Business intelligence gained much attention in 2019. What was once a wish-list item — having staff members dedicated to mining member data to uncover new service opportunities — has become central to the continued success and relevancy of credit unions everywhere.
Better BI is helping credit unions across the country build relationships with members that run deeper than mere financial services, and the field is poised to continue growing in 2020 and beyond.
For any BI department, two steps are paramount for success:
Step 1: Establish a strong foundation.
Step 2: Do something with the data.
These articles show how to do that and more.
Learn From The Hive Mind
Data science and business intelligence have become must-have tools at many successful credit unions.
“Data is the lifeblood of any analytics program,” says Daniel Hirschlein, assistant vice president for Grow Financial FCU ($2.7B, Tampa, FL). “Not making it a priority will seriously inhibit your analytics progress.”
Indeed, new roles and initiatives at credit unions across the country are dedicated to making the most of data to better serve members. Now, as credit unions look ahead to 2020, what do those credit unions that have the best-developed BI departments say about lessons learned? What would they do differently if they knew then what they know now?
Find out in “Expert Advice From Analytics Debuts And Do-Overs."
Look To The Team …
At Wings Financial Credit Union ($5.5B, Apple Valley, MN), HR partners with analytics to ensure a fit for mission and skills as the credit union’s steadily growing analytics and business intelligence functions focus on integrating capabilities across all departments.
Mike Lindberg, vice president of analytics and consulting services for the credit union, knows well the challenge of finding the right people in a job market ripe with competition. His task is made more challenging by the need to find people with the right mix of technical aptitude and collegial attitude to work in a collaborative culture across departmental lines.
Learn how Lindberg, along with HR business partner Linwood Mielke, work together to leverage analytical insights; create better, simpler solutions; and ensure leaders understand the cooperative’s business process in “The Art Of Choosing A Data Scientist.”
… But Name An Owner
John Sahagian describes himself as a “data nerd at heart,” and his 25-year career at BCU ($3.7B, Vernon Hills, IL) tracks the development of business intelligence as an emerging cross-silo discipline at today’s modern member-owned cooperative.
Sahagian was named BCU’s first chief data officer in July 2018, after seven years as vice president of marketing and business intelligence. In his previous role, he led the evolution of marketing from a provider of creative collateral to a multimedia growth engine. External and internal data were key parts of that process, and now, as chief data officer, Sahagian is charged with executing the credit union’s overall data and intelligence vision across strategies and systems.
Learn how he does this and more in “What’s In A Name: Chief Data Officer.”
Map Out Success
CAP COM Federal Credit Union ($1.8B, Albany, NY) has embarked on a data aggregation and analytics journey, using a three-year roadmap to align staff and systems to better understand what it knows about members and how to maximize those relationships. Johanna Robbins, CAP COM’s senior vice president of finance and business intelligence, established the credit union’s initial, high-level roadmap in 2017. Robbins and business intelligence analyst Mike Wiseman fleshed it out through 2018.
“We intentionally created the first version of the roadmap to be at a very high level as we worked to establish exactly what we wanted our BA/BI [business analytics/business intelligence] team to be and what role it was going to play in the organization,” Wiseman says.
Learn how the credit union built off this road map to unearth more meaningful member intelligence in “A 3-Year Roadmap To Better BI.”
It costs approximately $1 a minute for the average call center to serve a caller. As such reducing call volume by shifting calls to automated phone systems, online banking, and mobile apps can translate into big savings. For credit unions, outbound calling is an important channel for borrower communication, debt collection, and charge-off reduction, but how do they determine which slow payers are at risk of becoming delinquent borrowers or how soon and how often to call?
Analytics and member data are helping to answer those questions at Washington State Employees Credit Union ($3.2B, Olympia, WA). The credit union is employing analytics and machine learning to make smarter, more efficient use of resources, reduce collections costs, and improve collections results across its loan portfolio.
Learn how in “Analytics Offer A Smarter Approach To Collections And Underwriting.”
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