose your credit union is embarking on a business intelligence journey or already down the path and looking to increase the ROI of your data analytics investments. In that case, the data analytics team at Trellance can serve as your data Sherpa.
Contact us today and get the power to use rich data to guide your business decisions.